Adam Auton

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 uses a multivariate GWAS approach to identify genetic loci associated with reading ability and dyslexia, finding 35 new genome-wide significant loci and estimating SNP heritability at 24%.

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.

PRSformer predicts disease risk from large-scale genotypes using deep learning, outperforming linear models and summary-statistic methods in multi-ancestry cohorts.

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.

This study shows that credible sets in GWAS are affected by imputation quality and missing variants, and proposes a reweighting method to improve accuracy.

The paper analyzes 3.6 million individuals to find minimal evidence of non-additive genetic interactions for height.

This paper evaluates how the scale and quality of genetic data from the 23andMe cohort improve predictions of clinical success for drug targets.

This study shows large language models can accurately prioritize causal genes at GWAS loci, outperforming existing methods and offering a scalable solution.

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.

This paper uses a polygenic risk score to identify undiagnosed diabetes cases, finding that combining BMI and PRS captures most undiagnosed cases, including those with normal weight.

The paper estimates polygenic risk scores (PRS) for 12 diseases in a diverse cohort and finds higher disease incidence and earlier clinical manifestation in top PRS individuals.

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 a genetic association between the UGT2A1/UGT2A2 locus and COVID-19-related anosmia using a trans-ethnic GWAS.

Bonsai infers large human pedigrees from genotype data by assembling smaller pedigrees of close relatives, improving accuracy and efficiency through new formulas and methods.

The paper constructs polygenic indexes for 47 phenotypes across 11 datasets and provides a tool to correct errors-in-variables bias when using PGIs as proxies for the additive SNP factor.

This paper uses self-reported medical data to perform GWAS on 33 rare diseases, rediscovering known associations and finding novel ones, validated across multiple populations.

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 links genomic data with EHRs to identify health outcomes enriched in sub-populations, revealing both known and novel associations.

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

This paper introduces Ancestry Composition, a pipeline for ancestry deconvolution that uses over 14,000 reference haplotypes to improve accuracy and scalability.

This paper introduces cov-LDSC, a method to estimate heritability and its enrichment in tissue-specific gene sets in admixed populations, showing high concordance across populations but population-specific differences for some traits.

This paper introduces TPBWT for fast and robust IBD inference, showing improved speed and accuracy over existing methods, especially in handling phasing errors.

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 paper introduces within-family Mendelian randomization methods to reduce biases from family structure and shows they yield different results compared to population-based analyses.