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Clark DW, Okada Y, Moore KHS, Mason D, Pirastu N, Gandin I, Mattsson H, Barnes CLK, Lin K, Zhao JH, Deelen P, Rohde R, Schurmann C, Guo X, Giulianini F, Zhang W, Medina-Gomez C, Karlsson R, Bao Y, Bartz TM, Baumbach C, Biino G, Bixley MJ, Brumat M, Chai JF, Corre T, Cousminer DL, Dekker AM, Eccles DA, van Eijk KR, Fuchsberger C, Gao H, Germain M, Gordon SD, de Haan HG, Harris SE, Hofer E, Huerta-Chagoya A, Igartua C, Jansen IE, Jia Y, Kacprowski T, Karlsson T, Kleber ME, Li SA, Li-Gao R, Mahajan A, Matsuda K, Meidtner K, Meng W, Montasser ME, van der Most PJ, Munz M, Nutile T, Palviainen T, Prasad G, Prasad RB, Priyanka TDS, Rizzi F, Salvi E, Sapkota BR, Shriner D, Skotte L, Smart MC, Smith AV, van der Spek A, Spracklen CN, Strawbridge RJ, Tajuddin SM, Trompet S, Turman C, Verweij N, Viberti C, Wang L, Warren HR, Wootton RE, Yanek LR, Yao J, Yousri NA, Zhao W, Adeyemo AA, Afaq S, Aguilar-Salinas CA, Akiyama M, Albert ML, Allison MA, Alver M, Aung T, Azizi F, Bentley AR, Boeing H, Boerwinkle E, Borja JB, de Borst GJ, Bottinger EP, Broer L, Campbell H, Chanock S, Chee ML, Chen G, Chen YDI, Chen Z, Chiu YF, Cocca M, Collins FS, Concas MP, Corley J, Cugliari G, van Dam RM, Damulina A, Daneshpour MS, Day FR, Delgado GE, Dhana K, Doney ASF, Dörr M, Doumatey AP, Dzimiri N, Ebenesersdóttir SS, Elliott J, Elliott P, Ewert R, Felix JF, Fischer K, Freedman BI, Girotto G, Goel A, Gögele M, Goodarzi MO, Graff M, Granot-Hershkovitz E, Grodstein F, Guarrera S, Gudbjartsson DF, Guity K, Gunnarsson B, Guo Y, Hagenaars SP, Haiman CA, Halevy A, Harris TB, Hedayati M, van Heel DA, Hirata M, Höfer I, Hsiung CA, Huang J, Hung YJ, Ikram MA, Jagadeesan A, Jousilahti P, Kamatani Y, Kanai M, Kerrison ND, Kessler T, Khaw KT, Khor CC, de Kleijn DPV, Koh WP, Kolcic I, Kraft P, Krämer BK, Kutalik Z, Kuusisto J, Langenberg C, Launer LJ, Lawlor DA, Lee IT, Lee WJ, Lerch MM, Li L, Liu J, Loh M, London SJ, Loomis S, Lu Y, Luan J, Mägi R, Manichaikul AW, Manunta P, Másson G, Matoba N, Mei XW, Meisinger C, Meitinger T, Mezzavilla M, Milani L, Millwood IY, Momozawa Y, Moore A, Morange PE, Moreno-Macías H, Mori TA, Morrison AC, Muka T, Murakami Y, Murray AD, de Mutsert R, Mychaleckyj JC, Nalls MA, Nauck M, Neville MJ, Nolte IM, Ong KK, Orozco L, Padmanabhan S, Pálsson G, Pankow JS, Pattaro C, Pattie A, Polasek O, Poulter N, Pramstaller PP, Quintana-Murci L, Räikkönen K, Ralhan S, Rao DC, van Rheenen W, Rich SS, Ridker PM, Rietveld CA, Robino A, van Rooij FJA, Ruggiero D, Saba Y, Sabanayagam C, Sabater-Lleal M, Sala CF, Salomaa V, Sandow K, Schmidt H, Scott LJ, Scott WR, Sedaghati-Khayat B, Sennblad B, van Setten J, Sever PJ, Sheu WHH, Shi Y, Shrestha S, Shukla SR, Sigurdsson JK, Sikka TT, Singh JR, Smith BH, Stančáková A, Stanton A, Starr JM, Stefansdottir L, Straker L, Sulem P, Sveinbjornsson G, Swertz MA, Taylor AM, Taylor KD, Terzikhan N, Tham YC, Thorleifsson G, Thorsteinsdottir U, Tillander A, Tracy RP, Tusié-Luna T, Tzoulaki I, Vaccargiu S, Vangipurapu J, Veldink JH, Vitart V, Völker U, Vuoksimaa E, Wakil SM, Waldenberger M, Wander GS, Wang YX, Wareham NJ, Wild S, Yajnik CS, Yuan JM, Zeng L, Zhang L, Zhou J, Amin N, Asselbergs FW, Bakker SJL, Becker DM, Lehne B, Bennett DA, van den Berg LH, Berndt SI, Bharadwaj D, Bielak LF, Bochud M, Boehnke M, Bouchard C, Bradfield JP, Brody JA, Campbell A, Carmi S, Caulfield MJ, Cesarini D, Chambers JC, Chandak GR, Cheng CY, Ciullo M, Cornelis M, Cusi D, Smith GD, Deary IJ, Dorajoo R, van Duijn CM, Ellinghaus D, Erdmann J, Eriksson JG, Evangelou E, Evans MK, Faul JD, Feenstra B, Feitosa M, Foisy S, Franke A, Friedlander Y, Gasparini P, Gieger C, Gonzalez C, Goyette P, Grant SFA, Griffiths LR, Groop L, Gudnason V, Gyllensten U, Hakonarson H, Hamsten A, van der Harst P, Heng CK, Hicks AA, Hochner H, Huikuri H, Hunt SC, Jaddoe VWV, De Jager PL, Johannesson M, Johansson Å, Jonas JB, Jukema JW, Junttila J, Kaprio J, Kardia SLR, Karpe F, Kumari M, Laakso M, van der Laan SW, Lahti J, Laudes M, Lea RA, Lieb W, Lumley T, Martin NG, März W, Matullo G, McCarthy MI, Medland SE, Merriman TR, Metspalu A, Meyer BF, Mohlke KL, Montgomery GW, Mook-Kanamori D, Munroe PB, North KE, Nyholt DR, O'connell JR, Ober C, Oldehinkel AJ, Palmas W, Palmer C, Pasterkamp GG, Patin E, Pennell CE, Perusse L, Peyser PA, Pirastu M, Polderman TJC, Porteous DJ, Posthuma D, Psaty BM, Rioux JD, Rivadeneira F, Rotimi C, Rotter JI, Rudan I, Den Ruijter HM, Sanghera DK, Sattar N, Schmidt R, Schulze MB, Schunkert H, Scott RA, Shuldiner AR, Sim X, Small N, Smith JA, Sotoodehnia N, Tai ES, Teumer A, Timpson NJ, Toniolo D, Tregouet DA, Tuomi T, Vollenweider P, Wang CA, Weir DR, Whitfield JB, Wijmenga C, Wong TY, Wright J, Yang J, Yu L, Zemel BS, Zonderman AB, Perola M, Magnusson PKE, Uitterlinden AG, Kooner JS, Chasman DI, Loos RJF, Franceschini N, Franke L, Haley CS, Hayward C, Walters RG, Perry JRB, Esko T, Helgason A, Stefansson K, Joshi PK, Kubo M, Wilson JF. Associations of autozygosity with a broad range of human phenotypes. Nat Commun 2019; 10:4957. [PMID: 31673082 PMCID: PMC6823371 DOI: 10.1038/s41467-019-12283-6] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 08/30/2019] [Indexed: 11/20/2022] Open
