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Proteomics Clinical Applications Reviews 2015 Title Biomarkers for cardiovascular risk assessment in autoimmune diseases. Authors: Priscila Camillo Teixeira1,2; Philippe Ferber1; Nicolas Vuilleumier2; Paul Cutler1. Author affiliations: 1

Pharma Research and Early Development, Roche Innovation Center Basel, Switzerland.


Division of Laboratory Medicine, Department of Genetics and Laboratory Medicine, Geneva

University Hospitals, Switzerland. Corresponding author: Priscila Camillo Teixeira Pharmaceutical Sciences, Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche. Grenzacherstrasse 124 - Building 93/Room 4.38 4070 Basel, Switzerland Phone: +41 61 687 4571 Mail to: [email protected]

Keywords: Biomarkers, Autoimmune diseases, Cardiovascular diseases, Cardiovascular risk, Proteomics Received: 01-Sep-2014; Revised: 30-Nov-2014; Accepted: 15-Dec-2014 This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/prca.201400125. This article is protected by copyright. All rights reserved.


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Abbreviation List CV: Cardiovascular CVD: cardiovascular disease RA: rheumatoid arthritis SLE: systemic lupus erythematosus APS: antiphospholipid syndrome T1D: Type 1 Diabetes MI: myocardial infarction RF: rheumatic factors IgG: Immunoglobulin G Apo: Apolipoprotein anti-CCP: anti-cyclic citrullinated peptide aPL : antiphospholipid antibodies (aPL) aCL: anticardiolipin antibodies aβ2GPI :anti-β2-glycoprotein I antibodies LA: lupus anticoagulant CCC: chronic Chagas cardiomyopathy EULAR: European League Against Rheumatism IL: interleukin TNF-α: Tumor necrosis factor-alpha CRP: C-reactive protein VCAM-1: vascular cell adhesion molecule-1 ICAM-1: intercellular adhesion molecule-1 ELAM-1: endothelial leucocyte adhesion molecule-1 IFN-γ: Interfern-gamma anti-ApoA-I IgG : autoantibodies to apolipoprotein A-I HDL: high density lipoprotein HSP: Heat shock protein NT-proBNP: N-terminal prohormone of brain natriuretic peptide FRS: Framingham Risk Score AUC: area under curve ox-LDL: oxidized low density lipoprotein ADMA : asymmetric dimethyl arginine NO: nitric oxide LC: liquid chromatography This article is protected by copyright. All rights reserved.

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MS: mass spectrometry DYRK2: tyrosinephosphorylation- regulated kinase 2 FACS: fluorescence-activated cell sorting CyTOF: cytometry by time-of-flight (CyTOF) SRM: Selected reaction monitoring MRM: multiple reaction monitoring

Total number of words: 6748 words

Abstract Autoimmune diseases, such as antiphospholipid syndrome, systemic lupus erythematosus and rheumatoid arthritis, are characterized by a high prevalence of cardiovascular (CV) disease, which constitutes the leading causes of morbidity and mortality among such patients. Although such effects are partly explained by a higher prevalence of traditional CV risk factors, many studies indicate that such factors do not fully explain the enhanced CV risk in these patients. In addition, risk stratification algorithms based upon traditional CV risk factors are not as predictive in autoimmune diseases as in the general population. For these reasons, the timely and accurate assessment of CV risk in these highrisk populations still remains an unmet clinical need. An enhanced contribution of different inflammatory components of the immune response, as well as autoimmune elements (e.g. autoantibodies, autoantigens and cellular response) have been proposed to underlie the incremental CV risk observed in these populations. Recent advances in proteomic tools have contributed to the discovery of proteins involved in CV diseases, including some that may be suitable to be used as biological markers. In this review we summarize the main markers in

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the field of CV diseases associated with autoimmunity, as well as the recent advances in proteomic technology and their application for biomarker discovery in autoimmune disease.

