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Hoed Mden, Eijgelsheim M, Esko T, Brundel BJJM, Peal DS, Evans DM, Nolte IM, Segrè AV, Holm H, Handsaker RE, et al. Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders. Nat Genet. 2013 ;45(6):621-31.
Sarnowski C, Chen H, Biggs ML, Wassertheil-Smoller S, Bressler J, Irvin MR, Ryan KA, Karasik D, Arnett DK, Cupples AL, et al. Identification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program. PLoS One. 2021 ;16(7):e0253611.
Sarnowski C, Leong A, Raffield LM, Wu P, de Vries PS, DiCorpo D, Guo X, Xu H, Liu Y, Zheng X, et al. Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program. Am J Hum Genet. 2019 ;105(4):706-718.
Kelly TN, Sun X, He KY, Brown MR, Taliun SAGagliano, Hellwege JN, Irvin MR, Mi X, Brody JA, Franceschini N, et al. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. Hypertension. 2022 :101161HYPERTENSIONAHA12219324.
Gharib SA, Loth DW, Artigas MSoler, Birkland TP, Wilk JB, Wain LV, Brody JA, Obeidat M'en, Hancock DB, Tang W, et al. Integrative pathway genomics of lung function and airflow obstruction. Hum Mol Genet. 2015 ;24(23):6836-48.
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Wild PS, Felix JF, Schillert A, Teumer A, Chen M-H, Leening MJG, Völker U, Großmann V, Brody JA, Irvin MR, et al. Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function. J Clin Invest. 2017 ;127(5):1798-1812.
Tang W, Kowgier M, Loth DW, Artigas MSoler, Joubert BR, Hodge E, Gharib SA, Smith AV, Ruczinski I, Gudnason V, et al. Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function. PLoS One. 2014 ;9(7):e100776.
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 .
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.
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.
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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 .
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.
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.
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.
de Vries PS, Chasman DI, Sabater-Lleal M, Chen M-H, Huffman JE, Steri M, Tang W, Teumer A, Marioni RE, Grossmann V, et al. A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration. Hum Mol Genet. 2016 ;25(2):358-70.
Jackson VE, Latourelle JC, Wain LV, Smith AV, Grove ML, Bartz TM, Obeidat M'en, Province MA, Gao W, Qaiser B, et al. Meta-analysis of exome array data identifies six novel genetic loci for lung function. Wellcome Open Res. 2018 ;3:4.
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 .
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).
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 .
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 .
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.
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.

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