Daniel M. Jordan

This paper uses temporal modeling of Alzheimer's disease progression with metabolomics data to identify novel genetic loci associated with disease speed, independent of traditional case-control associations.

This study performs a genome-wide association study for Long COVID, identifying a significant association with the FOXP4 locus and highlighting the role of pulmonary dysfunction and COVID-19 severity.

This study uses Mendelian randomization to identify causal effects of plasma triglycerides on 2,600 disease traits, finding 19 significant associations including cardiovascular and non-atherosclerotic diseases.

The paper constructs a tissue-level phenome-wide network map linking genes and phenotypes using colocalized signals from the UK Biobank and Genotype-Tissue Expression project.

This study develops a method to detect recessive purifying selection in genes using population genetics simulations and applies it to empirical gene sets, finding significant enrichments for recessive selection in specific gene categories.

This paper introduces MOI-Pred, a tool for predicting recessive inheritance of missense variants, showing high accuracy in distinguishing recessive disease-causing variants.

The paper quantifies disease risk associated with 37,772 clinical variants across 72,434 individuals, revealing heterogeneity in penetrance and limitations of current variant classification systems.

The paper uses GTEx data to analyze GWAS loci, showing dose-dependent RNA effects and proposing target genes for 47% of loci using combined methods.

The paper calculates a deleterious load score using purifying selection weights and finds strong associations with 27 medical traits in the UK Biobank.

The paper quantifies horizontal pleiotropy across 372 phenotypes using UK Biobank data and finds it is widespread, especially in polygenic traits and regulatory regions.

The paper quantifies frequency-dependent genetic architectures and negative selection effects across 25 UK Biobank traits using a statistical model and imputed genotypes.

This paper reviews literature to improve clinical variant assessment by using citation data to enhance pathogenicity prediction.

The paper estimates genome-wide selection coefficients for heterozygous protein truncating variants using exome data from 60,706 individuals and identifies genes under strong selection.