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Author Title Type [ Year(Desc)]
Filters: Keyword is Genome-Wide Association Study and Author is Lange, Leslie A  [Clear All Filters]
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.
Magnani JW, Brody JA, Prins BP, Arking DE, Lin H, Yin X, Liu C-T, Morrison AC, Zhang F, Spector TD, et al. Sequencing of SCN5A identifies rare and common variants associated with cardiac conduction: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Circ Cardiovasc Genet. 2014 ;7(3):365-73.
Lange LA, Hu Y, Zhang H, Xue C, Schmidt EM, Tang Z-Z, Bizon C, Lange EM, Smith JD, Turner EH, et al. Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol. Am J Hum Genet. 2014 ;94(2):233-45.
2015
Schick UM, Auer PL, Bis JC, Lin H, Wei P, Pankratz N, Lange LA, Brody J, Stitziel NO, Kim DS, et al. Association of exome sequences with plasma C-reactive protein levels in >9000 participants. Hum Mol Genet. 2015 ;24(2):559-71.
Bis JC, Sitlani C, Irvin R, Avery CL, Smith AVernon, Sun F, Evans DS, Musani SK, Li X, Trompet S, et al. Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium. PLoS One. 2015 ;10(10):e0140496.
Tang W, Cushman M, Green D, Rich SS, Lange LA, Yang Q, Tracy RP, Tofler GH, Basu S, Wilson JG, et al. Gene-centric approach identifies new and known loci for FVIII activity and VWF antigen levels in European Americans and African Americans. Am J Hematol. 2015 ;90(6):534-40.
Durda P, Sabourin J, Lange EM, Nalls MA, Mychaleckyj JC, Jenny NSwords, Li J, Walston J, Harris TB, Psaty BM, et al. Plasma Levels of Soluble Interleukin-2 Receptor α: Associations With Clinical Cardiovascular Events and Genome-Wide Association Scan. Arterioscler Thromb Vasc Biol. 2015 ;35(10):2246-53.
Auer PL, Nalls M, Meschia JF, Worrall BB, Longstreth WT, Seshadri S, Kooperberg C, Burger KM, Carlson CS, Carty CL, et al. Rare and Coding Region Genetic Variants Associated With Risk of Ischemic Stroke: The NHLBI Exome Sequence Project. JAMA Neurol. 2015 ;72(7):781-8.
2022
Durda P, Raffield LM, Lange EM, Olson NC, Jenny NSwords, Cushman M, Deichgraeber P, Grarup N, Jonsson A, Hansen T, et al. Circulating Soluble CD163, Associations With Cardiovascular Outcomes and Mortality, and Identification of Genetic Variants in Older Individuals: The Cardiovascular Health Study. J Am Heart Assoc. 2022 ;11(21):e024374.
Winkler TW, Rasheed H, Teumer A, Gorski M, Rowan BX, Stanzick KJ, Thomas LF, Tin A, Hoppmann A, Chu AY, et al. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals. Commun Biol. 2022 ;5(1):580.
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.
Tcheandjieu C, Zhu X, Hilliard AT, Clarke SL, Napolioni V, Ma S, Lee KMin, Fang H, Chen F, Lu Y, et al. Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. Nat Med. 2022 ;28(8):1679-1692.
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.

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