1. Introduction Autoimmune diseases comprise a large number of disorders with varied pathogenesis that are currently characterized by more than 100 human diseases. In the broadest terms, autoimmune diseases occur because the physiological tolerance to self-antigens is lost, with the presence of T- and/or B-cell recognizing self-proteins (autoantigens). Therefore, autoimmune diseases are characterized by a primary dysfunction of the immune system with increased level of autoantibodies, inflammatory and mediatory cells resulting in chronic inflammation [1]. These diseases can affect the whole body (systemic) or a single organ or tissue (localized) and are the result of both genetic predisposition and environmental modulation. Studying the field of autoimmune diseases encounters several hurdles. For instance, there is no standardized definition of the normal human immune system and no comprehensive understanding of how this normal system is altered in autoimmune diseases. Perhaps more critically there is no understanding of the relationship between these characteristics and either the genetic composition or the environmental stimuli that either promote or protect the body from developing autoimmunity [2]. Frequently, the disease classifications are based on clinical manifestations, pathologic findings and a limited range of blood tests that monitor nonspecific markers of inflammation [2, 3]. Testing for the presence of serum antibodies is one of the most useful confirmatory assays for many diseases.

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An additional complexity is the fact that many autoimmune diseases share the same symptoms with other autoimmune diseases and other disease states. For instance, autoimmune diseases are characterized by a high degree of atherogenesis, cardiac impairment and subsequent higher cardiovascular (CV) risk [4]. This is in turn associated with poor prognosis. In some autoimmune patients (RA, Type 1 diabetes for example), there is an increased prevalence of silent/asymptomatic acute CV events, which renders their detection even more difficult. Knowing the mechanisms responsible for CV related damage in autoimmune diseases is important for choosing appropriate drugs that can block/slow the development of atherosclerosis. In this article we discuss the main autoimmune diseases associated with a high risk of developing CV diseases, and new approaches to assess potential biomarkers.

2. Cardiovascular Risk in Autoimmune Diseases Cardiovascular disease (CVD) is still the leading cause of mortality worldwide, responsible for about 30% of deaths. Atherosclerosis is one of the most common pathologic processes leading to CVD, including myocardial infarction (MI) and stroke. Some autoimmune conditions and immunological disorders, such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and antiphospholipid syndrome (APS), are characterized by enhanced atherosclerosis and consequently higher cardiovascular morbidity and mortality rates (Table 1) [5-12]. The clinical manifestations of cardiac involvement also include: pericarditis, myocarditis and myocardial fibrosis, rhythm and conduction disturbances, ischemic heart disease, valvular diseases, pulmonary hypertension, syncope, and heart failure [1]. CVD seems to occur at a younger age in patients with autoimmune diseases than in the general This article is protected by copyright. All rights reserved.


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population, and is often asymptomatic especially at early stages [4]. The development of atherosclerosis and cardiovascular diseases in autoimmune diseases involves genetic factors as well as other acquired and modifiable risk factors (hypertension, smoking, dyslipidemia, etc.). These diseases share several clinical and molecular features, but also have some unique distinguishing characteristics. 2.1. Rheumatoid arthritis Rheumatoid arthritis is a common autoimmune disorder, most often affecting women from 40 to 60 years old. The major symptoms of RA are chronic inflammation that mainly targets the synovial membrane, cartilage and bone. The cardiovascular, hematologic, and respiratory systems are frequently also affected [13]. Cardiovascular mortality accounts for 40-50% of all deaths in RA patients [14]. Moreover, the presence of RA is associated with an increased risk of the occurrence of stable angina, myocardial infarct, heart failure and stroke [15, 16]. Many individuals with RA produce rheumatic factors (RF), a group of autoantibodies, which are reactive with determinants in the Fc region of IgG. Such autoantibodies bind to normal circulating IgG, forming complexes that are deposited in the joints. These immune complexes are critical for RA diagnosis assessment and may also bare interesting predictive and prognostic properties. RF has been shown to activate the complement cascade, resulting in a type III hypersensitive reaction, which leads to chronic inflammation of the joints. A significant proportion (30%) of patients with RF positivity is asymptomatic and will develop the disease in the next 2 years; the same is true for antibodies against anti-cyclic citrullinated peptide (anti-CCP). Anti-cyclic citrullinated protein/peptide antibodies are part of the autoantibody system associated with RA, with diagnostic sensitivity of 70% and specificity of 95%.

