David J. Roberts

This study identifies genetic loci influencing variance in blood cell traits and shows that incorporating variance polygenic scores improves prediction accuracy.

This study identifies genetic determinants of blood gene expression and splicing, linking them to molecular phenotypes and health outcomes through QTL analysis and colocalization.

This study investigates how RAMP2 and RAMP3 modulate PTH1R function and signaling, showing RAMP2 enhances responses while RAMP3 reduces them, suggesting potential for targeted therapies.

The paper identifies misexpression of inactive genes in whole blood and links it to nearby rare structural variants using RNA and genome sequencing data.

The paper develops genetically personalised organ-specific metabolic models to identify associations between metabolic fluxes and disease risk, finding 97 fluxes linked to coronary artery disease.

The paper uses polygenic scores to identify plasma proteins causally linked to cardiometabolic diseases and finds some are targets for existing therapies.

This study uses Mendelian randomization to identify plasma proteins associated with stroke risk and potential therapeutic targets.

This study uses Mendelian randomization to examine if ACE inhibitors or cardiometabolic risk factors affect lung ACE2 and TMPRSS2 expression or plasma ACE2 levels, finding no overall association.

This study identifies 5,552 blood-cell trait-variant associations across 746,667 individuals from 5 global populations, including 71 novel loci and ancestry-specific variants not found in European ancestry populations.

This paper applies object detection networks to classify and localize cells in fluorescence microscopy, demonstrating effectiveness with small datasets and integrating an AR system for real-time imaging.

The paper identifies novel gene-trait associations and pathways involving rare variants in metabolic biomarkers linked to cardiovascular disease risk.

This study compares machine learning and univariate methods for constructing polygenic scores for 26 blood cell traits using UK Biobank and INTERVAL data, showing improved performance with learning methods.

This study performs GWAS on blood cell flow-cytometry phenotypes, identifies variant-trait associations, and links them to cellular structures and disease mechanisms.

This study identifies genetic loci associated with household income and links them to biological pathways and cognitive ability, showing genetic differences between income and education.

The paper identifies immune disease variants affecting Treg gene expression and highlights potential drug targets by linking GWAS signals with Treg QTLs.

The paper identifies 1,927 genetic associations with 1,478 plasma proteins using 10.6 million DNA variants and 3,301 individuals, revealing new drug targets and safety concerns.