Quantitative proteomics study reveals differential proteomic signature in dilated, restrictive, and hypertrophic cardiomyopathies
- 4 Downloads
Abstract
Cardiomyopathy is a disease of the heart muscle with varying etiologies and leads to heart failure. The pathways altered in the three forms of cardiomyopathy are not very clearly understood and hence in this study we attempted to identify differentially expressed proteins and pathways that are altered in the plasma of dilated, hypertrophic, and restrictive cardiomyopathy patients. For relative quantitation of the proteins we used both serial window acquisition of all theoretical mass spectra (SWATH-MS) and isobaric tags for relative and absolute quantitation techniques (iTRAQ). A total of 20 samples of DCM, HCM, RCM, and controls (5 each) were analyzed using SWATH while 3 samples in each group were analyzed using iTRAQ technique. Using SWATH, we could identify approximately 300 proteins in each of the four groups of which 205 proteins were found to be common. Of these 205 common proteins, 52, 58, and 52 proteins were found to be significantly differentially expressed in DCM, HCM, and RCM groups, respectively. Using iTRAQ, we could identify only about 150–180 proteins in the three experiments of which 96 were common. Our results indicated that most of the pathways that were enriched with the differentially expressed proteins, such as complement activation, platelet degranulation, immune response, etc., were common for DCM, RCM, and HCM. However, some of the pathways were unique as well to these groups. This study suggested that label-free SWATH in conjunction with iTRAQ-based quantitative proteomics approach could identify larger number of proteins and also highlights the importance of integrating two methods to dissect the molecular pathways involved in the progression of cardiomyopathies.
Keywords
Cardiomyopathy DCM HCM RCM iTRAQ SWATH ProteomicsAbbreviations
- SWATH
Sequential wide acquisition of theoretical fragments
- iTRAQ
Isobaric tag for relative and absolute quantification
- XIC
Extracted ion chromatogram
- DCM
Dilated cardiomyopathy
- HCM
Hypertrophic cardiomyopathy
- RCM
Restrictive cardiomyopathy
- TTOF
Triple-TOF
- DTT
Dithiothreitol
- IAA
Iodoacetamide
- RT
Retention time
- SCX
Strong cation exchange
- APOA
Apolipoprotein A
Notes
Acknowledgements
The authors acknowledge financial assistance from Council of Scientific and Industrial Research (CSIR), Ministry of Science and Technology, Govt. of India, India under the XII FYP project titled “Centre for Cardiovascular and Metabolic Disease Research (BSC0122)”. SG and SN acknowledge fellowship from CSIR. SV acknowledge UGC for funding. We thank Mr. Nitin Bhardwaj for measurement of biochemical parameter. We also thank the patients for giving their consent to participate in the study.
Compliance with ethical standards
Conflict of interest
All the authors declare that they have no conflict of interest.
Supplementary material
References
- Albakri A (2018) Restrictive cardiomyopathy: a review of literature on clinical status and meta-analysis of diagnosis and clinical management methods table of contents. Int Med Care 2(1):1–15Google Scholar
- Anderson L (2005) Candidate-based proteomics in the search for biomarkers of cardiovascular disease. J Physiol 563:23–60CrossRefGoogle Scholar
- Anonymous (1980) Report of the WHO/ISFC task force on the definition and classification of cardiomyopathies. Br Heart J 44:672–673CrossRefGoogle Scholar
- Basak T, Tanwar VS, Bhardwaj G et al (2016) Plasma proteomic analysis of stable coronary artery disease indicates impairment of reverse cholesterol pathway. Sci Rep 6:28042CrossRefGoogle Scholar
- Bhat A, Malakar D, Sengupta S (2016) Evaluation of SWATH-MS based quantification for its accuracy and consistency across concentrations of spiked-in peptides. J Proteins Proteom 7(2):115–120Google Scholar
