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Kilpeläinen TO, Bentley AR, Noordam R, Sung YJu, Schwander K, Winkler TW, Jakupović H, Chasman DI, Manning A, Ntalla I, et al. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nat Commun. 2019 ;10(1):376.
Noordam R, Bos MM, Wang H, Winkler TW, Bentley AR, Kilpeläinen TO, de Vries PS, Sung YJu, Schwander K, Cade BE, et al. Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration. Nat Commun. 2019 ;10(1):5121.
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 .
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.
Bentley AR, Sung YJ, Brown MR, Winkler TW, Kraja AT, Ntalla I, Schwander K, Chasman DI, Lim E, Deng X, et al. Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. Nat Genet. 2019 ;51(4):636-648.
Wang H, Noordam R, Cade BE, Schwander K, Winkler TW, Lee J, Sung YJu, Bentley AR, Manning AK, Aschard H, et al. Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure. Mol Psychiatry. 2021 .
de Vries PS, Brown MR, Bentley AR, Sung YJ, Winkler TW, Ntalla I, Schwander K, Kraja AT, Guo X, Franceschini N, et al. Multi-Ancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. Am J Epidemiol. 2019 .
Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, Rutten-Jacobs L, Giese A-K, van der Laan SW, Gretarsdottir S, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet. 2018 ;50(4):524-537.
Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, Rutten-Jacobs L, Giese A-K, van der Laan SW, Gretarsdottir S, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet. 2018 ;50(4):524-537.
Sun D, Richard M, Musani SK, Sung YJu, Winkler TW, Schwander K, Chai JFang, Guo X, Kilpeläinen TO, Vojinovic D, et al. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. HGG Adv. 2021 ;2(1).
Mahajan A, Spracklen CN, Zhang W, C Y Ng M, Petty LE, Kitajima H, Yu GZ, Rüeger S, Speidel L, Kim YJin, et al. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Nat Genet. 2022 ;54(5):560-572.
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.
Castellani CA, Longchamps RJ, Sumpter JA, Newcomb CE, Lane JA, Grove ML, Bressler J, Brody JA, Floyd JS, Bartz TM, et al. Mitochondrial DNA copy number can influence mortality and cardiovascular disease via methylation of nuclear DNA CpGs. Genome Med. 2020 ;12(1):84.
C Y Ng M, Shriner D, Chen BH, Li J, Chen W-M, Guo X, Liu J, Bielinski SJ, Yanek LR, Nalls MA, et al. Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes. PLoS Genet. 2014 ;10(8):e1004517.
Carty CL, Keene KL, Cheng Y-C, Meschia JF, Chen W-M, Nalls M, Bis JC, Kittner SJ, Rich SS, Tajuddin S, et al. Meta-Analysis of Genome-Wide Association Studies Identifies Genetic Risk Factors for Stroke in African Americans. Stroke. 2015 ;46(8):2063-8.
Kilarski LL, Achterberg S, Devan WJ, Traylor M, Malik R, Lindgren A, Pare G, Sharma P, Slowik A, Thijs V, et al. Meta-analysis in more than 17,900 cases of ischemic stroke reveals a novel association at 12q24.12. Neurology. 2014 ;83(8):678-85.
Liu C, Kraja AT, Smith JA, Brody JA, Franceschini N, Bis JC, Rice K, Morrison AC, Lu Y, Weiss S, et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet. 2016 ;48(10):1162-70.
Xu J, Bartz TM, Chittoor G, Eiriksdottir G, Manichaikul AW, Sun F, Terzikhan N, Zhou X, Booth SL, Brusselle GG, et al. Meta-analysis across Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium provides evidence for an association of serum vitamin D with pulmonary function. Br J Nutr. 2018 :1-12.
Schlosser P, Tin A, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, Weihs A, Yu Z, Hoppmann A, Grundner-Culemann F, et al. Meta-analyses identify DNA methylation associated with kidney function and damage. Nat Commun. 2021 ;12(1):7174.
Holmes MV, Asselbergs FW, Palmer TM, Drenos F, Lanktree MB, Nelson CP, Dale CE, Padmanabhan S, Finan C, Swerdlow DI, et al. Mendelian randomization of blood lipids for coronary heart disease. Eur Heart J. 2015 ;36(9):539-50.
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 .

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