Abstract
In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding.
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Harris DN, Ruczinski I, Yanek LR, Becker LC, Becker DM, Guio H, Cui T, Chilton FH, Mathias RA, O'Connor TD. Evolution of Hominin Polyunsaturated Fatty Acid Metabolism: From Africa to the New World. Genome Biol Evol 2019; 11:1417-1430. [PMID: 30942856 PMCID: PMC6514828 DOI: 10.1093/gbe/evz071] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/01/2019] [Indexed: 12/23/2022] Open
Abstract
The metabolic conversion of dietary omega-3 and omega-6 18 carbon (18C) to long chain (>20 carbon) polyunsaturated fatty acids (LC-PUFAs) is vital for human life. The rate-limiting steps of this process are catalyzed by fatty acid desaturase (FADS) 1 and 2. Therefore, understanding the evolutionary history of the FADS genes is essential to our understanding of hominin evolution. The FADS genes have two haplogroups, ancestral and derived, with the derived haplogroup being associated with more efficient LC-PUFA biosynthesis than the ancestral haplogroup. In addition, there is a complex global distribution of these haplogroups that is suggestive of Neanderthal introgression. We confirm that Native American ancestry is nearly fixed for the ancestral haplogroup, and replicate a positive selection signal in Native Americans. This positive selection potentially continued after the founding of the Americas, although simulations suggest that the timing is dependent on the allele frequency of the ancestral Beringian population. We also find that the Neanderthal FADS haplotype is more closely related to the derived haplogroup and the Denisovan clusters closer to the ancestral haplogroup. Furthermore, the derived haplogroup has a time to the most recent common ancestor of 688,474 years before present. These results support an ancient polymorphism, as opposed to Neanderthal introgression, forming in the FADS region during the Pleistocene with possibly differential selection pressures on both haplogroups. The near fixation of the ancestral haplogroup in Native American ancestry calls for future studies to explore the potential health risk of associated low LC-PUFA levels in these populations.
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Jian X, Satizabal CL, Smith AV, Wittfeld K, Bis JC, Smith JA, Hsu FC, Nho K, Hofer E, Hagenaars SP, Nyquist PA, Mishra A, Adams HHH, Li S, Teumer A, Zhao W, Freedman BI, Saba Y, Yanek LR, Chauhan G, van Buchem MA, Cushman M, Royle NA, Bryan RN, Niessen WJ, Windham BG, DeStefano AL, Habes M, Heckbert SR, Palmer ND, Lewis CE, Eiriksdottir G, Maillard P, Mathias RA, Homuth G, Valdés-Hernández MDC, Divers J, Beiser AS, Langner S, Rice KM, Bastin ME, Yang Q, Maldjian JA, Starr JM, Sidney S, Risacher SL, Uitterlinden AG, Gudnason VG, Nauck M, Rotter JI, Schreiner PJ, Boerwinkle E, van Duijn CM, Mazoyer B, von Sarnowski B, Gottesman RF, Levy D, Sigurdsson S, Vernooij MW, Turner ST, Schmidt R, Wardlaw JM, Psaty BM, Mosley TH, DeCarli CS, Saykin AJ, Bowden DW, Becker DM, Deary IJ, Schmidt H, Kardia SLR, Ikram MA, Debette S, Grabe HJ, Longstreth WT, Seshadri S, Launer LJ, Fornage M. Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38 for White Matter Hyperintensities on Brain Magnetic Resonance Imaging. Stroke 2019; 49:1812-1819. [PMID: 30002152 DOI: 10.1161/strokeaha.118.020689] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background and Purpose- White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods- In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results- At 17q25, we confirmed the association of multiple common variants in TRIM65, FBF1, and ACOX1 ( P<6×10-7). We also identified a novel association with 2 low-frequency nonsynonymous variants in MRPL38 (lead, rs34136221; PEA=4.5×10-8) partially independent of known common signal ( PEA(conditional)=1.4×10-3). We further identified a locus at 2q33 containing common variants in NBEAL1, CARF, and WDR12 (lead, rs2351524; Pall=1.9×10-10). Although our novel findings were not replicated because of limited power and possible differences in study design, meta-analysis of the discovery and replication samples yielded stronger association for the 2 low-frequency MRPL38 variants ( Prs34136221=2.8×10-8). Conclusions- Both common and low-frequency/rare functional variants influence WMH. Larger replication and experimental follow-up are essential to confirm our findings and uncover the biological causal mechanisms of age-related WMH.
