A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure.

MedStar author(s):
Citation: American Journal of Human Genetics. 102(3):375-400, 2018 03 01.PMID: 29455858Institution: MedStar Health Research InstituteForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: *Blood Pressure/ge [Genetics] | *Continental Population Groups/ge [Genetics] | *Genetic Loci | *Genome-Wide Association Study | *Smoking/ge [Genetics] | Cohort Studies | Diastole/ge [Genetics] | Epistasis, Genetic | Female | Humans | Male | Polymorphism, Single Nucleotide/ge [Genetics] | Quantitative Trait Loci/ge [Genetics] | Reproducibility of Results | Systole/ge [Genetics]Year: 2018Local holdings: Available online from MWHC library: 1949 - present (after 6 months)ISSN:
  • 0002-9297
Name of journal: American journal of human geneticsAbstract: Copyright (c) 2018 American Society of Human Genetics. All rights reserved.Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ~18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 x 10<sup>-8</sup>) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 x 10<sup>-8</sup>). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).All authors: 'an Luan J, Afaq S, Alfred T, Alver M, Amin N, Amini M, Arking D, Arnett DK, Aschard H, Aslibekyan S, Aung T, Barr RG, Bartz TM, Becker DM, Bentley AR, Bielak LF, Bierut LJ, Boehnke M, Boerwinkle E, Boissel M, Bottinger EP, Bouchard C, Bowden DW, Braund PS, Brody JA, Broeckel U, Brown MR, Cabrera CP, Cade B, Caizheng Y, Campbell A, Canouil M, Caulfield MJ, Chai JF, Chakravarti A, Chambers JC, CHARGE Neurology Working Group, Chasman DI, Chauhan G, Chen X, Chen YI, Cheng CY, Christensen K, Cocca M, COGENT-Kidney Consortium, Collins FS, Connell JM, Cooper RS, Cupples LA, de Faire U, de Las Fuentes L, de Mutsert R, de Silva HJ, Deary IJ, Debette S, Divers J, Dorajoo R, Dorr M, Duan Q, Eaton CB, Ehret G, Elliott P, Esko T, Evangelou E, Evans MK, Farrall M, Faul JD, Feitosa MF, Fisher VA, Fornage M, Forouhi NG, Forrester T, Fox ER, Franceschini N, Franco OH, Franks PW, Freedman BI, Friedlander Y, Froguel P, Gandin I, Gao C, Gao H, Gasparini P, Gauderman WJ, GIANT Consortium, Gieger C, Gigante B, Giulianini F, Goel A, Graff M, Gu CC, Gu D, Gudnason V, Guo X, Gupta P, Hagenaars SP, Harris SE, Harris TB, Hartwig FP, Hayward C, He J, Heikkinen S, Heng CK, Hirata M, Hofman A, Horimoto ARVR, Horta BL, Howard BV, Hsu FC, Hung YJ, Hunt S, Irvin MR, Jackson AU, Jia Y, Joehanes R, Jonas JB, Justice AE, Kahonen M, Kamatani Y, Kardia SLR, Kasturiratne A, Kato N, Katsuya T, Kaufman J, Kelly TN, Kerrison ND, Khor CC, Kilpelainen TO, Koh WP, Koistinen HA, Komulainen P, Kooner JS, Kooperberg C, Kraja AT, Krieger JE, Kritchevsky SB, Kubo M, Kuhnel B, Kuusisto J, Laakso M, Langefeld CD, Langenberg C, Launer LJ, Laurie CC, Leander K, Lee WJ, Lehne B, Lehtimaki T, Levy D, Lewis CE, Li C, Li Y, Liang KW, Lifelines Cohort Study, Lim SH, Lin KH, Lin S, Liu CT, Liu J, Liu J, Liu K, Liu Y, Liu Y, Loh M, Lohman KK, Long J, Loos RJF, Louie T, Lu Y, Magi R, Magnusson PKE, Mahajan A, Manning AK, Marten J, Matoba N, McKenzie CA, Meian H, Meitinger T, Metspalu A, Milani L, Momozawa Y, Mook-Kanamori DO, Morris AP, Morrison AC, Mosley TH Jr., Munroe PB, Munson P, Murray AD, Musani SK, Nalls MA, Nasri U, Nelson CP, Newman AB, Noordam R, Norris JM, North K, Ntalla I, O'Connell JR, Ogunniyi A, Oldehinkel AJ, Padmanabhan S, Palmas WR, Palmer ND, Pankow JS, Pedersen NL, Pereira AC, Peters A, Peyser PA, Polasek O, Province MA, Psaty BM, Raitakari OT, Rankinen T, Rao DC, Rauramaa R, Redline S, Reiner AP, Renstrom F, Rettig R, Rice K, Rice TK, Richard MA, Ridker PM, Robino A, Robinson JG, Rose LM, Rotimi CN, Rotter JI, Rudan I, Sabanayagam C, Salako BL, Samani NJ, Sandow K, Schmidt CO, Schreiner PJ, Schupf N, Schwander K, Scott J, Scott RA, Scott WR, Seshadri S, Sever P, Sheu WHH, Shu XO, Sim X, Sims M, Sitlani CM, Smith AV, Smith JA, Snieder H, Sofer T, Stancakova A, Starr JM, Strauch K, Sung YJ, Tai ES, Tajuddin SM, Takeuchi F, Tang H, Taylor KD, Tayo BO, Teo YY, Tham YC, Uitterlinden AG, van Dam RM, van der Harst P, van der Most PJ, van Duijn CM, Varga TV, Vojinovic D, Wagenknecht LE, Waldenberger M, Wang H, Wang L, Wang Y, Wang YX, Ware EB, Wareham NJ, Warren HR, Watkins H, Wei WB, Weir DR, Weiss S, Wen W, Wickremasinghe AR, Williams C, Wilson G, Winkler TW, Wojczynski MK, Wong TY, Wu T, Yanek LR, Yao J, Yuan JM, Zhang W, Zhao JH, Zhao W, Zheng W, Zhou Y, Zhu X, Zonderman ABFiscal year: FY2018Digital Object Identifier: Date added to catalog: 2018-02-28
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Journal Article MedStar Authors Catalog Article 29455858 Available 29455858

Available online from MWHC library: 1949 - present (after 6 months)

Copyright (c) 2018 American Society of Human Genetics. All rights reserved.

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ~18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 x 10<sup>-8</sup>) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 x 10<sup>-8</sup>). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).

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