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Updated: Jan 18, 2026
Isolation of High-density Lipoproteins for Non-coding Small RNA Quantification
Published on: November 28, 2016
Whole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals
Margaret Sunitha Selvaraj1,2,3, Xihao Li4,5, Zilin Li6
1Center for Genomic Medicine, Cardiovascular Research Center, , Massachusetts General Hospital Simches Research Center, 185 Cambridge Street, CPZN 5.238,, Boston, MA, 02114, USA.
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.