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van der Lee SJ, Knol MJ, Chauhan G, Satizabal CL, Smith AV, Hofer E, Bis JC, Hibar DP, Hilal S, van den Akker EB, Arfanakis K, Bernard M, Yanek LR, Amin N, Crivello F, Cheung JW, Harris TB, Saba Y, Lopez OL, Li S, van der Grond J, Yu L, Paus T, Roshchupkin GV, Amouyel P, Jahanshad N, Taylor KD, Yang Q, Mathias RA, Boehringer S, Mazoyer B, Rice K, Cheng CY, Maillard P, van Heemst D, Wong TY, Niessen WJ, Beiser AS, Beekman M, Zhao W, Nyquist PA, Chen C, Launer LJ, Psaty BM, Ikram MK, Vernooij MW, Schmidt H, Pausova Z, Becker DM, De Jager PL, Thompson PM, van Duijn CM, Bennett DA, Slagboom PE, Schmidt R, Longstreth WT, Ikram MA, Seshadri S, Debette S, Gudnason V, Adams HHH, DeCarli C. A genome-wide association study identifies genetic loci associated with specific lobar brain volumes. Commun Biol 2019; 2:285. [PMID: 31396565 PMCID: PMC6677735 DOI: 10.1038/s42003-019-0537-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 05/14/2019] [Indexed: 12/26/2022] Open
Abstract
Brain lobar volumes are heritable but genetic studies are limited. We performed genome-wide association studies of frontal, occipital, parietal and temporal lobe volumes in 16,016 individuals, and replicated our findings in 8,789 individuals. We identified six genetic loci associated with specific lobar volumes independent of intracranial volume. Two loci, associated with occipital (6q22.32) and temporal lobe volume (12q14.3), were previously reported to associate with intracranial and hippocampal volume, respectively. We identified four loci previously unknown to affect brain volumes: 3q24 for parietal lobe volume, and 1q22, 4p16.3 and 14q23.1 for occipital lobe volume. The associated variants were located in regions enriched for histone modifications (DAAM1 and THBS3), or close to genes causing Mendelian brain-related diseases (ZIC4 and FGFRL1). No genetic overlap between lobar volumes and neurological or psychiatric diseases was observed. Our findings reveal part of the complex genetics underlying brain development and suggest a role for regulatory regions in determining brain volumes.
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Sung YJ, de las Fuentes L, Winkler TW, Chasman DI, Bentley AR, Kraja AT, Ntalla I, Warren HR, Guo X, Schwander K, Manning AK, Brown MR, Aschard H, Feitosa MF, Franceschini N, Lu Y, Cheng CY, Sim X, Vojinovic D, Marten J, Musani SK, Kilpeläinen TO, Richard MA, Aslibekyan S, Bartz TM, Dorajoo R, Li C, Liu Y, Rankinen T, Smith AV, Tajuddin SM, Tayo BO, Zhao W, Zhou Y, Matoba N, Sofer T, Alver M, Amini M, Boissel M, Chai JF, Chen X, Divers J, Gandin I, Gao C, Giulianini F, Goel A, Harris SE, Hartwig FP, He M, Horimoto ARVR, Hsu FC, Jackson AU, Kammerer CM, Kasturiratne A, Komulainen P, Kühnel B, Leander K, Lee WJ, Lin KH, Luan J, Lyytikäinen LP, McKenzie CA, Nelson CP, Noordam R, Scott RA, Sheu WHH, Stančáková A, Takeuchi F, van der Most PJ, Varga TV, Waken RJ, Wang H, Wang Y, Ware EB, Weiss S, Wen W, Yanek LR, Zhang W, Zhao JH, Afaq S, Alfred T, Amin N, Arking DE, Aung T, Barr RG, Bielak LF, Boerwinkle E, Bottinger EP, Braund PS, Brody JA, Broeckel U, Cade B, Campbell A, Canouil M, Chakravarti A, Cocca M, Collins FS, Connell JM, de Mutsert R, de Silva HJ, Dörr M, Duan Q, Eaton CB, Ehret G, Evangelou E, Faul JD, Forouhi NG, Franco OH, Friedlander Y, Gao H, Gigante B, Gu CC, Gupta P, Hagenaars SP, Harris TB, He J, Heikkinen S, Heng CK, Hofman A, Howard BV, Hunt SC, Irvin MR, Jia Y, Katsuya T, Kaufman J, Kerrison ND, Khor CC, Koh WP, Koistinen HA, Kooperberg CB, Krieger JE, Kubo M, Kutalik Z, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lee JH, Lehne B, Levy D, Lewis CE, Li Y, Lim SH, Liu CT, Liu J, Liu J, Liu Y, Loh M, Lohman KK, Louie T, Mägi R, Matsuda K, Meitinger T, Metspalu A, Milani L, Momozawa Y, Mosley, Jr TH, Nalls MA, Nasri U, O'Connell JR, Ogunniyi A, Palmas WR, Palmer ND, Pankow JS, Pedersen NL, Peters A, Peyser PA, Polasek O, Porteous D, Raitakari OT, Renström F, Rice TK, Ridker PM, Robino A, Robinson JG, Rose LM, Rudan I, Sabanayagam C, Salako BL, Sandow K, Schmidt CO, Schreiner PJ, Scott WR, Sever P, Sims M, Sitlani CM, Smith BH, Smith JA, Snieder H, Starr JM, Strauch K, Tang H, Taylor KD, Teo YY, Tham YC, Uitterlinden AG, Waldenberger M, Wang L, Wang YX, Wei WB, Wilson G, Wojczynski MK, Xiang YB, Yao J, Yuan JM, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Chen YDI, Weir DR, de Faire U, Deary IJ, Esko T, Farrall M, Forrester T, Freedman BI, Froguel P, Gasparini P, Gieger C, Horta BL, Hung YJ, Jonas JB, Kato N, Kooner JS, Laakso M, Lehtimäki T, Liang KW, Magnusson PKE, Oldehinkel AJ, Pereira AC, Perls T, Rauramaa R, Redline S, Rettig R, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wareham NJ, Watkins H, Wickremasinghe AR, Wu T, Kamatani Y, Laurie CC, Bouchard C, Cooper RS, Evans MK, Gudnason V, Hixson J, Kardia SLR, Kritchevsky SB, Psaty BM, van Dam RM, Arnett DK, Mook-Kanamori DO, Fornage M, Fox ER, Hayward C, van Duijn CM, Tai ES, Wong TY, Loos RJF, Reiner AP, Rotimi CN, Bierut LJ, Zhu X, Cupples LA, Province MA, Rotter JI, Franks PW, Rice K, Elliott P, Caulfield MJ, Gauderman WJ, Munroe PB, Rao DC, Morrison AC. A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure. Hum Mol Genet 2019; 28:2615-2633. [PMID: 31127295 PMCID: PMC6644157 DOI: 10.1093/hmg/ddz070] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 03/25/2019] [Accepted: 03/26/2019] [Indexed: 12/24/2022] Open
Abstract
Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene-smoking interaction analysis and 38 were newly identified (P < 5 × 10-8, false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.
