[1st Edition] 9780128121795, 9780128120767

Table of contents :
Content:
CopyrightPage iv
ContributorsPages ix-x
PrefacePage xiGregory S. Makowski
Chapter One - CTRP1 in Liver DiseasePages 1-23P. Shabani, S. Emamgholipour, M. Doosti
Chapter Two - Rationally Designed Peptide Probes for Extracellular VesiclesPages 25-41R. Tamura, H. Yin
Chapter Three - Droplet-Based Digital PCR: Application in Cancer ResearchPages 43-91G. Perkins, H. Lu, F. Garlan, V. Taly
Chapter Four - Novel Biomarkers of Heart FailurePages 93-152A. Savic-Radojevic, M. Pljesa-Ercegovac, M. Matic, D. Simic, S. Radovanovic, T. Simic
Chapter Five - Advances in Clinical Mass SpectrometryPages 153-198D. French
Chapter Six - Testing for Chronic DiarrheaPages 199-244M. Raman
IndexPages 245-252

Citation preview

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Publisher: Zoe Kruze Acquisition Editor: Poppy Garraway Editorial Project Manager: Shellie Bryant Production Project Manager: Vignesh Tamil Cover Designer: Miles Hitchen Typeset by SPi Global, India

CONTRIBUTORS M. Doosti Department of Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran S. Emamgholipour Department of Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran D. French University of California San Francisco, San Francisco, CA, United States F. Garlan Universite Sorbonne Paris Cite, INSERM UMR-S1147, CNRS SNC 5014, Centre Universitaire des Saints-Pe`res, Equipe labelisee LIGUE Contre le Cancer, Paris, France H. Lu Universite Sorbonne Paris Cite, INSERM UMR-S1147, CNRS SNC 5014, Centre Universitaire des Saints-Pe`res, Equipe labelisee LIGUE Contre le Cancer, Paris, France M. Matic Institute of Medical and Clinical Biochemistry; Faculty of Medicine, University in Belgrade, Belgrade, Serbia G. Perkins Universite Sorbonne Paris Cite, INSERM UMR-S1147, CNRS SNC 5014, Centre Universitaire des Saints-Pe`res, Equipe labelisee LIGUE Contre le Cancer; European Georges Pompidou Hospital, AP-HP - Paris Descartes University, Paris, France M. Pljesa-Ercegovac Institute of Medical and Clinical Biochemistry; Faculty of Medicine, University in Belgrade, Belgrade, Serbia S. Radovanovic Medical Center “Bezanijska Kosa”, Belgrade, Serbia M. Raman University of Calgary, Calgary, AB, Canada A. Savic-Radojevic Institute of Medical and Clinical Biochemistry; Faculty of Medicine, University in Belgrade, Belgrade, Serbia P. Shabani Department of Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran D. Simic Faculty of Medicine, University in Belgrade; Clinic for Cardiovascular Diseases, Clinical Centre of Serbia, Belgrade, Serbia ix

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T. Simic Institute of Medical and Clinical Biochemistry; Faculty of Medicine, University in Belgrade, Belgrade, Serbia V. Taly Universite Sorbonne Paris Cite, INSERM UMR-S1147, CNRS SNC 5014, Centre Universitaire des Saints-Pe`res, Equipe labelisee LIGUE Contre le Cancer, Paris, France R. Tamura BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, United States H. Yin BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, United States

PREFACE The second volume of the Advances in Clinical Chemistry series for 2017 is presented. In Chapter 1, the role of adipokines in nonalcoholic fatty liver disease is explored. These unique molecules include the CTRP family that modulates numerous pathways including glucose and fatty acid metabolism and inflammation. CTRP appears linked to disease pathogenesis, and as such, this pleiotropic molecule may thus be suitable as a biomarker. In Chapter 2, extracellular vesicles are highlighted. These unique submicroscopic lipid vesicles, released from various cell types, play significant roles in transport of cell signaling molecules in physiologic as well as pathophysiologic states. In Chapter 3, the use of droplet-based polymerase chain reaction in cancer diagnostics is reviewed. This novel technology allows for the detection and quantification of rare nucleic acid sequences with sensitivity and precision previously unachievable by conventional methods. In Chapter 4, potential biomarkers of heart failure are presented. This disease remains a continuing health problem with increased incidence and prevalence. Biomarkers presented in this comprehensive review include those associated with myocardial stretch, injury, matrix remodeling, inflammation, renal dysfunction, neurohumoral activation, and oxidative stress. In Chapter 5, the increasing application of mass spectrometry in clinical laboratory diagnostics is reviewed. As a laboratorydeveloped test, this approach has shown continual evolution and challenges the use of traditional immunoassay methodology. Technologic advances and new clinical applications will be discussed. In Chapter 6, the role of the clinical laboratory is highlighted in diagnosis of chronic diarrhea. Diagnosis of this frequently encountered symptom is complicated by its diverse etiology and considerable overlap among its various forms such as malabsorptive, secretory, osmotic, inflammatory, and motility-related. The selection of an appropriate screening/confirmation strategy is fundamental to effective treatment. I thank Volume 79 contributors and colleagues for their peer review. I extend thanks to Shellie Bryant and Vignesh Tamil for expert editorial support. I hope the second volume for 2017 will be enjoyed. Comments and feedback from the readership are always appreciated. I would like to dedicate Volume 79 to my wife Melinda on the occasion of our 20th anniversary. It’s been wonderful. GREGORY S. MAKOWSKI xi

CHAPTER ONE

CTRP1 in Liver Disease P. Shabani1, S. Emamgholipour1, M. Doosti2 Department of Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran 2 Corresponding author: e-mail address: [email protected]

Contents 1. Introduction 2. Adiponectin and the C1q Family 3. CTRP1 Characteristics 3.1 Structure 3.2 Posttranslational Modifications of CTRP1 3.3 CTRP1 Expression 3.4 Serum Levels of CTRP1 4. Regulation of CTRP1 5. CTRP1 and NAFLD 5.1 CTRP1 Functions 6. Critical Evaluation of CTRP1 6.1 Insulin Resistance 6.2 CTRP1 and Obesity 6.3 CTRP1 and Atherosclerosis 7. Conclusion References

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Abstract Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disease occurs in significant percentage of general population. NAFLD is closely associated with entire spectrum of metabolic-related disorders including diabetes, obesity, and cardiovascular diseases. Considering several similar pathways underpinning metabolic disorders, presence of common molecular mediators contributing to pathomechanism of these disorders is expected. Mounting evidence has demonstrated important role of adipokines in the context of NAFLD. Adipokines produced by different tissues, mainly adipose, modulate numerous pathways including glucose and fatty acid metabolism and inflammation. CTRPs (C1q/TNF-related proteins) are a recently identified family of adipokines in which adiponectin is the most well-known ones. CTRP1 is a member of this family which has captured attention in recent years. CTRP1 enhances glucose and fatty acid oxidation, improves insulin sensitivity, attenuates plaque formation, and increases aldosterone production. Hence, various roles in metabolic pathways can link CTRP1 to NAFLD pathogenesis. 1

These authors contributed equally to this work.

Advances in Clinical Chemistry, Volume 79 ISSN 0065-2423 http://dx.doi.org/10.1016/bs.acc.2016.10.002

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2017 Elsevier Inc. All rights reserved.

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1. INTRODUCTION Liver diseases encompass viral hepatitis, nonalcoholic fatty liver disease (NAFLD), alcoholic fatty liver disease, autoimmune liver diseases, genetic liver diseases, and liver cancer. NAFLD is the most common disease affecting a large number of people worldwide. NAFLD remains among the most common chronic liver disease worldwide. Depending on the studied populations, the prevalence of NAFLD has been reported as a range from 6% to 33%. The presence of fat accumulation in at least 5% of hepatocytes based on liver biopsy is a well-known characteristics of NAFLD [1–3]. NAFLD encompasses a spectrum of liver disease varying from simple steatosis to nonalcoholic steatohepatitis (NASH), fibrosis, and cirrhosis, which may finally develop to hepatocellular carcinoma [4,5]. Liver cirrhosis may observe in one-third of NASH patients; however, abundant data show that fibrosis may develop both in NASH and NAFLD [6]. There is ample evidence that NAFLD is closely linked to insulin resistance, obesity, metabolic syndrome, and inflammation [7–10]. Dysregulated fatty acid influx to the liver, impaired fatty acid efflux, and defective de novo lipogenesis in liver cause increase in the hepatic lipid storage [8,11–13]. Accumulating evidence pointed out that adipocytokines and cytokines are major mediators in this process [14–18]. It is generally accepted that insulin resistance is one of the most important components of NAFLD and most patients with NAFLD and subjects who develop NASH also suffer from diabetes [19]. Although the exact mechanism of NAFLD has not been completely understood, a constellation of impaired inflammatory pathways, oxidative stress, lipotoxicity, and mitochondrial dysfunction are involved in NAFLD pathomechanism. Insulin resistance is defined as the failure of peripheral tissues to respond normally to insulin and contribute to related pathway of NAFLD pathogenesis [20,21]. Insulin is a multifunctional hormone that triggers cellular functions through its interaction with the insulin receptor and consequently dimerization and autophosphorylation of insulin receptor. There is evidence that alteration of the phosphatidylinositol 3-kinase (PI3K)-protein kinase B (PKB/AKT) and the mitogen-activated protein kinase (MAPK) pathways as two important pathways which act downstream of insulin receptor can cause insulin resistance [22,23]. Among different mediators contributing to insulin resistance, free fatty acids (FFAs) have been considered the most important molecules in this

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regard. There is accumulating evidence that hepatic insulin resistance is closely associated with enhanced hepatic fat storage [24,25]. Obesity is a widespread disease which is thought to affect 10% of the population worldwide by 2030 [26]. Based on the national investigations, there is an increase in the obesity prevalence in the United States. To support this notion, data from the more recent survey in the United States showed that more than one-third (34.9%) of adults were obese in 2011–2012. Moreover, the middle-aged adults had higher rate of obesity in comparison with younger or older adults [27]. In addition to western countries, obesity is also a pandemic social and clinical problems in other regions such as the United Arab Emirates, Arabic-speaking countries, and India [28–30]. Obesity results from an imbalance between food intake and energy expenditure, which in turn leads to an energy excess. Over time, the energy excess is predominantly stored in white adipose tissue as fat [31,32]. Obesity is strongly and independently associated with increased risk of cardiovascular diseases and type 2 diabetes [33–36]. Insulin resistance and enhanced adiposity augment the circulating level of FFAs in NAFLD. Insulin resistance overall causes defective lipolysis inhibition in adipose tissue. Among the adipose tissues, visceral fat is the major contributor to FFA accumulation in hepatocytes. Increase in FFA levels leads to elevated triglyceride synthesis and its accumulation and exacerbates insulin resistance in a vicious cycle [37–39]. Accumulation of lipid in hepatocytes causes a proinflammatory state in liver. Indeed, the lipotoxic products activate the macrophages of liver which secrete proinflammatory mediators including tumor necrosis factor alpha (TNFα), interleukin 1 (IL-1), and interleukin 6 (IL-6). Activated macrophages can produce transforming growth factor-β1 (TGF-β1). TGF-β1 in turn stimulates hepatic stellate cells which produces collagen and contributes to extracellular matrix deposition and ultimately promote fibrosis [40]. C1q/TNF-related proteins (CTRPs) as paralogues of adiponectin have been emerged as important modulators of metabolic and inflammatory pathways.

2. ADIPONECTIN AND THE C1q FAMILY In recent decade, the view that adipose tissue solely serves as the main source of triglycerides storage has been changed and new insight was gained into the metabolic and immunological roles of adipocytes and preadipocytes

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[41,42].There is ample evidence that this tissue is involved in the innate and acquired immune responses. Specifically, adipose tissue secretes a wide range of molecules such as pro- and antiinflammatory cytokines, adipokines, and several molecules associated with the innate immune system (e.g., the C1qTNF-related protein superfamily). Adipokines are a group of secretory proteins initially released from adipocytes and play important roles in regulating glucose and lipid metabolism, insulin signaling, and inflammatory pathways directly and indirectly [43–46]. Among adipokines secreted from adipose tissue, adiponectin has received a great deal of attention in experimental and clinical studies in humans and in vitro investigations in transgenic and knockout (KO) mice [47]. Adiponectin is an adipocyte-derived secretory protein that is composed of 247 amino acids and has molecular weight of 30 kDa. This protein has four distinct domains, and there are also five various configurations for adiponectin, which binds three kinds of receptors [48,49]. Based on available literature, adiponectin has been considered as reliable biomarker for several disorders including diabetes, metabolic syndrome, fatty liver, and obesity [50–52]. The well-known characteristic of adiponectin is the existence of a globular C-terminal domain and a collagenous N-terminal domain. There is evidence that posttranslational modification of the collagenous domain is involved in trimers, hexamers, and higher-order complexes formation. It was demonstrated that high-molecular-weight adiponectin is distinguishably decreased in men in comparison with women and in subjects with obesity and insulin resistance compared to lean and insulin-sensitive subjects [53–55]. Structurally, adiponectin belongs to the C1q protein family which was characterized based on having a C-terminal globular domain with sequence homology to the immune complement protein C1q. The characterization of adiponectin and its homotrimeric gC1 domain revealed that the structures of TNF-ligand family proteins and the C1q complement family proteins were diverged from a precursor recognition molecule of the innate immune system. This evolutionary link suggests that these proteins have shared functions too [49,56,57]. The C1q initiates activation of the classical pathway of the complement pathway and plays an important role in cell adhesion, regulation of B lymphocytes, maintaining immune tolerance via removing apoptotic cells and pathogens [57]. The most proportion of C1q ligands are recognized by the globular (gC1q) domain that contains a versatile charge pattern recognition region [57]. Specifically, the globular (gC1q) domain

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has a heterotrimeric organization located on C-terminal of collagen region. This structure also makes up three distinct chains: A (ghA), B (ghB), and C (ghC) [58,59]. In addition to complement proteins, the gC1q signature domain has been observed in many noncomplement proteins including collagen VIII and X, precerebellin, and hibernation proteins and possesses a compact jellyroll beta-sandwich fold. This organization is also found in functional TNF ligand family [57,59,60]. The 3D organization of the globular head domain of gC1q is similar to a flower named bouquet structure as it is composed of six heterotrimers (18 polypeptide chains). There is a collagenous stalk region consisting 22 complete Gly-X-Y collagen triplets in both C1q and adiponectin [49,57,58,61]. Two kinds of adiponectin receptors: AdipoR1 and AdipoR2 (adiponectin receptors type 1 and type 2) were recognized for globular or full-length adiponectin that have different binding affinities for this adipokine [62]. With regard to AdipoR1 and AdipoR2 as two high- and low-affinity receptors for gC1q and adiponectin, a dichotomy of the gC1q–receptor interaction has been suggested. These receptors are able to form both homoand heteromultimers [45,62]. Additionally, the function of these receptors is mediated in a mechanism dependent on activation of adenosine monophosphate-activated kinase (AMPK) and p38 mitogen-activated protein kinase (p38 MAPK), activation of peroxisome proliferator-activated receptor alpha (PPAR alpha), and phosphorylation of ACC (acetyl-CoA-carboxylase) [62,63]. Accordingly, the term C1q/TNF molecular superfamily was described as a new family of secreted proteins on the basis of sequence homology with the globular domain of adiponectin. Among the C1q family members, CTRP1–15 shares strikingly similar structural organization and biochemical properties with adiponectin.

3. CTRP1 CHARACTERISTICS 3.1 Structure Wong et al. identified a highly conserved family of proteins homologous to Acrp30/adiponectin by using GenBank EST and genomic databases with the adiponectin cDNA sequence. As these proteins have a C1q-like globular domain and a C-terminal complement factor C1q globular domain which have 3D organization resembling TNF-α, they were nominated CTRP [64].

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CTRP1 structure is similar to adiponectin and other family members. Overall, CTRP1 structure is similar to other family members and consists of four distinct domains: a signal peptide in order to secrete protein, an N-terminal domain with one or more conserved Cys residues, a collagen-like domain with various lengths of Gly-X-Y repeats, and a C-terminal globular C1q domain similar to the immune complement C1q (Fig. 1) [45,65]. As a functional domain, the C-terminal globular domain can bind other proteins or receptors. This domain is conserved and shows an amino acid identity of 27–73% among paralogous CTRPs (C1q/TNF-α superfamily). There is 53–100% amino acid identity in the short N-terminal variable regions of CTRPs in mice and their corresponding orthologues in humans. With regard to C-terminal globular domains, CTRPs and their corresponding orthologues in humans share 82–99% amino acid identity [64]. CTRPs were recognized as the adiponectin paralogues, but despite the obvious similarity between adiponectin and CTRPs in terms of 3D structure, these proteins are not extremely homologous with regard to the nucleotide or amino acid sequence. In addition to adiponectin, up to now 15 members were identified in the CTRP family of proteins [64–66]. Using alignment between adiponectin, complement C1q, and TNF family members, it was found that Tyr-161, Gly-159, Phe-237, and

Fig. 1 Structure of the CTRP family members. (A) Domain structure of CTRP monomeric protein which is composed of a signal peptide (S) at the N terminus, a variable region (V), a collagen domain (Gly-X-Y), and a globular C1q/TNF domain at C terminus. (B) Homotrimeric structure of CTRP. (C) Higher-order 3D structure of homotrimeric CTRP proteins.

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Leu-242 are highly conserved residues in adiponectin that are involved in the correct packing of the hydrophobic core of promoter [58,64,67,68].

3.2 Posttranslational Modifications of CTRP1 When COS 7 cells were transfected with full-length constructs encoding C-terminal HA-tagged mCTRP1, mCTRP2, and mCTRP7, the produced proteins could be found in supernatant of transfected cells. This experiment suggested that these proteins are released. There are 1, 1, 2, and 1 potential N-linked glycosylation sites conforming to the consensus motif N-X-S/T in mCTRP1, mCTRP2, mCTRP6, and mCTRP7, respectively [64]. Following secretion, CTRP1, CTRP2, CTRP6, CTRP12, and CTRP15 possess N-linked glycans, while CTRP3, CTRP5, CTRP9, CTRP10, CTRP11, and CTRP13 have other carbohydrate-related modifications. CTRP9 contains proline residues in the Gly-X-P repeats and lysine residues in the consensus GXKG(E/D) motif in the N-terminal collagen domain that are hydroxylated and glycosylated, respectively. These modifications alter the stability and function of these proteins [64,69–73]. Except for CTRP4, CTRP12, and CTRP15, the rest of CTRPs contains one or more GXKG(E/D) motifs in the collagen domain. This finding proposed that posttranslational modifications affect function and stability of other CTRPs [66,74]. For example, there is evidence that mCTRP1, mCTRP2, mCTRP3, mCTRP5, mCTRP6, and mCTRP7 contain 1, 1, 3, 1, 2, and 5 GXKG(E/D) motifs, respectively [64]. Functional studies by producing recombinant CTRPs in mammalian cells demonstrated that posttranslational modifications affect assembly of higherorder CTRP organizations and their activity [66]. Additionally, there are 1–3 cysteine residues in N-terminal variable region of all CTRPs [64]. All CTRPs are released as glycoproteins that the serum levels of most of them are different based on the gender and genetic background of the animal model used [64,75].

3.3 CTRP1 Expression Based on immunohistochemical analysis, northern blot, in situ hybridization, it was revealed that CTRP1 is expressed in many tissues of mice. CTRP1 expression in the mouse embryos is different based on developmental stages, and it has been considered as a member of CTRP family with early expression. In addition to adipose tissue as the main source of CTRP1 expression, this protein is secreted by cardiomyocytes, muscle cells,

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hepatocytes, kidney prostate, and ovary [75]. Of the secreting tissues of CTRP1, this protein is mainly expressed by stromal vascular cells, preadipocytes, and endothelial cells. In detail, CTRP1 is mainly expressed by stromal cells compared to primary adipocytes. The most proportion of CTRP1 in the vasculature system is expressed in smooth muscle cells and endothelial cells [76]. However, the main source of CTRP1 expression has not been thoroughly recognized. There is inconsistency regarding the major source of CTRP1 in humans.

3.4 Serum Levels of CTRP1 Using the antibodies against CTRPs, the presence of CTRP1 in the mice serum was detected. The size of CTRP1 in serum and also in secreted fulllength protein from transfected cells was alike. CTRP1 is found in circulation as a glycoprotein that its levels vary based on the genetic background of rodent models. In human, the concentration range of CTRP1 is in the ng/mL range. Animal model studies demonstrated that gender has no effect in the amount of circulating levels of CTRP1 [64,65,75].

4. REGULATION OF CTRP1 Rosiglitazone is the thiazolidinedione compound that is well known to improve insulin resistance through regulating adiponcetin gene expression. In addition, rosiglitazone is considered as transcription factor peroxisome proliferator-activated receptor g (PPARg) agonist [77,78]. Treatment of mice with rosiglitazone daily for 3 weeks at a dose of 15 mg/kg augmented the CTRP1 and adiponectin expression; however, it did not affect the mRNA expression of CTRP2, CTRP3, CTRP5, CTRP7, and CTRP10 [75]. There is also evidence that CTRP1 expression might be induced in inflammatory conditions. Administration of lipopolysaccharide caused increased CTRP1 gene expression in the epididymal adipose deposit in male Sprague–Dawley (SD) rats. Despite that the level of CTRP1 gene expression was low in adipocytes, it was shown that CTRP1 gene expression was highly detectable in primary adipocytes of SD rats in normal conditions [79]. It seems that isolation of adipose tissue in mice and its subsequent disturbance stimulate secretion of inflammatory cytokines, TNF-α, and IL-6 and alter gene reprogramming in isolated adipocytes [25,26].

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5. CTRP1 AND NAFLD 5.1 CTRP1 Functions Several lines of evidence supported the clinical significance of CTRP family in metabolic-related disorders [80–83]. Of the CTRP family, CTRP1 has received a great deal of attention in this regard [84–88]. Based on rodent and clinical studies, CTRP1 function can be categorized as follows (Fig. 2):

Fig. 2 Effects of CTRP1 on different tissues. (A) Muscle: CTRP1 increases movement of Glut 4 to plasma membrane of myotubes through phosphorylation of Akt, hence increases glucose uptake and subsequently reduces blood glucose level. It also increases fatty acid oxidation in muscle cells through phosphorylation of MAPK. (B) Liver: CTRP1 causes upregulation of HSL and ACC in liver, but it induces fatty acid oxidation and inhibits fatty acid synthesis by phosphorylation and inactivation of ACC. (C) Heart: CTRP1 exerts antiinflammatory effect in myocardial infarction milieu by abolishing induced expression of TNF-α, IL-6, and IL-1β and phosphorylation of NF-κB which occurs through SP1 activation. (D) Adrenal cortex: CTRP1 enhances aldosterone production by upregulating Nurr1 and NGFIB and consequently CYP11B1. (E) Vessels: CTRP1 exerts anticoagulatory effect by inhibiting aggregation and activation of platelets.

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5.1.1 Glucose Homeostasis The first findings which arise the hypothesis of CTRP1 involvement in diabetes were based on the fact that development of diabetes in obese Zucker diabetic rats (ZDF) is age dependent. So CTRP1 expression in obese and lean ZDF rats was assessed and compared during time and was not different 1 month after birth in two groups of rats. However, CTRP1 expression initiates to decrease in lean ZDF rats as opposed to obese ZDF rats in which CTRP1 expression was unaltered. At 4 months after birth, the change in CTRP1 expression was similar to month 2. The blood glucose and triglyceride were also increased in obese ZDF rats at 4 and 2 months after birth, respectively. The above-mentioned findings provide the evidence indicating parallel alteration of CTRP1 and diabetes indicators [79]. To uncover the role of CTRP1 in glucose homeostasis, recombinant CTRP1 (2 μg/g) was injected to wild-type mice (C57BL/6). CTRP1 reduced the blood glucose level, and the results were reproducible when used different batches of mice and recombinant CTRP1. Application of recombinant CTRP1 on differentiated mouse C2C12 myotubes led to activation of Akt and p44/42-MAPK signaling pathways, but it did not activate AMP-activated protein kinase (AMPK), ACC, mechanistic target of rapamycin (mTOR), or NF-κB pathways [75]. However, evaluation of skeletal muscle in CTRP1 tg mice showed phosphorylation of AMPK and ACC [89]. In contrast, fasting blood glucose (FBG) in CTRP1 knockout (CTRP1-KO) and wild-type mice was comparable [90]. The role of CTRP1 in glucose uptake was investigated on myotubes. In detail, after differentiating C2C12 myoblasts into myotubes, 1 μg/mL CTRP1 was added to myotubes cell culture. Glucose uptake was increased in CTRP1-treated cells, and it has been shown that it was due to increased movement of GLUT4 to plasma membrane. Given that activation of Akt plays an important role in GLUT4 mobilization, phosphorylation of Akt has been investigated. Administration of recombinant CTRP1 on C2C12 myotubes resulted in activation of Akt. Moreover, the role of CTRP1 in glucose consumption was evaluated by measuring the extracellular acidification rate (ECAR) for the measurement of glycolysis and the oxygen consumption rate (OCR) for the measurement of oxidative phosphorylation. CTRP1-treated cells showed increased ECAR by 25%, but regarding OCR, they showed no alteration [91].

