Bridget M. Riley-Gillis

The paper integrates GWAS and multi-omic QTLs to identify gene-biotype and phenotype associations related to COVID-19, revealing pleiotropy and causal links.

This study conducts a multi-ancestry GWAS meta-analysis of 56,146 AD cases and 602,280 controls, identifying 101 genomic loci, 15 novel to AD or eczema, and linking them to AD pathophysiology through functional analyses.

The paper demonstrates the feasibility of conducting clinical recall studies from the FinnGen biobank to collect customized clinical data from participants with Alzheimer's disease or mild cognitive disorder.

This study conducts a GWAS of preeclampsia and hypertensive disorders of pregnancy, identifying 18 genome-wide significant loci, including novel associations with blood pressure and placental function.

The paper characterizes CFTR variant diversity across six ancestries using UK Biobank whole exome sequences, identifying ancestry-specific variants and associations with CF-related phenotypes.

The paper performs single-variant and gene-based association analyses of 4,529 phenotypes using exome data from 426,370 UK Biobank individuals, finding associations linked to variant frequency and deleteriousness.

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.