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Saccone NL, Emery LS, Sofer T, Gogarten SM, Becker DM, Bottinger EP, Chen LS, Culverhouse RC, Duan W, Hancock DB, Hosgood HD, Johnson EO, Loos RJF, Louie T, Papanicolaou G, Perreira KM, Rodriquez EJ, Schurmann C, Stilp AM, Szpiro AA, Talavera GA, Taylor KD, Thrasher JF, Yanek LR, Laurie CC, Pérez-Stable EJ, Bierut LJ, Kaplan RC. Genome-Wide Association Study of Heavy Smoking and Daily/Nondaily Smoking in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Nicotine Tob Res 2019; 20:448-457. [PMID: 28520984 DOI: 10.1093/ntr/ntx107] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Accepted: 05/11/2017] [Indexed: 02/07/2023]
Abstract
Introduction Genetic variants associated with nicotine dependence have previously been identified, primarily in European-ancestry populations. No genome-wide association studies (GWAS) have been reported for smoking behaviors in Hispanics/Latinos in the United States and Latin America, who are of mixed ancestry with European, African, and American Indigenous components. Methods We examined genetic associations with smoking behaviors in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (N = 12 741 with smoking data, 5119 ever-smokers), using ~2.3 million genotyped variants imputed to the 1000 Genomes Project phase 3. Mixed logistic regression models accounted for population structure, sampling, relatedness, sex, and age. Results The known region of CHRNA5, which encodes the α5 cholinergic nicotinic receptor subunit, was associated with heavy smoking at genome-wide significance (p ≤ 5 × 10-8) in a comparison of 1929 ever-smokers reporting cigarettes per day (CPD) > 10 versus 3156 reporting CPD ≤ 10. The functional variant rs16969968 in CHRNA5 had a p value of 2.20 × 10-7 and odds ratio (OR) of 1.32 for the minor allele (A); its minor allele frequency was 0.22 overall and similar across Hispanic/Latino background groups (Central American = 0.17; South American = 0.19; Mexican = 0.18; Puerto Rican = 0.22; Cuban = 0.29; Dominican = 0.19). CHRNA4 on chromosome 20 attained p < 10-4, supporting prior findings in non-Hispanics. For nondaily smoking, which is prevalent in Hispanic/Latino smokers, compared to daily smoking, loci on chromosomes 2 and 4 achieved genome-wide significance; replication attempts were limited by small Hispanic/Latino sample sizes. Conclusions Associations of nicotinic receptor gene variants with smoking, first reported in non-Hispanic European-ancestry populations, generalized to Hispanics/Latinos despite different patterns of smoking behavior. Implications We conducted the first large-scale genome-wide association study (GWAS) of smoking behavior in a US Hispanic/Latino cohort, and the first GWAS of daily/nondaily smoking in any population. Results show that the region of the nicotinic receptor subunit gene CHRNA5, which in non-Hispanic European-ancestry smokers has been associated with heavy smoking as well as cessation and treatment efficacy, is also significantly associated with heavy smoking in this Hispanic/Latino cohort. The results are an important addition to understanding the impact of genetic variants in understudied Hispanic/Latino smokers.
