Mark J. Daly

This paper introduces GPrior, a gene prioritization tool that improves disease gene identification from GWAS by using ensemble positive-unlabeled learning.

The paper performs a GWAS meta-analysis of cervical cancer and links it to reproductive tract development, immune response, and cellular proliferation/apoptosis, while also identifying genetic risk factors for other cervical phenotypes.

The paper identifies a genetic variant in SPDL1 that links pulmonary fibrosis risk and cancer protection through antagonistic pleiotropy.

The paper identifies protein-truncating variants in ANGPTL8, ANGPTL4, and LIPG associated with lipid levels and cardiometabolic disease risk, and reports their associations with type 2 diabetes, coronary artery disease, and other adverse effects.

This study uses genetic data to examine testosterone's effects on health, finding sex-specific impacts on female reproductive health and complex associations with disease risk.

This paper introduces MAMA, a method for multi-ancestry GWAS meta-analysis, which identifies novel genetic associations and improves power across populations.

This study shows low-coverage sequencing is more accurate and cost-effective than GWAS arrays for detecting genetic variation in diverse African populations.

Tractor improves GWAS power and resolution by including admixed individuals through local ancestry-aware analysis.

This study identifies 13 genome-wide significant loci associated with SARS-CoV-2 infection or severe COVID-19 through a global meta-analysis of 49,562 patients.

This study identifies 15 new risk loci for otosclerosis and replicates known associations, highlighting shared genetic links with skeletal structure and bone-related disorders.

The paper investigates the association between age-related mosaic chromosomal alterations and infection risk in 767,891 individuals without blood cancer, finding increased infection susceptibility linked to mCAs.

The paper introduces a frailty model for genome-wide survival analysis in large biobanks, handling population structure and relatedness, and demonstrates its performance on real-world datasets.

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.

The paper uses the ABC Model to map enhancer-gene regulation across 131 cell types and tissues, linking GWAS variants to disease genes, particularly in IBD.

The paper predicts functional effects of missense variants in voltage-gated sodium and calcium channels using machine learning, achieving high accuracy in distinguishing gain and loss of function variants.

The paper identifies 7 novel IBD-causing genes in Ashkenazi Jewish IBD patients using exome sequencing and analyzes their overlap with early-onset IBD and other diseases.

The paper evaluates potential drug targets using loss-of-function genetic variants from gnomAD, highlighting the importance of deep curation and targeted recall studies for drug discovery.

From 125,748 exomes and 15,708 genomes, 443,769 high-confidence predicted loss-of-function variants yield LOEUF, a continuous gene intolerance score tracking mouse lethality, cell essentiality, and disease associations.

The paper develops an expression-based annotation metric to improve rare variant interpretation by filtering false-positive loss-of-function variants and identifying pathogenic variants in highly expressed exons.

Short-read genome sequencing of 14,891 diverse genomes yields 433,371 structural variants (SVs) for gnomAD; loss-constrained genes also resist duplication, and clinical SV carrier rates are benchmarked.

The paper analyzes loss-of-function variants in LRRK2 across large genomic datasets to assess the safety of partial LRRK2 inhibition as a Parkinson's disease therapy.

The paper systematically studies uORF variants in 15,708 genomes, showing they are under strong negative selection and contribute to disease.

The paper analyzes multi-nucleotide variants (MNVs) in 125,748 exomes and 15,708 genomes, identifying their distribution, mutational origins, and functional implications.

SAIGE-GENE is a scalable generalized linear mixed model for region-based association tests in large cohorts, efficiently handling over 400,000 samples with controlled type I error rates.

This study characterizes epigenetic aging in human classical monocytes, identifying age-associated DNA methylation changes and their links to gene expression and disease associations.

The paper identifies rare protein-altering variants in ANGPTL7 that lower intraocular pressure and reduce glaucoma risk by analyzing genotyping data from UK Biobank and FinnGen.

The paper identifies a missense variant in the MARC1 gene associated with protection against cirrhosis and lower liver enzyme and cholesterol levels.

This study uses polygenic risk scores from three biobanks to show that genetic susceptibility to traits like high blood pressure and obesity is associated with shorter lifespan.

The paper analyzes missense variants in 1,330 disease genes using 3D protein structures to identify mutational hotspots and their functional impact.

This study uses genetic and geographic data to analyze migration patterns and population structure in the US, revealing substructure and demographic history among different groups.