Jian Yang

This paper introduces SBayesR, a Bayesian method for polygenic prediction using GWAS summary statistics, achieving higher accuracy and efficiency than existing methods.

Across 37,688 Parkinson's cases, 18,618 proxy-cases and 1.4M controls, 90 risk signals map to 78 loci (37 new); an 1805-variant polygenic score explains 26-36% of heritability.

This paper applies Mendelian randomization to identify causal factors for Parkinson's disease using 5,839 exposures and reports twelve causal associations, including adiposity.

The paper examines genetic clustering of complex traits and disease risk in Great Britain, finding that socio-economic status influences allele distribution and regional outcomes.

The paper identifies potential causal genes for AMD by integrating GWAS and eQTL data and validating them in zebrafish models.

The paper identifies genetic variants associated with phenotypic variability and shows they exhibit genotype-by-environment interactions for obesity-related traits using UK Biobank data.

This paper introduces TWMR, a Mendelian Randomization method that identifies gene-trait associations by integrating GWAS and eQTL data, revealing 3,913 novel associations across 43 human phenotypes.

The paper examines how X-linked dosage compensation affects genetic variation in complex traits, finding more genetic variation in males than females for X-linked loci.

OSCA provides a tool for omic-data-based complex trait analysis using the MOMENT method, showing improved robustness and lower false positive rates in simulations.

This study performs GWAS on medication-use data from 320,000 UK Biobank participants, identifying 505 genetic loci and linking them to 16 known therapeutic targets.

This study uses conditional GWAS analysis to identify disorder-specific SNPs for psychiatric disorders, finding some variants with reduced pleiotropy effects.

This paper introduces a reference-free method for generating polygenic risk scores (PRS) that avoids over-fitting and computational inefficiencies, and demonstrates applications in pleiotropy detection and mixed-model association testing.

GWAS in over one million individuals identify 611 loci across risk tolerance and risky behaviors, revealing shared genetic architecture and implicating glutamatergic and GABAergic neurotransmission.

The paper replicates 55,000 DNA methylation QTLs using two cohorts and finds enrichment of trans mQTLs in specific genomic regions and complex traits.

The paper quantifies assortative mating on complex traits by analyzing SNP data from 400,000 individuals, finding significant evidence for height and educational attainment.

This paper uses Mendelian Randomisation to show that height reduces coronary artery disease risk independently of BMI, lipid, and blood pressure, but has no direct effect on type 2 diabetes risk after adjusting for BMI.

The paper improves age prediction from DNA methylation using larger datasets, showing reduced error and limitations in capturing biological ageing variation.

Meta-analysis of waist-to-hip ratio adjusted for BMI in 694,649 European-ancestry individuals identifies 463 signals in 346 loci, roughly one-third sexually dimorphic and mostly stronger in women.

This paper performs a meta-analysis of GWAS for height and BMI in 700,000 individuals, identifying 3,290 and 716 SNPs, with increased prediction accuracy.

This study identifies 139 common and 4 rare genetic variants associated with type 2 diabetes through GWAS and integrates gene expression and epigenomic data to highlight potential functional genes and regulatory mechanisms.

The paper finds a genetic association between schizophrenia risk and urban living, suggesting genetic factors influence migration to densely populated areas.

The paper identifies gene targets for brain-related traits using transcriptomic and methylomic data from blood, finding strong correlations between genetic effects in brain and blood tissues.

This study identifies six new Alzheimer's disease-associated loci using GWAS on family history data from UK Biobank and consortium data, with potential implications for precision medicine.

The paper extends bivariate LD score regression theory to account for population stratification, showing that the intercept can be inflated even without sample overlap.

The paper compares methods for estimating heritability and genetic architecture using whole genome data and finds that larger imputation panels improve accuracy of causal variant frequency estimates.

The paper estimates the joint distribution of effect size and MAF for genetic variants in 28 complex traits and detects widespread negative selection signatures.

This study uses genetic data to identify causal relationships between risk factors and common diseases, finding protective and bidirectional effects.

The paper develops a method to partition phenotypic variance attributable to parent-of-origin effects using genomic relatedness matrices.

This study shows that multi-site regulation of gene expression leads to biased eQTL fine mapping and highlights the need for joint multi-site analysis to improve accuracy.