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5.1.2 CTRP1 in Fatty Acid Metabolism One of the major regulatory mechanisms for fatty acid oxidation is phosphorylation of AMPK. Phosphorylation and subsequent activation of AMPK result in phosphorylation of ACC which accompanies with inactivation of this enzyme and followed by reduction of its product, malonyl-CoA. MalonylCoA is inhibitor of carnitine palmitoyl transferase 1 (CPT1), the rate-limiting enzyme catalyzing the import of fatty acyl-CoA into mitochondria for β-oxidation. Hence, phosphorylation of AMPK results in enhancing fatty acid oxidation. CTRP1 tg mice upon high-fat diet showed hyperphosphorylated AMPK and ACC in their skeletal muscle. But alteration in phosphorylation of AMPK and ACC was restricted to skeletal muscle, and it was not observed in liver. Administration of recombinant protein of CTRP1 in wild-type mice led to increase in phosphorylation of AMPK in skeletal muscle [89]. On the contrary, in another study which performed expression analysis of the genes involved in lipid metabolism in liver of CTRP1 tg mice, mRNA expression of hormone-sensitive lipase (HSL) and ACC was increased, and expression of adipose triglyceride lipase (ATGL) and fatty acid synthase (FAS) did not differ compared to wild-type mice. However, in skeletal muscle and white adipose tissue, mRNA levels of ATGL, HSL, FAS, and ACC were not changed in two groups. Protein expression analysis of HSL and ACC in liver of CTRP1 tg mice showed increased expression of ACC. However, concerning the enzyme activation, determined by measuring phosphorylation, phosphorylation of ACC was increased. So, although CTRP1 upregulated ACC, it could inhibit fatty acid synthesis in liver through ACC inactivation. The CTRP1inhibitory effect on hepatic fatty acid synthesis was confirmed by treatment of HepG2 hepatocyte cell line with recombinant protein of CTRP1 (1 μg/mL) which resulted in increase of phosphorylated ACC. Although mRNA expression of ACC was not altered in skeletal muscle of CTRP1 tg mice, phosphorylated ACC was increased. Increased level of phosphorylated ACC was also occurred in C2C12 myotubes after treatment with recombinant protein of CTRP1. Aside from inhibitory effect on fatty acid synthesis, CTRP1 has been turned to have stimulatory effect on fatty acid oxidation. Pretreatment of C2C12 myotubes with CTRP1 followed by treatment with palmitic acid led to enhanced rate of fatty acid oxidation [91]. 5.1.3 CTRP1 in Thrombus Formation CTRP1 has been reported to have anticoagulation effects. CTRP1 could inhibit aggregation and activation of platelets stimulated by incubation of

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platelet-rich plasma with fibrillar collagen type I. Inhibition of CTRP1mediated platelet activation was the result of CTRP1 binding to collagen. The binding was examined using labeled CTRP1 on immobilized collagen and was specific, saturable, with high affinity and reversible. Shear stress is an important mechanical stress induced by blood flow on vessels. Shear stress can influence structure and function of endothelium and correspondingly expression of its genes. Due to the significance of endothelium dysfunction in atherosclerosis, shear stress has a pivotal role in atherosclerosis development [92,93]. CTRP1 inhibitory effect on collagen-induced platelet aggregation under shear stress was assessed by perfusing citrated whole blood through a collagen-coated chamber under low and high rates of shear. In the absence of CTRP1, adhesion and deposition of platelets immediately were observable, but preincubation of whole blood with CTRP1 blocked adhesion and deposition of platelets. Evaluation of Von Willebrand factor (VWF) binding to collagen after CTRP1 addition showed that CTRP1 could inhibit VWF binding to collagen. Therefore, CTRP1 exerted its inhibitory effect on collagen-induced platelet aggregation through abolishing VWF binding to collagen. Evaluation of antithrombotic effect of ctrp1 in nonhuman primates showed that CTRP1 inhibited thrombus formation in carotid artery after injury and reestablished blood flow [76]. 5.1.4 CTRP1 in Inflammation The first evidence which linked CTRP1 to inflammation was in vivo upregulation of CTRP1 mRNA after lipopolysaccharides (LPS) injection. In fact, mRNA expression analysis of different tissues of SD rat showed no expression of CTRP1 in all examined tissues including liver, spleen, muscle, fat, heart, and kidney. However, upon intraperitoneal injection of LPS, two mRNA species of CTRP1 (3.3 and 1.8 kb) were observed in epididymal fat depot of rat. Examining time kinetics of CTRP1 mRNA expression, epididymal fat tissue showed initiation of expression 6 h after LPS injection and sustained 24 h thereafter. The possible contribution of LPS downstream targets such as TNF-α and IL-1β in CTRP1 induction has been investigated by intraperitoneal injection of TNF-α and IL-1β. A significant increase in mRNA transcripts of CTRP1 was observed after administration of TNF-α or IL-1β or TNF-α and IL-1β, and upregulation of CTRP1 mRNA was more prominent after coadministration of TNF-α and IL-1β. Hence, TNF-α and IL-1β could mimic stimulatory effect of LPS on CTRP1 mRNA expression in vivo. In vitro experiments—studying effect of TNF-α on expression of CTRP1 in human adipocyte cell

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line—confirmed increased expression of CTRP1 following inflammation stimulation [79]. CTRP1 expression is also influenced in inflammatory conditions. Myocardial infarction induction in mice led to increased level of circulating CTRP1. Although all studies compromise on increased level of CTRP1 in inflammation milieu, there is a contradiction regarding behavior of this molecule against inflammation. Most of studies have shown antiinflammatory effect of CTRP1, but a recent study has demonstrated its proinflammatory effect. In order to extrapolate the possible role of CTRP1 in myocardial infarction, CTRP1-KO mice were generated. Gene expression analysis of proinflammatory parameters has shown that while mRNA levels of TNF, IL-6, and IL-1β have unaltered in CTRP1-KO mice compared to wild types, but following myocardial infarction induction, mRNA levels of these proinflammatory markers were increased in CTRP1-KO compared to wild mice. The role of CTRP1 was confirmed by examining the overproduction of CTRP1 using the adenoviral vectors expressing full-length mouse CTRP1 (Ad-CTRP1) in wild mice. Administration of Ad-CTRP1 abolished the increased expression of TNF, IL-6, and IL-1β in infarcted heart. In a cell-based assay, administration of recombinant protein of CTRP1 in cultured cardiomyoctes, following LPS treatment, reduced LPS-induced expression of TNF, IL-6, and IL-1β. Application of recombinant protein of CTRP1 also reduced phosphorylation of NF-κB in cultured cardiomyoctes after LPS stimulation [90]. One of the suggested mechanisms underpinning antiinflammatory effect of CTRP1 was through activation of sphingosine-1-phosphate (SP1). SP1 which is synthesized from sphingosine through phosphorylation by sphingosine kinase (SK) plays key role in several pathways including inflammation [94,95]. Knockdown of SK1 in cardiomyocytes abolished the suppressive effect of CTRP1 on LPS-induced expression of TNF, IL-6, and IL-1β and also NF-κB phosphorylation. Concordantly, treatment of cardiomyocytes with SP1 antagonist reduced the suppressive effect of CTRP1 on LPS-induced NF-κB phosphorylation. Administration of SP1 on cardiomyocytes mimics the suppressive effect of CTRP1 on proinflammatory markers expression. SP1 acts through binding SP1 receptor and inducing accumulation of cAMP. Incubation of cardiomyocytes by CTRP1 increased cAMP level in the cells and pretreatment with SP1 antagonist blocked CTRP1-induced accumulation of cAMP. Subsequently, pretreatment of cardiomyocytes with inhibitor of adenylyl cyclase blocked the antiinflammatory effects of CTRP1.

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It seems that CTRP1 exerts its antiinflammatory effects through SP1/ cAMP axis [90]. However, treatment of HAECs, HUVECs, human monocytes, and THP-1 cells with different concentrations (0.01, 0.1, and 1 μg/mL) of CTRP1 led to increased production of adhesion molecules (vascular cell adhesion protein 1 (VCAM), intercellular adhesion molecule 1 (ICAM), and E-selectin) and also TNF-α and monocyte chemoattractant protein-1 (MCP-1) in the cytosol and also medium of the cells. Studying the inflammatory pathway of CTRP1 has demonstrated that CTRP1 treatment caused activation of p38 MAPK and phosphorylation and activation of p65 component of nuclear factor NF-κB. Consistently, pretreatment with p38 inhibitor blocked the stimulatory effect of CTRP1 on activation of NF-κB. Investigating inflammatory role of CTRP1 in CTRP1 / /apoE / mice and apoE / in aortas of mice which challenged with high-fat diet showed decreased level of adhesion molecules, TNF-α, phosphorylated p38, and phosphorylated NF-κB in CTRP1 / /apoE / mice compared to apoE / . CTRP1 / /apoE / mice also showed decreased level of serum TNF-α [96]. 5.1.5 CTRP1 in Aldosterone Production Aldosterone is the major mineralocorticoid in humans which takes part in regulation of blood pressure. Aldosterone is produced in zona glomerulosa of adrenal cortex by a sequential enzymatic reactions in which the final step is catalyzed by cytochrome P-450 11β-hydroxylase 2 (CYP11B2) [97]. CYP11B2 is exclusively expressed in zona glomerulosa and confined aldosterone production to zona glomerulosa [98,99]. Evaluation of expression patterns of CTRP1 in different tissues of SD rats showed CTRP1 mRNA is expressed in adrenal gland. CTRP1 is also expressed in human adrenal gland and human adrenocortical carcinoma cell line, H295R. CTRP1 protein was also detected in rat adrenal gland and H295R cells. Exploiting in situ hybridization protocol, it was found that mRNA expression of CTRP1 was specific to zona glomerulosa of adrenal cortex which is also the main site of aldosterone production. To elucidate the stimulatory effect of CTRP1 on aldosterone production, H295R cells were treated with different concentrations of CTRP1. Different concentrations of CTRP1 enhanced aldosterone production but it peaked at 40 ng/mL. Given the fact that angiotensin II also increases production of aldosterone, the coadministration of angiotensin II and CTRP1 was assessed. The findings showed that cotreatment of

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angiotensin II and CTRP1 additively enhanced mRNA expression of CYP11B2 and also aldosterone production [100]. The stimulatory effect of CTRP1 was attributed to enhanced expression of CYP11B2 mRNA. In fact, expression analysis of steroidogenic enzymes in H295R cells treated with CTRP1 showed significant induction of CYP11B2 mRNA expression and also protein expression. Upregulation of CYP11B2 mRNA in H295R cells under incubation of CTRP1 was nearly half less compared to incubation of angiotensin II. Furthermore, as opposed to CTRP1, angiotensin II can enhance expression of other steroidogenic enzymes too. Increase of intracellular calcium plays an important role in inducing CYP11B2 mRNA expression. Analysis of intracellular calcium concentration after CTRP1 treatment H295R cells revealed rapid transient increase in intracellular calcium concentration. Considering the important role of Nur-related factor 1 (Nurr1) and nerve growth factorinduced clone B (NGFIB) in induction of CYP11B2 mRNA expression, the expression of these growth factors was also assessed. CTRP1 could enhance gene and protein expression of Nurr1 and NGFIB which are also upregulated by angiotensin II. As reported, the CTRP1-induced aldosterone production was not mediated through angiotensin II receptor. Since stimulatory effects of CTRP1 and angiotensin II in aldosterone production are similar, the angiotensin II-induced aldosterone production through induction of CTRP1 was assessed. Angiotensin II treatment on H295R cells caused no alteration in CTRP1 mRNA expression, but analysis of CTRP1 in cell medium and cytosol showed increased level of CTRP1 level in medium and decreased level CTRP1 in the cytosol of the cells, indicating increase of CTRP1 secretion under angiotensin II treatment. Then by generating CTRP1 knockdown H295R cells, induction of aldosterone after angiotensin II treatment production was assessed. In CTRP1 knockdown H295R cells, both in basal level and when stimulated by angiotensin II, aldosterone production decreased significantly which indicates angiotensin II effect on aldosterone production at least partly mediated through CTRP1 [100].

6. CRITICAL EVALUATION OF CTRP1 Although there is no study directly addressing mechanism of CTRP1 function in experimental studies of fatty liver, increasing evidence supports possible contribution of CTRP1 to metabolic-related disorders including insulin resistance, obesity, and atherosclerosis.

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6.1 Insulin Resistance Clinical studies have revealed association of CTRP1 with insulin resistance [85,88]. Administration of one of the thiazolidinedione compounds, rosiglitazone, in mice increased mRNA expression of CTRP1 in adipose tissue. Thiazolidinediones are a class of antidiabetic drugs, and increasing expression of adiponectin is one of the mechanisms through which they can improve insulin resistance [75]. Alteration of glucose intolerance in response to CTRP1 has been studied in transgenic mouse models overexpressing CTRP1 (CTRP1 tg mice). Based on one report, FBG in CTRP1 tg mice and wild-type mice was not different, but glucose tolerance test assessed by area under the curve showed a bit more cumulative glucose disposal and improved insulin sensitivity in transgenic mice. Consistently, based on another report, although oral glucose tolerance test did not differ in wild-type and CTRP1 tg mice, but after high-fat diet treatment, CTRP1 tg mice showed less glucose intolerance relative to wildtype mice. Analysis of homeostasis model assessment of insulin resistance (HOMA-IR) also showed significantly lower HOMA-IR in the CTRP1 tg mice fed high-fat diet compared to wild-type mice fed high-fat diet. CTRP1 tg mice challenged with high carbohydrate diet using 10% sucrose water showed lower FBG and HOMA-IR relative to wild-type mice.

6.2 CTRP1 and Obesity In clinical context, circulating level of CTRP1 was correlated with body mass index (BMI) [85,88]. In addition to inflammation-induced expression of CTRP1 mRNA in epididymal fat tissue, CTRP1 mRNAs were also detected in epididymal fat tissue of ZDF (fa/fa) rats [79]. Expression of CTRP1 mRNA in adipose tissue of ob/ob mice relative to lean mice. Diet-induced obese mice in a study showed decreased level of circulating CTRP1. However, in another study, with a similar diet and treatment duration, the mice on high-fat diet had higher circulating level of CTRP1 relative to the mice on standard diet [91]. In order to elucidate metabolic functions of CTRP1, transgenic mouse models overexpressing CTRP1 (CTRP1 tg mice) have been generated. When fed with a standard chow diet, the body weight of CTRP1 tg mice and wild-type mice was not different, but feeding with a high-fat diet led to gaining less body weight in CTRP1 tg mice compared to wild types.

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Analysis of body composition showed the less-fat mass in CTRP1 tg mice which uncovered the difference in body weight was due to fat mass. Further analyses showed that the body weight difference stemmed from the difference between physical activities other than food intake. Consistently, analysis of energy balance showed higher oxygen consumption and carbon dioxide production but lower respiratory exchange rate (rate of carbon dioxide production/rate of oxygen consumption) in CTRP1 tg mice compared to wild-type mice. Therefore, the CTRP1 tg mice had enhanced metabolism, but lower respiratory exchange rate indicated their energy source was shifted to fatty acids [89]. However, in a similar study on CTRP1 tg mice, there was no significant between transgenic and wild-type mice in body weight, fat mass, and food intake after high-fat diet treatment [91].

6.3 CTRP1 and Atherosclerosis Several clinical studies have demonstrated increased level of circulating CTRP1 in coronary artery disease (CAD) patients compared to healthy subjects [84,96,101]. It has been also shown that circulating level of CTRP1 was associated with number of diseased coronary arteries and the atherosclerotic extent index. Analysis of protein expression in atherosclerotic plaques showed upregulation of CTRP1 compared to control vascular tissues. Expression of CTRP1 in peripheral blood mononuclear cell was in parallel with its circulating level and expression in vascular tissue and was higher in CAD group [96].

7. CONCLUSION Circulating level of CTRP1 was increased in NAFLD and was associated with metabolic parameters including BMI, HOMA-IR, and FBG. Considering close interrelationship between fatty liver, insulin resistance, and obesity, this association could result from glucose and fatty acid metabolism deficiency. Moreover, circulating level of CTRP1 was correlated with liver function markers including alanine aminotransferase and aspartate aminotransferase and also liver stiffness. One of the possible mechanisms which links CTRP1 to fatty liver is its potent role in controlling fatty acid metabolism. CTRP1 could enhance fatty acid oxidation through upregulating HSL and also inactivation of ACC. CTRP1 could also increase glucose uptake by activating Akt and enhance glucose consumption and ultimately ameliorate insulin sensitivity.

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[80] B. Ban, B. Bai, M. Zhang, J. Hu, M. Ramanjaneya, B.K. Tan, et al., Low serum cartonectin/CTRP3 concentrations in newly diagnosed type 2 diabetes mellitus: in vivo regulation of cartonectin by glucose, PLoS One 9 (11) (2014). e112931. [81] K.M. Choi, S.Y. Hwang, H.C. Hong, S.J. Yang, H.Y. Choi, H.J. Yoo, et al., C1q/ TNF-related protein-3 (CTRP-3) and pigment epithelium-derived factor (PEDF) concentrations in patients with type 2 diabetes and metabolic syndrome, Diabetes 61 (11) (2012) 2932–2936. [82] H. Qu, M. Deng, H. Wang, H. Wei, F. Liu, J. Wu, et al., Plasma CTRP-3 concentrations in Chinese patients with obesity and type II diabetes negatively correlate with insulin resistance, J. Clin. Lipidol. 9 (3) (2015) 289–294. [83] S. Emamgholipour, N. Moradi, M. Beigy, P. Shabani, R. Fadaei, H. Poustchi, et al., The association of circulating levels of complement-C1q TNF-related protein 5 (CTRP5) with nonalcoholic fatty liver disease and type 2 diabetes: a case-control study, Diabetol. Metab. Syndr. 7 (2015) 108. [84] D. Yuasa, K. Ohashi, R. Shibata, K. Takeshita, R. Kikuchi, R. Takahashi, et al., Association of circulating C1q/TNF-related protein 1 levels with coronary artery disease in men, PLoS One 9 (6) (2014). e99846. [85] P. Shabani, H. Naeimi Khaledi, M. Beigy, S. Emamgholipour, E. Parvaz, H. Poustchi, et al., Circulating level of CTRP1 in patients with nonalcoholic fatty liver disease (NAFLD): is it through insulin resistance? PLoS One 10 (3) (2015). e0118650. [86] Y. Xin, X. Lyu, C. Wang, Y. Fu, S. Zhang, C. Tian, et al., Elevated circulating levels of CTRP1, a novel adipokine, in diabetic patients, Endocr. J. 61 (9) (2014) 841–847. [87] J.-N. Tang, D.-L. Shen, C.-L. Liu, X.-F. Wang, L. Zhang, X.-X. Xuan, et al., Plasma levels of Cl q/TNF-related protein 1 and interleukin 6 in patients with acute coronary syndrome or stable angina pectoris, Am. J. Med. Sci. 349 (2) (2015) 130–136. [88] X. Pan, T. Lu, F. Wu, L. Jin, Y. Zhang, L. Shi, et al., Circulating complement-C1q TNF-related protein 1 levels are increased in patients with type 2 diabetes and are associated with insulin sensitivity in Chinese subjects, PLoS One 9 (5) (2014)e94478. [89] J.M. Peterson, S. Aja, Z. Wei, G.W. Wong, CTRP1 protein enhances fatty acid oxidation via AMP-activated protein kinase (AMPK) activation and acetyl-CoA carboxylase (ACC) inhibition, J. Biol. Chem. 287 (2) (2012) 1576–1587. [90] D. Yuasa, K. Ohashi, R. Shibata, N. Mizutani, Y. Kataoka, T. Kambara, et al., C1q/ TNF-related protein-1 functions to protect against acute ischemic injury in the heart, FASEB J. 30 (3) (2016) 1065–1075. [91] S. Han, J.S. Park, S. Lee, A.L. Jeong, K.S. Oh, H.I. Ka, et al., CTRP1 protects against diet-induced hyperglycemia by enhancing glycolysis and fatty acid oxidation, J. Nutr. Biochem. 27 (2016) 43–52. [92] K.S. Cunningham, A.I. Gotlieb, The role of shear stress in the pathogenesis of atherosclerosis, Lab. Invest. 85 (1) (2005) 9–23. [93] K.-S. Heo, K. Fujiwara, J.-I. Abe, Shear stress and atherosclerosis, Mol. Cells 37 (6) (2014) 435–440. [94] A.J. Snider, K.A. Orr Gandy, L.M. Obeid, Sphingosine kinase: role in regulation of bioactive sphingolipid mediators in inflammation, Biochimie 92 (6) (2010) 707–715. [95] G.F. Nixon, Sphingolipids in inflammation: pathological implications and potential therapeutic targets, Br. J. Pharmacol. 158 (4) (2009) 982–993. [96] L. Lu, R.Y. Zhang, X.Q. Wang, Z.H. Liu, Y. Shen, F.H. Ding, et al., C1q/TNFrelated protein-1: an adipokine marking and promoting atherosclerosis, Eur. Heart J. 37 (22) (2016) 1762–1771. [97] M. Lisurek, R. Bernhardt, Modulation of aldosterone and cortisol synthesis on the molecular level, Mol. Cell. Endocrinol. 215 (1–2) (2004) 149–159.

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[98] E. Hui, M.C. Yeung, P.T. Cheung, E. Kwan, L. Low, K.C. Tan, et al., The clinical significance of aldosterone synthase deficiency: report of a novel mutation in the CYP11B2 gene, BMC Endocr. Disord. 14 (2014) 29. [99] S. Portrat-Doyen, J. Tourniaire, O. Richard, P. Mulatero, B. Aupetit-Faisant, K.M. Curnow, et al., Isolated aldosterone synthase deficiency caused by simultaneous E198D and V386A mutations in the CYP11B2 gene, J. Clin. Endocrinol. Metab. 83 (11) (1998) 4156–4161. [100] J.H. Jeon, K.-Y. Kim, J.H. Kim, A. Baek, H. Cho, Y.H. Lee, et al., A novel adipokine CTRP1 stimulates aldosterone production, FASEB J. 22 (5) (2008) 1502–1511. [101] J.-N. Tang, D.-L. Shen, C.-L. Liu, X.-F. Wang, L. Zhang, X.-X. Xuan, et al., Plasma levels of C1q/TNF-related protein 1 and interleukin 6 in patients with acute coronary syndrome or stable angina pectoris, Am. J. Med. Sci. 349 (2) (2015) 130–136.

CHAPTER TWO

Rationally Designed Peptide Probes for Extracellular Vesicles R. Tamura, H. Yin1 BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, United States 1 Corresponding author: e-mail address: [email protected]

Contents 1. Introduction 2. Biological Importance of EVs 2.1 Exosomes and Anticancer Chemotherapeutic Resistance 2.2 EVs in Immune System 2.3 EVs in Cancer Progression and Metastasis 3. Isolation and Quantification 3.1 Isolation Methods 3.2 Nanoparticle Tracking Analysis 4. Probes for EVs 4.1 Protein Markers of EVs 4.2 Lipid- and Curvature-Sensing Proteins and Peptides 5. Applications 6. Conclusions and Future Perspectives Acknowledgments References

26 26 26 28 28 29 29 30 32 32 32 36 36 37 37

Abstract Extracellular vesicles (EVs) are submicroscopic lipid vesicles secreted from cells and play significant roles in cell-to-cell communication by transporting varieties of cell signaling molecules like proteins, DNA, mRNA, and microRNA. Recent studies showed that EVs are highly correlated with cancer progression and metastasis. However, there are some difficulties in probing each vesicle using popular analytical methods because of their small sizes and heterogeneous origins. These obstacles may be overcome by using a novel approach that senses highly curved membrane and negatively charged membrane lipids. In this chapter, we highlight the basic biological concepts of EVs, isolation, and quantification methods, and recent advent of peptide probes for EVs.

