Whole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals.
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2025-09
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Abstract
Background
Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability.Results
Here, we conduct the largest meta-analysis of whole genome sequencing for low-density lipoprotein cholesterol (LDL-C), a therapeutic target for coronary artery disease, analyzing data from 246 K participants and integrating 1.23B variants from the UK Biobank and the Trans-Omics for Precision Medicine (TOPMed) program. We identify numerous rare coding and non-coding gene associations related to LDL-C, with replication across 86 K participants in All of Us. Our findings are based on single-variant analyses, rare coding and non-coding variant aggregation tests, and sliding window approaches. Through this comprehensive analysis, we identify 704 novel single-variant associations, 25 novel rare coding variant aggregates, 28 novel rare non-coding variant aggregates, and one novel sliding window aggregate.Conclusions
This study provides a meta-analysis framework for large-scale whole genome sequence association analyses from diverse population groups, yielding novel rare non-coding variant associations.Type
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Selvaraj, Margaret Sunitha, Xihao Li, Zilin Li, Eric Van Buren, Sara Haidermota, Darina Postupaka, Whitney Hornsby, Joshua C Bis, et al. (2025). Whole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals. Genome biology, 26(1). p. 273. 10.1186/s13059-025-03698-0 Retrieved from https://hdl.handle.net/10161/33616.
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Scholars@Duke
Svati Hasmukh Shah
William Erle Kraus
My training, expertise and research interests range from human integrative physiology and genetics to animal exercise models to cell culture models of skeletal muscle adaptation to mechanical stretch. I am trained clinically as an internist and preventive cardiologist, with particular expertise in preventive cardiology and cardiac rehabilitation. My research training spans molecular biology and cell culture, molecular genetics, and integrative human exercise physiology and metabolism. I practice as a preventive cardiologist with a focus on cardiometabolic risk and exercise physiology for older athletes. My research space has both a basic wet laboratory component and a human integrative physiology one.
One focus of our work is an integrative physiologic examination of exercise effects in human subjects in clinical studies of exercise training in normal individuals, in individuals at risk of disease (such as pre-diabetes and metabolic syndrome; STRRIDE), and in individuals with disease (such as coronary heart disease, congestive heart failure and cancer).
A second focus of my research group is exploration of genetic determinates of disease risk in human subjects. We conduct studies of early onset cardiovascular disease (GENECARD; CATHGEN), congestive heart failure (HF-ACTION), peripheral arterial disease (AMNESTI), and metabolic syndrome. We are exploring analytic models of predicting disease risk using established and innovative statistical methodology.
A third focus of my group’s work is to understand the cellular signaling mechanisms underlying the normal adaptive responses of skeletal muscle to physiologic stimuli, such as occur in exercise conditioning, and to understand the abnormal maladaptive responses that occur in response to pathophysiologic stimuli, such as occur in congestive heart failure, aging and prolonged exposure to microgravity.
Recently we have begun to investigate interactions of genes and lifestyle interventions on cardiometabolic outcomes. We have experience with clinical lifestyle intervention studies, particularly the contributions of genetic variants to interventions responses. We call this Lifestyle Medicopharmacogenetics.
KEY WORDS:
exercise, skeletal muscle, energy metabolism, cell signaling, gene expression, cell stretch, heart failure, aging, spaceflight, human genetics, early onset cardiovascular disease, lifestyle medicine
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