Yan V. Sun

The paper identifies 800 exome-wide significant rare coding variants associated with blood lipids in over a million diverse individuals, including 130 driven by non-European-like populations.

This study conducts an X-chromosome-wide association study to identify genetic signals for heart failure and its subtypes, finding novel loci and replicating some in UK Biobank.

This study identifies two independent BMI-associated variants at the GLP1R locus with distinct associations with T2D risk, suggesting heterogeneous genetic mechanisms.

GENPHIRE uses a large language model to convert genotype profiles into embedded vectors for disease risk prediction, outperforming existing polygenic risk scores in UK Biobank data.

This study identifies novel genetic signals associated with severe obesity through GWAS and shows strong genetic overlap with BMI, highlighting shared comorbidities and lifestyle interactions.

The paper performs GWAS on cardiovascular outcomes in CKD patients, identifying stroke-associated SNVs but not replicating CHD findings, and finding genetic correlations with published GWAS.

The paper explores primary care providers' experiences with receiving genetic results from a national biobank study, highlighting challenges in integrating genetic information into routine care.

Population-stratified GWAS of 2,068 traits in 635,969 Million Veteran Program participants, 29% genetically non-European, yields 98,485 associations and 57,601 fine-mapped signals with largely shared cross-population architecture.

This study identifies six novel genetic loci associated with BMI change over adulthood using UK Biobank health records, finding lower heritability for BMI change compared to baseline BMI.

The paper describes the design and pilot results of a study returning genetic results for familial hypercholesterolemia to MVP participants, showing a reduction in LDL-C after genetic counseling.

This paper corrects collider bias in a GWAS of diabetes-related heart failure, identifying novel loci and showing bidirectional genetic associations between T2D and HF.

The paper identifies inflammation-related proteins associated with age, sex, and CD4+ cell count in HIV-positive individuals in South Africa, highlighting potential links to chronic diseases.

This study identifies novel genetic risk variants and potential drug targets for heart failure using GWAS and Mendelian randomization proteomics.

This study compares the genetic architecture of heart failure with preserved ejection fraction (HFpEF) and reduced ejection fraction (HFrEF), finding distinct genetic associations and highlighting HFpEF's heterogeneity.

This study analyzes clonal hematopoiesis in over a million diverse individuals, identifying 72 genome-wide significant loci and linking CHIP to various phenotypes.

This study conducts a trans-ancestry GWAS using chronic ALT elevation as a proxy for NAFLD, identifies 77 significant loci, and validates 17 SNPs with histology and imaging data, revealing genetic links to metabolic and inflammatory traits.

This study integrates rare large-effect expression variants into polygenic risk scores, showing improved prediction of complex traits by including these variants in risk assessment.

This study shows that FH genetic variants increase CAD risk even after adjusting for multiple LDL-C measurements from EHRs, indicating LDL-C data alone cannot fully explain the risk.

GEM enables scalable gene-environment interaction analysis in large samples, identifying novel loci in a gene-sex interaction study.

This study conducts a metabolomics analysis of cervical dystonia, identifying 289 significant metabolic differences and 9 associated biological pathways.

This study shows smoking increases type 2 diabetes risk through BMI, but not coronary artery disease risk, using Mendelian randomization.

Multi-ethnic type 2 diabetes (T2D) meta-analysis of 228,499 cases and 1,178,783 controls finds 318 previously unreported loci, 804 expression-colocalized genes, and 13 SNP-by-T2D vascular-outcome interactions.