Advances in Clinical Chemistry, Volume 79 ISSN 0065-2423 http://dx.doi.org/10.1016/bs.acc.2016.09.001

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2017 Elsevier Inc. All rights reserved.

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1. INTRODUCTION Exosomes and microvesicles, collectively referred to as extracellular vesicles (EVs), are submicroscopic lipid vesicles released by various types of cells to extracellular environment [1]. EVs play significant roles in cellto-cell communications by carrying cell signaling molecules, such as DNA, mRNA, microRNA, proteins, and lipids, to the recipient cells [2,3]. Exosomes have diameters from 30 to 100 nm formed by inward budding to late endosome. After exosomes are held in multivesicular bodies (MVB) in the cell, they are released by exocytosis pathway [4,5]. Microvesicles, on the other hand, have a diameter from 100 to 1000 nm and are formed by outward budding and fission of the plasma membrane [4]. The lipid composition of EVs is similar to that of the cell membrane but it has an increased level of the aminophospholipids, phosphatidylserine (PS), and phosphatidylethanolamine, compared to the outer leaflet of the cell membrane [1]. In addition, the membrane of exosomes contains the lipid ceramide formed during the production of exosomes [5]. Recently, a number of studies have revealed that EVs play significant roles in cancer progression and metastasis, and the immune system [6–8]. Applications of EVs to diagnosis and therapeutics have been of great interest in both academia and industry. However, the detection method of EVs is still under development because of their submicroscopic sizes and heterogeneous cellular origins. In this review, we will briefly discuss the functions of EVs in the biological system, the isolation, and characterization methods of EVs, and the recent advances of the peptide probes that sense the curvature and lipid composition of EVs (Fig. 1).

2. BIOLOGICAL IMPORTANCE OF EVs 2.1 Exosomes and Anticancer Chemotherapeutic Resistance One of the major contributing factors to cancer mortality is the acquisition of chemotherapeutic resistance [9]. Cancer cells that are exposed to drugs expel them to the extracellular environment by the multidrug resistance (MDR)–ATP-binding cassette transporter (ABC transporter) system, such as P-glycoproteins (P-gp) [10]. Exosomes have been recognized to carry ABC transporters to induce chemotherapeutic resistance. Corcoran et al.

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Fig. 1 Schematic illustration of the production and release of EVs. Exosomes are formed by inward budding to late endosome and held in MVB. Exosomes are released by exocytosis pathway. Microvesicles are formed by budding from the plasma membrane. EVs contain membrane proteins, globular proteins, mRNA, microRNA, and DNA.

have found that exosomes isolated from docetaxel-resistant variants of prostate cancer cells could confer a docetaxel resistance to docetaxel-sensitive recipient cells by transferring MDR-1/P-gp [11]. In addition to this, shed vesicles, like exosomes and microvesicles, could serve as a drug efflux mechanism in drug resistance acquisition. Shedden et al. have reported that gene expression associated with vesicle shedding correlates with drug sensitivities. Furthermore, they have also found doxorubicin and other drugs could be accumulated in vesicles and expelled to the extracellular environment [12]. Qu et al. have found that lncRNA, which correlates with clinically poor sunitinib response, could incorporate into exosomes and promote sunitinib resistance [13]. In addition to contributing to the drug resistance to small molecules, recent studies have revealed that exosomes could impede immunotherapies. Aung et al. have found that exosomes released from B-cell lymphoma that contain CD20 membrane proteins bind therapeutic anti-CD20 antibodies, therefore, protect the target cells from antibody attack. They also found that exosomes could protect the lymphoma cells from antibody-mediated complement-dependent cytolysis by consuming the complement [14]. Furthermore, exosomes released from HER2 overexpressing cancer cells have been shown to inhibit the attack of cancer reactive antibodies [15,16].

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2.2 EVs in Immune System The roles of EVs in the modulation of the immune system, especially in cancer development, have been studied in-depth. The cancer-derived EVs transfer signaling molecules, like proteins and nucleic acids, to the immune system and affect immunoregulation including antigen presentation, immune activation or suppression, and immune surveillance. For example, exosomes from various cell types carry MHC–peptide complexes that modulate CD4+ and CD8+ T cells. For more comprehensive and detailed information about the functions of EVs in immune system, see the following reviews: [8,17,18].

2.3 EVs in Cancer Progression and Metastasis The primary cause of human cancer deaths is the metastatic spread of the primary tumor cells to other organs in the body [19]. Cancer cells release some soluble factors and signaling molecules to the tumor microenvironment and the site of a future metastasis to promote cancer progression. There is growing evidence that tumor cell-derived exosomes deliver oncogenic proteins and nucleic acids, which are important in tumorigenesis, progression, and metastasis, to the recipient cells [20]. Recent studies revealed that tumor-derived exosomes contribute to the formation of a premetastatic niche, which is the permissive environment for incoming tumor cells [21]. Peinado et al. demonstrated that the exosomes derived from highly metastatic melanoma increased the metastatic behavior of primary tumors by educating bone marrow progenitors through the receptor tyrosine kinase MET and also induced vascular leakiness at premetastatic sites [7]. Melanoma-derived exosomes have also been shown to prepare lymph nodes for metastasis by promoting melanoma cell recruitment, extracellular matrix deposition, and vascular proliferation in the lymph nodes, and to induce the epithelial-to-mesenchymal transition resembling process that promotes metastasis [22,23]. Besides melanoma cells, exosomes derived from chronic myeloid leukemia cells promote angiogenesis [24], and colorectal cancer cells release Fas-ligand-bearing microvesicles that induce T-cell apoptosis leading to immune escape of cancer cells [25]. Most types of cancer cells secrete exosomes in greater amounts than normal cells [26–28]. The blood of melanoma and lung adenocarcinoma cancer patients contains increased levels of exosomes compared to normal donors [29–31]. Further, elevated levels of microRNA-containing exosomes and

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microvesicles have been found in prostate cancer patients [32]. The correlation between the amount of circulating EVs and cancer progression and prognosis has stimulated method to detect and quantify cancer-derived EVs. Alegre et al. found that melanoma biomarkers, MIA and S100B, could be detected in exosomes from melanoma patients and used for prognostic and diagnostic utility [33]. Tokuhisa et al. showed that exosomal microRNAs, miR-21 and -1225-5P, from peritoneum lavage fluid could serve as biomarkers of early diagnosis of gastric cancer [34]. Research into the applications of EVs as biomarkers of cancer diagnosis is an active field. We will here introduce the current advances in the research on probes, purification, and quantification for EVs, and we will also address the emerging fields of membrane-curvature and lipid-sensing peptides for the probes of EVs.

3. ISOLATION AND QUANTIFICATION 3.1 Isolation Methods Ultracentrifugation is the gold standard in isolating EVs. But it requires specialized equipment, and typical yields are not adequate [35]. Instead, ExoQuick™ (SBI, Mountain View, CA), a polymer-based reagent that precipitates EVs, became the first choice technology for the isolation of EVs [36,37]. ExoQuick™ does not require the ultracentrifugation steps and involves smaller sample volumes. Fig. 2 illustrates the isolation procedure of EVs from cell culture media. The cells are cultured for 2 days with unsupplemented media. The media is then spun down to remove cells and debris. The supernatant contains EVs that are precipitated with the ExoQuik™ solution. The pellets of EVs are resuspended with PBS, followed by size distribution analysis. In addition to ExoQuick™, there are several other methods to isolate EVs, such as OptiPrep™ (Sigma-Aldrich, St. Louis, MO) density gradient centrifugation and Total Exosome Isolation™ (Invitorgen, Waltham, MA) precipitation. Deun et al. evaluated these methods in terms of purity, exosome yield, protein and RNA yield, and ease of use. They showed that OptiPrep™ density gradient centrifugation outperforms the other three methods in the purity of exosomes and exosome-specific protein and RNA yield, but it is the most labor intensive method and the least total protein and RNA yield [38]. Therefore, further development of isolation methods of EVs is highly required.

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Isolate media and centrifuge

Supernatant Pellet

Cell culture

Supernatant

NTA

+ Precipitate EVs

EVs

ExoQuick

Fig. 2 Isolation method. Cells are incubated with unsupplemented media for 2 days. After removing cells and debris by centrifugation, the supernatant is mixed with ExoQuick™ solution. Centrifugation gives the pellets of EVs.

3.2 Nanoparticle Tracking Analysis There are several technologies employed for the analysis of submicroscopic particles like EVs. These include fluorescence microscopy, electron microscopy, flow cytometry, and dynamic light scattering (DLS). However, these methods have some drawbacks. Standard fluorescence microscopies, like confocal and widefield microscopies, and flow cytometry have detection limits due to the particle sizes of EVs. Confocal and widefield fluorescence microscopies have the best resolutions of approximately 200 nm [39], while flow cytometry is limited to particle sizes above 300 nm [40]. Electron microscopy is frequently used to demonstrate the presence of EVs, but it cannot provide quantitative data. Also, the size and shape of vesicles are altered during fixation [40]. DLS determines the size of particles, but it cannot distinguish between exosomes and microvesicles in heterogeneous solution because it is biased toward the detection of larger particles [41]. Nanoparticle tracking analysis (NTA) is a widely used method for the detection of EVs because it can identify both exosomes and microvesicles and determine the concentration of vesicles [42,43]. The NanoSight LM10 (Malvern Instruments, Malvern, UK) can detect particles from

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30 to 1000 nm. It combines laser light scattering microscopy with a chargedcoupled device (CCD) camera. A laser beam is passed through the chamber where the sample is incubated, and the particles scatter light that the CCD camera records. The NTA software calculates the diameter of particles using the Stokes–Einstein equation D¼

KB T 6πηr

(1)

where D is the diffusion coefficient, kB is Boltzmann’s constant, T is the temperature, η is the viscosity of the fluid, and r is the radius of the particle [40,44,45]. The average distance a particle diffuses from its origin can be calculated using the diffusion coefficient. The root-mean square displacement (Xrms) is obtained by the equation pffiffiffiffiffiffiffiffi Xrms ¼ 2Dt

(2)

where t is time [1]. Fig. 3. shows a sample size distribution of EVs isolated from the human breast cancer cell line (MDA-MB-231). EVs from MDA-MB-231 cells were isolated using the procedure described in Section 3.1.

Fig. 3 NTA analysis. Size distribution of EVs isolated from MDA-MB-231 cells.

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4. PROBES FOR EVs 4.1 Protein Markers of EVs As described earlier, the size distributions and concentrations of EVs can be measured by NTA. However, since the distinction between exosomes and microvesicles is ambiguous, and it is challenging to separate these vesicles from heterogeneous sample, molecular probes would help to identify EVs. EVs display some universal protein markers, such as tetraspanins (CD63, CD9, and CD81), heat shock proteins (HSP), and Rab family proteins, which are used for detection and characterization [46]. Tetraspanins are a protein super family that organize membrane microdomains and interacts with a variety of membrane and signaling proteins. Because tetraspanins are abundant in endocytic membranes, they are used as exosomal markers [47]. HSP are a group of chaperone proteins with a variety of roles. HSP localize on the surface of exosomes secreted by normal and cancer cells, and play key roles in cell-to-cell communications [48]. The small GTPases of the Rab protein family are involved in secretion of exosomes [49]. Exosomal markers are detected by standard analytical methods like Western blotting or ELISA. Kowal et al. showed a novel way to separate exosomes and microvesicles from a heterogeneous solution by their sedimentation speed and by floatation into a density gradient or by immune isolation with antibodies for exosome markers (CD9, CD63, and CD81). They found that several exosome markers, like major histocompatibility complex, flotillin, and HSP, are similarly present in all EVs [50].

4.2 Lipid- and Curvature-Sensing Proteins and Peptides The membranes of EVs contain rare lipids, such as ceramide, PS, and aminophospholipid, and have highly curved surfaces that give rise to lipidpacking defects [5,51–53]. These two unique traits are great targets to develop the probes for EVs. As discussed earlier, PS is normally sequestered on the inner leaflet of the plasma membrane in an ATP-dependent manner, but PS is enriched in the outer leaflet of EVs [4,54,55]. For example, platelet-derived EVs contain externalized PS after platelet activation and provide molecules for hemostasis and coagulation [56]. The most common probe for PS is annexin V, which binds PS-containing membrane in the presence of calcium ions [57]. The membrane-binding annexin core has

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four annexin repeats that contain five α-helices separated by loops that coordinate with calcium ions. This forms the bridge between annexin core and the phospholipid heads of the membrane [58]. Although most of lipids do not have a net charge, PS has a net negative charge, which helps to coordinate with calcium ion in annexin protein. As EVs expose PS to the outer leaflet of membrane, annexin V is used to quantify EVs by flow cytometry [59]. Compared to proteins like annexin V, peptides or peptidomimetics are getting more attention because of low manufacturing cost, relative ease of synthesis, and capability to incorporate unnatural amino acids [60]. Our group recently developed three types of peptide probes for EVs (Table 1). These peptides were designed based on the known membranesensing proteins. Myristoylated alanine-rich C kinase substrate (MARCKS) is a widely distributed protein that sequesters phosphatidyl inositol 4,5bisphosphate (PIP2) and regulates phospholipase C signaling [64,65]. The effector domain of MARCKS protein, called MARCKS-ED, consists of 25 amino acids. MARCKS protein binds negatively charged acidic lipids, like PIP2, by electrostatic interaction with the 13 basic amino acid residues of the effector domain. In addition, MARCKS-ED contains five phenylalanine residues that insert into the lipid bilayers of plasma membrane [66]. The interaction to PIP2 is regulated by protein kinase C or calcium-bound calmodulin. The phosphorylated MARCKS-ED dissociates from plasma membrane that leads to the release of PIP2 and inhibits actin filament cross-linking. Therefore, MARCKS-ED is involved in a number of cell signaling processes that modulates cell cycles and motilities, secretions, and vesicle transports [66,67]. Morton et al. synthesized the MARCKS-ED peptide by standard Fmoc solidphase peptide chemistry and showed that MARCKS-ED selectively binds PS-enriched synthetic lipid vesicles with exosome like size ( G, SMN1) were performed. This multiplexing has been applied to a pilot study with SMA patients [95]. Furthermore in a subsequent study of circulating tumor DNA (ctDNA) in CRC patients, results from

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multiplex and duplex dPCR analysis were found highly correlated (r2 ¼ 0.98) [100]. This strategy has been extended to the analysis of clinical samples both to qualify the integrity of tumor tissue DNA and also to quantify the presence of each of the most frequent mutations of the KRAS oncogene within those samples. Sample integrity was evaluated before next generation sequencing (NGS) analysis by targeting four amplicons of different sizes located throughout the genome [101]. The multiplex detection of the seven most frequent mutations of the KRAS oncogene and the wild-type sequence using a two-panel assay system has been validated both for the quantitative detection of ctDNA in the plasma of patients with advanced cancer [100] and the quantitative detection of rare mutated subclones within CRC tumor tissues [102]. This latter work gave insights into the clinical significance of the presence of rare subclones within patient tumors (see later in the manuscript). Jerome et al. have also demonstrated the development of a three-plex assay using a similar strategy in nanoliter droplets for the detection of human cytomegalovirus (CMV), human adenovirus species F, and an internal control. This internal control can be useful to evaluate efficiency of PCR reactions especially in the context of samples prone to assay inhibition [103]. Finally, the use of Eva Green DNA binding dye has also been described for droplet dPCR. By choosing amplicons with different sizes for each targeted DNA, McDermott et al. demonstrated that they could detect two different targets [104]. Ji et al. have described a method for quantifying copy number and point mutations with the use of a DNA binding dye [105]. This single color system is based on the use of different lengths of 50 primers that are specific for the different tested alleles in a droplet-based dPCR using a common 30 primer. The experiment results in the generation of amplicons of different sizes that will thus present different fluorescent signals after dye incorporation. The authors exemplify the use of this relatively simple and cost effective system (as compared with the use of Taqman probe-based assays) for the analysis of copy number in the protooncogene FLT3 and for the detection of the BRAF V600E mutations in control samples and cancer cell lines. They demonstrated sensitivity of less than 1% for the detection of mutations (DNA bearing target mutation diluted in DNA from normal cells). Many clinically pertinent works have now described the use of dropletbased dPCR for the detection of specific tumor mutations (previously identified in the patient’s tumor) within body effluents. Being able to efficiently

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track mutations in frequently mutated DNA regions without previous knowledge of the tumor genotype would, however, be of high benefit for patients. It would eliminate the necessity of designing assays for each individual patient and would also allow for the testing of patients when the molecular profiles of a patient’s tumor are not available or accessible. For CRC patients, the regions of interest would include, among others, the 12–13 codons of the exon 2 of the KRAS oncogene (predictive of nonresponse to anti-EGFR therapies) or frequently mutated regions of the TP53 or APC tumor suppressor genes. Makrigiorgos et al., developer of COLD-PCR, a method based on coamplification at lower denaturation temperatures, have combined their approach with droplet-based dPCR. The procedure is based on the use of two hydrolysis probes labeled with different fluorophores matching wild-type sequences (at two targeted locations) and allows for mutation scanning of the sequences targeted by these probes. The original COLD-PCR approach suppresses wild-type sequences and enables preferential amplification of mutation-containing DNA for mutations within the amplicon [106–108]. In this modified version of the technology, the method interrogates the sequences covered by the hydrolysis probes and relies on detecting changes in the ratio of COLDddPCR signals caused by the presence of mutation(s) within the probed region (
50 bp section of a specific sequence target could be scanned) [109]. The authors demonstrated it for the scanning of multiple mutations in TP53 and EGFR at 35 pg/mL [13]

HF

MRAHF Yes proANP [16]

Yes [17,18]

CHF Yes [19]

Yes [20,21]

AHF

Level of evidence IA [13]

hs-cTn assays

CHF

Level of evidence IA [13]

hs-cTn assays

HFABP

CHF Yes [22]

Yes [22–25]

GSTP1

CHF

Yes [26]

cTn

NT-proBNP, N-terminal-proBNP; BNP, brain natriuretic peptide; MR-proANP, mid-regional proatrial natriuretic peptide; ANP, atrial natriuretic peptide; cTn, cardiac troponins; H-FABP, heart-type fatty acid-binding protein; GSTP1, glutathione S-transferase P1; HF, heart failure; AHF, acute heart failure; CHF, chronic heart failure.

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than assessment of left ventricle function and ejection fraction (EF) of these patients [27]. Novelty in HF treatment is the use of neprilysin inhibitor combined with angiotensin II receptor inhibitor, so-called LCZ696 drug (Entresto TM), which is expected to augment circulating BNP concentrations and might affect applicability of BNP measurements in HF diagnosis/prognosis or treatment monitoring, without influence on NT-proBNP plasma concentration [28]. In CHF patients, BNP and NT-proBNP outperformed ANP in diagnosis and prognosis. One of the reasons is probably that in HF patients BNP concentrations overcome those of ANP and the gap increases with the disease progression. Besides, ANP has short half-life (2–5 min), as well as low reproducibility of assays used for its determination, which led to introduction of ANP’s prohormone (proANP) measurement instead. Prohormone, proANP, has a longer half-life and is significantly more stable in the blood than ANP, the mature peptide. For that reason, a novel assay which detects the mid-regional zone of proANP (MR-proANP) became available [29]. Indeed, research group of Gegenhuber et al. [20] showed that MR-proANP was equally powerful as NT-proBNP in predicting mortality in chronic HF patients. Lainscak et al. [21] reported that although both MR-proANP and NT-proBNP correlated well with left ventricular ejection fraction (LVEF), only increased MR-proANP serum levels were independent predictor of poor survival. In this line, prognostic accuracy of MR-proANP was even better than NT-proBNP in predicting mortality in chronic HF patients [30]. However, it has been suggested that combined determination of both MR-proANP with either BNP or NT-proBNP, improves diagnosis and prognosis in chronic HF patients. In acute HF, it has been shown that MR-proANP measurement (sensitivity 97%, specificity 59.9%, accuracy 73.6%) was similarly effective to BNP in acute HF diagnosis, especially in patients within BNP “gray zone” (BNP levels between 100 and 500 pg/mL) and in obese patients [16] Another large study, PRIDE study [19], found MR-proANP to be an independent predictor of HF diagnosis, as well as can be used for reclassification of both NT-proBNP false-negative and -positive results. In this line, study of Seronde et al. [17] provided firm evidence that all NPs have equal diagnostic power, but MR-proANP has the best long-term prognostic value in patients with acute HF. The most recent study of Lindberg et al. [18] reported that plasma MR-proANP independently predicts all-cause mortality, as well as cardiovascular mortality, admission due to recurrent MI, ischemic stroke, or HF in patients with STEMI (Table 1).

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3. BIOMARKERS OF MYOCYTE INJURY Increased rate of cell death, due to apoptosis or necrosis, is typical characteristic of HF [31] Apoptosis and necrosis of cardiomyocytes can result from either decreased heart perfusion or oxygen supply or increased myocardial wall stress. Additionally, elevated circulating neurohormones, high adrenergic activity, inflammation, and oxidative stress may also contribute. For that reason, molecules associated to myocardial injury have been widely investigated in HF.

3.1 Cardiac Troponins Troponins are regulatory proteins involved in the process of skeletal and cardiac muscle contraction. cTns are organized as troponin complex, which is composed from three different subunits: troponin C, which binds calcium; troponin I (cTnI), which inhibits contraction; troponin T (cTnT), which facilitates contraction by binding the troponin complex to tropomyosin [32]. Cardiac troponin C is present in both cardiac and skeletal muscle cells, while cTnI and cTnT are expressed as cardiac muscle-specific isoforms. Moreover, troponins in myocytes are present in two compartments, as functionally free cytosolic pool (free TnI) and major structural sarcomeric pool (TnT). After myocyte injury, troponins from both compartments can be detected in blood, showing different kinetics [33]. Since cTnT represents a larger pool, it is released slowly over several days to even 2 weeks after the onset of injury. On the other hand, cTnI is released relatively rapidly, within 1–2 h of myocyte injury. It is still not well understood whether reversibly injured cells with transiently permeable membranes can also release sarcoplasmic cTnT [34]. Lately, cTns gained a lot of attention as a prognostic biomarker of chronic HF patients. In patients with acute coronary syndrome (ACS), cTnI and cTnT have been widely used as the most accurate marker of myocardial necrosis, even despite its short half-life of 90 min. However, in the end of 20th century, Missov et al. [35] reported that cTnI is also detectable in the plasma of HF patients without ischemia. There are few possible causes of such “troponin leak” in the nonischemic HF. Namely, apoptosis and myocardial necrosis may be a result of increased myocardial wall stress, while decreased myocardial perfusion and oxygen delivery and/or diminished renal clearance may also contribute. Additionally, it has been reported that troponin plasma concentrations tightly correlates with LVEF. In non-ACS patients

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with acute HF, cTnI plasma concentration is higher than cTnT (51% vs 30%, respectively), and they both correlate with increased mortality [36]. Although cTn determination is recommended in the diagnosis of both acute and chronic HF with the highest level of evidence (IA) [13], most of the studies pointed out the significance of troponins in prognosis of HF patients. La Vecchia et al. [37] showed that plasma concentrations of both cTnI and cTnT were predictive of adverse clinical outcomes in HF patients. Moreover, study of Horwich et al. [38] reported that cTn level was one of the strongest predictors of chronic HF patient’s mortality, which was more potentiated in conjunction with BNP. In this line, group of Latini et al. [39] showed that increased plasma cTnT in CHF patients correlates with severity of HF, as well as, that it has a significant predictive role in these patients. Data from the Acute Decompensated Heart Failure National Registry (ADHERE) also reported increased mortality risk for patients with detectible cTn plasma concentration at the time of admission [40]. Since plasma concentrations of cTn were hardly detectable in CHF compared to ACS patients, few years ago, high-sensitivity troponin (hs-cTn) assays have been developed [41]. Namely, hs-cTn assay enables accurate measurement of very low troponin concentration and facilitate measurement of mainly cytoplasmic troponins [4]. In comparison to conventional cTn assays, which are capable to detect high cTn plasma concentrations in about one-quarter of HF patients, hs-cTn assays possess better analytical precision, offering 4–10-fold greater analytical sensitivity and measuring concentrations even 10–100-fold lower than by conventional method [42]. Therefore, by using hs-cTn assays, elevation in plasma troponins can be detected in virtually all patients with acute decompensated HF [43], as well as in majority of chronic HF patients [44]. Besides, it has been documented that serial measurements of hs-cTn in populations with chronic HF give additional prognostic information [44]. Namely, patients with increased plasma levels of cTn during hospitalization have a poorer outcome than patients with stable or declining cTn concentration (Table 1). However, in chronic HF patients, elevated cTn alone is not sufficient to indicate specific management strategy. Therefore, multimarker approach had been suggested in chronic HF patients.

