Roelof A. J. Smit

The paper establishes a global consortium to discover rare genetic associations by integrating data from multiple biobanks, identifying 514 gene-trait associations, many detectable only through cross-ancestry meta-analysis.

This study identifies genetic subtypes of obesity that uncouple adiposity from cardiometabolic risks, revealing distinct biological pathways and protein associations.

This study identifies novel genetic signals associated with severe obesity through GWAS and shows strong genetic overlap with BMI, highlighting shared comorbidities and lifestyle interactions.

This study maps the proteomic changes in plasma, saliva, and urine after acute exercise, identifying over 3,000 regulated proteins and their associations with disease and drug targets.

This study investigates genetic factors influencing weight loss from GLP1-RA and bariatric surgery in 10,960 individuals across 9 biobanks, finding no strong genetic associations with GLP1-RA effectiveness but a modest link between BMI polygenic scores and reduced bariatric surgery weight loss.

The paper identifies non-linear genetic regulation of plasma proteins using a deep learning method, finding dominance and epistasis effects in large cohorts.

The paper selects and validates ten polygenic risk scores for clinical use in diverse populations, focusing on chronic diseases and addressing disparities in predictive performance.

This paper constructs a multi-ethnic polygenic risk score for hypertension and shows it is associated with hypertension prevalence, progression, and related clinical outcomes.

This study identifies novel genetic loci for BMI, height, and WHRadjBMI in Hispanic/Latino populations and shows the benefits of ancestral diversity in GWAS.