Genetic Architecture and Clinical Outcomes of Combined Lipid Disturbances

Author:

Gilliland Thomas123ORCID,Dron Jacqueline S.42ORCID,Selvaraj Margaret Sunitha123ORCID,Trinder Mark25ORCID,Paruchuri Kaavya123ORCID,Urbut Sarah M.123ORCID,Haidermota Sara12ORCID,Bernardo Rachel12ORCID,Uddin Md Mesbah12ORCID,Honigberg Michael C.123ORCID,Peloso Gina M.6ORCID,Natarajan Pradeep1423ORCID

Affiliation:

1. Cardiovascular Research Center (T.G., M.S.S., K.P., S.M.U., S.H., R.B., M.M.U., M.C.H., P.N.), Massachusetts General Hospital, Boston, MA.

2. Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA (T.G., J.S.D., M.S.S., M.T., K.P., S.M.U., S.H., R.B., M.M.U., M.C.H., P.N.).

3. Department of Medicine, Harvard Medical School, Boston, MA (T.G., M.S.S., K.P., S.M.U., M.C.H., P.N.).

4. Center for Genomic Medicine (J.S.D., P.N.), Massachusetts General Hospital, Boston, MA.

5. Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada (M.T.).

6. Department of Biostatistics, Boston University School of Public Health, Boston, MA (G.M.P.).

Abstract

BACKGROUND: Dyslipoproteinemia often involves simultaneous derangements of multiple lipid traits. We aimed to evaluate the phenotypic and genetic characteristics of combined lipid disturbances in a general population-based cohort. METHODS: Among UK Biobank participants without prevalent coronary artery disease, we used blood lipid and apolipoprotein B concentrations to ascribe individuals into 1 of 6 reproducible and mutually exclusive dyslipoproteinemia subtypes. Incident coronary artery disease risk was estimated for each subtype using Cox proportional hazards models. Phenome-wide analyses and genome-wide association studies were performed for each subtype, followed by in silico causal gene prioritization and heritability analyses. Additionally, the prevalence of disruptive variants in causal genes for Mendelian lipid disorders was assessed using whole-exome sequence data. RESULTS: Among 450 636 UK Biobank participants: 63 (0.01%) had chylomicronemia; 40 005 (8.9%) had hypercholesterolemia; 94 785 (21.0%) had combined hyperlipidemia; 13 998 (3.1%) had remnant hypercholesterolemia; 110 389 (24.5%) had hypertriglyceridemia; and 49 (0.01%) had mixed hypertriglyceridemia and hypercholesterolemia. Over a median (interquartile range) follow-up of 11.1 (10.4–11.8) years, incident coronary artery disease risk varied across subtypes, with combined hyperlipidemia exhibiting the largest hazard (hazard ratio, 1.92 [95% CI, 1.84–2.01]; P =2×10 −16 ), even when accounting for non-HDL-C (hazard ratio, 1.45 [95% CI, 1.30–1.60]; P =2.6×10 −12 ). Genome-wide association studies revealed 250 loci significantly associated with dyslipoproteinemia subtypes, of which 72 (28.8%) were not detected in prior single lipid trait genome-wide association studies. Mendelian lipid variant carriers were rare (2.0%) among individuals with dyslipoproteinemia, but polygenic heritability was high, ranging from 23% for remnant hypercholesterolemia to 54% for combined hyperlipidemia. CONCLUSIONS: Simultaneous assessment of multiple lipid derangements revealed nuanced differences in coronary artery disease risk and genetic architectures across dyslipoproteinemia subtypes. These findings highlight the importance of looking beyond single lipid traits to better understand combined lipid and lipoprotein phenotypes and implications for disease risk.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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