This paper develops a machine learning framework to impute cross-platform proteomic data, improving replication of epidemiological findings and protein quality scoring.

bioRxiv · May 9, 2026 · PreprintBioinformatics

Refinement of a published gene-physical activity interaction impacting HDL-cholesterol: role of sex and lipoprotein subfractions

Kenneth E. Westerman, Tuomas O. Kilpeläinen, Magdalena del Rocío Sevilla-González, Margery A. Connelly, Alexis C. Wood, Michael Y. Tsai, Kent D. Taylor, Stephen S. Rich, Jerome I. Rotter, James D. Otvos, Amy R. Bentley, Samia Mora, Hugues Aschard, D. C. Rao, C. Charles Gu, , The CHARGE Gene‐Lifestyle Interactions Working Group

The paper refines a gene-physical activity interaction affecting HDL-cholesterol by analyzing lipoprotein subfractions and exploring sex differences across multiple cohorts.

Genetic Epidemiology · Jan 7, 2025Peer-reviewedGenetic & Genomic Medicine

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study

Yuxuan Wang, Margaret Sunitha Selvaraj, Xihao Li, Zilin Li, Jacob A. Holdcraft, Donna K. Arnett, Joshua C. Bis, John Blangero, Eric Boerwinkle, Donald W. Bowden, Brian E. Cade, Jenna C. Carlson, April P. Carson, Yii-Der Ida Chen, Joanne E. Curran, , Gina Marie Peloso

The paper identifies 83 rare lncRNA variant sets associated with blood lipid levels using WGS data from the TOPMed program and validates some in UK Biobank data.

The American Journal of Human Genetics · Oct 1, 2023Peer-reviewedGenetic & Genomic Medicine

Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Margaret Sunitha Selvaraj, Xihao Li, Zilin Li, Akhil Pampana, David Y. Zhang, Joseph Park, Stella W. Aslibekyan, Joshua C. Bis, Jennifer A. Brody, Brian E. Cade, Lee‐Ming Chuang, Ren‐Hua Chung, Joanne E. Curran, Lisa de las Fuentes, Paul S. de Vries, , Najib Ayas

The paper performs whole genome sequence analysis of plasma lipid levels in 66,329 individuals, identifying new lipid-associated alleles, including rare non-coding variants.

Nature Communications · Oct 11, 2022Peer-reviewedGenetics

Amerind ancestry predicts the impact of FADS genetic variation on omega-3 PUFA deficiency, cardiometabolic and inflammatory risk in Hispanic populations

Chaojie Yang, Brian Hallmark, Jin Choul Chai, Timothy D. O’Connor, Lindsay M. Reynolds, Alexis C. Wood, Michael C. Seeds, Yii‐Der Ida Chen, Lyn M. Steffen, Michael Y. Tsai, Robert C. Kaplan, Martha L. Daviglus, Lawrence J. Mandarino, Amanda M. Fretts, Rozenn N. Lemaître, , Ani W Manichaikul

The paper shows Amerind ancestry is linked to lower LC-PUFA levels and increased cardiometabolic risk in Hispanic populations due to FADS genetic variation.

Communications Biology · Jul 28, 2021Peer-reviewedGenetic & Genomic Medicine