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2025
Jakubek YA, Ma X, Stilp AM, Yu F, Bacon J, Wong JW, Aguet F, Ardlie K, Arnett DK, Barnes K, et al. Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood. Am J Hum Genet. 2025 ;112(2):276-290.
Lee S, Miller CL, Bentley AR, Brown MR, Nagarajan P, Noordam R, Morrison J, Schwander K, Westerman K, Kho M, et al. A Large-Scale Genome-wide Association Study of Blood Pressure Accounting for Gene-Depressive Symptomatology Interactions in 564,680 Individuals from Diverse Populations. Res Sq. 2025 .
Nagarajan P, Winkler TW, Bentley AR, Miller CL, Kraja AT, Schwander K, Lee S, Wang W, Brown MR, Morrison JL, et al. A large-scale genome-wide study of gene-sleep duration interactions for blood pressure in 811,405 individuals from diverse populations. Mol Psychiatry. 2025 .
Roselli C, Surakka I, Olesen MS, Sveinbjornsson G, Marston NA, Choi SHoan, Holm H, Chaffin M, Gudbjartsson D, Hill MC, et al. Meta-analysis of genome-wide associations and polygenic risk prediction for atrial fibrillation in more than 180,000 cases. Nat Genet. 2025 ;57(3):539-547.
Hu Y, Haessler J, Lundin JI, Darst BF, Whitsel EA, Grove M, Guan W, Xia R, Szeto M, Raffield LM, et al. Methylome-wide association analyses of lipids and modifying effects of behavioral factors in diverse race and ethnicity participants. Clin Epigenetics. 2025 ;17(1):54.
Li X, Chen H, Selvaraj MSunitha, Van Buren E, Zhou H, Wang Y, Sun R, McCaw ZR, Yu Z, Jiang M-Z, et al. A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies. Nat Comput Sci. 2025 ;5(2):125-143.
2024
Huang Y-J, Kurniansyah N, Goodman MO, Spitzer BW, Wang J, Stilp A, Laurie C, de Vries PS, Chen H, Min Y-I, et al. The expected polygenic risk score (ePRS) framework: an equitable metric for quantifying polygenetic risk via modeling of ancestral makeup. medRxiv. 2024 .
Weinstock JS, Chaudhry SA, Ioannou M, Viskadourou M, Reventun P, Jakubek YA, L Liggett A, Laurie C, Broome JG, Khan A, et al. The Genetic Determinants and Genomic Consequences of Non-Leukemogenic Somatic Point Mutations. medRxiv. 2024 .
Suzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Melloni GEM, Kanoni S, et al. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature. 2024 .
Nagarajan P, Winkler TW, Bentley AR, Miller CL, Kraja AT, Schwander K, Lee S, Wang W, Brown MR, Morrison JL, et al. A Large-Scale Genome-Wide Study of Gene-Sleep Duration Interactions for Blood Pressure in 811,405 Individuals from Diverse Populations. medRxiv. 2024 .
Hrytsenko Y, Shea B, Elgart M, Kurniansyah N, Lyons G, Morrison AC, Carson AP, Haring B, Mitchell BD, Psaty BM, et al. Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores. Sci Rep. 2024 ;14(1):12436.
Lundin JI, Peters U, Hu Y, Ammous F, Avery CL, Benjamin EJ, Bis JC, Brody JA, Carlson C, Cushman M, et al. Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations. Epigenetics. 2024 ;19(1):2333668.
Mei H, Simino J, Li L, Jiang F, Bis JC, Davies G, W Hill D, Xia C, Gudnason V, Yang Q, et al. Multi-omics and pathway analyses of genome-wide associations implicate regulation and immunity in verbal declarative memory performance. Alzheimers Res Ther. 2024 ;16(1):14.
Rocheleau G, Clarke SL, Auguste G, Hasbani NR, Morrison AC, Heath AS, Bielak LF, Iyer KR, Young EP, Stitziel NO, et al. Rare variant contribution to the heritability of coronary artery disease. Nat Commun. 2024 ;15(1):8741.
2023
Liu X, Sun X, Zhang Y, Jiang W, Lai M, Wiggins KL, Raffield LM, Bielak LF, Zhao W, Pitsillides A, et al. Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk. J Am Heart Assoc. 2023 :e029090.
Zhang Y, Liu X, Wiggins KL, Kurniansyah N, Guo X, Rodrigue AL, Zhao W, Yanek LR, Ratliff SM, Pitsillides A, et al. Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-analysis of Community-Based Cohorts. Neurology. 2023 .
Kurniansyah N, Goodman MO, Khan AT, Wang J, Feofanova E, Bis JC, Wiggins KL, Huffman JE, Kelly T, Elfassy T, et al. Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups. Nat Commun. 2023 ;14(1):3202.
Fuentes Lde Las, Schwander KL, Brown MR, Bentley AR, Winkler TW, Sung YJu, Munroe PB, Miller CL, Aschard H, Aslibekyan S, et al. Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci. Front Genet. 2023 ;14:1235337.
Willems SM, Ng NHJ, Fernandez J, Fine RS, Wheeler E, Wessel J, Kitajima H, Marenne G, Sim X, Yaghootkar H, et al. Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization. Wellcome Open Res. 2023 ;8:483.
Hrytsenko Y, Shea B, Elgart M, Kurniansyah N, Lyons G, Morrison AC, Carson AP, Haring B, Mitchel BD, Psaty BM, et al. Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores. medRxiv. 2023 .
Jakubek YA, Zhou Y, Stilp A, Bacon J, Wong JW, Ozcan Z, Arnett D, Barnes K, Bis JC, Boerwinkle E, et al. Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing. Nat Genet. 2023 ;55(11):1912-1919.
Kavousi M, Bos MM, Barnes HJ, Cardenas CLLino, Wong D, Lu H, Hodonsky CJ, Landsmeer LPL, Turner AW, Kho M, et al. Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification. Nat Genet. 2023 ;55(10):1651-1664.
Suzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Rayner NW, Bocher O, et al. Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. medRxiv. 2023 .
Chen F, Wang X, Jang S-K, Quach BC, J Weissenkampen D, Khunsriraksakul C, Yang L, Sauteraud R, Albert CM, Allred NDD, et al. Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing. Nat Genet. 2023 ;55(2):291-300.
Li X, Quick C, Zhou H, Gaynor SM, Liu Y, Chen H, Selvaraj MSunitha, Sun R, Dey R, Arnett DK, et al. Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. Nat Genet. 2023 ;55(1):154-164.

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