Jie Zheng

This study uses Mendelian randomization to identify risk factors for kidney function decline in CKD and the general population, finding causal effects of type-2 diabetes and high TSH.

This study uses Mendelian randomization to assess how cardiometabolic drugs affect kidney function, finding specific drug targets influence eGFR and related biomarkers.

This study uses reverse Mendelian randomization to identify non-causal plasma proteins associated with glioma risk, finding links to immune system processes and potential biomarkers.

This paper uses Mendelian randomization and electronic health records to show SGLT2 inhibitors reduce prostate cancer risk, with additional evidence from differential expression analysis.

This study uses GWAS and Mendelian randomization to show that lower sclerostin levels increase risk of hypertension, type 2 diabetes, myocardial infarction, and atherogenic lipid profiles.

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.

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.

PWCoCo improves genetic colocalisation by integrating conditional and colocalisation analyses, enabling robust detection of independent signals and secondary loci in high-dimensional omics data.

This study uses multi-ancestry Mendelian randomization to identify six protein targets for COVID-19 severity, showing ancestry-specific effects.

The paper uses genetic variation to assess the causal impact of food choices on health outcomes, identifying robust associations between eating patterns and several diseases.

This study combines protein and gene expression QTLs to evaluate their concordance in drug target validation, finding that 25-30% of QTL pairs show discordant effects.

The paper describes the continental ancestry and population structure of non-white British individuals in the UK Biobank using reference populations and clustering methods.

This study uses multivariable Mendelian randomization to show that higher bone mineral density causally increases osteoarthritis risk independently of body mass index.

This study shows genetic associations of CRP variants with BMI differ between individuals with and without cardiometabolic diseases, suggesting BMI modifies these genetic effects.

This study identifies TMEM232 as a gene associated with atopic dermatitis through haplotype analysis and targeted capture sequencing.

The paper identifies genetic variants and phenotypes associated with participation in optional UK Biobank components and shows common participation bias across studies.

This study uses Mendelian randomization and colocalization to identify 12 genes, three novel, associated with glioma risk across tissues and subtypes.

EpiGraphDB is a graph database and analytical platform for health data science, demonstrating its utility through case studies on pleiotropy, drug targets, and causal inference.

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

OpenGWAS serves 14582 harmonised, complete GWAS summary datasets (125.8 billion associations) via API, R/Python clients and GWAS-VCF downloads, with glue code for Mendelian randomization, colocalisation and fine-mapping.

This study uses Mendelian randomization to show education and intelligence both causally lower Alzheimer's disease risk, with intelligence having an independent effect.

This study uses bidirectional Mendelian randomization to investigate causal relationships between inflammatory markers and depression, finding a causal effect of IL-6 on major depressive disorder.

MR-TRYX identifies novel causal pathways by leveraging horizontal pleiotropy in Mendelian randomization analyses using GWAS summary data.

This paper uses Mendelian Randomization to show that higher circulating sclerostin levels causally reduce bone mineral density and increase fracture risk.

This study identifies 64 new genetic signals for osteoarthritis using UK Biobank data, including 52 novel loci, and highlights potential therapeutic targets with existing drugs.

PhenoSpD estimates phenotypic correlations and corrects multiple testing using GWAS summary statistics, reducing dimensionality for complex traits.

This study uses Mendelian randomization to identify genetic loci that may influence disease through DNA methylation changes, finding 1,191 effects across 62 traits with high replication in UK Biobank.

LD Hub provides a centralized database and web interface for performing LD score regression on GWAS summary data to estimate SNP heritability and genetic correlations across traits.