- Biswas A, Das S, Kapoor M et al (2018) Familial hypertrophic cardiomyopathy—identification of cause and risk stratification through exome sequencing. Gene 660:151–156CrossRefGoogle Scholar
- Brown RD, Mitchell MD, Long CS (2005) Pro-inflammatory cytokines and cardiac extracellular matrix: regulation of fibroblast phenotype. In: Interstitial fibrosis in heart failure. Developments in cardiovascular medicine, vol 253. Springer, New York, pp 57–81CrossRefGoogle Scholar
- Burke MA, Cook SA, Seidman JG et al (2016) Clinical and mechanistic insights into the genetics of cardiomyopathy. J Am Coll Cardiol 68:2871–2886CrossRefGoogle Scholar
- Caillard A, Sadoune M, Cescau A et al (2018) QSOX1, a novel actor of cardiac protection upon acute stress in mice. J Mol Cell Cardiol 119:75–86CrossRefGoogle Scholar
- Cieniewski-Bernard C, Mulder P, Henry JP et al (2008) Proteomic analysis of left ventricular remodeling in an experimental model of heart failure. J Proteome Res 7:5004–5016CrossRefGoogle Scholar
- Colak D, Alaiya AA, Kaya N et al (2016) Integrated left ventricular global transcriptome and proteome profiling in human end-stage dilated cardiomyopathy. PLoS One 11:e0162669CrossRefGoogle Scholar
- Emdin M, Vittorini S, Passino C et al (2009) Old and new biomarkers of heart failure. Eur J Heart Fail 11:331–335CrossRefGoogle Scholar
- Engebretsen KV, Lunde IG, Strand ME et al (2013) Lumican is increased in experimental and clinical heart failure, and its production by cardiac fibroblasts is induced by mechanical and proinflammatory stimuli. FEBS J 280:2382–2398CrossRefGoogle Scholar
- Fu ZQ, Li XY, Liu XH et al (2008) Overexpression of sarcoplasmic reticulum calcium ATPase induced hemodynamic and proteomic changes in a dog model of heart failure. Zhonghua Xin Xue Guan Bing Za Zhi 36:260–265Google Scholar
- Garcia A, Eiras S, Parguina AF et al (2011) High-resolution two-dimensional gel electrophoresis analysis of atrial tissue proteome reveals down-regulation of fibulin-1 in atrial fibrillation. Int J Cardiol 150:283–290CrossRefGoogle Scholar
- Geyer PE, Kulak NA, Pichler G et al (2016) Plasma proteome profiling to assess human health and disease. Cell Syst 2:185–195CrossRefGoogle Scholar
- Geyer PE, Holdt LM, Teupser D et al (2017) Revisiting biomarker discovery by plasma proteomics. Mol Syst Biol 13:942CrossRefGoogle Scholar
- Gopal DM, Sam F (2013) New and emerging biomarkers in left ventricular systolic dysfunction–insight into dilated cardiomyopathy. J Cardiovasc Transl Res 6:516–527CrossRefGoogle Scholar
- Guo Y, Cui L, Jiang S et al (2017) Proteomics of acute heart failure in a rat post-myocardial infarction model. Mol Med Rep 16:1946–1956CrossRefGoogle Scholar
- Hazebroek M, Dennert R, Heymans S (2012) Idiopathic dilated cardiomyopathy: possible triggers and treatment strategies. Neth Heart J 20:332–335CrossRefGoogle Scholar
- Huang CY, Yang YH, Lin LY et al (2018) Renin-angiotensin-aldosterone blockade reduces atrial fibrillation in hypertrophic cardiomyopathy. Heart 104:1276–1283CrossRefGoogle Scholar
- Izquierdo I, Rosa I, Bravo SB et al (2016) Proteomic identification of putative biomarkers for early detection of sudden cardiac death in a family with a LMNA gene mutation causing dilated cardiomyopathy. J Proteom 148:75–84CrossRefGoogle Scholar
- Jun HO, Kim DH, Lee SW et al (2011) Clusterin protects H9c2 cardiomyocytes from oxidative stress-induced apoptosis via Akt/GSK-3beta signaling pathway. Exp Mol Med 43:53–61CrossRefGoogle Scholar
- Konstandin MH, Volkers M, Collins B et al (2013) Fibronectin contributes to pathological cardiac hypertrophy but not physiological growth. Basic Res Cardiol 108:375CrossRefGoogle Scholar
- Kruska M, El-Battrawy I, Behnes M et al (2017) Biomarkers in cardiomyopathies and prediction of sudden cardiac death. Curr Pharm Biotechnol 18:472–481CrossRefGoogle Scholar
- Li GH, Shi Y, Chen Y et al (2009) Gelsolin regulates cardiac remodeling after myocardial infarction through DNase I-mediated apoptosis. Circ Res 104:896–904CrossRefGoogle Scholar
