Wei Zhou

This paper uses proteome-wide Mendelian randomization across multiple ancestries to identify causal protein-disease associations and drug targets in over 1.26 million individuals.

Meta-analysis of harmonized GWAS from up to 18 biobanks (six ancestry groups) across 14 endpoints replicated 320 known loci and identified 188 apparently novel loci.

This paper provides a framework for genomics-driven drug discovery using cross-population GWAS meta-analysis, identifying candidate drugs for 13 diseases through three methodologies.

This study performs a large multi-ancestry meta-analysis of IPF genetics, identifying seven novel genome-wide significant loci and highlighting pleiotropy with severe COVID-19 and sex-heterogeneity at the MUC5B locus.

The paper outlines best practices for conducting multi-ancestry transcriptome-wide association studies (TWAS) using the Global Biobank Meta-analysis Initiative data, addressing challenges in ancestry and tissue specificity.

The paper improves rare variant association testing by introducing SAIGE-GENE+ which reduces type I error and computational costs, identifying 551 gene-phenotype associations in UK Biobank WES data.

The paper performs single-variant and gene-based association analyses of 4,529 phenotypes using exome data from 426,370 UK Biobank individuals, finding associations linked to variant frequency and deleteriousness.

This paper integrates GWAS data with functional genomic datasets to identify regulatory mechanisms and causal genes underlying lipid-related traits.

The paper introduces a method to improve genetic association studies by incorporating family disease history and addressing case-control imbalance, showing improved power and calibration.

This study conducts a multi-ancestry GWAS for venous thromboembolism, identifies novel loci, and validates their function in zebrafish.

Finnish-enriched low-frequency variants, often coding, underlie many GWAS signals across 1,932 register endpoints in 218,792 Finns; a 15-disease meta-analysis with Estonian and UK biobanks adds 30 unreported associations.

This paper identifies two novel genetic loci associated with ischemic stroke and finds sex and ancestry differences in their effects.

The paper evaluates family history and polygenic scores as predictors for coronary artery disease and type 2 diabetes using the Trondelag Health Study and UK Biobank.

A coronary artery disease GWAS of 181,522 cases among 1,165,690 participants yields 241 associations (54 new); an eight-predictor consensus nominates 185 candidate causal genes, 94 with ≥3 predictors.

The paper identifies a genetic variant in SPDL1 that links pulmonary fibrosis risk and cancer protection through antagonistic pleiotropy.

This study identifies three genetic loci associated with chronic widespread musculoskeletal pain, with the RNF123 locus replicated in independent cohorts.

The paper introduces POLMM, a mixed model for ordinal categorical phenotypes in GWAS, showing it is computationally efficient, controls type I error, and identifies more significant variants than existing methods.

This study combines multiple GWAS of ageing traits to identify genetic components associated with human ageing and finds LPA and VCAM1 as potential drug targets.

This study identifies 13 genome-wide significant loci associated with SARS-CoV-2 infection or severe COVID-19 through a global meta-analysis of 49,562 patients.

This study identifies seven novel genetic loci for Alzheimer's disease using a large GWAS and highlights microglia and immune pathways as key contributors to disease pathology.

The paper introduces a frailty model for genome-wide survival analysis in large biobanks, handling population structure and relatedness, and demonstrates its performance on real-world datasets.

SAIGE-GENE is a scalable generalized linear mixed model for region-based association tests in large cohorts, efficiently handling over 400,000 samples with controlled type I error rates.

The paper develops a region-based rare variant test for unbalanced binary phenotypes, showing improved type I error control and scalability, and identifies 10 rare variant associations in UK Biobank whole exome data.

This study identifies 147 genetic loci associated with eGFR, including 53 novel ones, and finds sex-specific effects on kidney function.

The paper identifies loss-of-function variants affecting liver-related blood traits that reduce CVD risk without increasing metabolic disease risk, highlighting potential therapeutic targets.

The paper analyzes whole genome sequences from 16,324 individuals to identify genetic variants associated with blood lipid levels and develops a polygenic score for LDL-C.

This paper introduces SAIGE, a method that improves the accuracy of genetic association tests in unbalanced case-control studies by using saddlepoint approximation, and demonstrates its effectiveness on UK Biobank data.

This study identifies 111 genetic loci and 163 risk variants associated with atrial fibrillation using a GWAS of over 1 million individuals.

This study identifies two new genetic loci associated with aortic valve stenosis through a large genome-wide association study.

This study uses Mendelian Randomization to show that higher BMI causally increases the risk of psoriasis and eczema, with a stronger effect on psoriasis.