3.2 Heart-Type Fatty Acid-Binding Protein Fatty acid-binding proteins (FABPs) are small intracellular lipid-binding proteins composed of 126–137 amino acids, with molecular weight of

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about 15–20 kDa. They can be found in nearly all tissues, especially those with intense fatty acid metabolism (like intestine, liver, and heart) [45]. The FABP superfamily participates in intracellular long-chain fatty acid transport, regulation of gene transport, as well as in protecting ischemic cardiac myocytes [46]. This protein superfamily is encoded by nine different genes and different FABPs have usually been named according to their dominant expression in certain tissue [47]. The myocardial isoform, heart-type fatty acid-binding protein (H-FABP) is encoded by the FABP3 gene and beside its abundant expression in the cardiomyocytes, it can be also found in skeletal muscles and the renal distal tubular cells [48]. Since it is present at high levels in the cardiomyocytes, H-FABP is quickly, within 20 min, detectable into the blood after cardiac damage. The peak plasma levels are reached after 3–4 h and it returns to referent range in 18–30 h [49]. Two research groups pointed out the potential usefulness of H-FABP in diagnostics of AMI nearly three decades ago [49,50]. However, there are some literature data suggesting that H-FABP may be a useful tool for detecting risk assessment in chronic HF. In children with chronic HF, Sun et al. [51] recently reported serum H-FABP concentration to be increased and related to disease severity. Regarding predictive value of H-FABP, study of Sugiura et al. [52] investigated the predictive utility of combined detection of this biomarker together with myosin light chain-I, cTnT, and CK-MB in prognosis of congestive HF patients and showed their relation to increased risk of future acute deterioration. Investigation of Niizeki et al. [23] showed that combined measurement of BNP and H-FABP at hospital admission might be useful in risk stratification for both cardiac death and nonfatal cardiac events in chronic HF patients. Moreover, another study from the same research group demonstrated that serial measurement of H-FABP concentration (at both admission and discharge) provides additional prognostic information in chronic HF. Namely, patients with high concentrations of H-FABP in both time points are at highest risk of cardiac events (death and worsening chronic HF requiring readmission) [24]. Recent studies pointed out the individual prognostic value of H-FABP. Study of Cabiati et al. [25] showed that high H-FABP levels were associated with a poorer prognosis in end-stage HF patients with mechanical circulatory support. Similarly, in population of children with CHF research group of Zoair et al. [22] found that H-FABP was significantly elevated in the

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serum and this was associated with adverse outcome, suggesting its value as a useful diagnostic and prognostic predictor (Table 1). H-FABP can be measured by various assays including ELISA, EIA, microparticle enhanced immunoassay, fully automated latex-agglutination assay and qualitative lateral-flow assay [45]. The summary estimates of sensitivity and specificity for quantitative assays are both around 80%, while for the qualitative assays sensitivity is much lower than specificity (68% and 92%), respectively [53].

3.3 Glutathione S-Transferase P1 Glutathione S-transferase P1 (GSTP1) represents the most prevalent mammalian isoenzyme of glutathione S-transferase superfamily, which have important role in detoxification and antioxidant defense [54,55]. Just like some other GSTs, GSTP1, also has additional role in maintaining the cellular redox state [56] and also possess noncatalytic ligand-binding activity. Some of these protein:protein interaction results in antiinflammatory and antiapoptotic effects of GSTP1. Namely, GSTP1 can act as an endogenous inhibitor of c-Jun N-terminal kinase (JNK), proapoptotic member of MAPK (mitogen-activated protein kinase) signaling pathway [57]. Moreover, GSTP1 can act as an endogenous inhibitor of tumor necrosis factor α (TNFα) receptor-associated factor 2 (TRAF2), resulting in inhibition of TRAF2-induced MAPK activation [58]. Complex pathophysiology of HF implicates increased activation of both JNK and p38 signaling pathways, which may lead to higher apoptosis of cardiomyocytes. In an attempt to rescue ischemic cardiomyocytes, several studies have used this concept to create the new treatment strategies by targeting MAPK pathway with p38-MAPK inhibitors [59]. Increased GSTP1 expression represents one of the cellular responses to oxidative stress or proinflammatory stimuli, which are present in chronic HF patients [60]. For that reason, GSTP1 lately gained a lot of attention as potential biomarker in monitoring cardiac function in chronic HF patients. Indeed, study of Andrukhova et al. [61] suggested that GSTP1 may be associated with end-stage HF. Although both elevated serum GSTP1 and proBNP were associated with NYHA III/IV, serum GSTP1 had a better diagnostic power in HF patients compared to proBNP (Table 1). Additionally, they reported lower specificity of proBNP compared to GSTP1 in prediction of LV function in HF patients. Furthermore, recent study of Andrukhova et al. [26]

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showed potent cardioprotective effect of single-dose GSTP1 administration early after MI. They speculated that inhibition of p38-mediating cardiomyocyte apoptosis and proinflammatory mechanisms, early after MI by GSTP1, might result in salvage of cardiomyocytes in the infarct zone and reduction of the initial infarct size. Of course, further studies are necessary to confirm such an assumption.

4. BIOMARKERS OF MATRIX REMODELING Cardiac fibrosis impairs ventricular function and contributes to both systolic and diastolic dysfunction, thus having a central role in HF progression. In that process, serum peptides derived from collagen metabolism can reflect both synthesis and degradation of collagen [62]. Indeed, it has been shown that the ratio between marker of collagen synthesis (procollagen type I amino-terminal propeptide, PINP) and marker of collagen breakdown (collagen type I cross-linked carboxy-terminal telopeptide) could be a useful marker of collagen accumulation [63]. A multimarker panel consisting of increased levels of MMP-2, tissue inhibitor of MMP-4, and collagen III N-terminal propeptide (PIIINP), accompanied by decreased levels of MMP-8, has been reported to be characteristic of HF with preserved EF [64], while increased turnover of extracellular matrix has also been reported in patients with acute decompensated HF [62].

4.1 Galectin-3 As part of subfamily of lectins, galectins comprises 15 members that bind to a set of cell surface receptors and extracellular matrix glycoproteins [65]. Galectin-3 is a unique member of chimera-type galectins, which contains a carbohydrate-recognition-binding domain that enables the specific binding of β-galactosides [66]. Galectin-3 is involved in cell adhesion, activation, proliferation, apoptosis, as well as cell migration [67] clearly implying its potential role in both acute and chronic inflammation and tissue fibrinogenesis [68,69]. Indeed, the involvement of galectin-3 in various “inflammatory/fibrotic” conditions such as arthritis, asthma, pneumonia, atherosclerosis, kidney disease, and HF has been described [10,69,70]. Animal studies have shown that galectin-3 plays a key role in tissue fibrosis and ventricular remodeling [71]. Apart from significant galectin-3 expression in rat HF models, considerable deposition

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of collagen after pericardial instillation of galectin-3 was also observed. Even more, mouse “knockouts” for galectin-3 are resistant to left ventricular pressure and volume overload, with a slower progression to left ventricular dysfunction or HF [71]. Having in mind the role of galectin-3 in cardiac remodeling, as important processes in HF development and progression, its biomarker utility has just recently emerged [9,72–74]. Indeed, the clear association of this biomarker with both the progression and severity of HF was obtained in clinical trials. The first study in which galectin-3 measuring was performed, the PRIDE study [75], showed that NT-proBNP has significantly better biomarker utility in HF diagnosis, while galectin-3 outperformed NT-proBNP in predicting 60-day mortality in patients with acute or acutely decompensated HF. However, it is important to note that although both biomarkers are good indicators of mechanical/overload response in HF, their concentrations are influenced by many factors, such as age, sex, kidney function, obesity, and diabetes [6]. Prognostic utility of galectin-3 was also obtained for patients with chronic ambulatory HF [76], and more importantly for low-risk HF patients in risk assessment for 30-day and 180-day mortality and HF rehospitalizations after an episode of acute HF [77,78] (Table 2). Interestingly, several clinical studies investigated the possibility that galectin-3 might be important as prognostic markers in HF patients with preserved EF. Indeed, de Boer and colleagues [70] reported that galectin-3 was especially predictive of death in those HF patients without LV systolic dysfunction. The most recent study [79] which included 1385 ambulatory HF cohort with reduced (1141), preserved (106), and recovered (138) LVEF compared the prognostic accuracy of four biomarkers (galectin-3, soluble isoform of suppression of tumorigenicity 2 (sST2), troponin I, and BNP) at years 1 and 5. They found significant association between galectin-3 concentrations and risk of adverse events, which is more pronounced among HF patients with preserved LVEF. Even more, based on the data of galectin-3 as the most accurate discriminator of risk among HF patients with preserved LVEF after 5 years follow-up, they concluded that this biomarker could have important prognostic value for long-term events within this cohort of HF patients. The results of [80] further confirmed prognostic utility of galectin-3 in HF patients with preserved EF, especially in context of response to treatment. Regarding measurement of galectin, two automated galectin methods were recently reported (VIDAS and ARCHITECT assay) [81,82].

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Table 2 Biomarkers of Matrix Remodeling and Inflammation in HF Response Analytical Suitability to Treatment of the Test Marker HF Type Diagnosis Prognosis

Galectin-3 ADHF

sST2

GDF-15

60-Day mortality [75]

CHF

Short- and long-term mortality [76–79]

HFpEF

Short- and long-term mortality [70,79,80]

AHF

Level of evidence A/IIb Short- and long-term mortality [83–85]

CHF

Level of evidence B/IIb [83,84,86,87]

HFnEF

VIDAS, ARCHITECT [81,82]

Qualitative: point-of-care assay 35 ng/mL [88]

Yes [89]

HFpEF, Yes HFrEF [89,90] AHF

Yes [80]

Yes [89,90]

Yes [91] Yes [92]

sST2, soluble isoform of suppression of tumorigenicity 2; GDF-15, growth differentiation factor-15; ADHF, acute decompensated heart failure; CHF, chronic heart failure; HFpEF, HF with preserved ejection fraction; AHF, acute heart failure; HFnEF, HF with normal ejection fraction; HFrEF, HF with reduced ejection fraction.

4.2 Soluble Isoform of Suppression of Tumorigenicity 2 In the last several years, sST2 is bringing much attention as a novel biomarker of HF, which integrates inflammation, fibrosis, and cardiac stress [83,93]. ST2 gene located on chromosome 2 encodes two isoforms of ST2 protein: transmembrane (ST2L) and soluble (sST2). Transmembrane

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isoform, ST2L belongs to an IL-1 family of receptors and has important immunomodulatory role mediated by IL-33 signaling [94]. Secretion of IL-33, induced mainly by mechanical strain of cardiac fibroblasts and cardiomyocytes [95], results in activation of downstream signaling pathways and consequent prevention of cardiomyocyte hypertrophy. Experimental data also suggested antiapoptotic effect of IL-33-induced signaling by increasing the expression of antiapoptotic Bcl-2 protein and inhibiting the activation of executor caspase-3 [96]. On the other hand, the presence of elevated concentrations of soluble isoform of ST2 (sST2), acting as “decoy” receptor for IL-33, can alleviate this cardioprotective effect of IL-33 [84]. Indeed, it has been shown that in various cancers and inflammatory diseases, including HF, concentrations of soluble isoform of ST2, sST2, are significantly increased. Even more, based on numerous results on significant association of sST2 with both the severity and poor outcome in HF, this biomarker has recently been included in the ACCF/AHA guideline (2013) for additive risk stratification of acute and chronic HF patients [12]. Interestingly, very recent investigation suggested that sST2 provides prognostic information even in low-risk community-based population studies [83]. Until now, numerous studies, based mainly on investigation of patients with acute dyspnea presenting to the emergency department, showed limited diagnostic significance of sST2 in HF syndrome [75,85]. Moreover, obtained data on predictive value of sST2 for overall mortality in patients with acute dyspnea regardless of cause [85,97], further indicated that sST2 cannot be considered a useful tool for the HF diagnosis in patients with acute dyspnea. To conclude, sST2 lacks disease specificity and, therefore, is not a valuable marker for the diagnosis of HF. Quite contrary, sST2 seems to be a promising prognostic biomarker in both acute and chronic HF. The results of clinical studies on acute and chronic HF demonstrate that sST2 is strongly associated with HF severity and poor outcome [75,85,86,98–100]. Regarding the investigation on the relationship between sST2 levels and cardiac structure and function, Shah et al. [99] described association of sST2 levels with higher LV-end systolic area and volume and inverse relation to LVEF. As shown in study of Januzzi et al. [85], increased concentrations of sST2 predicted the prognosis with AUC of 0.80 for 1-year mortality in acutely decompensated HF patients. Moreover, there was a dose-dependent relationship between sST2 concentrations and risk of death at 1 year, since sST2 concentration greater than 0.20 ng/mL strongly predicted 1-year mortality in patients with and without HF [85]. What is more, even a percent change in sST2 during treatment

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for acute HF has been predictive of 90-day mortality (AUC of 0.783) in patients with acutely decompensated HF [98]. Regarding chronic HF, patients with the highest decile of sST2 concentration had a HR of 3.2 in comparison to those with the lowest sST2 decile after analysis of more than 1100 patients [86]. Recently, several studies indicated that serial testing for sST2 increases the prognostic information gained in comparison to a single measurement. According to this, in patients with chronic HF, the importance of serial sST2 measurements has predictive role in worsening of left ventricular remodeling. Even more, in these patients, serial measurements of sST2, using an upper reference limit of 35 μg/L could be useful for predicting HF events, such as risk for either hospitalization or death from HF [101]. Prognostic value of ST2 dynamics has been also investigated in acute HF using prospective real-life measurements. Namely, based on significant prognostic value of sST2 concentration dynamics, between admission and discharge, for all-cause death and HF rehospitalization in 1-year period (HR 2.32), sST2 was shown to have important role in improving prognosis stratification, especially in comparison to clinical variables and NT-proBNP. In this line are the results on association of declining sST2 concentrations with improved prognosis of HF patients [98,102,103]. Based on above-mentioned results, another promising role of sST2, that can be proposed, is the role of sST2 as a “guide” in prevention of HF complications [83,93]. Furthermore, intriguing data on explorative studies in end-stage HF patients highlight potential roles of serial measurements of sST2 to track progress of clinical interventions (e.g., left ventricular device implantation, acute cardiac allograft rejection, pulmonary artery catheterguided therapy) [83,87]. Thus, serial measurements of sST2 could therefore theoretically assist therapeutic decision making in HF patients. Although the first ELISA assay for the measurement of sST2 in human serum/plasma was constructed in 2000 [104], currently commercially available assays for sST2 measurement are neither standardized nor FDA or CE approved as yet [88,105]. Recently, a point-of-care assay that uses fingerstick whole blood for qualitatively measuring sST2 (with a cut-off at 35 μg/L) has been developed, while a quantitative version of this pointof-care assay is supposed to be coming soon. In the near future, an assay for measurement of sST2 on automated platforms will probably also be made available [88] (Table 2). In conclusion, there is a large body of evidence that sST2 is a strong prognostic biomarker, that provides independent and additive prognostic

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information in patients with HF. It is important to note that concentration of sST2 is not affected by age, renal function, or body mass index, representing advantage in comparison to other biomarkers, especially natriuretic peptides [105]. For that reason, measurement sST2 has been adopted by the current ACCF/AHA guidelines for additive risk stratification of acute (class of recommendation of IIb, level of evidence of A) and chronic HF (class of recommendation of IIb, level of evidence B) [12]. Potential future applications of sST2 include monitoring of HF with possibility for sST2-guided therapy.

5. BIOMARKERS OF INFLAMMATION In HF syndrome, chronic inflammation represents one of the underlying mechanisms of gradual cardiac depression, clearly correlating with pathogenesis, progression, severity, and prognosis of the disease. Namely, inflammatory mediators participate in HF pathophysiology by direct impact on cardiac myocytes, fibroblasts, as well as on β-adrenergic receptors leading to hypertrophy, fibrosis and impaired cardiac contractility, or inducing apoptosis. From the first study, 1956, which showed correlation of C-reactive protein (CRP) with HF [106], inflammation biomarkers have been the subject of intense examination in HF patients. Beside clear correlation with the severity of disease, traditional inflammatory biomarkers, CRP, TNFα, and interleukin-6 also have prognostic value, clearly implying their potential role in testing novel antiinflammatory therapies in HF patients [8,107]. Even more, in elderly subjects without HF, elevated concentrations of those biomarkers significantly increases risk of HF development [8,108].

5.1 Growth Differentiation Factor-15 Growth differentiation factor-15 (GDF-15) is a member of transforming growth factor β superfamily, acting as a stress-responsive cytokine and frequently associated with cardiometabolic risk. It is highly expressed in cardiomyocytes, adipocytes, macrophages, endothelial cells, and vascular smooth muscle cells, especially during tissue injury and inflammatory states [77,109]. Although the exact molecular mechanism of GDF-15 is not fully elucidated, several reports suggested its potentially protective role by inhibiting proapoptotic molecules, such as JNK, Bcl-2-associated death promoter, and epidermal growth factor receptor, and activating the survival signaling pathways (Smad, eNOS, PI3K, and AKT) [77]. GDF-15 expression is highly induced in cardiomyocytes after ischemia/reperfusion and after MI, especially in cardiomyocytes of the infarct border zone [109]. It seems that

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this increased expression of GDF-15 has cardioprotective role, mediated by downstream signaling activation of Smad1/5 and ALK4/5/7 receptors, as well as upregulation of Bcl-xL and β-catenin. It has been suggested that transcription factor p53, which responds to various cellular stress signals, such as hypoxia, ischemia, oxidative stress, inflammation, or acute tissue injuries, is involved in regulation of GDF-15 expression [110]. Moreover, several studies indicate that angiotensin receptor blockers also regulate GDF-15 expression [111]. However, more therapeutic intervention studies are needed to understand whether GDF-15 can be used as a prognostic marker for therapeutic intervention in different cardiovascular disorders. Apart from upregulated expression of GDF-15 in inflammation, cancer, pulmonary disease, diabetes, and renal disease [9,112], increased GDF-15 levels are also associated with cardiovascular diseases, such as HF, atherosclerosis, and endothelial dysfunction [9,113]. Regarding chronic HF, it has been shown that increased GDF-15 concentrations were associated with HF severity, as well as other biomarkers of neurohormonal activation, inflammation, myocyte injury, and renal dysfunction [114]. What is more, one study determined that GDF-15 could be a novel promising biomarker in HF patients with normal ejection fraction (HFnEF). Namely, increased GDF-15 concentration was determined in HF patients with either mild or moderate to severe left ventricular diastolic dysfunction, regardless of the presence of coronary artery disease (CAD) or other established risk factors, which are frequently associated with HFnNF [89]. Moreover, one of the advantages of simultaneous measurements of GDF-15 in reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF) might be that GDF15, unlike NT-proBNP, is similarly elevated in both types of HF. Apart from its diagnostic role, prognostic value of GDF-15 has been shown in predicting adverse outcomes in patients with acute chest pain, MI, or chronic angina [115,116]. Moreover, the data from clinical studies clearly imply that GDF-15 can have prognostic role in all-cause mortality in HF patients. Regarding HFpEF and HFrEF, the incremental prognostic utility of GDF-15, over NT-proBNP and hsTnT, was also provided for both HF conditions [89,90]. Further, serial measurements of GDF-15 concentrations could have additional prognostic value in these patients. To conclude, GDF-15 could be promising biomarker of inflammatory stress, which represents one of underlying mechanism in progression of HF, regardless of EF. Lok et al. [91] reported for the first time that highly elevated GDF-15 concentrations can be reversible to some extent, after measuring GDF-15

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in NYHA IV, nonischemic, and nonvalvular HF patients, before and after intervention with left ventricular assist device (LVAD). They found that the GDF-15 levels were gradually reduced after LVAD implantation. This finding suggests that GDF-15 could also be used as prognostic marker to measure the response to a potentially life-saving therapeutic intervention [91]. Serial testing of GDF-15 concentrations (at baseline and at days 2, 5, 14, and 60) was performed in 1161 patients with acute HF and moderate renal impairment as part of acute heart failure (RELAX-AHF) study, which examined the effect of serelaxin. They found that baseline GDF-15 concentrations were not associated with adverse outcomes in these patients, while increase of GDF-15 concentrations at days 2 and 14 were associated with a higher risk to either rehospitalization or cardiovascular death (CV) (Table 2). Furthermore, it has been shown that serelaxin treatment results in significant decrease of GDF-15 concentrations in comparison to HF patients on placebo [92]. In summary, GDF-15 could be a promising diagnostic biomarker marker for mild to moderate HF with normal EF or the absence of CAD. Moreover, this biomarker might also have important prognostic role in all-cause mortality in HF patients, as recently confirmed in several studies which found beneficial effects of GDF-15 as a component of a multibiomarker strategy in HF prognosis. Furthermore, its potential as a prognostic marker for therapeutic intervention for different cardiovascular disorders needs to be clarified in future investigations.

6. BIOMARKERS OF RENAL DYSFUNCTION The interaction between cardiac and renal diseases has been recognized over the years [117,118]. The coexistence of both cardiac and renal disorder, due to the fact that dysfunction of one organ leads to dysfunction of the other, has been shown to significantly increase morbidity and mortality in patients with so-called cardiorenal syndrome (CRS) [117,119]. Since patients with either acute or chronic HF might have significant decline of renal function [120,121], some novel renal biomarkers have been identified in an attempt to aid in the early diagnosis, monitoring, and prognosis of patients with HF [117–119,122]. Although various molecules can be used as either functional or damage markers of kidney injury (creatinine, cystatin C, neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), interleukin-18, liver-type fatty acid-binding protein, N-acetyl-β-Dglucosaminidase, β-2 microglobulin, retinol-binding protein-4, glutathione

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S-transferases), only few have been shown to, individually or within a multimarker panel, have diagnostic and prognostic utility in HF [8,117,119,122,123].

