George Papanicolaou

This study integrates CAD GWAS with transcriptomic data to identify genes and networks associated with CAD and subclinical atherosclerosis.

This study identifies tissue-specific lncRNA responses to endurance exercise in rats, revealing sex differences and potential therapeutic implications.

The paper identifies impactful rare variants by integrating multi-omic data from MESA, showing that combining expression and protein data increases the detection of rare stop and frameshift variants.

This study shows that MASHR improves transcriptome prediction across populations, leading to more replicable discoveries in multi-ethnic transcriptome-wide association studies.

The paper develops genetic predictors of plasma protein abundance in diverse populations and demonstrates their utility in proteome-wide association studies (PWAS) for complex traits.

This study uses TOPMed whole genome sequences to improve imputation quality and detect rare variant associations in admixed African and Hispanic/Latino populations, identifying two novel associations with hematological traits.

This study identifies 93 genetic loci associated with kidney function across four ancestry groups and highlights causal effects on kidney-related diseases.

This paper introduces SAPPHO methods to detect pleiotropy in GWAS by modeling shared patterns of genetic associations, finding 16 additional and 124 novel loci in meta-analysis.

This study identifies 47 novel genetic loci associated with PR interval through genome-wide association meta-analysis across multiple populations.