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2.2. Anti-phospholipid syndrome The anti-phospholipid syndrome (APS or Hughes’ syndrome) consists of an autoimmune multi-systemic disorder characterized clinically by recurrent thrombosis and pregnancy morbidity, accompanied by mild to moderate thrombocytopenia and elevated titers of antiphospholipid antibodies (aPL), including anticardiolipin antibodies (aCL), anti-β2glycoprotein I antibodies (aβ2GPI), and lupus anticoagulant (LA). The pathogenesis of this autoimmune disease is not yet completely understood, however the syndrome has been well characterized and has become one of the most common syndromes in the world, e.g. 20–30% of all deep vein thrombosis are due to APS [17]. Moreover, prospective studies show an association between aPL and episodes of venous thrombosis [18], myocardial infarction and stroke [19]. 2.3. Systemic lupus erythematosus Systemic lupus erythematosus (SLE) is one of the best examples of a systemic autoimmune disease. It typically appears in women between 20 and 40 years of age; the ratio of male to female is 10:1, and it is characterized by fever, weakness, arthritis, skin rashes, pleurisy, and kidney dysfunction. Affected individuals may produce autoantibodies to a vast array of tissue antigens, such as DNA, histones, red blood cells, platelets, leukocytes, and clotting factors; interaction of these auto-antibodies with their specific antigens produces various symptoms. Autoantibodies specific for red blood cells or platelets, for example, can lead to complement-mediated lysis, resulting in hemolytic anemia and thrombocytopenia, respectively. In individuals with SLE, the prevalence of CVD ranges from 6 to 10%, and the risk of developing CVD are 4–8 times higher than in the normal population. In a prospective study, it was examined risk factors specifically for CVM, which accounted for almost 50% of This article is protected by copyright. All rights reserved.


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deaths in a cohort of 208 SLE patients [20]. Moreover, acute myocardial infarction is reported as a cause of death in 3–25% of individuals with SLE [21]. 2.4. Cardiac Autoimmune Diseases / Myocarditis Defined as mononuclear inflammation of the heart muscle with damage to adjacent myocytes, myocarditis is a major cause of sudden death in adolescents and young adults [22, 23]. In about 21% of cases, myocarditis evolves into chronic inflammatory dilated cardiomyopathy, which further progresses to heart failure [24]. The outcome of dilated cardiomyopathy is poor with a 5 year mortality of 46% [22]. Although in the majority of cases the cause of autoimmune myocarditis remains unknown, some evidence supports an association with a prior viral, bacterial or parasitic infection. One example of myocarditis with an autoimmune component is the Chagas cardiomyopathy, initially caused by the protozoan Trypanosoma cruzi. The inflammatory process, although more intense in the acute phase, is clinically silent but incessant in patients in the indeterminate and chronic phases of the disease. The autoimmune hypothesis of pathogenesis has predicted that Tcells infiltrating the myocardium should recognize heart proteins as a result of the chronic infection [25]. Several studies documented autoimmune recognition of neoantigens, cardiovascular receptors, highly conserved proteins, and cardiac myosin by sera or T-cells from patients with Chagas disease and experimentally infected animals. Both, T. cruzispecific and autoimmune CD4+ T cells that cross-reactively recognize cardiac myosin and T. cruzi proteins populate the myocardium of patients with Chronic Chagas cardiomyopathy (CCC), indicating that antigenic stimuli contribute to sustained inflammation-induced myocardial damage [26-28]. The persistent inflammation, associated with accelerated cardiac remodeling, leads to the severe CCC and consequently heart failure [29].

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3. Cardiovascular Risk Stratification Tools Risk factor assessment algorithms, including the SCORE and the Framingham risk equation, are recommended worldwide as part of CVD risk management in the large population [30, 31]. These equations allow for stratifying subjects into low, intermediate, high and very high risk groups. Current clinically-based risk stratification methods, such as Framingham, Procam and SCORE have however been shown to be insufficient in predicting CVD. For instance, 60% of events happen in patients identified as being at low or moderate risk [32] and 30-50% of patients at risk are identified by a major CV event [33]. Taking into account that patients with autoimmune diseases, such as RA, have two to three times more frequent asymptomatic carotid atherosclerosis compared with patients without RA [34], this will have a major impact on correct classification and hence treatment in patients with autoimmune diseases. For example, the European League Against Rheumatism (EULAR) created the modified (m) SCORE, which consists of applying a multiplier of 1.5 in patients with RA that met 2 of 3 criteria, including disease duration more than 10 years; rheumatoid factor or anti-cyclic citrullinated peptide positivity; and the presence of extra-articular manifestation [35]. Discovering new risk factors and biomarkers would help to improve the current stratification methods and may also represent an opportunity to identify new pathways associated with CVD and clinical targets.