6.1 Neutrophil Gelatinase-Associated Lipocalin NGAL, also known as lipocalin-2 (LCN2), belongs to the lipocalin family of proteins. Lipocalins are a large group of small extracellular proteins which have been associated with inflammation, transport of small hydrophobic ligands, such as steroids, lipids, and pheromones, as well as the synthesis of prostaglandins [124–128]. Furthermore, NGAL has been shown to act as a growth and differentiation factor in multiple cell types, including developing and mature renal epithelia [129]. This acute phase protein is encoded by LCN2 gene and composed of 178 amino acids, with approximate molecular mass of 25 kDa [124,130]. Structurally, human NGAL is organized in 8β-sheets running in an antiparallel direction, thus forming “lipocalin” domain. This domain is responsible for binding of lipocalins to their ligands [131]. The fact that, although initially discovered as a component of the late granules of human neutrophils [130], NGAL has differential expression in several human tissues (e.g., kidney, lungs, breast, trachea, bone marrow, stomach, small intestine, colon) [132], suggested the potential use of NGAL as a biomarker in the diagnosis and/or prognosis of various acute and chronic benign, as well as malignant diseases [132]. Many studies have shown the role of NGAL in early detection of acute kidney disease [133]. Since decline in renal function has been shown to significantly contribute to morbidity and mortality in both acute decompensated HF and chronic HF, apart from its role as a biomarker of kidney injury, NGAL has also been suggested as biomarker of HF [118,126,134]. However, it seems that NGAL itself plays a role in HF pathogenesis. Namely, neutrophil activation followed by the subsequent NGAL release participates in the development of inflammatory reactions during the course of HF [127]. Aghel et al. [134] have shown that significantly higher serum levels of NGAL in patients with acute decompensated HF, at the time of admission, are associated with increased risk of developing worsening of renal function. It was further suggested that, when compared to creatinine, serum NGAL is even more sensitive marker of renal dysfunction [133,135]. This finding implies possible application of NGAL in assessing prognosis of patients with acute HF syndromes, which are known to have impaired renal function in 20–30% of cases [136]. In this line, Alvelos et al. [137] have

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shown that serum NGAL is an independent predictor of worse short-term prognosis in patients with acute HF. Similarly, plasma NGAL as a measure of kidney injury at the time of hospital discharge is considered a strong prognostic indicator in patients with acute HF [126]. Urinary NGAL was also found to be increased in HF patients with worsening of kidney function, which was recognized as a strong and independent predictor of the prognostic end point (all-cause mortality or hospitalizations for HF) [138] (Table 3). Siasos et al. [120] have shown that, in patients with HF, NGAL levels are associated with LVEF, as well as, biomarkers of inflammation and cardiac remodeling (cystatin C, BNP, TNFα, MMP-9), further suggesting a Table 3 Biomarkers of Renal Dysfunction in HF HF Marker Type

Diagnosis Prognosis

NGAL ADHF

KIM1

Worsening of renal function [134]

AHF

Independent predictor of short-term prognosis [135]

HF

Independent predictor of all-cause mortality or hospitalization for HF [138]

HF

CHF

Response Analytical to Suitability of Treatment the Test

Tubular injury [142]

Blood point-ofcare Triage [139] Urinary NGAL ARCHITECT [140] Both blood and urine [141]

60-Day rehospitalization [143] Urinary Long-term outcome [138,144,145]

NGAL, neutrophil gelatinase-associated lipocalin; KIM-1, kidney injury molecule 1; ADHF, acute decompensated heart failure; AHF, acute heart failure; HF, heart failure; CHF, chronic heart failure.

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common pathogenetic mechanism of renal dysfunction, inflammation, and cardiac dysfunction. The role of NGAL, as a biomarker of severity and prognosis in patients with HF, is also supported by recent findings on correlation of serum NGAL levels with HF severity and hemodynamic improvement after ventricular assist device (VAD) placement in patients with advanced HF [146]. However, although significant association between serum NGAL levels and severity of HF, caused by idiopathic dilated cardiomyopathy (DCM), in children was confirmed, the relationship to indices of myocardial function was not observed [147]. There are many facts in favor of NGAL determination in patients with HF, although this protein has many functions, some of which are not clarified as yet. Its concentration in blood and urine increases within 2 h after renal impairment, preceding the increase of serum creatinine [148], which is very important considering the interplay between heart and kidney. Importantly, unlike other markers of renal injury, neither urine nor serum NGAL levels are significantly affected by diuretic therapy in chronic HF patients [149]. It is important to note that NGAL can be measured in whole blood, serum, plasma, and urine by commercially available analytical immunoassays [150]. First data on NGAL in urine and plasma were obtained using enzyme-linked immunosorbent assays that were not for everyday clinical use [148,151]. However, a whole blood point-of-care competitive immunoassay (Triage NGAL test), with high level of sensitivity and specificity (84% and 94%, respectively), was soon developed [139]. Few years later, an automated commercial method for urinary NGAL was introduced, based on chemiluminescent microparticle immunoassay on the ARCHITECT platform [140]. Apart from this, an enhanced turbidimetric immunoassay (NGAL test) on automated clinical biochemistry analyzers was developed for both urine and plasma NGAL determination [141]. Of course, there are certain limitations regarding the use of this promising biomarker in everyday clinical practice, such as whether serum or urine NGAL concentrations should be determined and how urinary NGAL should be interpreted (in relation to creatinine levels or not), as well as recommendations regarding diagnostic thresholds are lacking [141]. Furthermore, current methodology used for NGAL determination cannot differentiate between monomeric and dimeric (homo- or hetero-) NGAL forms [152]. All this suggests that further studies, which will confirm diagnostic utility of NGAL, are needed.

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6.2 Kidney Injury Molecule-1 KIM-1 is a type I transmembrane glycoprotein, with immunoglobulin- and mucine-like domains in its extracellular part and a short intracellular domain with a tyrosine phosphorylation signaling motif [153]. KIM-1 gene or protein expression is not present in the proximal tubule of the normal kidney [154]. However, any pathophysiological state leading to dedifferentiation of the epithelium or toxic kidney injury induces KIM-1 mRNA synthesis, followed by KIM-1 synthesis and its accumulation on the apical membrane of proximal tubule in the affected region [154–156]. It has been shown that KIM-1 modulates the regeneration and repair of a postischemic kidney injury [157]. What is more, urinary KIM-1 is considered a scavenger receptor on renal epithelial cells responsible for conversion of normal proximal tubule cells into a phagocyte [154]. Apart from its rather important role as a biomarker in acute kidney injury, it has been suggested that urinary KIM-1 levels might also be considered a valid biomarker of tubular injury in both acute and chronic HF, in which renal dysfunction is common [142]. In this line, it has been shown that urinary KIM-1 levels are increased in patients with HF and frequently correlate with the severity of the disease [144,145,158]. Hence, urinary KIM-1 levels can be used in prediction of CRS and may further be associated to long-term clinical outcomes in patients with chronic HF [138,144,145]. On the contrary, Verbrugge et al. [159] failed to confirm the role of urinary KIM-1 in predicting persistent renal impairment or all-cause mortality in patients with acute decompensated HF, suggesting KIM-1, as a relatively modest predictors of acute kidney impairment in acute decompensated HF. Considering the fact that urinary and plasma KIM-1 levels are shown to correlate among themselves [160], Grodin et al. [161] tried to determine the possible association of plasma KIM-1 levels with adverse clinical outcomes in acute decompensated HF. However, baseline plasma KIM-1 levels and KIM-1 levels during hospitalization could not be associated to adverse outcomes in acute decompensated HF after adjustment for standard kidney function indices [161]. Another recent study also evaluated plasma KIM-1 in terms of clinical outcomes in HF, suggesting that plasma KIM-1 predicts only 60-day HF rehospitalization, but not 180-day mortality nor 60-day death or cardiovascular rehospitalization [143] (Table 3). On the other hand, predictive role of plasma KIM-1 was not found in chronic HF [143].

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Urinary KIM-1, as a biomarker of acute kidney injury, was detected for the first time by immunoassay more than a decade ago [162]. Recently, in their meta-analysis on the diagnostic value of urinary KIM-1 for acute kidney injury, Shao et al. [163] have estimated urinary KIM-1 ELISA to have sensitivity and specificity of 74% and 86%, respectively. On the other hand, circulating plasma KIM-1 levels are determined using the single-molecule counting immunoassay technology [164]. Namely, plasma KIM-1 levels are quantified using a plate-based sandwich immunoassay, followed by the single molecule of detection antibody counting [161,164]. Being a newer biomarker for acute kidney injury, and especially with respect to its application as biomarker of HF, KIM-1 needs to be further evaluated in large adequately powered clinical studies that would focus on the assay method, its sensitivity and specificity.

7. BIOMARKERS NEUROHUMORAL ACTIVATION One of the hallmarks of HF is neurohumoral activation. The sympathetic nervous system (SNS) and, in counterbalance, the parasympathetic nervous system (PNS), as parts of autonomic nervous system, play the critical role in cardiovascular homeostasis maintenance [165–168]. Activation of SNS and other neurohumoral factors represents a compensatory mechanism, activated even before the appearance of clinical symptoms, by which failing heart is trying to preserve adequate perfusion to the peripheral tissues. On the other hand, prolonged SNS and renin–angiotensin–aldosterone system activation, as well as reduced PNS activity, dysregulation of nitric oxide (NO) signaling and inflammatory cytokine release further contribute to pathogenesis of HF [168–171]. Over the past decades, attempts have been made in developing systems for monitoring of neurohumoral activation pathways, based on the idea that application of biologically meaningful and objective biomarker of neurohumoral activation might contribute to diagnosis of HF and improve HF monitoring. Plasma norepinephrine concentration, as a measure of SNS activation, was suggested as a better prognostic factor in comparison to commonly used indexes of cardiac performance more than 30 years ago [172]. Nowadays, apart from norepinephrine, plasma renin activity, angiotensin II, and aldosterone, novel biomarkers of neurohumoral activation are established.

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7.1 Adrenomedullin Adrenomedullin (ADM) belongs to the calcitonin gene-related peptide superfamily [173]. It is a 52-amino acid peptide, which is synthesized as part of a larger precursor molecule, termed preproadrenomedullin, consisting of 185 amino acids [173]. Although originally detected in the adrenal medulla, ventricle, kidney, and lung [174], ADM is expressed in all tissues of the body [175,176]. Ever since Sugo et al. [177] have shown that endothelial cells actively synthesize and secrete ADM, this peptide with a potent vasodilatatory effect is regarded as a secretory product of the vascular endothelium, together with NO and endothelin [173,177]. Plasma levels of ADM are elevated in HF and further correlate to disease severity [178–180]. Namely, it has been shown that elevated plasma ADM levels in patients with HF are in correlation with decreasing LVEF, as well as increasing pulmonary artery pressure and presence of diastolic dysfunction [180,181]. Furthermore, increasing plasma ADM levels, in ambulatory patients with chronic HF, were found to correlate with increasing NYHA class in these patients [179]. The clinical application of ADM is limited because of its short half-life in plasma and instability [182]. For that reason, commercial immunoassays of more stable analyte, mid-regional fragment of pro-adrenomedullin (MRproADM), that could stoichiometrically be related to ADM, have been developed [16,183,184]. Indeed, prognostic value of MR-proADM was confirmed in patients with acute HF [16,19]. Furthermore, MR-proADM has been identified as an independent predictor of mortality in patients with acute decompensated HF [126], as well as, of adverse outcomes in chronic HF [185] or stable coronary disease [186]. Maisel et al. [126] have shown that MR-proADM identifies patients with high 90-day mortality, while it also adds prognostic value to natriuretic peptides in patients presenting with acute shortness of breath [126]. This is further confirmed by results of Klip et al. [187] who found that MR-proADM has a strong prognostic value for morbidity and mortality in patients with HF after acute MI and that it has stronger predictive value than BNP and NT-proBNP [187]. In patients with chronic HF, MR-proADM was identified as an independent predictor of mortality, which correlated with NYHA class and added prognostic information to NT-proBNP [188] (Table 4). Although it is undoubtable that MR-proADM as a biomarker has excellent sensitivity in HF detection and prediction of cardiovascular death, it is far less specific since it is widely distributed and increased in various diseases [185].

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Table 4 Biomarkers of Neurohumoral Activation in HF

Marker

HF Type

ADM

CHF

MRAHF proADM

Diagnosis Prognosis

Yes [16,19] Independent predictor of mortality [126]

CHF

Adverse outcomes [185] Independent predictor of mortality [187,188]

ADHF

Analytical Suitability of the Test

Independent predictor [179]

ADHF

Copeptin HF

Response to Treatment

Independent predictor of mortality [189,190] Long-term mortality [191] 90-Day mortality [126]

ADM, adrenomedullin; MR-proADM, mid-regional fragment of pro-adrenomedullin; CHF, chronic heart failure; AHF, acute heart failure; ADHF, acute decompensated heart failure; HF, heart failure.

7.2 Copeptin Due to its important role in maintenance of water balance in the body, by affecting free water reabsorption by the kidney, blood volume, body fluid osmolality, vasoconstriction, and myocardial contractile function, as well as cell proliferation, arginine vasopressin (AVP), or antidiuretic hormone has been recognized as a potentially important neurohormonal mediator in the development of HF [168,192,193]. Decades ago, it has been shown that levels of circulating AVP are increased in chronic congestive HF

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[194–196]. In that line, AVP represents a potentially attractive target for therapy in both acute and chronic HF. However, similarly to ADM, direct measurement of AVP has many obstacles, due to its small size and very short half-life of 24 min [197]. Hence, copeptin, a 39-amino acid long C-terminal segment of preprovasopressin, which ideally reflects AVP release, is used instead [189,198]. Namely, AVP gene encodes a pre-pro-protein (pre-proAVP), mainly synthesized in the paraventricular neurons of the hypothalamus and in the supraoptical nucleus. During axonal transport, pre-pro-AVP is proteolytically cleaved into multiple protein products, including the neuropeptide hormone AVP and two other peptides, neurophysin 2 and copeptin (C-terminal (CT)-proAVP). These molecules are stored in the neurohypophysis or secreted into the bloodstream upon appropriate stimuli [199]. Since copeptin is stable for days after blood withdrawal and can be easily measured by sandwich immunoluminometric assay, yielding results within 3 h, it represents an excellent surrogate for AVP [200]. In patients with HF, copeptin has been shown as a very good predictor of outcome and it was even suggested as a better predictor of death than BNP, a decade ago [189]. Its superiority in comparison to BNP and NT-proBNP was further confirmed in a study which showed association of copeptin with severity of HF, as well as proved copeptin as a potent independent predictor of mortality [190]. Copeptin was also associated to LVEF, remodeling, and clinical HF in survivor of MI [201]. In patients with acute HF, elevated copeptin indicated increased 90-day mortality [126], while its excellent predictive value was also found in patients with chronic, stable coronary disease [186,202]. Recently published prospective cohort study in patients with HF and reduced EF demonstrated strong and independent prognostic value of copeptin for all-cause mortality in a 5-year follow-up [191] (Table 4). Taken together, elevated levels of copeptin indicate a poor prognosis in HF patients. Its determination might contribute to prognostic evaluation of HF patients. What is more, apart from its role as an independent prognostic marker in HF, copeptin levels might have even more significant application as a part of multimarker risk prediction panels.

8. BIOMARKERS OF OXIDATIVE STRESS Oxidative stress has an important role in the pathophysiology of different cardiovascular diseases, including HF [203–205]. Oxidative stress in chronic HF is believed to be a consequence of increased circulating

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neurohormones and hemodynamic disorder, as well as inflammation and decreased oxygen delivery. On the other hand, disturbed redox balance in patients with chronic HF might contribute to further impairment of cardiac function, either by oxidative damage to vital cellular molecules, or by affecting cell signaling involved in cell survival and death.

8.1 Ceruloplasmin Ceruloplasmin belongs to the α2-glycoprotein fraction of plasma proteins. It is synthesized in liver and has been known for long time as the acute phase reactant and protein involved in cooper transport. However, there are several novel functions ascribed to this protein that may be clinically relevant in chronic HF. Thus, ceruloplasmin has both prooxidant and antioxidant properties and has been described as a “moonlighting protein” due to its many and varied activities [206]. Ceruloplasmin antioxidant function is mainly related to its ferroxidase I activity (FeOxI) [207], as well as, glutathione peroxidase activity [208]. FeOxI is responsible for the conversion of reactive Fe2+ into Fe3+ (form bound in transferrin), in that way preventing Fe2+ from participating in the generation of hydroxyl radicals [209]. Recently, inhibition of myeloperoxidase (MPO) was added to the list of antioxidant ceruloplasmin properties [210]. On the other hand, prooxidant functions include amine oxidase [211] and NO oxidase [212] activities. Ferroxidase I activity significantly influences iron-dependent formation of reactive oxygen and nitrogen species and is supposed to provide protection against oxidative burst in CHF. On the other hand, ceruloplasmin has also been shown to have important NO oxidase catalytic activity, resulting in decreased NO bioavailability in plasma. Both in vitro and in vivo studies have shown that this NO oxidase activity is decreased in plasma after ceruloplasmin immunodepletion and in humans with aceruloplasminemia [212,213]. Animal studies have shown that NO and NO synthases play a key role in normal cardiac physiology [214,215]. NO also has a protective role in the ischemic and failing heart, mediated by several mechanisms, including the stimulation of soluble guanylyl cyclase, which leads to a decrease in the concentration of intracellular Ca2+ and the inhibition of oxidative stress. The question arises which of the variety of roles that ceruloplasmin has in the metabolism of free radicals is dominant in HF. In subjects with asymptomatic disease, higher plasma ceruloplasmin levels are associated with incident HF as shown in Atherosclerosis Risk in Communities (ARIC) study,

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performed on more than 9000 participants during follow-up of more than 10 years [216]. This association of high ceruloplasmin concentration with HF, remained even after adjusting for other biomarkers known to have a role in HF prediction, such as NT-proBNP, hs-cTnT, and hsCRP [217]. There are evidence on strong independent prognostic value of high circulating ceruloplasmin levels in stable HF patients undergoing elective coronarography [216] (Table 5). According to the data of the study recently performed by Xu et al. [224] ceruloplasmin levels increase in CHF and the level of increase correlates with the degree of HF, probably reflecting the inflammatory status of these patients. In the view of the fact that ceruloplasmin may have dual role in oxidative metabolism, the association of high ceruloplasmin concentrations with risk and worsening of CHF might be explained either as an increase in it’s NO oxidase activity, or decrease in Table 5 Biomarkers of Oxidative Stress in HF

Marker

HF Type Diagnosis Prognosis

Ceruloplasmin HF

Independent predictor [216]

MPO

HF

Adverse cardiac events [218,219] Adverse clinical outcomes [220]

CHF

Long-term mortality [221]

8-OHdG

CHF

Independent predictor of cardiac events [222]

Trx1

CHF

Independent predictor of cardiac events [223]

Analytical Response to Suitability Treatment of the Test

MPO, myeloperoxidase; 8-OHdG, 8-hydroxy-20 -deoxyguanosine; Trx1, thioredoxin1; HF, heart failure; CHF, chronic heart failure.

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its antioxidant FeOxI activity. Although the first assumption, that high levels of ceruloplasmin decrease the available NO in the heart through increased NO oxidase activity, and as a result, enhanced oxidative stress causes more dysfunction seems biologically plausible, there are still no data on NO oxidase activity in clinical setting [212]. Regarding FeOxI activity, elevation of ceruloplasmin levels in patients with advanced HF was associated to a lower serum FeOxI activity with a close inverse relationship [225]. Namely, decrease in FeOxI activity was related to the severity of HF according to NYHA classification. Molecular basis of decreased ceruloplasmin FeOxI activity in plasma has been recently discerned. Specifically, peroxynitrite, whose production is increased in HF, affects ceruloplasmin antioxidant function through amino acid modification. In support of this close link, Cabassi et al. [225] demonstrated, in ex vivo and in vitro experiments, that peroxynitrite induces ceruloplasmin tyrosine nitration and cysteine thiol oxidation, and that these changes result in a significant reduction of ceruloplasmin-related FeOxI activity. Therefore, it seems quite logical that reduced FeOX activity was associated with a significant increase in 2-year mortality. However, ceruloplasmin level was not associated with mortality in CHF patients [225]. In addition to oxidative modifications of ceruloplasmin, which lead to altered FeOxI activity, there is another noncatalytic role of ceruloplasmin which may be relevant for oxidative stress in CHF patients. Namely, ceruloplasmin has been suggested as a potent inhibitor of purified MPO, thus inhibiting production of hypochlorous acid even at low concentrations [226]. It has been demonstrated that, in plasma from ceruloplasmin knockout mice, MPO was able to act as a potent oxidizing enzyme, while no significant oxidation was observed in plasma from wild-type animals [210]. Ceruloplasmin and MPO binding has been suggested to be related to an electrostatic interaction between the cationic nature of MPO and the anionic charges of ceruloplasmin [227]. This way, ceruloplasmin provides protective shield against excessive generation of free radicals by MPO in inflammatory states. Very recently, Cabassi et al. [228] investigated the relationship between plasma MPO activity, ceruloplasmin level, and FeOxI activity, together with nitrosative stress, inflammatory, neurohormonal, and nutritional biomarkers. Their results confirmed that plasma MPO activity and ceruloplasmin were increased, while FeOxI activity decreased in HF compared to healthy subjects. Furthermore, MPO activity was positively related to ceruloplasmin, while no correlation was found between ceruloplasmin-related FeOxI and MPO activity. The question of whether

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posttranslational modifications of ceruloplasmin also affect its ability to bind MPO and exert its antioxidative role by protein:protein interaction should be addressed in further clinical and experimental studies. Based on recent data it may be concluded high ceruloplasmin level might be helpful in recognition of individuals at increased risk of HF. In the course of CHF development determination of ceruloplasmin and its FeOxI activity provides additional data on CHF worsening. Measurement of FeOxI activity would provide important prognostic information in CHF patients.

8.2 Myeloperoxidase MPO belongs to a group of enzymes found in neutrophils that produce hypochlorous acids and free radicals [229]. The oxidants generated by MPO provide a front-line defense against phagocytosed pathogens [230]. However, in case of incomplete phagosome closure or during chronic inflammation, MPO can be released into the extracellular space. In such setting, the oxidants may cause damage to key macromolecular targets and contribute to the pathophysiology of many inflammatory diseases. Hypochlorous acid, the enzyme’s major product, is a strong oxidant that reacts with proteins, lipids, and DNA [229], hence, promoting both apoptosis and necrosis [231,232]. When redox-active compounds, generated by MPO, oxidize tyrosine, urate, and xenobiotics, damaging radicals are produced [229,233,234]. These radicals promote chain reactions or couple with superoxide to further form reactive hydroperoxides [235,236]. Apart from neutrophils, MPO is also expressed in monocytes and tissueassociated macrophages. Upon secretion, it accumulates along the endothelium and in the subendothelial space. Both endothelial NO bioavailability and vascular tone are profoundly altered by MPO [237]. Hypochlorous acid, produced in oxidation of chloride by hydrogen peroxide catalyzed by MPO, may react with tyrosyl-residues in proteins to produce 3-chlorotyrosine chlorotyrosine, a specific marker for oxidant activity of MPO-containing cells [238,239]. MPO is, therefore, a marker which combines components of oxidative stress and inflammation [220]. Elevated levels of MPO have been detected in all stages of heart disease [240] and are associated with major adverse cardiac events [218,219]. Data from several studies showed involvement of polymorphonuclear neutrophils activation and MPO-release in severe HF [241–243]. Moreover, higher MPO levels were observed in patients with more aggressive disease

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[220,241]. In their study, Tang et al. [241] correlated MPO levels with both chronic HF clinical phenotype and BNP concentrations and found higher MPO concentration in chronic HF patients in comparison to healthy subjects, which was further associated with NYHA class. However, MPO levels were not related to LV ejection fraction. A cut-off value of MPO at 230 pmol/L had a sensitivity of 72% and a specificity of 77% in the detection of CHF, after adjustment for age and BNP concentration [220]. Besides, a high level of MPO in the plasma of patients with HF seems to be a predictor of future adverse clinical events [220] (Table 5). Thus, within the Cardiovascular Health Study, MPO levels were evaluated in healthy elderly participants, who were followed in 5–10 years period whether they will develop HF. Those within the highest MPO quartile (>432 pmol/L) showed a higher risk of developing HF, after adjustment for MI, age, gender, systolic BP, smoking, c-LDL, diabetes, and any cardiovascular disease. The association was more pronounced after exclusion of MI as a predisposing factor for HF and adjusting for CRP and cystatin C. Interestingly, the association was stronger in individuals without traditional CVD risk factors. These results shed more light into the specific role of inflammation in pathophysiology of chronic HF, in addition to well-known risk factors. In a similar manner, Ng et al. [244] conducted a large prospective screening community study, on randomly selected 1360 subjects and determined their plasma MPO and CRP, as well as, urine BNP levels. MPO and CRP concentrations contributed to the diagnostic properties of BNP in detecting left ventricular systolic dysfunction, as confirmed by echocardiography, and maximized specificity up to 94.3% with a negative predictive value of >99% [244]. All three biomarkers were independent predictors of left ventricular systolic dysfunction and plasma MPO showed the best specificity values when considered alone at a cut-off level of 33.9 μg/L. Thus, when determination of MPO is combined with CRP, it adds to the specificity of NT-proBNP screening measurements in the detection of left ventricular systolic dysfunction [244]. In this line, Rudolph et al. [242] showed elevated plasma MPO, elastase, and NT-proBNP levels in patients with impaired LV function. The elevation of MPO concentration was not related to the etiology of HF (ischemic vs nonischemic) or other traditional confounding variables, while MPO levels were related to EF and LV-end diastolic diameter evaluated with echocardiography and only weak correlation was observed between MPO and NT-proBNP plasma levels. In another prospective study, baseline serum MPO levels were correlated with overall

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mortality in a mean follow-up period of 40.9  11.3 months in patients with chronic HF [221]. Positive correlation between elevated MPO levels and NYHA class was detected, while MPO showed only marginal value in predicting all-cause mortality in CHF patients. In combination with NT-proBNP, MPO increased NT-proBNP mortality prediction in the group of patients with intermediate NT-proBNP concentration (between the 25th and 75th percentile). In conclusion, MPO levels might contribute to evaluation of disease severity, whole it shows weak predictive ability. Very recently, MPO was included into the multimarker panel for assessing HF, together with myocyte injury (TnI) [40,245,246], neurohormonal activation (BNP) [11], inflammation (CRP) [247], myocyte stress (ST2) [248], vascular growth and remodeling (sFlt-1) [86], inflammation (CRP) [247], oxidative stress (uric acid [249], MPO [241,250]), and renal dysfunction (creatinine). In a multicenter cohort of 1513 chronic systolic HF patients, parsimonious multimarker score was calculated and its performance in predicting risk of death, cardiac transplantation, or VAD placement was assessed. Patients in the highest tercile of the multimarker score had a 13.7-fold increased risk of adverse outcomes compared to the lowest tercile. Apart from studies that analyzed predictive role of MPO in CHF screening, only few investigated the value of MPO in CHF worsening, such as development of acutely decompensated HF. Unfortunately, obtained results are not encouraging. Namely, Shah et al. [99] provided a report that in a cohort of patients presenting to an emergency department with dyspnea, no differences in MPO were observed between patients with acute decompensated HF and those with chronic HF or apparently healthy subjects. Wu [251] analyzed potential reasons for discrepancies between studies with regard to methodology and sample processing and stability. Although different antibodies were used in various methods [99,220,241], a comparison of methods showed good correlation, suggesting that these antibody differences did not account for the discrepancies. Shih and coworkers [252] further suggested that MPO is reasonably stable and that EDTA is the preferred anticoagulant. Fortunately, the samples used for MPO testing in each of mentioned reports were collected in EDTA tubes. Still, the critical issue found by Wu [251] is the cut-off concentration used to determine pathological results. In both of the reports by Tang and coworkers [220,241], diagnostic utility conferred by MPO concentrations were within

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the reference interval, a situation similar to what was observed when highsensitivity CRP was implemented for cardiovascular risk assessment.

