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Filters: Author is Brody, Jennifer A and Keyword is Genetic Predisposition to Disease [Clear All Filters]

2014

Lubitz SA, Lunetta KL, Lin H, Arking DE, Trompet S, Li G, Krijthe BP, Chasman DI, Barnard J, Kleber ME, et al. Novel genetic markers associate with atrial fibrillation risk in Europeans and Japanese. J Am Coll Cardiol. 2014 ;63(12):1200-10.

Lin H, Sinner MF, Brody JA, Arking DE, Lunetta KL, Rienstra M, Lubitz SA, Magnani JW, Sotoodehnia N, McKnight B, et al. Targeted sequencing in candidate genes for atrial fibrillation: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study. Heart Rhythm. 2014 ;11(3):452-7.

2015

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.

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.

Germain M, Chasman DI, de Haan H, Tang W, Lindström S, Weng L-C, de Andrade M, de Visser MCH, Wiggins KL, Suchon P, et al. Meta-analysis of 65,734 individuals identifies TSPAN15 and SLC44A2 as two susceptibility loci for venous thromboembolism. Am J Hum Genet. 2015 ;96(4):532-42.

2017

Sims R, van der Lee SJ, Naj AC, Bellenguez C, Badarinarayan N, Jakobsdottir J, Kunkle BW, Boland A, Raybould R, Bis JC, et al. Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease. Nat Genet. 2017 ;49(9):1373-1384.

2018

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.

2019

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.

2021

Mikhaylova AV, McHugh CP, Polfus LM, Raffield LM, Boorgula MPreethi, Blackwell TW, Brody JA, Broome J, Chami N, Chen M-H, et al. Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program. Am J Hum Genet. 2021 ;108(10):1836-1851.

2022

Thibord F, Klarin D, Brody JA, Chen M-H, Levin MG, Chasman DI, Goode EL, Hveem K, Teder-Laving M, Martinez-Perez A, et al. Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors. Circulation. 2022 ;146(16):1225-1242.

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.

Elgart M, Lyons G, Romero-Brufau S, Kurniansyah N, Brody JA, Guo X, Lin HJ, Raffield L, Gao Y, Chen H, et al. Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations. Commun Biol. 2022 ;5(1):856.

Hindy G, Dornbos P, Chaffin MD, Liu DJ, Wang M, Selvaraj MSunitha, Zhang D, Park J, Aguilar-Salinas CA, Antonacci-Fulton L, et al. Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes. Am J Hum Genet. 2022 ;109(1):81-96.

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.