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 employed aptamer-based affinity-capture plasma proteomics to measure 1305 plasma proteins at one month post-MI in a New Zealand cohort (CDCS) including 181 post-MI patients who were subsequently hospitalized for HF compared with 250 post-MI patients 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 co-regulated in post-MI HF using Weighted Gene Co-expression Network Analysis (WCGNA). A Singapore cohort (IMMACULATE) of 223 post-MI patients, of which 33 patients were hospitalized for HF (median follow-up 2.0 years), was used for further candidate enrichment of plasma proteins 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 non-myocyte cardiac cells isolated from a murine MI model, and single-cell and single-nuclei transcriptomes of cardiac myocytes from murine HF models and human HF patients. 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. WCGNA prioritised 63 of the 212 proteins that demonstrated significantly higher correlations among patients who developed post-MI HF compared with event-free controls (dataset 1). Cross-cohort meta-analysis of the IMMACULATE cohort identified 36 plasma proteins associated with post-MI HF (dataset 2) while single-cell transcriptomes identified 15 gene-protein candidates (dataset 3). The majority of prioritized proteins were of matricellular origin. The 6 most highly-enriched proteins that were common to all 3 datasets included well-established biomarkers of post-MI HF - N-terminal B-type natriuretic peptide and troponin T - as well as newly-emergent biomarkers - angiopoietin-2, thrombospondin-2, latent transforming growth factor-β binding protein-4 and follistatin-related protein-3. Conclusions: Large-scale human plasma proteomics, cross-referenced to unbiased cardiac cell transcriptomics at single-cell resolution, prioritized protein candidates associated with post-MI HF for further mechanistic and clinical validation.

Plasma extracellular vesicles (EVs) are lipid membrane vesicles involved in several biological processes including coagulation. Both coagulation and lipid metabolism are strongly associated with cardiovascular events. Lowering very-low- and low-density lipoprotein ((V)LDL) particles via dextran sulphate LDL apheresis also removes coagulation proteins. It remains unknown, however, how coagulation proteins are removed in apheresis. We hypothesize that plasma EVs that contain high levels of coagulation proteins are concomitantly removed with (V)LDL particles by dextran sulphate apheresis. For this, we precipitated (V)LDL particles from human plasma with dextran sulphate and analyzed the abundance of coagulation proteins and EVs in the precipitate. Coagulation pathway proteins, as demonstrated by proteomics and a bead-based immunoassay, were over-represented in the (V)LDL precipitate. In this precipitate, both bilayer EVs and monolayer (V)LDL particles were observed by electron microscopy. Separation of EVs from (V)LDL particles using density gradient centrifugation revealed that almost all coagulation proteins were present in the EVs and not in the (V)LDL particles. These EVs also showed a strong procoagulant activity. Our study suggests that dextran sulphate used in LDL apheresis may remove procoagulant EVs concomitantly with (V)LDL particles, leading to a loss of coagulation proteins from the blood.

Objective: While the risk of acute coronary events has been associated with biological variability of circulating cholesterol, the association with variability of other atherogenic lipids remains less understood. We evaluated the longitudinal variability of 284 lipids and investigated their association with asymptomatic coronary atherosclerosis. Approach and Results: Circulating lipids were extracted from fasting blood samples of 83 community-sampled symptom-free participants (age 41–75 years), collected longitudinally over 6 months. Three types of coronary plaque volume (calcified, lipid-rich, and fibrotic) were quantified using computed tomography coronary angiogram. We first deconvoluted between-subject (CV _g ) and within-subject (CV _w ) lipid variabilities. We then tested whether the mean lipid abundance was different across groups categorized by Framingham risk score and plaques phenotypes (lipid-rich, fibrotic, and calcified). Finally, we investigated whether visit-to-visit variability of each lipid was associated with plaque burden. Most lipids (72.5%) exhibited higher CV _g than CV _w . Among the lipids (n=145) with 1.2-fold higher CV _g than CV _w , 26 species including glycerides and ceramides were significantly associated with Framingham risk score and the 3 plaque phenotypes (false discovery rate <0.05). In an exploratory analysis of person-specific visit-to-visit variability without multiple testing correction, high variability of 3 lysophospholipids (lysophosphatidylethanolamines 16:0, 18:0, and lysophosphatidylcholine O-18:1) was associated with lipid-rich and fibrotic (noncalcified) plaque volume while high variability of diacylglycerol 18:1_20:0, triacylglycerols 52:2, 52:3, and 52:4, ceramide d18:0/20:0, dihexosylceramide d18:1/16:0, and sphingomyelin 36:3 was associated with calcified plaque volume. Conclusions: High person-specific longitudinal variation of specific nonsterol lipids is associated with the burden of subclinical coronary atherosclerosis. Larger studies are needed to confirm these exploratory findings.

