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Yuxuan Wang

Postdoctoral Researcher
Broad Institute


Cited by 556

Research Story

Blood lipid levels — cholesterol and triglycerides — are among the most heritable traits in the human body, yet for most of the genome we still don't know why certain DNA variants raise or lower them. My research approaches this problem from two directions at once: hunting for new genetic signals in datasets spanning hundreds of thousands of people, and developing the statistical methods needed to find signals that classical approaches miss entirely. The work ultimately connects DNA to disease — asking not just where the signals are, but what they mean for heart health.

5 Papers
206 Citations
4 Journals
Theme A
Lipid GWAS Meta-analysis
The first systematic maps of the lipid genome came from genome-wide association studies (GWAS) — experiments that genotype hundreds of thousands of people and test millions of common DNA variants for association with cholesterol and triglyceride levels. As a co-first author on two landmark GLGC papers, I helped push this science from simply cataloguing genomic locations to understanding what they mean. The 2022 Genome Biology paper asked which genes each signal acts through, whether the same loci affect men and women differently (sexual dimorphism), and whether they simultaneously influence multiple lipid traits (pleiotropy). A companion AJHG paper applied a functional genomics lens — layering data on gene regulation, tissue-specific activity, and epigenetic marks — to decode what the noncoding variants are actually doing at the molecular level.
Theme B
Lipid Whole-Genome Sequencing
Array-based GWAS captures only common variants — those present in at least 1% of the population. Whole-genome sequencing (WGS) reads every base pair, opening the genome to rarer, potentially more impactful variants. As part of the TOPMed consortium, I helped analyze WGS data from over 66,000 people to identify new lipid-associated loci across the allele frequency spectrum (Nature Communications, 2022). My first-author AJHG 2023 paper went further: it specifically hunted for rare variants in long non-coding RNAs — a class of the genome largely invisible to GWAS — and found significant associations with blood lipid levels, opening a new layer of the lipid genome. A 2025 Genome Biology study extended this approach to 246,000 individuals for LDL cholesterol, one of the largest lipid sequencing studies to date.