Mine Koprulu

The paper uses genome-wide association testing on embeddings from a medical-history foundation model to identify genetic signals linked to biological pathways and drug targets.

This study integrates genetic variation with plasma protein measurements in South Asians to identify pQTLs and build a proteogenomic disease network for understudied populations.

This study examines the proteomic and clinical impact of human knockouts in British South Asians, identifying significant protein under- and over-expression and developing a machine learning model to predict variant benignity.

The paper uses nanoparticle enriched mass spectrometry proteomics in British South Asians to identify novel variant-protein-disease mechanisms through integrative analysis of exome sequencing and proteomic data.

This study identifies 40 circulating proteins associated with cancer risk using MR and colocalization, highlighting potential therapeutic targets and adverse effects of protein-altering interventions.

The paper investigates sex differences in the genetic regulation of the plasma proteome and finds most genetic effects are similar between sexes, with few sex-differential effects that do not translate to disease risk.

The paper uses antibody-based proteomics to identify disease-causing genes and proteins by analyzing plasma proteome data from 1,180 individuals, finding new gene-protein-disease links and improving causal gene assignment in GWAS loci.

This paper improves genetic scores for adiposity traits in East Asian populations by using trans-ancestry meta-analysis, increasing variance explained compared to European-derived scores.

This study identifies rare loss of function variants in four genes associated with beneficial changes in body fat distribution using genome-wide and exome-sequence data from UK Biobank.

The paper compares pQTLs across two proteomic platforms, finding shared and platform-specific pQTLs and identifying factors contributing to platform differences.

This study identifies CASC20 and KIF26B as genetic loci associated with heterotopic ossification through genome-wide association and functional analyses.

This study identifies 64 new genetic signals for osteoarthritis using UK Biobank data, including 52 novel loci, and highlights potential therapeutic targets with existing drugs.