Jared O’Connell

The paper analyzes the impact of CYP2C19 genotype on SSRI side effects and discontinuation rates in a large sample of individuals.

This study finds that higher polygenic risk scores for breast cancer are associated with longer survival in patients, suggesting a link between genetic predisposition and less aggressive tumors.

This study compares polygenic risk scores for Parkinson's disease across seven ancestries, finding varying predictive accuracy and highlighting the need for ancestry-specific models.

This study compares eQTL discovery in African and European ancestry cohorts, finding more eQTLs in African samples and improved GWAS variant-to-gene mapping using African eQTLs.

This study identifies genetic correlations between hyposmia and Parkinson's disease, finding a strong causal link from PD to hyposmia but weaker evidence for the reverse.

This study investigates the shared genetic architecture between rhythm and dyslexia using large-scale genome-wide association studies.

The paper benchmarks haplotype phasing methods on large datasets and introduces HAPTIC, an inter-chromosomal phasing method achieving low error rates for parent-of-origin classification.

This paper introduces PROSPER, an ensemble penalized regression method for multi-ancestry polygenic risk prediction, showing improved performance across diverse populations.

MUSSEL improves polygenic risk prediction across populations by integrating GWAS summary statistics and using Bayesian hierarchical modeling with ensemble learning.

This paper conducts a multi-ancestry genome-wide meta-analysis of Parkinson's disease, identifying 78 independent loci and 23 genes associated with PD risk.

The paper investigates the association between autozygosity and common diseases in multiple cohorts, finding significant links to twelve diseases and estimating autozygosity's contribution to type 2 diabetes cases.

The paper introduces CT-SLEB, a method for multi-ancestry polygenic prediction that improves performance in non-European populations using GWAS summary statistics and simulation studies.

This study identifies 49 genetic loci associated with sleep apnoea risk using multi-trait GWAS, with 29 replicated in a large cohort, and finds genetic correlations with several complex traits.

This study conducts a genome-wide association study to identify genetic variants linked to musical beat synchronization, finding high polygenicity with 69 significant loci and heritability estimates of 13%-16%.

The paper identifies sex-differential participation bias in genetic studies by performing GWAS on sex in 3.3 million individuals, finding 158 loci associated with sex and highlighting traits like BMI that may influence participation.

This study identifies genetic loci associated with daytime napping and finds potential causal links between napping and cardiometabolic traits.

The paper identifies HLA-B*55:01 as a genetic risk factor for penicillin allergy through genome-wide analysis of electronic health records and imputed HLA data.

This study identifies one known and two novel genetic variants associated with heart failure through GWAS and multi-omic analyses, revealing potential causal mechanisms and shared heritability with musculoskeletal traits.

Quality-controlled genotypes for 488,377 UK Biobank participants at 805,426 markers, imputed to ~96 million variants, plus ancestry PCs, kinship (30.3% have close relatives enrolled) and HLA calls.