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de Vries PS, Brown MR, Bentley AR, Sung YJ, Winkler TW, Ntalla I, Schwander K, Kraja AT, Guo X, Franceschini N, Cheng CY, Sim X, Vojinovic D, Huffman JE, Musani SK, Li C, Feitosa MF, Richard MA, Noordam R, Aschard H, Bartz TM, Bielak LF, Deng X, Dorajoo R, Lohman KK, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Evangelou E, Graff M, Alver M, Boissel M, Chai JF, Chen X, Divers J, Gandin I, Gao C, Goel A, Hagemeijer Y, Harris SE, Hartwig FP, He M, Horimoto ARVR, Hsu FC, Jackson AU, Kasturiratne A, Komulainen P, Kühnel B, Laguzzi F, Lee JH, Luan J, Lyytikäinen LP, Matoba N, Nolte IM, Pietzner M, Riaz M, Said MA, Scott RA, Sofer T, Stančáková A, Takeuchi F, Tayo BO, van der Most PJ, Varga TV, Wang Y, Ware EB, Wen W, Yanek LR, Zhang W, Zhao JH, Afaq S, Amin N, Amini M, Arking DE, Aung T, Ballantyne C, Boerwinkle E, Broeckel U, Campbell A, Canouil M, Charumathi S, Chen YDI, Connell JM, de Faire U, de las Fuentes L, de Mutsert R, de Silva HJ, Ding J, Dominiczak AF, Duan Q, Eaton CB, Eppinga RN, Faul JD, Fisher V, Forrester T, Franco OH, Friedlander Y, Ghanbari M, Giulianini F, Grabe HJ, Grove ML, Gu CC, Harris TB, Heikkinen S, Heng CK, Hirata M, Hixson JE, Howard BV, Ikram MA, Jacobs DR, Johnson C, Jonas JB, Kammerer CM, Katsuya T, Khor CC, Kilpeläinen TO, Koh WP, Koistinen HA, Kolcic I, Kooperberg C, Krieger JE, Kritchevsky SB, Kubo M, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lemaitre RN, Li Y, Liang J, Liu J, Liu K, Loh M, Louie T, Mägi R, Manichaikul AW, McKenzie CA, Meitinger T, Metspalu A, Milaneschi Y, Milani L, Mohlke KL, Mosley TH, Mukamal KJ, Nalls MA, Nauck M, Nelson CP, Sotoodehnia N, O'Connell JR, Palmer ND, Pazoki R, Pedersen NL, Peters A, Peyser PA, Polasek O, Poulter N, Raffel LJ, Raitakari OT, Reiner AP, Rice TK, Rich SS, Robino A, Robinson JG, Rose LM, Rudan I, Schmidt CO, Schreiner PJ, Scott WR, Sever P, Shi Y, Sidney S, Sims M, Smith BH, Smith JA, Snieder H, Starr JM, Strauch K, Tan N, Taylor KD, Teo YY, Tham YC, Uitterlinden AG, van Heemst D, Vuckovic D, Waldenberger M, Wang L, Wang Y, Wang Z, Wei WB, Williams C, Wilson G, Wojczynski MK, Yao J, Yu B, Yu C, Yuan JM, Zhao W, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Deary IJ, Esko T, Farrall M, Franks PW, Freedman BI, Froguel P, Gasparini P, Gieger C, Horta BL, Kamatani Y, Kato N, Kooner JS, Laakso M, Leander K, Lehtimäki T, Magnusson PKE, Penninx B, Pereira AC, Rauramaa R, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wang YX, Wareham NJ, Watkins H, Weir DR, Wickremasinghe AR, Zheng W, Elliott P, North KE, Bouchard C, Evans MK, Gudnason V, Liu CT, Liu Y, Psaty BM, Ridker PM, van Dam RM, Kardia SLR, Zhu X, Rotimi CN, Mook-Kanamori DO, Fornage M, Kelly TN, Fox ER, Hayward C, van Duijn CM, Tai ES, Wong TY, Liu J, Rotter JI, Gauderman WJ, Province MA, Munroe PB, Rice K, Chasman DI, Cupples LA, Rao DC, Morrison AC. Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. Am J Epidemiol 2019; 188:1033-1054. [PMID: 30698716 PMCID: PMC6545280 DOI: 10.1093/aje/kwz005] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 01/05/2019] [Accepted: 01/08/2019] [Indexed: 12/27/2022] Open
Abstract
A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.
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Bentley AR, Sung YJ, Brown MR, Winkler TW, Kraja AT, Ntalla I, Schwander K, Chasman DI, Lim E, Deng X, Guo X, Liu J, Lu Y, Cheng CY, Sim X, Vojinovic D, Huffman JE, Musani SK, Li C, Feitosa MF, Richard MA, Noordam R, Baker J, Chen G, Aschard H, Bartz TM, Ding J, Dorajoo R, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Zhao W, Graff M, Alver M, Boissel M, Chai JF, Chen X, Divers J, Evangelou E, Gao C, Goel A, Hagemeijer Y, Harris SE, Hartwig FP, He M, Horimoto ARVR, Hsu FC, Hung YJ, Jackson AU, Kasturiratne A, Komulainen P, Kühnel B, Leander K, Lin KH, Luan J, Lyytikäinen LP, Matoba N, Nolte IM, Pietzner M, Prins B, Riaz M, Robino A, Said MA, Schupf N, Scott RA, Sofer T, Stancáková A, Takeuchi F, Tayo BO, van der Most PJ, Varga TV, Wang TD, Wang Y, Ware EB, Wen W, Xiang YB, Yanek LR, Zhang W, Zhao JH, Adeyemo A, Afaq S, Amin N, Amini M, Arking DE, Arzumanyan Z, Aung T, Ballantyne C, Barr RG, Bielak LF, Boerwinkle E, Bottinger EP, Broeckel U, Brown M, Cade BE, Campbell A, Canouil M, Charumathi S, Chen YDI, Christensen K, Concas MP, Connell JM, de Las Fuentes L, de Silva HJ, de Vries PS, Doumatey A, Duan Q, Eaton CB, Eppinga RN, Faul JD, Floyd JS, Forouhi NG, Forrester T, Friedlander Y, Gandin I, Gao