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Filters: Keyword is Genome-Wide Association Study and Author is Redline, Susan [Clear All Filters]

2011

Fox ER, Young HJ, Li Y, Dreisbach AW, Keating BJ, Musani SK, Liu K, Morrison AC, Ganesh S, Kutlar A, et al. Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study. Hum Mol Genet. 2011 ;20(11):2273-84.

2012

J Smith G, Avery CL, Evans DS, Nalls MA, Meng YA, Smith EN, Palmer C, Tanaka T, Mehra R, Butler AM, et al. Impact of ancestry and common genetic variants on QT interval in African Americans. Circ Cardiovasc Genet. 2012 ;5(6):647-55.

Butler AM, Yin X, Evans DS, Nalls MA, Smith EN, Tanaka T, Li G, Buxbaum SG, Whitsel EA, Alonso A, et al. Novel loci associated with PR interval in a genome-wide association study of 10 African American cohorts. Circ Cardiovasc Genet. 2012 ;5(6):639-46.

Dastani Z, Hivert M-F, Timpson N, Perry JRB, Yuan X, Scott RA, Henneman P, Heid IM, Kizer JR, Lyytikäinen L-P, et al. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals. PLoS Genet. 2012 ;8(3):e1002607.

2013

Monda KL, Chen GK, Taylor KC, Palmer C, Edwards TL, Lange LA, C Y Ng M, Adeyemo AA, Allison MA, Bielak LF, et al. A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry. Nat Genet. 2013 ;45(6):690-6.

Sabater-Lleal M, Huang J, Chasman D, Naitza S, Dehghan A, Johnson AD, Teumer A, Reiner AP, Folkersen L, Basu S, et al. Multiethnic meta-analysis of genome-wide association studies in >100 000 subjects identifies 23 fibrinogen-associated Loci but no strong evidence of a causal association between circulating fibrinogen and cardiovascular disease. Circulation. 2013 ;128(12):1310-24.

2014

Yoneyama S, Guo Y, Lanktree MB, Barnes MR, Elbers CC, Karczewski KJ, Padmanabhan S, Bauer F, Baumert J, Beitelshees A, et al. Gene-centric meta-analyses for central adiposity traits in up to 57 412 individuals of European descent confirm known loci and reveal several novel associations. Hum Mol Genet. 2014 ;23(9):2498-510.

Loth DW, Artigas MSoler, Gharib SA, Wain LV, Franceschini N, Koch B, Pottinger TD, Smith AVernon, Duan Q, Oldmeadow C, et al. Genome-wide association analysis identifies six new loci associated with forced vital capacity. Nat Genet. 2014 ;46(7):669-77.

Ellis J, Lange EM, Li J, Dupuis J, Baumert J, Walston JD, Keating BJ, Durda P, Fox ER, Palmer CD, et al. Large multiethnic Candidate Gene Study for C-reactive protein levels: identification of a novel association at CD36 in African Americans. Hum Genet. 2014 ;133(8):985-95.

2017

Liang J, Le TH, Edwards DRVelez, Tayo BO, Gaulton KJ, Smith JA, Lu Y, Jensen RA, Chen G, Yanek LR, et al. Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations. PLoS Genet. 2017 ;13(5):e1006728.

2019

Cade BE, Chen H, Stilp AM, Louie T, Ancoli-Israel S, Arens R, Barfield R, Below JE, Cai J, Conomos MP, et al. Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep. PLoS Genet. 2019 ;15(4):e1007739.

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.

2020

Zhao X, Qiao D, Yang C, Kasela S, Kim W, Ma Y, Shrine N, Batini C, Sofer T, Taliun SAGagliano, et al. Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants. Nat Commun. 2020 ;11(1):5182.

2022

Li Z, Li X, Zhou H, Gaynor SM, Selvaraj MSunitha, Arapoglou T, Quick C, Liu Y, Chen H, Sun R, et al. A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. Nat Methods. 2022 ;19(12):1599-1611.

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.

Kurniansyah N, Goodman MO, Kelly TN, Elfassy T, Wiggins KL, Bis JC, Guo X, Palmas W, Taylor KD, Lin HJ, et al. A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood. Nat Commun. 2022 ;13(1):3549.

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.

Wang Z, Choi SWan, Chami N, Boerwinkle E, Fornage M, Redline S, Bis JC, Brody JA, Psaty BM, Kim W, et al. The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations. Front Endocrinol (Lausanne). 2022 ;13:863893.

2023

Weinstock JS, Gopakumar J, Burugula BBharathi, Uddin MMesbah, Jahn N, Belk JA, Bouzid H, Daniel B, Miao Z, Ly N, et al. Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis. Nature. 2023 ;616(7958):755-763.

Kurniansyah N, Goodman MO, Khan AT, Wang J, Feofanova E, Bis JC, Wiggins KL, Huffman JE, Kelly T, Elfassy T, et al. Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups. Nat Commun. 2023 ;14(1):3202.

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.

Li X, Quick C, Zhou H, Gaynor SM, Liu Y, Chen H, Selvaraj MSunitha, Sun R, Dey R, Arnett DK, et al. Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. Nat Genet. 2023 ;55(1):154-164.