8.3 8-Hydroxy-20 -Deoxyguanosine Among cellular macromolecules, DNA is one of the major ROS targets. When hydroxyl radical or singlet oxygen hydroxylate C-8 position of 20 -deoxyguanosine, marker of oxidative DNA damage, 8-hydroxy-20 deoxyguanosine (8-OHdG) is produced [253–256]. Regarding specific oxidative byproducts which reflect the production of ROS in the failing heart, 8-OHdG seems to have the good potential, since it was detected immunohistochemically in human cardiac tissue of patients with severe DCM [257,258]. Thus, 8-OHdG belongs to the very few oxidative byproducts in serum of CHF patients, which have proven cardiac origin. Namely, Kobayashi and coworkers [259] measured 8-OHdG in the blood from aortic root (Ao) and coronary sinus (CS) in chronic HF patients and controls and found serum 8-OHdG to be significantly higher in the CS than the Ao in chronic HF patients. They also found that urinary 8-OHdG was associated with symptomatic status and cardiac dysfunction in these patients [259]. Moreover, there was a significant correlation between urinary 8-OHdG and LVEF, pulmonary capillary wedge pressure, or left ventricular end-diastolic volume index as well as BNP. Urinary 8-OHdG appears to reflect the clinical severity of CHF on the basis of symptomatic status and cardiac dysfunction. Thus, urinary 8-OHdG is a clinically useful biomarker used to evaluate the severity of CHF, as well as, the status of oxidative stress in patients with CHF, also recently suggested by Szczurek et al. [259,260]. The prognostic significance of urinary 8-OHdG was evaluated by Susa et al. [222], who showed urinary 8-OHdG, together with BNP, to be independent predictors of cardiac events, such as death of worsening of cardiac function (Table 5). It is important to note that treatment with carvedilol might be effective for decreasing the oxidative DNA damage [258]. Indeed, carvedilol treatment in the study of Susa et al. [222] demonstrated significantly decreased urinary 8-OHdG concentration along with the improved NYHA class, LVEF, and BNP concentration after treatment. Despite intriguing results confirming the potential clinical application of urinary 8-OHdG determination, there are still some methodological constraints. Namely, the methodology available up to date for 8-OHdG measurement refers to ELISA kits. Efforts should be made to introduce new biotechnologies (immunochemistry) for the measurement of this compound in everyday practice.

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8.4 Thioredoxin 1 Thioredoxin 1 (Trx1) has a crucial role in maintaining the redox balance in various cells [261]. Trx1 possesses two thiol moieties, which get reducing elements from NADPH in reaction catalyzed by thioredoxin reductase (TR). The reduced Trx1 has ability to reduce disulfide bonds in proteins and help them either to maintain their native structure or to change conformation in response to various stimuli. In this way, NADPH, TR, and Trx1 are form Trx system, and the reducing equivalents generated by this system are consumed to reduce disulfide bonds in proteins. Beside, Trx1 alters S-nitrosylation of cysteine moieties by removing or adding NO. This kind of protein modification also influences its conformation and consequently, protein function. Due to its ability to modify cysteine residues, Trx1 affects a wide array of cellular functions [261]. Thus, Trx1 decreases oxidative stress by reducing peroxiredoxin, which in turn reduces H2O2. Additionally, Trx1 also regulates activities and subcellular localization of transcription factors and intracellular signaling molecules [262]. Regarding functional role of Trx1 in the heart, it should be noted that its expression is increased in response to stress. Several studies performed in animal models showed that Trx1 in the heart [263–265] suppresses pathological hypertrophy. Moreover, Trx1 is essential for ion channel remodeling and increases contractility, angiogenesis [266], and improvement of mitochondrial function [262]. In the view of all beneficial Trx1 effects, attempts have been made for pharmacological application of recombinant Trx1 (r-Trx1). Since r-Trx1 can be easily taken up by cells [267], the idea that r-Trx1 may be useful for treatment of various pathological conditions in the heart, including cardiac hypertrophy, is biologically plausible. As suggested by Matsushima et al. [268], the development of orally active small molecule compounds mimicking the action of Trx1 may eventually allow the use Trx1 for long-term treatment of pathological hypertrophy and HF. First evidence in support of the hypothesis that plasma Trx1 might be useful as biomarker of chronic HF came in 2004 when Jekell et al. [269] compared baseline plasma Trx levels between chronic HF patients and controls. In this study, CHF patients exhibited significantly higher plasma concentration of Trx in comparison to controls, that correlated with severity of disease (NYHA III > NYHA II) and degree of oxidative stress. These findings were confirmed in a recent study of Otaki et al. [223], which provided novel results concerning the prognostic role of Trx1 in CHF. Namely, they demonstrated that Trx1 was an independent predictor of cardiac events and that patients in highest Trx1 tercile had the lowest cardiac event free survival

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during follow-up of 1250 days [223] (Table 5). Additionally, patients with elevated plasma Trx1 had higher levels of renal tubular damage markers. Although the authors were unable to confirm the precise mechanisms of Trx1 secretion in CHF patients, it should be noted that the ROC curve of Trx1 for future cardiac events had better characteristics than that of BNP [223]. Having in mind the pathophysiological significance of thioredoxin in cardiac hypertrophy, which is a hallmark of CHF, the role of this protein in identification of CHF patients, as well as prognostic biomarker requires further testing in longitudinal multicentric studies.

9. FUTURE ASPECTS The interest in microRNAs (miRNAs), a class of small noncoding RNAs, in cardiovascular diseases is increasing. These noncoding RNAs, 18–25-nucleotide-long, have the ability to bind mature mRNA molecules and affect their translation, thus serving as important posttranscriptional modulators of gene expression. Genetic data have identified the roles of miRNAs in basic pathological processes associated with HF, such as apoptosis, fibrosis, myocardial hypertrophy, and cardiac remodeling [270]. To date, miRNA profiling studies, conducted in the human failing heart, have shown significant miRNA alterations with implications in pathogenesis and progression of HF. Furthermore, next-generation sequencing in human failing left ventricles of end-stage HF patients was recently performed and interestingly, the miRNA signatures differed significantly according to pathology preceding HF [271]. Indeed, it has been shown that miRNA signatures corresponded to the clinical diagnosis of HF in about 70% [272]. However, cardiac tissue miRNA signatures have a limited diagnostic value, since the sample is obtained from a cardiac biopsy. On the other hand, a number of studies have focused on the miRNA expression in HF patients peripheral blood samples. Among them, several have pointed to an increase in miR-423-5p, often in combination with a number of other miRNAs, which can be used to identify patients with systolic HF, while the correlation with clinical prognostic parameters was also observed [273]. Furthermore, it was suggested that increased plasma levels of miR-423-5p can be useful in diagnostics of HF, since they correlated positively with NT-proBNP levels [274]. Moreover, another study brought to light two miRNAs that could possibly be used as prognostic markers of the clinical outcome in CHF [275]. The obtained data suggested that the pattern of circulating miRNAs expression may be representative of distinct time

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points during HF progression, and as such, they may be utilized as prognostic tool. Additionally, early evidence indicates that circulating miRNAs could also be used to monitor response to HF treatment [276]. As previously mentioned, several dysregulated miRNAs have been associated to HF, thus the targeted modulation of miRNA expression and activity may be a promising therapeutic approach to improve HF clinical management. The targeted regulation of miRNA pathways could be facilitated by a variety of molecular tools, divided into two main categories: antimiRNAs (antagomiRs) and miRNA mimics.

10. CONCLUSION There are various reasons in favor of biomarker application in HF diagnosis, monitoring, and prognosis. Namely, traditional ways to assess and manage HF might be limited due to subjective interpretation, time limitation and, sometimes, invasive nature of applied methodology. For that reason, the number of potential biomarkers that could enable accurate risk stratification of HF patients and provide reliable information regarding monitoring and prognosis of HF patients is almost exponentially increasing over the years. Advances in functional genomics, proteomics, metabolomics, as well as bioinformatics aid clarify which of the numerous putative biomarkers might be informative with respect to diagnosis, prognosis, and monitoring of therapy in HF. Recently, several novel HF biomarkers have been granted regulatory approval for clinical use and showed to be independently associated with prognosis. However, many of them have limited role in diagnosis, while only few data are available on therapeutic intervention studies. Still, these markers may be used to identify patients at the highest risk for various outcomes. In the process of novel biomarker validation, the data should be obtained from larger multicentric studies. Although validation in at least two adequately sized clinical studies should be viewed as a minimum, biomarkers recommended for routine clinical use in HF by professional society guidelines have demonstrated consistent risk relationships in 10 or more studies. What is more, the benchmark for evaluation of prognostic significance of novel biomarker should consist of findings from multiple studies that utilized prospectively collected samples among HF patients, with well-characterized clinical outcomes, in which the evaluated biomarker is independently associated with the risk of death or death and nonfatal clinical events.

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In order to be clinically useful, a biomarker has to be easily measured at low expense and provide additive information that might influence medical decisions. Besides numerous attempts, standardized assays with satisfactory sensitivity and specificity, and precise cut-off and reference values have not been introduced for many biomarkers as jet. It is also important to note that clinical value of individual biomarkers within the single time points, in both diagnosis and outcome prediction, in HF is limited. Therefore, selective use of these biomarkers within multimarker panels is reasonable in patients for whom a more complete assessment of the absolute risk is desired by the clinician. Moreover, “multimarker” approach integrates information from pathophysiologically distinct processes and may indeed enhance risk stratification in HF (Table 6) [277–282]. When generating multimarker panels, composed of several parallely measured biomarkers, certain facts must be considered. Namely, comparisons of biomarkers determined in the same study population must account for their inherent correlation, meaning that people with high values of one marker will likely have high values of another. Furthermore, the incremental

Table 6 Multimarker Panels in HF Combination of Markers

Clinical Significance

References

H-FABP, MLC-I, TnT, CK-MB

Prognosis of congestive Sugiura HF et al. [52]

H-FABP, BNP

Niizeki Cardiac death and nonfatal cardiac events in et al. [23] CHF

Pro-BNP, hsCRP, MPO

HFrEF

Ng et al. [244]

BNP, CRP, PAI, homocysteine, aldosterone-to-renin ratio, urinary albumin-to-creatinine ratio

Development of HF

Velagaleti et al. [277]

NT-proBNP, hsTnT, sST2

Prognosis in ADHF

PascualFigal et al. [278]

BNP, TnI, hsCRP, MPO, sFlt-1, sTLR-2, creatinine, uric acid

Prediction of adverse events in CHF

Ky et al. [279]

NT-proBNP, hsTnT, sST2

Risk stratification of death in CHF

Lupo´n et al. [280] Continued

130 Table 6 Multimarker Panels in HF—cont’d Combination of Markers

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Clinical Significance

References

NT-proBNP, hsTnT, TIMP-1, GDF-15, Prognosis in CHF IBP-4

Jungbauer et al. [281]

Soluble neprilysin, NT-proBNP, hsTnT, sST2

Bayes-Genis et al. [102]

CHF

NT-proBNP, sST2, MR-proADM, CRP Prognosis in ADHF

Mebazaa et al. [282]

H-FABP, heart fatty acid-binding protein; MLC-I, myosin light chain-I; TnT, troponin T; CK-MB, creatine kinase isoenzyme MB; BNP, B-type natriuretic peptide; MPO, myeloperoxidase; hsCRP, highsensitivity C-reactive protein; PAI, plasminogen activator inhibitor-1; NT-proBNP, N-terminal pro-Btype natriuretic peptide; sST2, soluble isoform of suppression of tumorigenicity 2; TnI, troponin I; GDF15, growth differentiation factor-15; sFlt-1, soluble fms-like tyrosine kinase receptor-1; sTLR2 soluble toll-like receptor-2; TIMP-1, metalloproteinase inhibitor 1; MR-proADM, mid-regional fragment of pro-adrenomedullin; TnI, troponin I.

utility of adding a new biomarker to a known panel of biomarkers has to be estimated by ROC analysis [283]. Hence, the future of biomarker application in HF lies in the multimarker panel strategy, which would include specific combination of biomarkers that reflect different pathophysiological processes underlying HF. Apart from their role in diagnosis and prognosis of HF, application of “multimarker” profiling might contribute to individualized treatment approach in HF patients.

ACKNOWLEDGMENTS The authors would like to acknowledge the assistance of Tatjana Djukic, Sonja Suvakov, and Vesna Coric for technical support.

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Acad. Sci. U.S.A. 101 (2004) 11471–11476, http://dx.doi.org/10.1073/ pnas.0402941101. S. Matsushima, D. Zablocki, J. Sadoshima, Application of recombinant thioredoxin1 for treatment of heart disease, J. Mol. Cell. Cardiol. 51 (2011) 570–573, http://dx.doi. org/10.1016/j.yjmcc.2010.09.020. A. Jekell, A. Hossain, U. Alehagen, U. Dahlstr€ om, A. Rosen, Elevated circulating levels of thioredoxin and stress in chronic heart failure, Eur. J. Heart Fail. 6 (2004) 883–890, http://dx.doi.org/10.1016/j.ejheart.2004.03.003. M.G. Katz, A.S. Fargnoli, R.D. Williams, A.P. Kendle, N.M. Steuerwald, C.R. Bridges, MiRNAs as potential molecular targets in heart failure, Future Cardiol. 10 (2014) 789–800, http://dx.doi.org/10.2217/fca.14.64. S. Leptidis, H. El Azzouzi, S.I. Lok, R. de Weger, S. Olieslagers, S. Olieslagers, N. Kisters, G.J. Silva, S. Heymans, E. Cuppen, E. Berezikov, L.J. De Windt, P. da Costa Martins, A deep sequencing approach to uncover the miRNOME in the human heart, PLoS One 8 (2013) e57800, http://dx.doi.org/10.1371/journal.pone.0057800. S. Ikeda, S.W. Kong, J. Lu, E. Bisping, H. Zhang, P.D. Allen, T.R. Golub, B. Pieske, W.T. Pu, Altered microRNA expression in human heart disease, Physiol. Genomics 31 (2007) 367–373, http://dx.doi.org/10.1152/physiolgenomics.00144.2007. Y. Goren, M. Kushnir, B. Zafrir, S. Tabak, B.S. Lewis, O. Amir, Serum levels of microRNAs in patients with heart failure, Eur. J. Heart Fail. 14 (2012) 147–154, http://dx.doi.org/10.1093/eurjhf/hfr155. K.-L. Fan, H.-F. Zhang, J. Shen, Q. Zhang, X.-L. Li, Circulating microRNAs levels in Chinese heart failure patients caused by dilated cardiomyopathy, Indian Heart J. 65 (2013) 12–16, http://dx.doi.org/10.1016/j.ihj.2012.12.022. L. Qiang, L. Hong, W. Ningfu, C. Huaihong, W. Jing, Expression of miR-126 and miR-508-5p in endothelial progenitor cells is associated with the prognosis of chronic heart failure patients, Int. J. Cardiol. 168 (2013) 2082–2088, http://dx.doi.org/ 10.1016/j.ijcard.2013.01.160. B.A. Dickinson, H.M. Semus, R.L. Montgomery, C. Stack, P.A. Latimer, S.M. Lewton, J.M. Lynch, T.G. Hullinger, A.G. Seto, E. van Rooij, Plasma microRNAs serve as biomarkers of therapeutic efficacy and disease progression in hypertension-induced heart failure, Eur. J. Heart Fail. 15 (2013) 650–659, http:// dx.doi.org/10.1093/eurjhf/hft018. R.S. Velagaleti, P. Gona, M.G. Larson, T.J. Wang, D. Levy, E.J. Benjamin, J. Selhub, P.F. Jacques, J.B. Meigs, G.H. Tofler, R.S. Vasan, Multimarker approach for the prediction of heart failure incidence in the community, Circulation 122 (2010) 1700–1706, http://dx.doi.org/10.1161/CIRCULATIONAHA.109.929661. D.A. Pascual-Figal, S. Manzano-Ferna´ndez, M. Boronat, T. Casas, I.P. Garrido, J.C. Bonaque, F. Pastor-Perez, M. Valdes, J.L. Januzzi, Soluble ST2, high-sensitivity troponin T- and N-terminal pro-B-type natriuretic peptide: complementary role for risk stratification in acutely decompensated heart failure, Eur. J. Heart Fail. 13 (2011) 718–725, http://dx.doi.org/10.1093/eurjhf/hfr047. B. Ky, B. French, W.C. Levy, N.K. Sweitzer, J.C. Fang, A.H.B. Wu, L.R. Goldberg, M. Jessup, T.P. Cappola, Multiple biomarkers for risk prediction in chronic heart failure, Circ. Heart Fail. 5 (2012) 183–190, http://dx.doi.org/10.1161/ CIRCHEARTFAILURE.111.965020. J. Lupo´n, M. de Antonio, A. Gala´n, J. Vila, E. Zamora, A. Urrutia, A. Bayes-Genis, Combined use of the novel biomarkers high-sensitivity troponin T and ST2 for heart failure risk stratification vs conventional assessment, Mayo Clin. Proc. 88 (2013) 234–243, http://dx.doi.org/10.1016/j.mayocp.2012.09.016. C.G. Jungbauer, J. Riedlinger, D. Block, S. Stadler, C. Birner, M. Buesing, W. K€ onig, G. Riegger, L. Maier, A. Luchner, Panel of emerging cardiac biomarkers contributes

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for prognosis rather than diagnosis in chronic heart failure, Biomark. Med 8 (2014) 777–789, http://dx.doi.org/10.2217/bmm.14.31. [282] A. Mebazaa, S. Di Somma, A.S. Maisel, A. Bayes-Genis, ST2 and multimarker testing in acute decompensated heart failure, Am. J. Cardiol. 115 (2015) 38B–43B, http://dx. doi.org/10.1016/j.amjcard.2015.01.039. [283] R.S. Vasan, Biomarkers of cardiovascular disease: molecular basis and practical considerations, Circulation 113 (2006) 2335–2362, http://dx.doi.org/10.1161/ CIRCULATIONAHA.104.482570.

CHAPTER FIVE

Advances in Clinical Mass Spectrometry D. French1 University of California San Francisco, San Francisco, CA, United States 1 Corresponding author: e-mail address: [email protected]

Contents 1. 2. 3. 4.

Introduction Gas Chromatography-Mass Spectrometry Liquid Chromatography-Tandem Mass Spectrometry Sample Preparation 4.1 Protein Precipitation 4.2 Solid-Phase Extraction 4.3 Liquid–Liquid Extraction 4.4 Supported Liquid Extraction 5. Clinical Applications of Mass Spectrometry 5.1 Therapeutic Drug Monitoring 5.2 Toxicology 5.3 Steroid Hormones 5.4 Thyroid Hormones 5.5 Inborn Errors of Metabolism 6. Recent Advances in Clinical Mass Spectrometry 6.1 Microbiology Applications 6.2 Protein and Peptide Analysis 6.3 Tissue Imaging 7. Conclusions References

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Abstract Although mass spectrometry has been used clinically for decades, the advent of immunoassay technology moved the clinical laboratory to more labor saving automated platforms requiring little if any sample preparation. It became clear, however, that immunoassays lacked sufficient sensitivity and specificity necessary for measurement of certain analytes or for measurement of analytes in specific patient populations. This limitation prompted clinical laboratories to revisit mass spectrometry which could additionally be used to develop assays for which there was no commercial source. In this chapter, the clinical applications of mass spectrometry in therapeutic drug monitoring,

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toxicology, and steroid hormone analysis will be reviewed. Technologic advances and new clinical applications will also be discussed.

1. INTRODUCTION In the past decade, mass spectrometry (MS) has received a lot of attention from the clinical laboratory community. Gas chromatography-mass spectrometry (GCMS) has been used for decades in clinical laboratories for toxicology, therapeutic drug monitoring (TDM), and steroid hormone testing but over the last 10 years, liquid chromatography tandem mass spectrometry (LC-MS/MS) has become increasingly popular for clinical applications. Further, high-resolution mass spectrometry (HR-MS) has changed the way we think about clinical mass spectrometry in terms of untargeted analysis and different types of ionization utilized with these types of instruments allow for great flexibility for different clinical applications. In order to implement mass spectrometry assays, the clinical laboratory has to develop the assay and complete a full validation as these assays are considered laboratory developed tests (LDTs). Currently, the validation must include documentation of linearity, precision, sensitivity, specificity, accuracy, reference intervals, reportable range, interfering substances, carryover, and stability [1]. Mass spectrometry-specific parameters that should also be included in validation are determination of matrix effects (ion suppression) and extraction recovery [2]. A comprehensive guidance to method development and validation can be found in the CLSI C62-A document published in October 2014. As the Food and Drug Administration (FDA) has decided to assert its authority to regulate LDTs as medical devices, only time will tell as to the extent of the changes in clinical and analytical validation and postvalidation necessary for a laboratory to implement an LDT for clinical testing [3].

2. GAS CHROMATOGRAPHY-MASS SPECTROMETRY Gas chromatography (GC) is a separation technique using gas flow through a glass or metal column that separates compounds based on both volatility and interaction with the liquid stationary phase [4]. The flow from the GC containing the analytes of interest is ionized in the source by electron (EI) or chemical ionization (CI) [5]. The ions enter the quadrupole mass

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Fig. 1 A GC–MS fragmentation spectrum of cocaine. The molecular ion is at m/z 303, and prominent ions that could be used for SIM analysis are at m/z 182 and 82 [6]. An example of ion ratio calculations is shown.

spectrometer, where ions of a specific mass (precursor ion) can be fragmented (EI) before they enter the MS. This is a form of “hard” ionization and so compounds show a lot of fragmentation [5]. The precursor ion can still be visible on the spectrum and, along with two or more product ions, is monitored and ratios of their abundance aid in the identification of the compound of interest (SIM: selected ion monitoring) [5,6]. Ion ratios are useful to show specificity in a method as they should remain consistent within the calibrators, quality control, and patient samples. If the ion ratios are not the same, it could indicate that there is an interference in the method [4]. An example is shown of cocaine in Fig. 1, where the precursor ion of mass to charge ratio (m/z) 303 and the fragment ions of m/z 182 and 82 are monitored [7]. The ion ratios are calculated to verify that it is actually cocaine that is being measured.