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4. Currently CVD predictors in autoimmune diseases Despite the traditional cardiovascular risk factors being more prevalent in patients with autoimmune diseases than in the general population, they do not seem to fully explain the enhanced risk. Several potential biomarkers have been considered for CV risk in autoimmune diseases. Because endothelial dysfunction is an essential initial step in atherogenesis [36], the availability of a sensitive biomarker reflecting the degree of endothelial function could be an appealing option for the screening of early athersoclerosis in those patients. Additionally, it has become clear that at a later stage of the disease, atherosclerosis is a chronic inflammatory disease in which immune response and autoimmune elements (autoantibodies, autoantigens and autoreactive lymphocytes) play a key role. The presence of inflammation mediators, including serum amyloid A protein, cytokines, chemokines, prothrombotic molecules and adhesion receptors have been implicated in enhanced cardiovascular impairment in autoimmune conditions. Different selfantigens or modified self-molecules have been identified as targets of humoral and cellular immune responses in patients with atherosclerotic disease. Oxidative stress, increasingly reported in these patients, is a major event causing structural modification of proteins with consequent appearance of neoepitopes. These neoepitopes can themselves become targets of autoimmune reactions, sustaining the inflammatory mechanisms involved in endothelial dysfunction and plaque development [37]. Certainly, many other risk factors, as well as environmental conditions, remain to be discovered that will help the understanding of the high CVD risk in patients with immunological disorders (Figure 1).

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4.1. Inflammatory markers Several studies have shown the involvement of inflammatory mediators (e.g. C-reactive protein, IL-1, IL-6 and TNF-α), biomarkers of endothelial dysfunction (e.g. vascular cell adhesion molecule [VCAM]-1, intercellular adhesion molecule [ICAM]-1 and endothelial leucocyte adhesion molecule [ELAM]-1) and prothrombotic factors (e.g. haptoglobin, von Willebrand factor and tissue plasminogen activator inhibitor) in the development of CVD in patients with autoimmune diseases, in particular RA [38, 39]. Interestingly, evidence suggests that lower cholesterol levels, but high levels of inflammation, are associated with CVD in RA patients [40]. This association has significant clinical implications for therapy because many of the drugs used in the symptomatic treatment of RA, such as non-steroidal anti-inflammatory drugs and the cyclooxygenase (COX)-2-specific inhibitors, affect mediators of both inflammation and thrombosis [12]. Among other important mediators and therefore therapeutic targets of RA, tumor necrosis factor alpha and interleukin-6 have been shown to be key players in the pathophysiolgoy of the disease, as well as being strong predictors of subsequent CV events. These results provided the rationale to develop biological agents directed against IL-6 and TNF, which are now considered as a second line of therapy. Interestingly anti-TNF and anti-IL-6 antibodies have been shown not only effective in treating refractory RA but also effective to reduce CV events in patients [41]. Therefore RF, anti-CCP antibodies, IL-6 and TNF-alpha are respectively key biomarkers for RA diagnosis, prognosis and therapy. In a Lupus prospective cohort study, it was demonstrated that the cardiovascular mortality was associated with high levels of sVCAM-1, hsCRP and aPL, demonstrating that systemic and vascular inflammation as well as prothrombotic autoantibodies are important

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cardiovascular risk factors. With the exception of smoking, traditional risk factors had less impact [20]. Furthermore, although the presence of aPL is a necessary pre-condition, APSassociated clotting is frequently related to innate inflammatory immune responses [42]. In CCC, the presence of a T cell-rich mononuclear inflammatory infiltrate and the relative scarcity of parasites in the heart suggested that chronic inflammation secondary to the autoimmune recognition of cardiac proteins could be a major pathogenic mechanism for the development of heart failure. Sera from CCC patients cross-reacted with cardiac myosin and T. cruzi protein B13. T cell lines from the infiltrate produce inflammatory cytokines, such as, IFN-γ and TNF-α. Conversely, IFN-γ-induced genes and chemokines were found to be upregulated in CCC heart samples, and IFN-γ is able to induce cardiomyocyte expression of atrial natriuretic factor, a key member of the hypertrophy/heart failure signature [43]. 4.2. Autoantibodies and autoantigens in CVD Although circulating antibodies do not always play a pathogenic role, they represent specific markers of ongoing tissue damage. Circulating autoantibodies have been critically linked to cardiovascular diseases. In general, systemic autoimmune disorders such as SLE and APS are B-cell dependent, and organ-specific diseases such as Type 1 Diabetes and myocarditis are less dependent on autoantibodies, although B cells can play important roles as antigen presenting cells, and antibodies can possibly enhance disease pathogenesis. Nevertheless, there is accumulating evidence showing that humoral autoimmunity might play an important role in CVD, by modulating atherogenesis and cardiac damage. Several autoantigens and their respective autoantibodies have been considered to be associated with CVD, such as anti-HSP-60, anti-oxLDL, anti-βGPI and anti-HDL/apolipoprotein AI IgG [44-48]. More precisely, autoantibodies to apolipoprotein A-I (anti-ApoA-I IgG), the major This article is protected by copyright. All rights reserved.