- Liu S, Xia Y, Liu X et al (2017) In-depth proteomic profiling of left ventricular tissues in human end-stage dilated cardiomyopathy. Oncotarget 8:48321–48332Google Scholar
- Luk A, Ahn E, Soor GS et al (2009) Dilated cardiomyopathy: a review. J Clin Pathol 62:219–225CrossRefGoogle Scholar
- Maron BJ (2002) Hypertrophic cardiomyopathy: a systematic review. JAMA 287:1308–1320Google Scholar
- Maron BJ, Maron MS, Semsarian C (2012) Genetics of hypertrophic cardiomyopathy after 20 years: clinical perspectives. J Am Coll Cardiol 60:705–715CrossRefGoogle Scholar
- Martinelli AEM, Maranhao RC, Carvalho PO et al (2018) Cholesteryl ester transfer protein (CETP), HDL capacity of receiving cholesterol and status of inflammatory cytokines in patients with severe heart failure. Lipids Health Dis 17:242CrossRefGoogle Scholar
- Mcnally EM, Barefield DY, Puckelwartz MJ (2015) The genetic landscape of cardiomyopathy and its role in heart failure. Cell Metab 21:174–182CrossRefGoogle Scholar
- Mogensen J, Arbustini E (2009) Restrictive cardiomyopathy. Curr Opin Cardiol 24:214–220CrossRefGoogle Scholar
- Naito AT, Sumida T, Nomura S et al (2012) Complement C1q activates canonical Wnt signaling and promotes aging-related phenotypes. Cell 149:1298–1313CrossRefGoogle Scholar
- Nihoyannopoulos P, Dawson D (2009) Restrictive cardiomyopathies. Eur J Echocardiogr 10:iii23–iii33CrossRefGoogle Scholar
- Orrem HL, Nilsson PH, Pischke SE et al (2018) Acute heart failure following myocardial infarction: complement activation correlates with the severity of heart failure in patients developing cardiogenic shock. ESC Heart Fail 5:292–301CrossRefGoogle Scholar
- Pilichou K, Thiene G, Bauce B et al (2016) Arrhythmogenic cardiomyopathy. Orphanet J Rare Dis 11:33CrossRefGoogle Scholar
- Prinz C, Farr M, Hering D et al (2011) The diagnosis and treatment of hypertrophic cardiomyopathy. Dtsch Arztebl Int 108:209–215Google Scholar
- Priori SG, Blomstrom-Lundqvist C, Mazzanti A et al (2015) 2015 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: the task force for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death of the European Society of Cardiology (ESC)Endorsed by: association for european paediatric and congenital cardiology (AEPC). Europace 17:1601–1687Google Scholar
- Raghow R (2016) An ‘Omics’ perspective on cardiomyopathies and heart failure. Trends Mol Med 22:813–827CrossRefGoogle Scholar
- Rehulkova H, Rehulka P, Myslivcova Fucikova A et al (2016) Identification of novel biomarker candidates for hypertrophic cardiomyopathy and other cardiovascular diseases leading to heart failure. Physiol Res 65:751–762Google Scholar
- Rosello-Lleti E, Alonso J, Cortes R et al (2012) Cardiac protein changes in ischaemic and dilated cardiomyopathy: a proteomic study of human left ventricular tissue. J Cell Mol Med 16:2471–2486CrossRefGoogle Scholar
- Roura S, Gamez-Valero A, Lupon J et al (2018) Proteomic signature of circulating extracellular vesicles in dilated cardiomyopathy. Lab Invest 98:1291–1299CrossRefGoogle Scholar
- Schoenhoff FS, Fu Q, Van Eyk JE (2009) Cardiovascular proteomics: implications for clinical applications. Clin Lab Med 29:87–99CrossRefGoogle Scholar
- Schott P, Asif AR, Graf C et al (2008) Myocardial adaptation of energy metabolism to elevated preload depends on calcineurin activity: a proteomic approach. Basic Res Cardiol 103:232–243CrossRefGoogle Scholar
- Trujillo G, Kew RR (2004) Platelet-derived thrombospondin-1 is necessary for the vitamin D-binding protein (Gc-globulin) to function as a chemotactic cofactor for C5a. J Immunol 173:4130–4136CrossRefGoogle Scholar
- Verk B, Nemec Svete A, Salobir J et al (2017) Markers of oxidative stress in dogs with heart failure. J Vet Diagn Invest 29:636–644CrossRefGoogle Scholar
- Vikhorev PG, Vikhoreva NN (2018) Cardiomyopathies and related changes in contractility of human heart muscle. Int J Mol Sci 19:2234CrossRefGoogle Scholar