3. LIQUID CHROMATOGRAPHY-TANDEM MASS SPECTROMETRY Liquid chromatography (LC) is a technique that separates compounds in a complex liquid mixture on a chromatography column based on the polarity of the compounds of interest in the sample and the interaction they have with the column [2,5]. A number of different types of column with different functional groups exist that function to separate compounds more efficiently depending on the structure. When coupled to a tandem (or triple quadrupole) mass spectrometer, the flow from the LC system is ionized

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before it enters the mass spectrometer. Ionization is most commonly accomplished with electrospray (ESI) or atmospheric pressure chemical ionization (APCI), but atmospheric pressure photoionization (APPI) has also been utilized for clinical applications [2,5]. Selected reaction monitoring (SRM) is commonly applied in clinical laboratories for targeted, quantitative analysis [8]. In SRM, the ions enter the first quadrupole, where a precursor ion is selected. Ions with this m/z then enter the collision cell (quadrupole 2), where they are fragmented by collision-activated dissociation. In quadrupole 3, fragment ions with specific m/z are selected. The precursor ion/fragment ion pair is called a mass transition. It is best practice to monitor two mass transitions per analyte and internal standard, and then ion ratios of the analyte abundance can be calculated between the two mass transitions adding another layer of selectivity to the method [2,9]. As with SIM, the ion ratios for SRM will remain consistent between the calibrators, quality control, and patient samples. Deviations from the expected ion ratio could be indicative of an interference in the LC-MS/MS method. An example can be seen in Fig. 2 for testosterone, where the precursor ion m/z is 289, and the fragment ion m/z is 97 and 109.

Fig. 2 The extracted ion chromatogram from SRM analysis of testosterone using the molecular ion of m/z 289 and fragment ions of m/z 97 and 109. Blue chromatographic trace is transition 289/97 and red trace is transition 289/109.

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4. SAMPLE PREPARATION Before mass spectrometry analysis, patient samples, whether urine, serum, plasma, or other fluids, generally require a cleanup step or an extraction process. For urine samples, this can be as simple as a dilution, but depending on the application, a more elaborate cleanup process may be required. The most commonly used extraction methods are protein precipitation (PPT) which can be combined with online extraction, solid-phase extraction (SPE), liquid-liquid extraction (LLE), and supported liquid extraction (SLE).

4.1 Protein Precipitation PPT involves the addition of an organic solvent, such as methanol or acetonitrile to a patient sample. The organic solvent causes the proteins in the patient sample to precipitate out of solution, and after centrifugation, the proteins form a pellet at the bottom of the tube. The supernatant can then be both dried down and reconstituted or can be directly injected onto the LC system for MS analysis. Zinc sulfate is also commonly added to the organic solvent. This procedure was initially described when using whole blood but has subsequently been utilized with plasma and serum [10–14]. Although the exact mechanism of action is not completely understood, it is thought that the zinc cations form insoluble salts with the negatively charged protein molecules at a pH above the isoelectric point of the protein, thus enhancing PPT [11]. An advantage of PPT is that it is very quick, but a disadvantage is that the sample remains somewhat unclean and that can cause issues with matrix effects (ion suppression) in MS methods potentially leading to loss of both sensitivity and reproducibility [15]. Another cleanup step that is often combined with PPT is online extraction [16–18]. After the PPT, the supernatant is injected onto the LC system which has an extraction column attached to it. This column can have various different selectivity (e.g., ionexchange, reversed phase) and so is chosen based upon the retention of the analytes that are being measured. In online extraction, the sample is injected onto the column, the column is washed with either solvent or aqueous solution so that the analytes of interest are retained by the column, but the matrix components are washed away to waste. Then the flow from the extraction column is diverted to the analytical column for LC and then MS analysis [16–18].

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4.2 Solid-Phase Extraction In SPE, the patient sample is applied to a column containing a sorbent with selectivity such that it will retain the analytes of interest [19]. Examples include anion exchange, cation exchange, and mixed-mode sorbents. The SPE columns are conditioned, the patient sample is added, the column is washed and then the analytes are eluted from the column [19]. The wash and elution steps can be optimized for the analyte of interest. After elution, the samples can be dried down and reconstituted or directly injected onto the GC or LC system, or in online SPE with LC, the samples are injected directly onto the analytical chromatographic column [19]. Using SPE, the samples that are injected onto the GC or LC system are very clean and have minimal matrix remaining [15]; however, as can be appreciated, the SPE process is labor intensive.

4.3 Liquid–Liquid Extraction In LLE, two immiscible liquids are mixed together, and there is an extraction or partitioning of components from one liquid phase into the other liquid phase. In this way, analytes of interest will partition into one of these liquids leaving matrix and other unwanted components in the other, discarded liquid [19]. The liquids that are commonly used are the aqueous patient sample such as serum, and an organic solvent such as hexane, ethyl acetate, or methyl tert-butyl ether [19,20]. In clinical applications, analytes of interest usually partition into the organic phase from the aqueous phase, the organic solvent is dried down and the analytes reconstituted before MS analysis. LLE is labor intensive, although it is possible to automate this procedure, but the samples that are injected onto the LC system are very clean which can help increase the sensitivity and precision of the method [15].

4.4 Supported Liquid Extraction A relatively new advancement in the sample preparation field is SLE. This method is similar to both SPE and LLE in that a sorbent is used that initially retains the whole-patient sample, but after allowing the sorbent to rest briefly, the analytes of interest are eluted from the sorbent with a solution optimized for the analytes of interest [21,22]. SLE cleans the sample in a manner as effective as LLE, the procedure is similar to SPE, but it is far less labor intensive than either of these methods [22].

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5. CLINICAL APPLICATIONS OF MASS SPECTROMETRY 5.1 Therapeutic Drug Monitoring TDM is necessary for drugs that have a narrow therapeutic concentration range, where if the concentration in a patient is too low, the drug is not efficacious, but if the concentration is too high, the patient could have potentially very toxic side effects [23]. Examples of drugs where TDM is implemented include tacrolimus, cyclosporine, voriconazole, and busulfan [24–26]. There are immunoassays available for a number of drugs that require TDM on most manufacturers’ platforms which allows clinical laboratories to easily integrate these assays into their normal workflow. However, some of these drugs are not used frequently enough for large immunoassay manufacturers to devote the time and money to develop assays. To date, there are no FDA-approved immunoassays available for drugs such as busulfan and voriconazole, and the only FDA-approved immunoassay for everolimus has to be run using third party reagents as a user-defined test on an open immunoassay or chemistry system. This leads laboratories to either send samples to reference laboratories or develop their own methods. Sending samples to reference laboratories can have a significant impact on turn-around time, requires temperature-controlled shipping, can impact the stability of the sample, and is costly. Therefore, mass spectrometry is a viable option to be able to implement these assays in-house. 5.1.1 Immunosuppressants The first, and currently only, FDA-approved mass spectrometry assay is the MassTrak Immunosuppressants kit that measures tacrolimus [27]. In order to retain its FDA-approved status, this kit has to be used as part of a total solution for a clinical laboratory that includes the LC system, the MS, software, and reagent kit. The advantage of using this solution is that the clinical laboratory does not need expertise to develop the method, and they would only have to verify assay performance instead of having to fully validate the assay if it were a LDT [1,2]. A disadvantage is that as mentioned earlier, this tacrolimus assay is the only FDA-approved assay and so the laboratory would have to develop and validate any other assays they would want to implement and they would be considered LDTs. Further, if other analytes were added into the tacrolimus method, this would make it an FDA-modified test or potentially an LDT, and again would require full validation [1,2].

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One study compared the results from the MassTrak immunosuppressants LC-MS/MS kit to an established tacrolimus immunoassay [28]. They found that the correlation between patient results was acceptable, but the MS-based kit had a negative bias of, on average, 18.5% compared to the immunoassay method. Although the authors tried to determine which assay was correct using a certified tacrolimus reference material, they were not successful [28]. The immunosuppressants tacrolimus, sirolimus, and cyclosporine are commonly monitored in patients who have undergone solid organ transplants in whole-blood samples run on independent immunoassays in clinical laboratories [24,28,29]. The main advantage of immunoassays is that they are easy to run and offer high-throughput and quick turn-around times which is important in TDM. Prior to immunoassay analysis, a sample extraction process has to be carried out on the whole-blood sample, and depending on the manufacturer of the immunoassay, this can vary between the different immunosuppressant drugs. Commonly the extraction process involves taking a sample of whole blood and adding a PPT reagent. Depending on the assay, a heating step may be required. The samples are then vortexed to mix them, and then centrifuged. An aliquot of the supernatant is then taken and analyzed on the immunoassay instrument. An advantage of mass spectrometry is that one assay can be developed for all of these immunosuppressant drugs together, which unifies the sample preparation process and so can improve workflow in the laboratory compared to immunoassay [29–31]. The sample volume requirements for LC-MS/MS methods are also generally lower than for immunoassay (e.g., 50 μL vs 200 μL for tacrolimus) [32,33]. Further, with improvements in online extraction, the MS user can essentially load the samples and walk away. When using online extraction, typically the whole-blood sample has to be aliquoted, and either injected straight onto the online extraction column or a PPT reagent may be added before injection [34]. Another advance in sample preparation is the availability of liquid handlers, which can automate most of the manual pipetting steps which would aid in both immunoassay and MS analysis for immunosuppressants [35]. A challenge of immunoassay analysis of immunosuppressants is the potential for interference in these methods that involves the presence of metabolites. These drugs are metabolized by CYP3A4 (cyclosporine) and CYP3A5 (tacrolimus and sirolimus) which are polymorphic enzymes, and could alter the concentration of both parent drug and metabolites in certain individuals [24]. Different immunoassays may also detect different

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Fig. 3 The structures of sirolimus and everolimus.

metabolites to different degrees and therefore, the measured concentration may not be accurate [29]. Contrary to this, MS methods are capable of detecting the parent drug and the metabolites that are produced independently of each other. Further, monitoring metabolites may allow determination of potentially more toxic metabolites vs “normal” metabolism which would aid in individualizing treatment for a given patient [29,34]. Due to the structural similarity between sirolimus and everolimus (Fig. 3), there is significant cross-reactivity between the immunoassays for these compounds. Therefore, if a patient is transitioning between these two drugs, their blood would have to be run on a MS method that independently quantifies sirolimus and everolimus to ensure that accurate concentrations of each drug are determined. On the other hand, this cross-reactivity can allow everolimus concentrations to be monitored using the sirolimus immunoassay. A mathematical equation has to be used to determine the correct everolimus concentration since there is not 100% cross-reactivity [36]. The only available FDA-approved everolimus immunoassay has to be run as a third party user-defined assay on major manufacturer chemistry analyzers, and so this would allow laboratories who do not have a chemistry analyzer that is open-channel, or do not have the capability to develop a MS method, to use an already FDA-approved assay (sirolimus) as a LDT. However, this would require a full analytical validation [1]. A new development in the analysis of tacrolimus has been the extraction of this drug from dried blood spots followed by analysis by LC-MS/MS [37,38]. Owing to increases in the sensitivity of MS/MS instruments, smaller sample volume is allowing analysis of lower concentrations of clinically relevant compounds. Since patients taking tacrolimus are monitored

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indefinitely, the concept of collecting a blood sample at home and mailing it to the laboratory instead of having to go to a blood-draw station and having a venipuncture is considerably more appealing. It may also aid in patient testing compliance as it reduces the time spent, and potentially the travel cost to the patient [37,38]. A challenge of dried blood spot analysis is extracting the drug from the blood spot. In one study, the spot was punched out, homogenized, and then the proteins were extracted using a methanol and zinc sulfate PPT containing internal standard [37], and in another, an acetonitrile and zinc sulfate PPT containing internal standard were used [38]. Tacrolimus is typically measured at the trough concentration with a therapeutic target concentration of 5–15 ng/mL. In these studies, a limit of quantitation of 1 and 1.2 ng/mL was obtainable when extracting tacrolimus from dried blood spots, with clinically acceptable precision and accuracy [37,38]. Tacrolimus was found to be stable in dried blood spots for 1 week at room temperature and refrigerated at 4°C [37]. In another study, cyclosporine, tacrolimus, sirolimus, and everolimus were analyzed from dried blood spots in a method that showed clinically acceptable precision, accuracy, and limits of quantitation [39]. Further, this group determined that the hematocrit of the blood sample had a significant impact on the results with a low hematocrit (20%) causing a negative bias of 20% and 28% for sirolimus and everolimus, respectively. They also found that if a high sirolimus or everolimus concentration sample was combined with a low hematocrit (25%), this could affect the extraction efficiency of the drugs from the filter paper [39]. Analysis of tacrolimus in dried blood spots has also been taken a step further by a group that used paper spray-tandem mass spectrometry. This technique ionizes the tacrolimus directly from the dried blood spot without extraction, or chromatography, with a run-time of 3 min, enabling fastthroughput of these samples and reduction in the consumption of solvents [40]. The assay had clinically acceptable precision and accuracy and patient results compared well between this method, a LC-MS/MS method and an immunoassay. However, a whole-blood sample from venipuncture is still required followed by addition of internal standard before the laboratory spots the blood onto the filter paper [40]. 5.1.2 Busulfan Busulfan is a drug used in patients before undergoing a hematopoietic stem cell transplant as a myeloablative conditioning regimen [41]. Patients receiving busulfan are typically monitored using pharmacokinetic sampling at

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different time points after drug administration due to significant interindividual variation in clearance and a narrow therapeutic range [26,42,43]. There are currently no automated FDA-approved immunoassays available for busulfan and so the only option for clinical laboratories is to send patient samples out to a reference laboratory, or to develop a method using GC- or LC-MS or MS/MS in the laboratory [44,45]. Busulfan can be given at various time intervals, for example, every 6, 12, or 24 h for 4 days depending on the dosing protocol. Since turn-around time for busulfan results is important as the next dose has to be given on time, sending samples to a reference laboratory is not ideal and can be costly. There are a number of reports documenting MS methods developed to measure busulfan, predominantly using GC-MS [44,46] or LC-MS/MS [18,45,47–50]. The GC-MS methods tend to use a higher patient sample volume than the LC-MS/MS methods, and further, they use LLE which would produce a very clean sample but increases the analysis time in the laboratory [44,46]. The LC-MS/MS methods predominantly use PPT which is a faster extraction procedure, but does not clean up the samples as well as other methods [45,47]. Further, LC-MS/MS methods tend to have shorter analytical run times than the GC-MS methods, from 2 to 5 min compared to 6–18.5 min [44,46,49,50]. As mentioned earlier, turn-around time is very important in busulfan analysis so any reduction in sample preparation and analytical run time is advantageous. As multiple samples are drawn from patients receiving busulfan, an advantage of using LC-MS/MS is that the method can be developed using only a small sample volume, for example, 50 μL [45,47]. This is of particular benefit to pediatric patients who may get six blood samples drawn over a period of 6 h in order to sufficiently determine the area under the curve and steady-state concentration of this drug so as to optimize the next busulfan dose [26]. With the advent of MS instruments with increased sensitivity, the sample volume could potentially be reduced even further. One group reported using dried blood spots for analysis of busulfan which would reduce the sample volume requirements and therefore be of great benefit in pediatric patients. However, since busulfan is normally measured in plasma, new therapeutic targets may have to be established for whole-blood analysis [51]. 5.1.3 Antifungals Azole antifungal drugs such as voriconazole, posaconazole, ketoconazole, fluconazole, and itraconazole are used in patients primarily to treat invasive aspergillosis and/or candidiasis infections [52,53]. Since these drugs exhibit

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large intra- and interindividual variability due to metabolism by cytochrome P450 enzymes, dosing when fasting vs after a meal, and drug–drug interactions, TDM is recommended when they are prescribed [52]. A third party immunoassay is available for voriconazole measurement that can be implemented on major vendor’s chemistry analyzers; however, it is not yet FDA-approved meaning the laboratory would have to do a full analytical validation should they wish to implement this assay [1,54]. An advantage of using this immunoassay is that since it is performed on random access chemistry analyzers, testing can be performed 24/7 which would improve the turn-around time over batched MS methods. The lack of available immunoassays for antifungal drugs compels clinical laboratories to either send samples for analysis to reference laboratories or to develop their own methods using high-performance liquid chromatography (HPLC), or LC-MS, or LC-MS/MS [55–59]. The majority of published LC-MS/MS methods use serum or plasma for analysis of one or more antifungals, and metabolites, and the required sample volume ranges from 5 to 200 μL, which is reasonable even for pediatric patients [58–62]. A disadvantage of using MS-based methods over immunoassay methods is the requirement for sample preparation. For the antifungal drugs, sample preparation is mostly kept to a minimum with a number of studies utilizing PPT [58,62]. However, simplifying the sample preparation in this way does not eliminate all of the matrix components that can cause suppression of the MS signal, for example, phospholipids, which can add unwanted variation to the method [15]. Some authors have employed LLE, SLE, or online extraction after PPT, to help eliminate these matrix components [59,63,64]; however, this increases the turn-around time of the assay. A published LC-MS method used 50 μL of plasma spotted on a dry sample spot device for analysis of voriconazole, posaconazole, and itraconazole and found it stable for up to 2 weeks [57]. This type of sample collection device would obviate the need for, and cost of temperature-controlled sample transportation for sending samples to reference laboratories for analysis by MS methods. In another study, dried blood spot analysis of voriconazole, fluconazole, and posaconazole was found to be suitable for TDM of these triazoles by LC-MS/MS [65]. Patients that are prescribed antifungal drugs are most likely immunocompromised and may be critically ill. Therefore, a reduction in the blood volume taken from the patient would be an obvious advantage of dried blood spot sampling, especially in pediatric patients. A further advantage is the perceived reduction in pain experienced by

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patients in dried blood spot sampling vs venipuncture; although critically ill, patients in a hospital would likely have a central line for blood sampling (pain perception was recorded by patient questionnaire) [65]. If the patients are released from hospital while still prescribed these drugs, DBS sampling would allow TDM to continue by the patient being able to self-administer a finger-stick, collect the blood spot on the card, and ship the DBS card to the laboratory. Since it is possible to measure all of these antifungal drugs in one MS method, the workflow is not as challenging for the laboratory to implement as it would be if an assay had to be developed for each drug independently, although a complete analytical validation would be necessary for each drug within the method. Further, isavuconazole is a new azole drug that was approved for use in the treatment of invasive aspergillosis and mucormycosis in 2015. Currently only one reference laboratory offers testing for this drug, limiting the availability for clinical laboratories and increasing the turnaround time over offering this assay in-house. However, this drug could potentially be added into a current azole MS method and analytically validated, allowing the workflow to remain similar which is a great advantage of this technology. The only additional work for the laboratory would be to manufacture new lots of calibrators and quality control material containing isavuconazole, or purchase them from a vendor.

5.2 Toxicology Clinical toxicological analysis has historically been carried out by thin-layer chromatography (TLC), radioimmunoassay, LC with ultraviolet detection, and/or GC-MS [66,67]. In the advent of enzyme-based immunoassay technology, it became common practice to utilize immunoassay screening followed by GC-MS confirmation if the immunoassay screen was positive [68]. Immunoassay screening involves separate screens for each class of compounds, for example, opioids, amphetamines, and benzodiazepines. The advantages of this technique are that it is carried out on a random urine sample and it is rapid. For patients presenting to the Emergency Department, these immunoassay screens can give clinicians information regarding their patients in a short time frame allowing more timely intervention. A disadvantage of this technique is that immunoassays do not give compound-specific information, and for some of these assays, there is crossreactivity with other drugs that can be obtained over-the-counter. An example is dextromethorphan and diphenhydramine cross-reacting with

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Fig. 4 The structures of phencyclidine, dextromethorphan, and diphenhydramine.

phencyclidine immunoassays [69] (Fig. 4). However, one thing to note is that the cross-reactivity is assay, and manufacturer, specific and some information regarding this can be found in the package insert of the immunoassay reagents (although the information presented is not necessarily all encompassing) [70]. Once an immunoassay screen has been carried out and the result is positive, it is common to analyze the same urine sample on another, more specific methodology to confirm what com-pound (s) are causing the positive; commonly called a drug confirmation assay [68]. This is generally carried out by GC-MS using SIM analysis [4], or more recently using SRM on LC-MS/MS instruments [4]. For example, if an opiate immunoassay is carried out on a urine sample and it is positive, an MS assay run on the same urine sample could confirm that it was in fact morphine and codeine that are in the sample. One disadvantage of using GC-MS or LC-MS/MS for toxicological analysis is that these assays are targeted. This means that they only detect the drugs that the method was designed to detect. For example, an opiate confirmation method could be developed to include morphine, codeine, hydromorphone, and hydrocodone. But if a patient is taking oxycodone, this assay will not detect this drug [4]. In order to circumvent both federal drug enforcement laws and drug testing (e.g., workplace or medical), illegal drug manufacturers constantly change the structures of currently regulated drugs or add new compounds

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forming what are known as “designer drugs” [71]. Examples include synthetic cannabinoids such as “spice” herbal incense compounds and new stimulant agents such as “bath salts.” “Spice” or “K2” products are used in the same way as Δ9-tetrahydrocannabinol (THC; marijuana) in that they are smoked or used in vape pens or hookah. These products are sold as “Crazy Monkey,” “Mr Happy,” “Crazy Clown,” and others and contain synthetic cannabinoids such as PB-22, JWH-018, JWH-073, AB-CHMINACA, and ADB-PINACA [72–76]. They affect the same cannabinoid receptor as THC (CB1), but they can be much more potent [74]. Although products such as “spice” are commonly perceived to be safe since they are sold over-the-counter in head shops or on the internet, there are a number of published case reports citing symptoms such as anxiety, acute coronary syndrome, acute kidney injury, seizures, psychosis, and even death in patients that are subsequently found to have smoked or ingested these products [72,73,77]. Bath salts or “legal highs” are also sold in head shops and on the internet as products such as “Vanilla Sky,” “White Lightning,” and “Cloud 9,” but reports have been published citing symptoms such as peripheral vasoconstriction, seizures, acute myocardial infarction, rhabdomyolysis, and death in patients who have used these products [71,78,79]. These compounds are used to mimic the effects of methamphetamine and methylenedioxymethylamphetamine (MDMA). The major components of bath salts are synthetic cathinones, but other classes of drug such as piperazines have also been found to be contained within them [78–80]. These compounds are agonists to α- and β-adrenergic receptors and cause sustained release of norepinephrine, serotonin, and dopamine causing stimulatory and hallucinogenic effects such as tachycardia and elevation in mood followed by depression, psychosis, and suicidal thoughts [71,78,79]. A challenge for Emergency Department physicians is to deduce what their patients have taken when they present to the ED. To further complicate this diagnosis, designer or synthetic drugs may or may not cross-react with existing immunoassays [81]. MS assays in use in clinical laboratories for toxicology testing tend to be targeted, in that the laboratory has prior knowledge of the drugs that are to be included in the method [82]. Due to this, targeted GC-MS or LC-MS/MS assays (using SIM and SRM, respectively) are generally not designed to detect the newest drugs that are being sold for recreational use [4,83]. It is certainly easier to add a new designer drug to an existing GC-MS or LC-MS/MS method than to develop a new immunoassay, assuming that a drug reference standard

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material is available. This is therefore a benefit of MS technology vs immunoassay in toxicological analysis. Somewhat recent advances in MS technology allow sensitive, untargeted analyses to be carried out by HR-MS, and it has been shown that this type of analysis on these instruments can compare favorably to targeted analysis by LC-MS/MS [84]. Examples of HR-MS are time-of-flight (TOF) or orbitrap MS [4,85]. These instruments can detect distinct molecular formulas by measuring the molecular weight of the unfragmented molecular ion of a compound to four decimal places without prior knowledge of what the compound is [84,86]. Fragmentation may also take place allowing mass spectra to be collected [84,86]. Once a molecular formula is established, accurate mass databases or even public search engines can be used to identify the unknown compound; or in the case of mass spectra, there are also spectral databases that can be searched [84,86,87]. In order to conclusively determine that a compound is indeed present, a drug reference standard is required so that the LC retention time can be matched, as well as the molecular ion and mass spectra. However, a “presumptive” positive result deduced from only a molecular formula or spectral match may give a clinical toxicologist enough information if used in the context of the clinical presentation of the patient [4]. One issue with untargeted analysis is how to analytically validate such a method in order to show it is acceptable for clinical use, which is still under discussion. Toxicology testing is routinely carried out in urine and serum. The detection window for drugs in these matrices depends on the half-life of the drug in the body, but it tends to vary from minutes to a few days. One method of lengthening the drug detection window to weeks, months, or even years is to carry out drug analysis in hair samples. An advantage of using hair samples is that they are not subject to easy, undetectable adulteration as a urine sample could be, and further, samples are easy to collect. There are important issues that have to be considered when using hair samples such as contributions from the external environment, variable growth rates between individuals, differences in drug binding between hair types and the effect of washing hair on the stability of the drugs [88,89]. It has been demonstrated that it takes approximately 4–5 weeks after the drug exposure for the drug to emerge from the scalp [90]. Current recommendations document that a strand of hair should be cut as close as possible to the scalp, and then the hair cut into three segments of 2 cm each, and each segment analyzed independently [90]. Sample preparation is challenging for hair analysis and involves mincing the hair samples, washing and digestion before the

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drugs are extracted by common methods such as LLE [91,92] and SPE [93] or both [94]. Hair analysis is currently predominantly confined to the forensic toxicology and antidoping fields, but it may have clinical applicability [89,95]. To date, published LC-MS/MS methods describe hair analysis for hydrocodone and hydromorphone [96], psychoactive drugs including benzodiazepines, antidepressants, and antipsychotics [97], 35 licit and illicit drugs including opioids, amphetamines, cocaine, and benzodiazepines [94], methadone and metabolites [91], buprenorphine and norbuprenorphine [92], amphetamine-type-stimulants including synthetic cathinones and piperazines [98], and ethyl glucuronide [93], all of which could potentially be useful clinically, for example, in monitoring compliance and abstinence from drugs of abuse in patients prescribed pain medication.

