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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.

Nauffal V, Morrill VN, Jurgens SJ, Choi SHoan, Hall AW, Weng L-C, Halford JL, Austin-Tse C, Haggerty CM, Harris SL, et al. Monogenic and Polygenic Contributions to QTc Prolongation in the Population. Circulation. 2022 .

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.

Gorski M, Jung B, Li Y, Matias-Garcia PR, Wuttke M, Coassin S, Thio CHL, Kleber ME, Winkler TW, Wanner V, et al. Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline. Kidney Int. 2020 .

Porcu E, Medici M, Pistis G, Volpato CB, Wilson SG, Cappola AR, Bos SD, Deelen J, Heijer Mden, Freathy RM, et al. A meta-analysis of thyroid-related traits reveals novel loci and gender-specific differences in the regulation of thyroid function. PLoS Genet. 2013 ;9(2):e1003266.

Postmus I, Warren HR, Trompet S, Arsenault BJ, Avery CL, Bis JC, Chasman DI, de Keyser CE, Deshmukh HA, Evans DS, et al. Meta-analysis of genome-wide association studies of HDL cholesterol response to statins. J Med Genet. 2016 ;53(12):835-845.

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.

Dehghan A, Dupuis J, Barbalic M, Bis JC, Eiriksdottir G, Lu C, Pellikka N, Wallaschofski H, Kettunen J, Henneman P, et al. Meta-analysis of genome-wide association studies in >80 000 subjects identifies multiple loci for C-reactive protein levels. Circulation. 2011 ;123(7):731-8.

Bis JC, Kavousi M, Franceschini N, Isaacs A, Abecasis GR, Schminke U, Post WS, Smith AV, Cupples AL, Markus HS, et al. Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque. Nat Genet. 2011 ;43(10):940-7.

van Leeuwen EM, Sabo A, Bis JC, Huffman JE, Manichaikul A, Smith AV, Feitosa MF, Demissie S, Joshi PK, Duan Q, et al. Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels. J Med Genet. 2016 ;53(7):441-9.

Ellinor PT, Lunetta KL, Albert CM, Glazer NL, Ritchie MD, Smith AV, Arking DE, Müller-Nurasyid M, Krijthe BP, Lubitz SA, et al. Meta-analysis identifies six new susceptibility loci for atrial fibrillation. Nat Genet. 2012 ;44(6):670-5.

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.

Hancock DB, Eijgelsheim M, Wilk JB, Gharib SA, Loehr LR, Marciante KD, Franceschini N, van Durme YMTA, Chen T-H, R Barr G, et al. Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function. Nat Genet. 2010 ;42(1):45-52.

Stolk L, Perry JRB, Chasman DI, He C, Mangino M, Sulem P, Barbalic M, Broer L, Byrne EM, Ernst F, et al. Meta-analyses identify 13 loci associated with age at menopause and highlight DNA repair and immune pathways. Nat Genet. 2012 ;44(3):260-8.

Ward-Caviness CK, de Vries PS, Wiggins KL, Huffman JE, Yanek LR, Bielak LF, Giulianini F, Guo X, Kleber ME, Kacprowski T, et al. Mendelian randomization evaluation of causal effects of fibrinogen on incident coronary heart disease. PLoS One. 2019 ;14(5):e0216222.

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.

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 .

L

Manousaki D, Dudding T, Haworth S, Hsu Y-H, Liu C-T, Medina-Gómez C, Voortman T, van der Velde N, Melhus H, Robinson-Cohen C, et al. Low-Frequency Synonymous Coding Variation in CYP2R1 Has Large Effects on Vitamin D Levels and Risk of Multiple Sclerosis. Am J Hum Genet. 2017 ;101(2):227-238.

Wessel J, Chu AY, Willems SM, Wang S, Yaghootkar H, Brody JA, Dauriz M, Hivert M-F, Raghavan S, Lipovich L, et al. Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility. Nat Commun. 2015 ;6:5897.

Sung YJ, Winkler TW, Fuentes Lde Las, Bentley AR, Brown MR, Kraja AT, Schwander K, Ntalla I, Guo X, Franceschini N, et al. A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure. Am J Hum Genet. 2018 ;102(3):375-400.

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 .

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