DANIEL A. DICORPO

The paper introduces MultiSTAAR, a statistical framework for multi-trait rare variant analysis in WGS studies, identifying new lipid trait associations in diverse populations.

This paper conducts a multi-ancestry time-to-event GWAS to identify genetic variants associated with incident cardiovascular disease in people with type 2 diabetes, finding three novel loci and confirming known CAD variants.

The paper demonstrates that TOPMed imputation improves the identification of rare variants associated with type 2 diabetes in Latino populations, leading to novel associations and better polygenic scores.

The paper identifies a gene-diet interaction modifying the association between macronutrient intake and glycemic traits, highlighting challenges in detecting such interactions due to measurement error and sample size.

The paper performs whole genome sequence association analysis of fasting glucose and insulin levels in diverse cohorts, identifying 22 significant variants across 16 gene regions, including rare variants.

The paper identifies rare non-coding variants from whole genome sequencing in the TOPMed program, showing they contribute significantly to type 2 diabetes heritability.

The paper identifies genetic variants affecting HbA1c levels in multi-ancestry cohorts, showing ancestry-specific impacts on diabetes diagnosis via HbA1c.