H, Ghanbari M, Gharib SA, Gigante B, Giulianini F, Grabe HJ, Gu CC, Harris TB, Heikkinen S, Heng CK, Hirata M, Hixson JE, Ikram MA, Jia Y, Joehanes R, Johnson C, Jonas JB, Justice AE, Katsuya T, Khor CC, Kilpeläinen TO, Koh WP, Kolcic I, Kooperberg C, Krieger JE, Kritchevsky SB, Kubo M, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lewis CE, Li Y, Liang J, Lin S, Liu CT, Liu J, Liu K, Loh M, Lohman KK, Louie T, Luzzi A, Mägi R, Mahajan A, Manichaikul AW, McKenzie CA, Meitinger T, Metspalu A, Milaneschi Y, Milani L, Mohlke KL, Momozawa Y, Morris AP, Murray AD, Nalls MA, Nauck M, Nelson CP, North KE, O'Connell JR, Palmer ND, Papanicolau GJ, Pedersen NL, Peters A, Peyser PA, Polasek O, Poulter N, Raitakari OT, Reiner AP, Renström F, Rice TK, Rich SS, Robinson JG, Rose LM, Rosendaal FR, Rudan I, Schmidt CO, Schreiner PJ, Scott WR, Sever P, Shi Y, Sidney S, Sims M, Smith JA, Snieder H, Starr JM, Strauch K, Stringham HM, Tan NYQ, Tang H, Taylor KD, Teo YY, Tham YC, Tiemeier H, Turner ST, Uitterlinden AG, van Heemst D, Waldenberger M, Wang H, Wang L, Wang L, Wei WB, Williams CA, Wilson G, Wojczynski MK, Yao J, Young K, Yu C, Yuan JM, Zhou J, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Cooper RS, de Faire U, Deary IJ, Elliott P, Esko T, Farrall M, Franks PW, Freedman BI, Froguel P, Gasparini P, Gieger C, Horta BL, Juang JMJ, Kamatani Y, Kammerer CM, Kato N, Kooner JS, Laakso M, Laurie CC, Lee IT, Lehtimäki T, Magnusson PKE, Oldehinkel AJ, Penninx BWJH, Pereira AC, Rauramaa R, Redline S, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wang JS, Wang YX, Wareham NJ, Watkins H, Weir DR, Wickremasinghe AR, Wu T, Zeggini E, Zheng W, Bouchard C, Evans MK, Gudnason V, Kardia SLR, Liu Y, Psaty BM, Ridker PM, van Dam RM, Mook-Kanamori DO, Fornage M, Province MA, Kelly TN, Fox ER, Hayward C, van Duijn CM, Tai ES, Wong TY, Loos RJF, Franceschini N, Rotter JI, Zhu X, Bierut LJ, Gauderman WJ, Rice K, Munroe PB, Morrison AC, Rao DC, Rotimi CN, Cupples LA. Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. Nat Genet 2019; 51:636-648. [PMID: 30926973 PMCID: PMC6467258 DOI: 10.1038/s41588-019-0378-y] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Accepted: 02/07/2019] [Indexed: 12/08/2022]
Abstract
The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.
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Kraja AT, Liu C, Fetterman JL, Graff M, Have CT, Gu C, Yanek LR, Feitosa MF, Arking DE, Chasman DI, Young K, Ligthart S, Hill WD, Weiss S, Luan J, Giulianini F, Li-Gao R, Hartwig FP, Lin SJ, Wang L, Richardson TG, Yao J, Fernandez EP, Ghanbari M, Wojczynski MK, Lee WJ, Argos M, Armasu SM, Barve RA, Ryan KA, An P, Baranski TJ, Bielinski SJ, Bowden DW, Broeckel U, Christensen K, Chu AY, Corley J, Cox SR, Uitterlinden AG, Rivadeneira F, Cropp CD, Daw EW, van Heemst D, de Las Fuentes L, Gao H, Tzoulaki I, Ahluwalia TS, de Mutsert R, Emery LS, Erzurumluoglu AM, Perry JA, Fu M, Forouhi NG, Gu Z, Hai Y, Harris SE, Hemani G, Hunt SC, Irvin MR, Jonsson AE, Justice AE, Kerrison ND, Larson NB, Lin KH, Love-Gregory LD, Mathias RA, Lee JH, Nauck M, Noordam R, Ong KK, Pankow J, Patki A, Pattie A, Petersmann A, Qi Q, Ribel-Madsen R, Rohde R, Sandow K, Schnurr TM, Sofer T, Starr JM, Taylor AM, Teumer A, Timpson NJ, de Haan HG, Wang Y, Weeke PE, Williams C, Wu H, Yang W, Zeng D, Witte DR, Weir BS, Wareham NJ, Vestergaard H, Turner ST, Torp-Pedersen C, Stergiakouli E, Sheu WHH, Rosendaal FR, Ikram MA, Franco OH, Ridker PM, Perls TT, Pedersen O, Nohr EA, Newman AB, Linneberg A, Langenberg C, Kilpeläinen TO, Kardia SLR, Jørgensen ME, Jørgensen T, Sørensen TIA, Homuth G, Hansen T, Goodarzi MO, Deary IJ, Christensen C, Chen YDI, Chakravarti A, Brandslund I, Bonnelykke K, Taylor KD, Wilson JG, Rodriguez S, Davies G, Horta BL, Thyagarajan B, Rao DC, Grarup N, Davila-Roman VG, Hudson G, Guo X, Arnett DK, Hayward C, Vaidya D, Mook-Kanamori DO, Tiwari HK, Levy D, Loos RJF, Dehghan A, Elliott P, Malik AN, Scott RA, Becker DM, de Andrade M, Province MA, Meigs JB, Rotter JI, North KE. Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits. Am J Hum Genet 2019; 104:112-138. [PMID: 30595373 PMCID: PMC6323610 DOI: 10.1016/j.ajhg.2018.12.001] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Accepted: 12/06/2018] [Indexed: 12/16/2022] Open
Abstract
Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E-04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E-03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E-06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.
