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Journal Article

Napier MD, Franceschini N, Gondalia R, Stewart JD, Méndez-Giráldez R, Sitlani CM, Seyerle AA, Highland HM, Li Y, Wilhelmsen KC, et al. Genome-wide association study and meta-analysis identify loci associated with ventricular and supraventricular ectopy. Sci Rep. 2018 ;8(1):5675.

de Vries PS, Sabater-Lleal M, Huffman JE, Marten J, Song C, Pankratz N, Bartz TM, de Haan HG, Delgado GE, Eicher JD, et al. A genome-wide association study identifies new loci for factor VII and implicates factor VII in ischemic stroke etiology. Blood. 2019 ;133(9):967-977.

Carr DF, Francis B, Jorgensen AL, Zhang E, Chinoy H, Heckbert SR, Bis JC, Brody JA, Floyd JS, Psaty BM, et al. Genomewide Association Study of Statin-Induced Myopathy in Patients Recruited Using the UK Clinical Practice Research Datalink. Clin Pharmacol Ther. 2019 ;106(6):1353-1361.

Sabater-Lleal M, Huffman JE, de Vries PS, Marten J, Mastrangelo MA, Song C, Pankratz N, Ward-Caviness CK, Yanek LR, Trompet S, et al. Genome-Wide Association Trans-Ethnic Meta-Analyses Identifies Novel Associations Regulating Coagulation Factor VIII and von Willebrand Factor Plasma Levels. Circulation. 2018 .

Noordam R, Sitlani CM, Avery CL, Stewart JD, Gogarten SM, Wiggins KL, Trompet S, Warren HR, Sun F, Evans DS, et al. A genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. J Med Genet. 2017 ;54(5):313-323.

Do AN, Zhao W, Baldridge AS, Raffield LM, Wiggins KL, Shah SJ, Aslibekyan S, Tiwari HK, Limdi N, Zhi D, et al. Genome-wide meta-analysis of SNP and antihypertensive medication interactions on left ventricular traits in African Americans. Mol Genet Genomic Med. 2019 ;7(10):e00788.

van Rooij FJA, Qayyum R, Smith AV, Zhou Y, Trompet S, Tanaka T, Keller MF, Chang L-C, Schmidt H, Yang M-L, et al. Genome-wide Trans-ethnic Meta-analysis Identifies Seven Genetic Loci Influencing Erythrocyte Traits and a Role for RBPMS in Erythropoiesis. Am J Hum Genet. 2017 ;100(1):51-63.

Lindström S, Wang L, Smith EN, Gordon W, Vlieg Avan Hylcka, de Andrade M, Brody JA, Pattee JW, Haessler J, Brumpton BM, et al. Genomic and transcriptomic association studies identify 16 novel susceptibility loci for venous thromboembolism. Blood. 2019 ;134(19):1645-1657.

Yang Y, Bartz TM, Brown MR, Guo X, Zilhão NR, Trompet S, Weiss S, Yao J, Brody JA, deFilippi CR, et al. Identification of Functional Genetic Determinants of Cardiac Troponin T and I in a Multiethnic Population and Causal Associations With Atrial Fibrillation. Circ Genom Precis Med. 2021 ;14(6):e003460.

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.

Huan T, Nguyen S, Colicino E, Ochoa-Rosales C, W Hill D, Brody JA, Soerensen M, Zhang Y, Baldassari A, Elhadad MAhmed, et al. Integrative analysis of clinical and epigenetic biomarkers of mortality. Aging Cell. 2022 ;21(6):e13608.

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.

Christophersen IE, Rienstra M, Roselli C, Yin X, Geelhoed B, Barnard J, Lin H, Arking DE, Smith AV, Albert CM, et al. Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation. Nat Genet. 2017 ;49(6):946-952.

Lindström S, Brody JA, Turman C, Germain M, Bartz TM, Smith EN, Chen M-H, Puurunen M, Chasman D, Hassler J, et al. A large-scale exome array analysis of venous thromboembolism. Genet Epidemiol. 2019 .

Tajuddin SM, Schick UM, Eicher JD, Chami N, Giri A, Brody JA, W Hill D, Kacprowski T, Li J, Lyytikäinen L-P, et al. Large-Scale Exome-wide Association Analysis Identifies Loci for White Blood Cell Traits and Pleiotropy with Immune-Mediated Diseases. Am J Hum Genet. 2016 ;99(1):22-39.

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.

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.

Tin A, Li Y, Brody JA, Nutile T, Chu AY, Huffman JE, Yang Q, Chen M-H, Robinson-Cohen C, Mace A, et al. Large-scale whole-exome sequencing association studies identify rare functional variants influencing serum urate levels. Nat Commun. 2018 ;9(1):4228.

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.

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 .

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.

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.

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.

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