Background: Because of a nonresponse to aspirin (aspirin resistance), patients with acute coronary syndrome (ACS) are at increased risk of developing recurrent event. The in vitro platelet function tests have potential limitations, making them unsuitable for the detection of aspirin resistance. We investigated whether miR‐19b‐1‐5p could be utilized as a biomarker for aspirin resistance and future major adverse cardio‐cerebrovascular (MACCE) events in patients with ACS. Methods and Results: In this cohort study, patients with ACS were enrolled from multiple tertiary hospitals in Christchurch, Hong Kong, Sarawak, and Singapore between 2011 and 2015. MiR‐19b‐1‐5p expression was measured from buffy coat of patients with ACS (n=945) by reverse transcription quantitative polymerase chain reaction. Platelet function was determined by Multiplate aggregometry testing. MACCE was collected over a mean follow‐up time of 1.01±0.43 years. Low miR‐19b‐1‐5p expression was found to be related to aspirin resistance as could be observed from sustained platelet aggregation in the presence of aspirin (‐Log‐miR‐19b‐1‐5p, [unstandardized beta, 44.50; 95% CI, 2.20–86.80; P <0.05]), even after adjusting for age, sex, ethnicity, and prior history of stroke. Lower miR‐19b‐1‐5p expression was independently associated with a higher risk of MACCE (‐Log‐miR‐19b‐1‐5p, [hazard ratio, 1.85; 95% CI, 1.23–2.80; P <0.05]). Furthermore, a significant interaction was noted between the inverse miR‐19b‐1‐5p expression and family history of premature coronary artery disease ( P =0.01) on the risk of MACCE. Conclusions: Lower miR‐19b‐1‐5p expression was found to be associated with sustained platelet aggregation on aspirin, and a higher risk of MACCE in patients with ACS. Therefore, miR‐19b‐1‐5p could be a suitable marker for aspirin resistance and might predict recurrence of MACCE in patients with ACS.

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. This work aims to investigate the translational potential of a multi-omics study (comprising metabolomics, lipidomics, glycomics, and metallomics) in revealing biomechanistic insights into AMI. Following the N-glycomics and metallomics studies performed by our group previously, untargeted metabolomic and lipidomic profiles were generated and analysed in this work via the use of a simultaneous metabolite/lipid extraction and liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis workflow. The workflow was applied to blood plasma samples from AMI cases (n = 101) and age-matched healthy controls (n = 66). The annotated metabolomic (number of features, n = 27) and lipidomic (n = 48) profiles, along with the glycomic (n = 37) and metallomic (n = 30) profiles of the same set of AMI and healthy samples were integrated and analysed. The integration method used here works by identifying a linear combination of maximally correlated features across the four omics datasets, via utilising both block-partial least squares-discriminant analysis (block-PLS-DA) based on sparse generalised canonical correlation analysis. Based on the multi-omics mapping of biomolecular interconnections, several postulations were derived. These include the potential roles of glycerophospholipids in N-glycan-modulated immunoregulatory effects, as well as the augmentation of the importance of Ca–ATPases in cardiovascular conditions, while also suggesting contributions of phosphatidylethanolamine in their functions. Moreover, it was shown that combining the four omics datasets synergistically enhanced the classifier performance in discriminating between AMI and healthy subjects. Fresh and intriguing insights into AMI, otherwise undetected via single-omics analysis, were revealed in this multi-omics study. Taken together, we provide evidence that a multi-omics strategy may synergistically reinforce and enhance our understanding of diseases.

Background: The comparison of coronary computed tomography angiography plaques and perivascular adipose tissue (PVAT) between patients with acute myocardial infarction (AMI) posttreatment and patients with stable coronary artery disease is poorly understood. Our objective was to evaluate the differences in coronary computed tomography angiography–quantified plaque and PVAT characteristics in patients post‐AMI and identify signs of residual inflammation. Methods and Results: We analyzed 205 patients (age, 59.77±9.24 years; 92.20% men) with AMI ≤1 month and matched them with 205 patients with stable coronary artery disease (age, 60.52±10.04 years; 90.24% men) based on age, sex, and cardiovascular risk factors. Coronary computed tomography angiography scans were assessed for nonculprit plaque and vessel characteristics, plaque volumes by composition, high‐risk plaques, and PVAT mean attenuation. Both patient groups exhibited similar noncalcified plaque volumes (383.35±313.23 versus 378.63±426.25 mm ³ , P =0.899). However, multivariable analysis revealed that patients post‐AMI had a greater patient‐wise noncalcified plaque volume ratio (estimate, 0.089 [95% CI, 0.053–0.125], P <0.001), largely attributed to a higher fibrofatty and necrotic core volume ratio, along with higher peri‐lesion PVAT mean attenuation (estimate, 3.968 [95% CI, 2.556–5.379], P <0.001). When adjusted for vessel length, patients post‐AMI had more high‐risk plaques (estimate, 0.417 [95% CI, 0.298–0.536], P <0.001) per patient. Conclusions: Patients post‐AMI displayed heightened noncalcified plaque components, largely due to fibrofatty and necrotic core content, more high‐risk plaques, and increased PVAT mean attenuation on a per‐patient level, highlighting the necessity for refined risk assessment in patients with AMI after treatment.