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Ward-Caviness CK, de Vries PS, Wiggins KL, Huffman JE, Yanek LR, Bielak LF, Giulianini F, Guo X, Kleber ME, Kacprowski T, Groß S, Petersman A, Davey Smith G, Hartwig FP, Bowden J, Hemani G, Müller-Nuraysid M, Strauch K, Koenig W, Waldenberger M, Meitinger T, Pankratz N, Boerwinkle E, Tang W, Fu YP, Johnson AD, Song C, de Maat MPM, Uitterlinden AG, Franco OH, Brody JA, McKnight B, Chen YDI, Psaty BM, Mathias RA, Becker DM, Peyser PA, Smith JA, Bielinski SJ, Ridker PM, Taylor KD, Yao J, Tracy R, Delgado G, Trompet S, Sattar N, Jukema JW, Becker LC, Kardia SLR, Rotter JI, März W, Dörr M, Chasman DI, Dehghan A, O’Donnell CJ, Smith NL, Peters A, Morrison AC. Mendelian randomization evaluation of causal effects of fibrinogen on incident coronary heart disease. PLoS One 2019; 14:e0216222. [PMID: 31075152 PMCID: PMC6510421 DOI: 10.1371/journal.pone.0216222] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 04/16/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Fibrinogen is an essential hemostatic factor and cardiovascular disease risk factor. Early attempts at evaluating the causal effect of fibrinogen on coronary heart disease (CHD) and myocardial infraction (MI) using Mendelian randomization (MR) used single variant approaches, and did not take advantage of recent genome-wide association studies (GWAS) or multi-variant, pleiotropy robust MR methodologies. METHODS AND FINDINGS We evaluated evidence for a causal effect of fibrinogen on both CHD and MI using MR. We used both an allele score approach and pleiotropy robust MR models. The allele score was composed of 38 fibrinogen-associated variants from recent GWAS. Initial analyses using the allele score used a meta-analysis of 11 European-ancestry prospective cohorts, free of CHD and MI at baseline, to examine incidence CHD and MI. We also applied 2 sample MR methods with data from a prevalent CHD and MI GWAS. Results are given in terms of the hazard ratio (HR) or odds ratio (OR), depending on the study design, and associated 95% confidence interval (CI). In single variant analyses no causal effect of fibrinogen on CHD or MI was observed. In multi-variant analyses using incidence CHD cases and the allele score approach, the estimated causal effect (HR) of a 1 g/L higher fibrinogen concentration was 1.62 (CI = 1.12, 2.36) when using incident cases and the allele score approach. In 2 sample MR analyses that accounted for pleiotropy, the causal estimate (OR) was reduced to 1.18 (CI = 0.98, 1.42) and 1.09 (CI = 0.89, 1.33) in the 2 most precise (smallest CI) models, out of 4 models evaluated. In the 2 sample MR analyses for MI, there was only very weak evidence of a causal effect in only 1 out of 4 models. CONCLUSIONS A small causal effect of fibrinogen on CHD is observed using multi-variant MR approaches which account for pleiotropy, but not single variant MR approaches. Taken together, results indicate that even with large sample sizes and multi-variant approaches MR analyses still cannot exclude the null when estimating the causal effect of fibrinogen on CHD, but that any potential causal effect is likely to be much smaller than observed in epidemiological studies.
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Al-Sofiani ME, Yanek LR, Faraday N, Kral BG, Mathias R, Becker LC, Becker DM, Vaidya D, Kalyani RR. Diabetes and Platelet Response to Low-Dose Aspirin. J Clin Endocrinol Metab 2018; 103:4599-4608. [PMID: 30265320 PMCID: PMC6232753 DOI: 10.1210/jc.2018-01254] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 09/24/2018] [Indexed: 01/16/2023]
Abstract
CONTEXT Previous studies have suggested less cardioprotective benefit of aspirin in adults with diabetes, raising concerns about "aspirin resistance" and potentially reduced effectiveness for prevention of cardiovascular disease (CVD). OBJECTIVE To examine differences in platelet response to aspirin by diabetes status. DESIGN, SETTING, PARTICIPANTS We examined platelet response before and after aspirin (81 mg/day for 14 days) in 2113 adults (175 with diabetes, 1,938 without diabetes), in the Genetic Study of Aspirin Responsiveness cohort, who had family history of early-onset CVD. MAIN OUTCOME MEASURES In vivo platelet activation (urinary thromboxane B2), in vitro platelet aggregation to agonists (arachidonic acid, adenosine diphosphate, collagen), and platelet function analyzer-100 closure time. RESULTS Although adults with diabetes had higher in vivo platelet activation before aspirin, the reduction in in vivo platelet activation after aspirin was similar in those with vs without diabetes. Likewise, the reduction in multiple in vitro platelet measures was similar after aspirin by diabetes status. In regression analyses adjusted for age, sex, race, BMI, smoking, platelet counts, and fibrinogen levels, in vivo platelet activation remained higher in adults with vs without diabetes after aspirin (P = 0.04), but this difference was attenuated after additional adjustment for preaspirin levels (P = 0.10). No differences by diabetes status were noted for any of the in vitro platelet measures after aspirin in fully adjusted models that also accounted for preaspirin levels. CONCLUSIONS In vitro platelet response to aspirin does not differ by diabetes status, suggesting no intrinsic differences in platelet response to aspirin. Instead, factors extrinsic to platelet function should be investigated to give further insights into aspirin use for primary prevention in diabetes.
