Arshed A Quyyumi | PubMed Health

PubMed2026

Multi-ancestry genetic architecture of heart failure subtypes.

Heart failure (HF) affects 6.7 million people in the US and includes two major subtypes, HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF), with distinct genetic architectures. We meta-analyze genome-wide association studies (GWAS) of 38,781 HFrEF cases, 38,163 HFpEF cases, and 526,135 controls across European, African, Hispanic, and Asian ancestries using the Million Veteran Program and Vanderbilt University DNA Databank (BioVU). We identify 46 genome-wide significant loci for HFrEF (9 novel) and 3 loci for HFpEF (1 novel). Four HFrEF loci are detected in African ancestry participants near CD36, SPI1, TRIM48, and SPNS3, with lead SNPs showing low risk-allele frequencies in European populations. In the all-cause HF meta-analysis (200,070 cases, 2,076,466 controls), we identify 136 loci (12 novel). Gene-based tests, tissue enrichment, transcriptome-wide association, and fine-mapping implicate vascular, metabolic, and TGF-β/Smad signaling pathways and nominate candidate causal genes, clarifying shared and subtype-specific risk across ancestries.

Humans↗

PubMed2026

Proteomics-Based Soluble Urokinase Plasminogen Activator Receptor Levels Are Associated With Adverse Cardiovascular Outcomes in the General Population: Insights From the UK Biobank.

BACKGROUND: Elevated soluble urokinase plasminogen activator receptor (suPAR) levels are associated with inflammation, immune activation, and major adverse cardiovascular events in coronary artery disease. Encoded by the PLAUR gene, suPAR levels are influenced by the rs4760 genetic variant. Whether proteomics-based suPAR levels predict adverse outcomes in the general population remains unknown. METHODS: Proteomics-based suPAR levels were measured using the Olink Immunoassay in 33 963 UK Biobank participants without known coronary artery disease. Fine-Gray and Cox proportional hazards models assessed associations between suPAR and major adverse cardiovascular events (primary outcome: cardiovascular mortality, nonfatal myocardial infarction, or stroke), cardiovascular mortality, and all-cause mortality (secondary outcomes), after adjustment for demographic and clinical risk factors, hs-CRP (high-sensitivity C-reactive protein), and the rs4760 variant. Incremental discrimination was evaluated using C-statistics. RESULTS: Participants were aged 56.4 (SD, 8.2) years; 45% were men, and 93.4% were White. Over a median follow-up of 14 years (476 177 person-years), 10.7% experienced major adverse cardiovascular events, 2.6% experienced cardiovascular mortality, and 9.4% experienced all-cause mortality. Each 1-SD increment in proteomics-based suPAR was associated with significantly higher risk of major adverse cardiovascular events (hazard ratio [HR], 3.2 [95% CI, 2.9-4.5]), cardiovascular mortality (HR, 5.9 [95% CI, 5.1-6.9]), and all-cause mortality (HR, 5.0 [95% CI, 4.6-5.5]), independent of clinical risk factors and hs-CRP. Additional adjustment for rs4760 did not attenuate these associations. Proteomics-based suPAR significantly improved discrimination beyond clinical risk factors (C-statistic: 0.719 versus 0.732; P<0.001). CONCLUSIONS: Proteomics-based suPAR independently predicts adverse cardiovascular outcomes in the general population, beyond conventional risk factors, hs-CRP, and genetic predisposition to elevated suPAR levels.

Humans↗