Sridharan Raghavan

This study evaluates polygenic score prediction accuracy and cross-ancestry portability across 3,994 PGSs in diverse populations, identifying factors affecting their performance and equity.

This study identifies genetic loci associated with diabetic peripheral neuropathy, implicating serine biosynthesis in disease susceptibility through convergent evidence from common and rare variants.

This study models the genomic architecture of adiposity and anthropometrics across the lifespan, identifying shared and distinct genetic factors and their associations with health outcomes.

This paper develops a pipeline for translating type 1 diabetes polygenic risk scores into clinical use, showing they can distinguish type 1 from type 2 diabetes and identify high-risk individuals.

This study calibrates polygenic risk scores (PRS) for African American adults based on genetic ancestry, improving risk stratification and effect estimation for type 2 diabetes and height.

Summix2 uses mixture modeling to estimate and adjust for substructure in genetic summary data, improving the robustness and equity of research using diverse datasets.

This study conducts an epigenome-wide association study (EWAS) meta-analysis of BMI in African American adults, identifying 208 significant CpGs and 54 DMRs associated with BMI, including novel and replicated findings.

This study identifies 12,111 SNPs associated with height from 5.4 million individuals, explaining most common SNP-based heritability and showing ancestry-specific prediction accuracy.

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