Jimmy Z. Liu

This study uses prescription analgesic use data to identify 140 genetic associations with chronic pain, including 78 novel loci, and suggests new biological mechanisms.

The paper evaluates the transportability of in-vitro gene perturbation models to in-vivo human phenotypes using CRISPR data and UK Biobank, finding some models are predictive while others are not.

This study uses population-scale whole genome sequencing to identify novel rare protein-coding variants associated with cardiometabolic traits, revealing new biological mechanisms and gene functions.

This study identifies eight genes associated with adult cognitive function through rare coding variants and shows how KDM5B dosage affects cognitive traits in mice and humans.

This study examines the impact of rare protein-truncating variants on human lifespan using whole-exome sequencing data from the UK Biobank, identifying significant associations with several genes.

The paper describes exome sequencing of 200,643 UK Biobank participants, providing a rich resource of coding variants for genetic and drug discovery research.

The paper profiles gene expression in human microglia from 141 patients, identifies population shifts in acute brain injury, maps eQTLs, and fine-maps Alzheimer's risk variants using hIPSC-derived macrophages.

The paper analyzes whole exome sequencing data from the UK Biobank to identify rare coding variants associated with major depressive disorder and reveals genetic overlaps with other psychiatric disorders.

Meta-analysing UK Biobank family-history GWAS with diagnosed-AD GWAS yields 37 loci, four novel (NCK2, TSPAN14, SPRED2, CCDC6); fine-mapping, colocalisation and network scoring prioritize causal genes.

The paper identifies genetic and RNAi-based pairwise interactions between lipid-related genes that modulate plasma and cellular lipid levels, suggesting potential drug target pairs for lipid-lowering therapies.

The paper introduces a multivariate GWAS framework that identifies functional variants and disease associations by transforming multivariate results into univariate phenotypes for follow-up analysis.

This paper uses Mendelian randomization and colocalization to identify causal relationships between plasma proteins and disease phenotypes, finding 111 putatively causal effects.

The paper identifies genetic variants associated with subjective well-being, depressive symptoms, and neuroticism using genome-wide association studies and proxy-phenotype analyses.