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protein fraction of high density lipoprotein (HDL), have been shown to be both a marker and a mediator of cardiovascular disease, promoting atherogenesis and unstable atherosclerotic plaque, through the engagement of innate immunity receptors [45, 49-51]. Anti-apoA-I antibodies were first identified in patients with SLE and APS [52], assuming that these autoantibodies had a part in thrombogenesis [53]. Vuilleumier et al., demonstrated that anti-apoA-I antibody levels were also raised in patients with acute coronary syndrome without autoimmune disease [54]. High levels of anti-apoA-I IgG were shown to predict acute cardiovascular events in a cohort of 133 patients with RA during a median follow-up period of nine years (hazard ratio [HR] 4.2, 95% CI 1.5-12.1, p = 0.0008) [55]. From the same cohort of patients, a study showed that, when compared to NT-proBNP and ox-LDL, antiapoA-1 IgG was the only biomarker to significantly improve the prognostic ability of the Framingham Risk Score (FRS), with area under curve (AUC) increasing from 0.72 to 0.81 [56]. In patients with APS, studies have shown that anti-phospholipid antibodies (aPLs) and other autoantibodies are responsible for the development of atherothrombosis. aPLs promote the overexpression of tissue factor (TF) and protease activated receptors (PARs) [57-59]. They are associated with the altered protein profile of monocytes and are related to thrombosis development, including overexpression of annexins I and II as well as RhoA proteins among others [60]. In addition, aPLs promote oxidative perturbations and mitochondrial dysfunction [61-63] and also trigger an inflammatory cascade with increased expression of several cytokines, chemokines and mediators of endothelial dysfunction [64, 65]. aPLs crossreact with oxidised low density lipoproteins (ox-LDLs), thus accelerating their influx into macrophages and promoting monocyte activation and atherosclerosis development [66]. Moreover, serum levels of anticardiolipin (aCL) antibodies correlate with the incidence and severity of acute coronary syndrome, myocardial infarction and stroke [67, 68]. The This article is protected by copyright. All rights reserved.


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presence of anti-citrullinated protein antibodies (anti-CCP) in RA patients is also correlated with worse joint involvement and several extra-articular manifestations, i.e., higher incidence of ischemic heart disease, independent of classic cardiovascular factors and higher mortality rate [69, 70]. 4.3. Other CVD biomarkers Besides the presence of inflammatory mediators and components of inflammatory response, other mediators could also be involved in cardiovascular outcome associated with autoimmune diseases. For instance, there is increasing evidence indicating a close association between plasma asymmetric dimethyl arginine (ADMA) levels and cardiovascular disease in patients with autoimmune diseases. ADMA is an endogenous inhibitor of NO synthase and has recently emerged as a novel marker of endothelial dysfunction; it has already been demonstrated that plasma ADMA levels are high in RA patients [71]. The high levels of ADMA could be associated with endothelial dysfunction, which is characterized by a reduction in nitric oxide (NO) production by NO synthase. Studies have shown that higher ADMA levels in SLE patients are associated with coronary calcium, a poor prognosis and are more prone to develop mild carotid plaque [71].

5. Proteomic approaches for biomarker discovery The main limitation in defining cardiovascular biomarkers specific for autoimmune disease is the high complexity of the disease. Proteomic technologies, together with other omics approaches, provide novel tools for the discovery of biomarkers for diagnosis, prediction of disease course, guiding therapeutic selection, and monitoring response to therapy.

