Aaron Leong

Multi-ancestry polygenic risk scores for the prediction of type 2 diabetes and complications in diverse ancestries.

This paper develops and validates multi-ancestry polygenic risk scores for type 2 diabetes prediction and complications across diverse populations.

Common genetic variants near SLC2A2 and glycemic response to glimepiride in the GRADE comparative effectiveness clinical trial

The paper identifies genetic variants near SLC2A2 that influence glycemic response to glimepiride in type 2 diabetes patients.

Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes

The paper conducts a large-scale rare variant GWAS meta-analysis of type 2 diabetes, identifying novel variants in monogenic diabetes genes and assessing their pathogenicity.

Discovering cellular programs of intrinsic and extrinsic drivers of metabolic traits using LipocyteProfiler

The paper introduces LipocyteProfiler, a high-throughput microscopy assay to profile lipid-storing cells and identifies cellular programs linked to metabolic traits like insulin resistance and lipodystrophy.

The power of TOPMed imputation for the discovery of Latino enriched rare variants associated with type 2 diabetes

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.

A combined polygenic score of 21,293 rare and 22 common variants significantly improves diabetes diagnosis based on hemoglobin A1C levels

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

Validation of a Trans-Ancestry Polygenic Risk Score for Type 2 Diabetes in Diverse Populations

This paper develops a trans-ancestry polygenic risk score for type 2 diabetes and validates it across diverse populations to improve equitable risk prediction.

The impact of non-additive genetic associations on age-related complex diseases.

This study applies an improved GWAS strategy to age-related diseases, identifying new genetic loci by using multiple reference panels, analyzing the X chromosome, and testing non-additive models.

Rare Non-coding Variation Identified by Large Scale Whole Genome Sequencing Reveals Unexplained Heritability of Type 2 Diabetes: Trans-Omics for Precision Medicine (TOPMed) Program

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

A long noncoding RNA, LOC157273, is the effector transcript at the chromosome 8p23.1-PPP1R3B metabolic traits and type 2 diabetes risk locus

The paper identifies LOC157273 as a negative regulator of PPP1R3B and glycogen deposition in human hepatocytes, linking it to type 2 diabetes risk.

Impact of rare and common genetic variants on diabetes diagnosis by hemoglobin A1c in multi-ancestry cohorts: The Trans-Omics for Precision Medicine Program.

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

A Comprehensive Reanalysis Of Publicly Available GWAS Datasets Reveals An X Chromosome Rare Regulatory Variant Associated With High Risk For Type 2 Diabetes.

The paper reanalyzes T2D GWAS data to identify a rare X chromosome variant associated with increased T2D risk in males.