Alex Bloemendal

The Evidence Aggregator: AI reasoning applied to rare disease diagnostics

The Evidence Aggregator (EvAgg) uses generative AI to streamline rare disease diagnostics by extracting and summarizing genetic variant and clinical information from literature, improving efficiency and accuracy.

Scalable automated reanalysis of genomic data in research and clinical rare disease cohorts

The paper develops an automated tool for reanalyzing genomic data in rare disease cohorts, showing improved diagnostic yields through iterative reanalysis.

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank

The paper identifies compound heterozygous variants in UK Biobank data and shows their phenotypic impact on common diseases using statistical phasing and mixed models.

GUIDE deconstructs genetic architectures using association studies

This paper introduces GUIDE, a method to identify latent genetic factors from GWAS data, revealing biological pathways and environmental influences in complex traits.

Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies

The paper introduces LD graphical models (LDGMs) for efficient linkage disequilibrium representation in diverse ancestry studies, showing significant runtime improvements and better polygenic prediction.

Analysis of genetic dominance in the UK Biobank

The paper evaluates dominance effects in over 1,000 UK Biobank phenotypes using GWAS, finding no significant dominance contribution to phenotypic variance from common variation.

Mapping the convergence of genes for coronary artery disease onto endothelial cell programs

The paper maps coronary artery disease risk loci to endothelial cell gene programs, identifying convergence on the CCM pathway and a new CAD gene, TLNRD1.

A data harmonization pipeline to leverage external controls and boost power in GWAS

This paper presents a data harmonization pipeline for GWAS that improves power by integrating external controls and reduces batch effects, demonstrating its effectiveness in a Crohn's disease study.

Paternal-age-related de novo mutations and risk for five disorders

The paper estimates the risk of five disorders from paternal-age-related de novo mutations using whole-exome-sequencing data and Danish registry data.

Phenotype-specific information improves prediction of functional impact for noncoding variants

PINES improves noncoding variant functional impact prediction by integrating phenotype-dependent epigenetic annotations.

Ultra-rare disruptive and damaging mutations influence educational attainment in the general population

This study finds that ultra-rare disruptive variants in highly constrained genes are associated with reduced educational attainment in the general population.

Gibbs Free Energy of Protein-Protein Interactions Reflects Tumor Stage

The paper correlates Gibbs free energy of protein-protein interactions with tumor stage and 5-year survival in cancer patients.