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Nevertheless, significant work remains to develop, refine, validate and apply proteomics technologies to identify biomarkers in autoimmune disease. Several proteomics approaches have been applied to the study of biomarkers and pathophysiological mechanisms involved in autoimmune diseases, including: (i) immunoproteomics for autoantigen discovery [72]; (ii) autoantigen microarrays to characterize autoantibody responses [73]; (iii) antibody array technologies to profile cytokines and other biomolecules; and reversed phase protein array studies to analyze inflammatory markers and signaling pathways [74]; (iv) flow cytometry, including mass cytometry, for analysis of phosphoproteins and other mediators in specific cell populations [75]; (v) liquid chromatography – mass spectrometry (LC-MS) for identification of autoantigens and neoepitopes generated by posttranslational modification of proteins [76]; and (vi) differential proteomics for qualitative and quantitative comparison of proteomes in various experimental or pathological conditions [77, 78]. 5.1. Immunoproteomics Immunoproteomics is a concept used to identify disease-associated antigens that elicit immune responses by combining protein separation (two-dimensional electrophoresis or gel-free separation), immunological detection (Western blotting) and MS, or combining immunocapture and MS [72]. Proteins derived from cells or tissue may be separated by one or two-dimensional electrophoresis. Using immunoblotting, patient sera containing autoantibodies can be used to detect immunogenic proteins present in the protein extract. Such detected proteins are further identified by enzymatic digestion followed by MS analysis. This methodology is quite common in the field of allergen discovery [79], but has also been applied to determine autoantibodies against cardiac proteins [80].

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5.2. Protein Microarrays Protein microarrays provide a high-throughput platform that enables the profiling of serum antibodies to a large number of protein antigens. Autoantigen microarrays are produced by attaching hundreds of proteins, peptides and other biomolecules to a surface. Arrays are incubated with patient serum, and spectrally resolvable fluorescent labels used to detect autoantibody binding to specific autoantigens on the array. The value of autoantibodies as biomarkers in diagnosis, prognosis and treatment is well recognized in autoimmune diseases, as discussed previously, including Type 1 Diabetes. For example, protein microarrays were applied for profiling of autoantibodies in T1D, being conducted in twostage, sequential serological immunoreactivity screening and independent validation study. The two stages of screening resulted in the identification of 26 candidate autoantigens including ZnT8 (p < 0.005, FDR < 10%). Candidate genes were selected for further validation, confirming a sensitivity of 36% at the specificity of 98% for the dual specificity tyrosinephosphorylation- regulated kinase 2 (DYRK2), thus demonstrating the use of protein microarrays in the search for novel T1D and other autoimmune diseases associated autoantibodies [81]. Furthermore, protein arrays consisting of miniaturized multiplexed sandwich immunoassays allow the simultaneous expression analysis of dozens of signaling molecules such as the cytokines and chemokines involved in the regulation of the immune system [74]. Using this methodology, a study showed that synovial cell line obtained from an RA patient released the RA-related soluble mediators IL-6, CCL2, CXCL1–3, CXCL8 following rheumatoid arthritis synovial fibroblast stimulation, helping to get a better understanding of the regulatory

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molecular processes occurring in human chondrocytes during the RA-related destruction of cartilage [82]. 5.3. Flow cytometry Flow cytometry, in the guise of fluorescence-activated cell sorting (FACS), is very well known for its application to cell characterization and sorting, biomarker detection and protein analysis. Recently, the number of studies using the combination of flow cytometry with mass spectrometry has increased. The cytometry by time-of-flight (CyTOF) mass cytometry uses multiple antibodies; each tagged with multiple copies of an individual heavy metal ion, and measures their binding to cells by mass spectrometry. Such a system has already been used to quantitate differences in cellular constitution and drug responses of individual cells in a complex mixture of cells such as bone marrow [83, 84]. 5.4. Epitope mapping by mass spectrometry The use of mass spectrometry for antigen discovery has already been demonstrated. An epitope mapping methodology using antigen purification, enzymatic digestion and peptide sequencing by mass spectrometry was used for identification of new ApoA-I epitopes recognized by autoantibodies in samples from patients with cardiovascular diseases [85]. The epitope definition of autoantibodies against ApoA-I is the first step towards a better understanding of the pathogenic role of these autoantibodies in autoimmune diseases and their effectiveness as biomarkers for risk of cardiovascular disease. Moreover, this methodology has the potential for use in cardiovascular risk stratification in patients with autoimmune diseases [45, 55, 86, 87]. Mass spectrometry is also the core technology for qualitative and quantitative analysis of MHC-presented peptide repertoires. After