5.3 Steroid Hormones Steroid hormones are, analytically, one of the most challenging groups of compounds to analyze in the clinical chemistry laboratory. They are formed from a common cholesterol precursor and can vary from each other by just the position of a hydroxyl group, making analysis by both immunoassay and MS challenging. Further, some of these hormones, such as testosterone and estradiol, are found at extremely low concentrations in patient serum (ng/dL or pg/mL concentrations, respectively). Steroid hormones are most commonly measured clinically in serum, urine, and saliva [99–101]. Steroid hormones have been analyzed for clinical purposes by a number of methodologies historically. First, they were measured by GC-MS, then radioimmunoassay, followed by a return to GC-MS, automated immunoassay, and finally more recently, LC-MS/MS. The steroid hormone pathway was first elucidated by GC-MS analysis; however, in the advent of radioimmunoassay, analysis became more sensitive, although the sample preparation remained similar, and a number of laboratories began using this technology instead [102,103]. However, the use, and disposal, of radioactive material made this technology cumbersome and so some clinical laboratories moved to, or back to, GC-MS analysis [102,103]. When automated immunoassay instruments were introduced into the clinical laboratory, steroid hormone assays using this technology were also developed. The advantage of the immunoassay was that no sample preparation was required, and patient serum samples could just be placed on the instrument [102,103]. However, it was soon discovered that due to the lack of sample preparation and the cross-reactivity of the antibodies in these assays for similarly

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structured compounds, they were not as specific and sensitive as radioimmunoassays or GC-MS. This was illustrated in a number of published papers, and one example is dehydroepiandrostenedione sulfate cross-reacting in immunoassays designed to detect only testosterone [102–106]. Before steroid hormones can be analyzed by GC-MS, serum, urine, or saliva samples have to be extracted (commonly by LLE) and derivatized in order to make them more volatile and to increase the thermal stability [107]. This adds time and cost to the method, but increases both sensitivity and chromatographic resolution [107]. However, using LC-MS/MS, the steroid hormones no longer need to be derivatized (although derivatization can still be utilized to increase sensitivity) [108,109] and can be analyzed as the native hormone after sample extraction commonly via LLE, SLE, or SPE [20,22,110]. This simplifies the sample preparation process enabling a higher sample throughput. Currently, LC-MS/MS is utilized in a number of clinical laboratories for steroid hormone analysis [20,22,111–113]. An advantage of using MS to measure steroid hormones is the capability of quantifying multiple steroid hormones in one injection as opposed to requiring a distinct immunoassay for each hormone [111,114], although care has to be taken to chromatographically separate analytes that are isomers with the same SRM transitions, for example, testosterone and dehydroepiandrosterone (Fig. 5). Further, in certain clinical situations, MS is the only way to measure steroid hormones such as when patients are taking metyrapone and clinicians want to know their cortisol concentration, or if dexamethasone and cortisol concentrations are to be measured in patients who are undergoing a dexamethasone suppression test [114,115]. Cortisol precursors that result from use of metyrapone will cross-react with cortisol immunosassays and dexamethasone is not currently available by automated immunoassay [115,116]. An important consideration for analysis of testosterone by LC-MS/MS is the use of gel-containing blood collection tubes. The gel in clot activator tubes that are currently available causes interfering peaks in the commonly monitored SRM transitions for testosterone that can falsely elevate the testosterone concentration, especially at low testosterone concentrations (Fig. 6A) [20,117,118]. One way to ensure that the gel does not interfere with testosterone quantification is to chromatographically separate the interfering peak from the testosterone peak via the LC method. One study showed that this was possible in a 7-min LC run time [20]. Further, the length of time that the serum sits on the gel before it is aliquoted has a

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Fig. 5 An extracted ion chromatogram from SRM analysis of the common testosterone transitions 289/97 and 289/109. Dehydroepiandrosterone and epitestosterone share these transitions and have to be chromatographically separated from testosterone in order to be quantified independently.

significant impact on the size of the interfering peak; the longer the serum sits on the gel, the larger the interfering peaks [117]. A technique that has recently aided in analysis of steroid hormones is differential mobility spectrometry (DMS), a form of ion mobility spectrometry. This technique is not new, but until recently, it has not been used in clinical laboratories. It adds another layer of selectivity to LC-MS/MS analysis following sample introduction and atmospheric pressure ionization but before the ions enter the MS. This technique functions by separating analyte ions of interest from interfering ions based upon ion mobility. This occurs through application of high and low electric fields, and a compensation voltage that is optimized for the analyte of interest so that these analyte ions enter the MS, while interfering ions are deflected [119,120]. This application is particularly useful in steroid analysis due to the similarity in structure between these

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Fig. 6 The extracted ion chromatogram for testosterone transition 289/97 can be seen in a red top tube (left hand panel) and gold top tube (right hand panel) extracted using LLE (A) run without differential ion mobility spectrometry and (B) run with differential ion mobility spectrometry.

analytes, the presence of isomers, and the fact that many steroids share common fragment ions which can cause interference in quantification [119–122]. These potential interferences can therefore be preseparated by DMS before they enter the MS. DMS could also increase the sensitivity of the analysis of low concentration steroids such as estradiol and testosterone by reducing matrix interferences (although the overall signal is reduced), and potentially reduce the need for the extensive sample preparation that is often utilized in steroid hormone analysis, such as LLE [120]. Use of DMS can also alleviate the interference in testosterone methods from gel-containing sample collection tubes which simplifies data analysis for clinical laboratory staff and allows the laboratory to accept the commonly used gold top tubes for testosterone analysis (Fig. 6A and B). Although HR-MS analysis of steroid hormones is not commonly applied in the clinical laboratory, this type of MS would simplify analysis of steroid hormones whose structures only differ slightly [4,123]. Any change in molecular formula would enable the HR-MS instruments to detect the

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analytes independently, and if fragmentation is not used, then the common fragment ions would not be able to cause interference as they can potentially do in LC-MS/MS analysis [4,123]. The limitations of using HR-MS are that the current sensitivity may not be sufficient for low concentration steroid hormones such as estradiol and testosterone in certain patient populations, and the dynamic range is limited which may impact the ability of one method to detect steroid hormones in multiple different patient populations [4]. Further, isomeric compounds would still require LC separation before they enter the MS [4].

5.4 Thyroid Hormones Measurement of thyroid stimulating hormone in serum or plasma by immunoassay is the first test that is performed when a clinician wants to investigate the thyroid function of a patient. The thyroid hormones thyroxine (T4) and triiodothyronine (T3) are commonly subsequently measured in serum or plasma clinically to help aid in determining the type of thyroid dysfunction, or to monitor patients with thyroid disease [124,125]. These hormones circulate either bound to protein (albumin, transthyretin, and primarily thyroxine-binding globulin (
70%)) or free in the blood (FT4 and FT3;
0.01% of the total) [124,126]. The free hormone hypothesis indicates that the free hormones are the biologically active forms and are therefore of most interest to clinicians when evaluating the thyroid function of their patients [124]. Total T4 and total T3 measurement is also utilized and is most commonly accomplished by immunoassays that first displace the hormone from the binding proteins so that it is available to the antibodies of the immunoassay [127]. When measuring free hormones, they can either be measured directly, or by first separating the free hormone from the protein-bound hormone [124,125]. In laboratories that directly measure free hormones, it is carried out by analogue immunoassay analysis [128]. The immunoassay can either be classified as a one-step or two-step assay [124,125]. In one-step assays, the signal is inversely proportional to the free hormone concentration measured in the presence of binding proteins. In this type of assay, a solid-phase antibody is used with a labeled hormone analogue that cannot bind to binding proteins in the patient sample, or there is a solid-phase hormone analogue with a labeled antibody [129]. In two-step assays, the free hormone in the patient sample interacts with solid-phase antibodies, the sample is then washed away, and a labeled free hormone is then allowed to bind to any empty

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solid-phase antibodies [124,125,129]. Although these direct immunoassay methods are fast and automated, their accuracy is still debated. It has been shown that when patients have altered binding protein concentrations, in pregnancy, renal failure and when patients use drugs that displace T4 and T3 from their binding proteins, the direct assays are not reliable [124,125,129]. Further, heterophile and autoantibodies can also affect these immunoassays by causing either falsely high or low results depending on the type of interference that is caused in the different assays [125,130,131]. In order to physically separate the free hormone from the protein-bound hormone, laboratories can use either equilibrium dialysis or ultrafiltration, both of which allow only the free hormone to pass through a semipermeable membrane without disturbing the free hormone equilibrium [125,132]. The free hormone is then measured in the dialysate or filtrate [125,132]. These methods require very specific and tightly controlled conditions including temperature and pH, which renders them too labor intensive for most clinical laboratories to routinely use [125,132]. Further, the potential for the hormone to adsorb to either the dialysis or ultrafiltration membranes has to be carefully investigated [125,132]. Ultrafiltration can be performed more quickly than equilibrium dialysis, but to date, this method does not achieve the same sensitivity, and there is still no consensus on which method should be used [125]. The advantage of using either equilibrium dialysis or ultrafiltration to physically separate the free hormones from the proteinbound hormones before analysis is that the assays are therefore unaffected by binding protein concentration, pregnancy, renal failure, and heterophile or autoantibodies that commonly affect immunoassay measurement [125,132]. Traditionally, free hormones were measured by radioimmunoassay following physical separation from the protein-bound hormones, but due to the lack of availability of commercial kits, and the issues with both using, and disposing of, radioactive materials, these assays were replaced by analogue immunoassays and more recently with LC-MS/MS [125,133–136]. Initially LC-MS/MS instruments did not have the required sensitivity to measure the free thyroid hormones and were only utilized for total T4 and T3 [137–139]; however, the newer generation LC-MS/MS instruments are of sufficient sensitivity that free thyroid hormones can be quantified at pmol/L concentrations [136,140,141]. An advantage of LC-MS/MS is that it is possible to measure both FT4 and FT3 in one method instead of two separate methods as is the case with radioimmunoassay or immunoassay [135,136].

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5.5 Inborn Errors of Metabolism Inborn errors of metabolism (IEM) arise from deficiencies or abnormalities in enzymes, cofactors, or transporters in the body that are responsible for a particular metabolic step in a biochemical pathway. These steps may be involved in many cellular processes and may control, for example, DNA replication, protein synthesis, or specific biochemical compounds required for cellular integrity. The resulting effects are accumulation of a specific substrate, or deficiency of a desired product or both which disrupts the pathway [142]. IEMs are a significant cause of morbidity and mortality in children, and even though each one is rare, they collectively constitute a significant proportion of childhood genetic disorders [143,144]. This led to screening for IEMs being included in newborn screening programs so that treatment could be implemented as soon as possible. Initially, single-screening assays were used to detect single disorders, but with the advent of newer technology such as MS, panels of analytes can now be screened simultaneously using one sample from the patient [144,145]. Common laboratory tests are usually carried out in patients suspected of having an IEM to help direct clinicians to the correct preliminary diagnosis before more comprehensive and complicated testing is undertaken. These include but are not limited to blood tests such as a complete blood count, peripheral smear, liver enzymes, blood urea nitrogen, bilirubin, glucose, ketones, pH, blood gases, lactate pyruvate, and ammonia and urine tests such as detection of reducing substances, the cyanide nitroprusside test, the dinitropheylhydrazine test, and documentation of the color and odor of the urine [146]. The tests most commonly used to screen for metabolic defects, where MS plays a role are amino acid analysis, organic acid analysis, and acylcarnitine analysis, in both newborn screening and in older patients suspected to have an IEM, and these are discussed in further detail later [143–146]. Although they are being discussed separately, it should be noted that two or more of these analyses are now often combined into one MS method since it can reduce the time of analysis, and further, many of the analytes measured are markers for several disorders [147–150]. 5.5.1 Amino Acid Analysis Amino acid analysis is commonly carried out in patients suspected of having an IEM and can also be used to monitor the effectiveness of intervention or therapy, or to determine patient compliance with therapy during treatment [151,152]. Sample types that are commonly analyzed for amino acids are

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whole blood (dried blood spots), serum or plasma, urine, and sometimes cerebrospinal fluid (CSF). Patient samples are often prepared by precipitating the proteins using acid or organic solvent and analyzing the supernatant, or in some cases, derivatization is also carried out [146,152]. One example of an abnormal amino acid profile is the significant increase in plasma phenylalanine seen in patients with phenylketonuria. This disease was first screened for in newborns using the Guthrie bacterial inhibition assay from dried blood spots [153]. Amino acid analysis can be designed to detect all amino-group containing compounds including urea and ammonia. Historically, this type of analysis was carried out by TLC [154]. Subsequently, HPLC coupled to a spectrophotometer or fluorometer was used as these methods are more sensitive and specific [155]. In order to detect the amino acids that do not absorb light, the patient sample is derivatized before or after chromatography analysis to produce derivatives that are detectable using a spectrophotometer or fluorometer [156]. Amino acid analyzers are another commonly used methodology, and they function similar to HPLC in that the amino acids are separated by charge and hydrophobicity on a column, are identified by retention time, and subsequently derivatized to enable detection [157]. An advantage of these analyzers is that they are fairly automated, but a disadvantage is the long run time of up to 2 h resulting in a low-throughput of samples as well as the potential for interferences in the method by other substances found in the complex matrices that are analyzed [157,158]. More recently, MS has been utilized for amino acid analysis as this methodology is more specific and less prone to interferences than the previously discussed methods, and further, it has a faster analysis time than amino acid analyzers [159]. MS can be combined with LC for amino acid analysis, but direct infusion of the patient sample into the MS without use of LC has also been used, and this can significantly reduce the sample analysis time [159,160]. However, a disadvantage of direct infusion into the MS without using LC is that isomeric amino acids cannot be separated and therefore cannot be quantified independently as they can when LC-MS/MS is utilized [159]. Studies comparing amino acid analysis by different methodologies have reported variation between methods. In one study comparing phenylalanine analysis by amino acid analyzer, HPLC, and tandem MS, they found that the concentrations measured by the amino acid analyzer in plasma were approximately 15% higher than those found in whole-blood analysis by HPLC and tandem MS [151]. In a more recent study, direct infusion tandem MS using

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dried blood spots and an amino acid analyzer were compared in the measurement of both phenylalanine and tyrosine. The authors found that the tandem MS method gave phenylalanine and tyrosine concentrations that were 26.1% and 15.5% lower, respectively, than the amino acid analyzer concentrations. Since there are published target concentrations for phenylalanine in patients with phenylketonuria (120–360 μM under 12 years old and 120–900 μM thereafter), it is important that clinicians know about these potential analytical differences and that patients are monitored over time by the same method [152]. A recent publication documented the use of hydrophilic interaction liquid chromatography followed by tandem mass spectrometry for analysis of amino acids in plasma without derivatization. The method is capable of analyzing 36 amino acids with a short run time of 18 min and is capable of independently quantifying isomeric amino acids such as leucine and isoleucine, but it was not capable of quantifying isoleucine and alloisoleucine independently [161]. 5.5.2 Organic Acid Analysis Organic acids are intermediates in the degradation pathways of amino acids, fats, and carbohydrates. Organic acid analysis of urine is commonly carried out in patients suspected of having an IEM, where abnormal organic acids are identified, and the excretion pattern of all the organic acids can also be determined [162]. Methylmalonic acidemia is an organic acid disorder of propionate catabolism and results in accumulation of methylmalonic acid in plasma and urine which is detected by organic acid analysis [163]. Initially, organic acid analysis was accomplished by GC-MS since this technology allowed for identification of distinct compounds after separation by chromatography. The organic acids are extracted from the urine using organic solvents such as ethyl acetate or diethyl ether once it has been acidified and saturated with salt, or they can be extracted from urine using anion exchange resin [157]. Derivatization is also commonly used to stabilize and/ or volatilize the organic acids for analysis [164]. The sample preparation is fairly time consuming and the run time for each sample can be around 30 min depending on the number of organic acids detected by the method [157]. The sample preparation can be automated although it has been reported that the results are not as consistent as the manual procedure [165]. Organic acid analysis is still commonly carried out by GC-MS for detection of IEM, but other techniques such as capillary electrophoresis (CE), nuclear magnetic resonance (NMR), and LC-MS/MS have also been reported [166–168]. Each technique has strengths and weaknesses compared

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to GC-MS. CE requires smaller sample volumes, but it lacks sensitivity and precision and has a complex sample preparation [169]. NMR offers equal sensitivity to all analytes, but the sensitivity is not sufficient, the instrumentation is expensive, and is highly specialized. LC-MS/MS reduces the sample preparation as derivatization is not required, but lacks the availability of reproducible spectral libraries and the instrumentation is of higher cost. Therefore, GC-MS has remained the method of choice for organic acid analysis [164]. One recent advance in organic acid analysis was the first reported use of SLE as sample preparation method for a serum methylmalonic acid LC-MS/MS assay [170]. As discussed earlier, SLE has the ability to significantly decrease the sample preparation time over other extraction methodologies which reduces the turn-around time of the results for clinicians and patients [22]. However, the technique is not without its challenges as this group reported that there is the potential for “cross-talk” between the wells of the SLE plate [170]. In order to eliminate this, they had to use plates with round bottom wells in addition to a cover for the plate that increased the spacing between the wells [170]. 5.5.3 Carnitine and Acylcarnitine Analysis Carnitine plays a role in the transportation of fatty acids into the mitochondria and the catabolism of branched-chain amino acids, and it also assists in the excretion of organic acids in some IEMs. An acyl group from a large number of organic acids can be esterified to carnitine to form acylcarnitine. Accumulation of the different acylcarnitines can occur in IEM, and the distinct pattern of the types of acylcarnitines observed is indicative of where the enzyme deficiency occurs [162]. Medium-chain acyl-coenzyme A dehydrogenase (MCAD) deficiency is the most common disorder of fatty acid β-oxidation, and the predominant marker used for diagnosis is octanoyl carnitine, although this acylcarnitine is not specific for MCAD deficiency [171]. Like amino acid analysis, acylcarnitine analysis was historically carried out by GC, TLC, or HPLC from tissue or urine samples [172–175]. More recently, HPLC was used to measure free carnitine and acylcarnitines in plasma samples [176]. Currently, the most commonly used MS/MS methods first derivatize acylcarnitines from dried blood spots, serum, or plasma to butyl esters making them more amenable to ionization due to the positive charge. The samples are then directly infused into the MS/ MS instrument, and a precursor ion scan is performed [143,177,178].

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Although these methods are simple and rapid, the disadvantage is the inability to separate isomeric and isobaric acylcarnitines and therefore the potential for false positive results [179,180]. Using LC-MS/MS, the interference from isomers and isobars can be reduced or eliminated, and this technique has been used to distinguish the acylcarnitines with acyl groups of 2–20 carbons in length in a short run time from dried blood spots, plasma, and urine [162,181]. A recent study documented a clinically validated LC-MS/MS method capable of detecting carnitine, the carnitine precursor butyrobetaine, and 65 different acylcarnitines in less than 14 min. One disadvantage is the extensive sample preparation that includes SPE and derivatization [182]. Another study reported the use of CE coupled to MS for analysis of amino acids and acylcarnitines from dried blood spots and plasma. This method reduced the requirement for extensive sample preparation and is capable of separating isobaric and isomeric analytes [149].

6. RECENT ADVANCES IN CLINICAL MASS SPECTROMETRY 6.1 Microbiology Applications Traditional microbiology techniques used to speciate organisms are labor intensive, can take several days to obtain the answer, and require decision-making processes regarding selection of manual or automated biochemical tests, as well as a Gram stain and 16S ribosomal RNA sequencing, if required. A new advance in this field has been the advent of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF) [183–185]. Using soft ionization, MALDI-TOF enables the detection of intact cellular components that can then be compared to individual mass spectrometric fingerprints, or spectra, contained in databases in order to identify specific organisms. This technique still currently requires that the organism from the patient sample be cultured and grown on media, but once colonies are obtained, a colony is mixed with matrix, spotted onto a slide and inserted into the MALDI-TOF instrument [184]. A genus and frequently a speciation result are obtained within minutes, and this can lead to major cost savings in clinical laboratories with regards to labor and consumables [186]. Some studies have been successfully carried out to determine whether patient samples can be placed directly onto the MALDI-TOF slides instead of having to grow the organisms first from urine [187] and CSF [188]. Further, it was also determined that positive blood culture bottles may be tested directly by MALDI-TOF rather than having to subculture them to solid

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media, although a sample processing step was required first to remove some macromolecules that are found in both the blood and media [189,190]. There are currently two FDA-approved MALDI-TOF systems available for this purpose: MALDI Biotyper CA System (Bruker Daltonics Inc., Fremont, CA) which is approved for the identification of Gram-negative bacterial colonies from human specimens and the VITEK® MS (bioM
erieux Inc., Durham, NC) which is approved for the identification of 193 different microorganisms and yeasts. The systems include the mass spectrometer, the software required to run the instrument and a database that is searched to determine what organisms are present in a patient sample. In order to retain FDA-approved status, no additional organisms can be added to the database by the end-user. If organisms are added, it would require full analytical validation, but it would allow clinical laboratories to increase the utility of MALDI-TOF for detection of organisms in their patient population [191]. To date, studies have shown the utility of MALDI-TOF analysis in Gram-negative bacteria [183], Gram-positive bacteria [192], Gram-positive aerobic bacteria [193], mycobacteria [194,195], yeasts [196,197], Enterobacteriaceae [198], anaerobic bacteria [199–201], non-Enterobacteriaceae Gram-negative bacilli [202], fastidious Gram-negative bacteria [203], and molds [204,205]. However, MALDITOF will not replace rapid bench tests for some organisms (e.g., Staphylococcus aureus), and in the cases of inconclusive MALDI-TOF results, 16S rRNA sequencing will still be required [184]. Although susceptibility testing by MALDI-TOF is possible, it is not yet ready for routine clinical use [206]. One study did show promising results in that the authors found that it possible to distinguish between vancomycin non-susceptible and vancomycin susceptible S. aureus which would enable faster initiation of the appropriate antibiotic treatment, potentially reducing mortality rates for patients with sepsis [207]. More studies using different organisms and drugs are necessary to establish whether this performs well enough to be clinically useful.

6.2 Protein and Peptide Analysis Analysis of proteins by mass spectrometry is not new; however, detection and quantitation of clinically relevant proteins in a sufficiently sensitive, accurate, and precise manner for clinical use have been of significant challenge. Targeted LC-MS/MS methods are most likely to be used clinically, and they begin with trypsin digestion of the proteins into smaller peptides. These peptides can then be measured by SRM as was discussed with small molecule

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analysis earlier [208]. One of the first clinically relevant proteins to be quantified by LC-MS/MS was thyroglobulin (Tg) [209]. Tg is a serum tumor marker that is used clinically to monitor patients treated for thyroid carcinoma [210]. Current immunoassays for thyroglobulin have sufficient functional sensitivity (