Prioritizing Candidates of Post–Myocardial Infarction Heart Failure Using Plasma Proteomics and Single-Cell Transcriptomics. Issue 15 (13th October 2020)

• Record Type: Journal Article
• Authors: Chan, Mark Y.; Efthymios, Motakis; Tan, Sock Hwee; Pickering, John W.; Troughton, Richard; Pemberton, Christopher; Ho, Hee-Hwa; Prabath, Joseph-Francis; Drum, Chester L.; Ling, Lieng Hsi; Soo, Wern-Miin; Chai, Siang-Chew; Fong, Alan; Oon, Yen-Yee; Loh, Joshua P.; Lee, Chi-Hang; Foo, Roger S.Y.; Ackers-Johnson, Matthew Andrew; Pilbrow, Anna; Richards, A. Mark
• Is Part Of: Circulation. Volume 142:Issue 15(2020)
• Publication Date: 2020-10-13
• Subjects: heart failure -- myocardial infarction -- proteomics -- transcriptome; Blood -- Circulation -- Periodicals; Cardiovascular system -- Periodicals; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; Blood Circulation; Cardiovascular System; Vascular Diseases; 616.1
• DOI: 10.1161/CIRCULATIONAHA.119.045158
• Languages: English
• ISSNs: 0009-7322

Abstract

Abstract : Background: Heart failure (HF) is the most common long-term complication of acute myocardial infarction (MI). Understanding plasma proteins associated with post-MI HF and their gene expression may identify new candidates for biomarker and drug target discovery. Methods: We used aptamer-based affinity-capture plasma proteomics to measure 1305 plasma proteins at 1 month post-MI in a New Zealand cohort (CDCS [Coronary Disease Cohort Study]) including 181 patients post-MI who were subsequently hospitalized for HF in comparison with 250 patients post-MI who remained event free over a median follow-up of 4.9 years. We then correlated plasma proteins with left ventricular ejection fraction measured at 4 months post-MI and identified proteins potentially coregulated in post-MI HF using weighted gene co-expression network analysis. A Singapore cohort (IMMACULATE [Improving Outcomes in Myocardial Infarction through Reversal of Cardiac Remodelling]) of 223 patients post-MI, of which 33 patients were hospitalized for HF (median follow-up, 2.0 years), was used for further candidate enrichment of plasma proteins by using Fisher meta-analysis, resampling-based statistical testing, and machine learning. We then cross-referenced differentially expressed proteins with their differentially expressed genes from single-cell transcriptomes of nonmyocyte cardiac cells isolated from a murine MI model, and single-cell and single-nucleus transcriptomes of cardiac myocytes from murine HF models and human patients with HF. Results: In the CDCS cohort, 212 differentially expressed plasma proteins were significantly associated with subsequent HF events. Of these, 96 correlated with left ventricular ejection fraction measured at 4 months post-MI. Weighted gene co-expression network analysis prioritized 63 of the 212 proteins that demonstrated significantly higher correlations among patients who developed post-MI HF in comparison with event-free controls (data set 1). Cross-cohort meta-analysis of the IMMACULATE cohort identified 36 plasma proteins associated with post-MI HF (data set 2), whereas single-cell transcriptomes identified 15 gene-protein candidates (data set 3). The majority of prioritized proteins were of matricellular origin. The 6 most highly enriched proteins that were common to all 3 data sets included well-established biomarkers of post-MI HF: N-terminal B-type natriuretic peptide and troponin T, and newly emergent biomarkers, angiopoietin-2, thrombospondin-2, latent transforming growth factor-β binding protein-4, and follistatin-related protein-3, as well. Conclusions: Large-scale human plasma proteomics, cross-referenced to unbiased cardiac transcriptomics at single-cell resolution, prioritized protein candidates associated with post-MI HF for further mechanistic and clinical validation. Abstract : Supplemental Digital Content is available in the text.