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immunoaffinity purification of detergent-solubilized peptide-MHC complexes followed by acid elution of peptides, liquid chromatography-mass spectrometry is applied to determine individual peptide sequences and, thus, allow qualitative characterization of the MHCbound repertoire [77]. 5.5. Discovery / Shotgun proteomics Differential proteomics for qualitative and quantitative comparison of proteomes in various experimental or pathological conditions involves a broad range of technologies, whose selection will depend on the scope of the study. For instance, a study evaluated changes in protein expression of monocytes from patients with APS, applying two-dimensional electrophoresis and mass spectrometry analysis. The proteins that were more significantly altered among monocytes from APS patients with thrombosis (annexin I, annexin II, protein disulfide isomerase, Nedd8, RhoA proteins, and Hsp60) were functionally related to the induction of a pro-coagulant state as well as an autoimmune-related response [60]. Another quantitative proteomic approach, using 8-plex iTRAQ labeling, was applied for the discovery of serum proteomic biomarkers for prediction of response to infliximab, monoclonal antiTNF antibody, treatment in rheumatoid arthritis. It combined depletion of the most abundant serum proteins, two-dimensional LC fractionation, protein identification and relative quantification with a hybrid Orbitrap mass spectrometer. Using this methodology, 14 serum proteins were identified, showing differential abundance between the responder and non-responder patients with RA treated with infliximab, including complement factors and apolipoproteins (apoB-100, apoA-II and apoM) that were significantly more abundant in non-responder patients [88]. This kind of study has the potential to find biomarker for

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stratification of patients in order to treat anticipated non-responders with an alternative drug. 5.6. Targeted proteomics The traditional shotgun approach, described earlier, is generally used to identify as many proteins as possible in a complex biological sample, across a wide dynamic range. However, it is not accurate or sensitive enough for a systematic and robust quantification. Selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), is a powerful targeted mass spectrometry approach for precise quantitation of a well-defined subset of proteins/peptides (usually 50-100 target ions). In this approach, only a limited number of peptides from a protein are monitored. [78]. SRM/MRM measures unique peptides from specific proteins [89]. Until now, few studies have been performed using the SRM approach to verify and validate CVD potential protein biomarkers in autoimmune conditions. However, interest is growing in its application for detection and quantitation of changes in concentration of endogenous proteins with clinical relevance to cardiac pathophysiology [90]. For example, Domanski et al., have developed a highly-multiplexed SRM-based assay for determination of CVD status and disease classification for clinical research. In this study, 67 putative biomarkers of CVD, largely composed of proteins involved in the coagulation and thrombolysis pathways, acute-phase reactants, inflammatory markers and components of lipoproteins were screened in plasma samples [91]. The same approach could be applied to access CVD biomarkers in immunological conditions, enhancing the understanding of the pathological mechanisms associated to the higher risk for cardiovascular diseases as observed in some autoimmune diseases.

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6. Conclusions As patients with autoimmune diseases are at higher risk of developing cardiovascular diseases than the general population, it is essential to detect endothelial dysfunction and impairment in the cardiovascular system at an early stage. Studies have shown the beneficial effects of new anti-rheumatic drugs on cardiovascular damage and their efficacy in reducing the atherosclerosis process due to anti-inflammatory mechanisms. In this way, proteomics studies could help to identify novel biomarkers that together with traditional risk factors and the described mechanisms of cardiovascular diseases specific to RA, SLE, APS and myocarditis, might help to target vulnerable patients and monitor the beneficial effects of pharmacological agents.

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Figure 1. Possible factors involved in the high incidence of cardiovascular diseases and atherosclerosis in patients with autoimmune diseases

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Proteomics - Clinical Applications

Table 1. Some autoimmune diseases associated with higher morbidity/mortality due to cardiovascular diseases. Disease Rheumatoid arthritis

CVD mortality (%) 40-50%

Anti-phospholipid syndrome Systemic lupus erythematosus





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Main biomarkers rheumatoid factor, anti-CCP antibody, anti-ApoA-I IgG, IL-6, TNF-alfa, ADMA, homocysteine, anti-dsDNA lupus anticoagulant, aCL antibodies, anti-β2GPI antibodies sVCAM-1, hsCRP and aPL, inflammatory cytokines, ADMA, anti-dsDNA IFN-gamma, TNF-alpha, chemokines, autoantibodies

References [41]; [11]; [92]; [87]; [55] [93]; [94]; [95]; [96]; [97]; [20]; [96] [24]; [26]; [29]

Biomarkers for cardiovascular risk assessment in autoimmune diseases.

Autoimmune diseases, such as antiphospholipid syndrome, systemic lupus erythematosus, and rheumatoid arthritis, are characterized by a high prevalence...
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