Ryan Koesterer

The paper identifies ancestry-specific T2D risk variants in South Asian populations through exome-wide association study and functional validation.

The paper introduces the T1D Knowledge Portal, a resource for querying genetic and functional data related to type 1 diabetes to aid in hypothesis generation and target discovery.

The paper develops a polygenic score incorporating rare and common variants to improve diabetes diagnosis using HbA1C levels, identifying more undiagnosed cases than chance.

The paper evaluates penetrance and variable expressivity of monogenic metabolic conditions using exome data from 77,184 individuals, finding that monogenic variants have larger effect sizes than polygenic scores but low penetrance.

This study identifies rare genetic variants associated with type 2 diabetes using exome sequencing of 20,791 cases and 24,440 controls, and provides a Bayesian framework to improve variant prioritization.