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Ligthart S, Vaez A, Võsa U, Stathopoulou MG, de Vries PS, Prins BP, Van der Most PJ, Tanaka T, Naderi E, Rose LM, Wu Y, Karlsson R, Barbalic M, Lin H, Pool R, Zhu G, Macé A, Sidore C, Trompet S, Mangino M, Sabater-Lleal M, Kemp JP, Abbasi A, Kacprowski T, Verweij N, Smith AV, Huang T, Marzi C, Feitosa MF, Lohman KK, Kleber ME, Milaneschi Y, Mueller C, Huq M, Vlachopoulou E, Lyytikäinen LP, Oldmeadow C, Deelen J, Perola M, Zhao JH, Feenstra B, Amini M, Lahti J, Schraut KE, Fornage M, Suktitipat B, Chen WM, Li X, Nutile T, Malerba G, Luan J, Bak T, Schork N, Del Greco M F, Thiering E, Mahajan A, Marioni RE, Mihailov E, Eriksson J, Ozel AB, Zhang W, Nethander M, Cheng YC, Aslibekyan S, Ang W, Gandin I, Yengo L, Portas L, Kooperberg C, Hofer E, Rajan KB, Schurmann C, den Hollander W, Ahluwalia TS, Zhao J, Draisma HHM, Ford I, Timpson N, Teumer A, Huang H, Wahl S, Liu Y, Huang J, Uh HW, Geller F, Joshi PK, Yanek LR, Trabetti E, Lehne B, Vozzi D, Verbanck M, Biino G, Saba Y, Meulenbelt I, O'Connell JR, Laakso M, Giulianini F, Magnusson PKE, Ballantyne CM, Hottenga JJ, Montgomery GW, Rivadineira F, Rueedi R, Steri M, Herzig KH, Stott DJ, Menni C, Frånberg M, St Pourcain B, Felix SB, Pers TH, Bakker SJL, Kraft P, Peters A, Vaidya D, Delgado G, Smit JH, Großmann V, Sinisalo J, Seppälä I, Williams SR, Holliday EG, Moed M, Langenberg C, Räikkönen K, Ding J, Campbell H, Sale MM, Chen YDI, James AL, Ruggiero D, Soranzo N, Hartman CA, Smith EN, Berenson GS, Fuchsberger C, Hernandez D, Tiesler CMT, Giedraitis V, Liewald D, Fischer K, Mellström D, Larsson A, Wang Y, Scott WR, Lorentzon M, Beilby J, Ryan KA, Pennell CE, Vuckovic D, Balkau B, Concas MP, Schmidt R, Mendes de Leon CF, Bottinger EP, Kloppenburg M, Paternoster L, Boehnke M, Musk AW, Willemsen G, Evans DM, Madden PAF, Kähönen M, Kutalik Z, Zoledziewska M, Karhunen V, Kritchevsky SB, Sattar N, Lachance G, Clarke R, Harris TB, Raitakari OT, Attia JR, van Heemst D, Kajantie E, Sorice R, Gambaro G, Scott RA, Hicks AA, Ferrucci L, Standl M, Lindgren CM, Starr JM, Karlsson M, Lind L, Li JZ, Chambers JC, Mori TA, de Geus EJCN, Heath AC, Martin NG, Auvinen J, Buckley BM, de Craen AJM, Waldenberger M, Strauch K, Meitinger T, Scott RJ, McEvoy M, Beekman M, Bombieri C, Ridker PM, Mohlke KL, Pedersen NL, Morrison AC, Boomsma DI, Whitfield JB, Strachan DP, Hofman A, Vollenweider P, Cucca F, Jarvelin MR, Jukema JW, Spector TD, Hamsten A, Zeller T, Uitterlinden AG, Nauck M, Gudnason V, Qi L, Grallert H, Borecki IB, Rotter JI, März W, Wild PS, Lokki ML, Boyle M, Salomaa V, Melbye M, Eriksson JG, Wilson JF, Penninx BWJH, Becker DM, Worrall BB, Gibson G, Krauss RM, Ciullo M, Zaza G, Wareham NJ, Oldehinkel AJ, Palmer LJ, Murray SS, Pramstaller PP, Bandinelli S, Heinrich J, Ingelsson E, Deary IJ, Mägi R, Vandenput L, van der Harst P, Desch KC, Kooner JS, Ohlsson C, Hayward C, Lehtimäki T, Shuldiner AR, Arnett DK, Beilin LJ, Robino A, Froguel P, Pirastu M, Jess T, Koenig W, Loos RJF, Evans DA, Schmidt H, Smith GD, Slagboom PE, Eiriksdottir G, Morris AP, Psaty BM, Tracy RP, Nolte IM, Boerwinkle E, Visvikis-Siest S, Reiner AP, Gross M, Bis JC, Franke L, Franco OH, Benjamin EJ, Chasman DI, Dupuis J, Snieder H, Dehghan A, Alizadeh BZ. Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. Am J Hum Genet 2018; 103:691-706. [PMID: 30388399 PMCID: PMC6218410 DOI: 10.1016/j.ajhg.2018.09.009] [Citation(s) in RCA: 253] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 09/20/2018] [Indexed: 02/07/2023] Open
Abstract
C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10-8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.
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Feitosa MF, Kraja AT, Chasman DI, Sung YJ, Winkler TW, Ntalla I, Guo X, Franceschini N, Cheng CY, Sim X, Vojinovic D, Marten J, Musani SK, Li C, Bentley AR, Brown MR, Schwander K, Richard MA, Noordam R, Aschard H, Bartz TM, Bielak LF, Dorajoo R, Fisher V, Hartwig FP, Horimoto ARVR, Lohman KK, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Wojczynski MK, Alver M, Boissel M, Cai Q, Campbell A, Chai JF, Chen X, Divers J, Gao C, Goel A, Hagemeijer Y, Harris SE, He M, Hsu FC, Jackson AU, Kähönen M, Kasturiratne A, Komulainen P, Kühnel B, Laguzzi F, Luan J, Matoba N, Nolte IM, Padmanabhan S, Riaz M, Rueedi R, Robino A, Said MA, Scott RA, Sofer T, Stančáková A, Takeuchi F, Tayo BO, van der Most PJ, Varga TV, Vitart V, Wang Y, Ware EB, Warren HR, Weiss S, Wen W, Yanek LR, Zhang W, Zhao JH, Afaq S, Amin N, Amini M, Arking DE, Aung T, Boerwinkle E, Borecki I, Broeckel U, Brown M, Brumat M, Burke GL, Canouil M, Chakravarti A, Charumathi S, Ida Chen YD, Connell JM, Correa A, de las Fuentes L, de Mutsert R, de Silva HJ, Deng X, Ding J, Duan Q, Eaton CB, Ehret G, Eppinga RN, Evangelou E, Faul JD, Felix SB, Forouhi NG, Forrester T, Franco OH, Friedlander Y, Gandin I, Gao H, Ghanbari M, Gigante B, Gu CC, Gu D, Hagenaars SP, Hallmans G, Harris TB, He J, Heikkinen S, Heng CK, Hirata M, Howard BV, Ikram MA, John U, Katsuya T, Khor CC, Kilpeläinen TO, Koh WP, Krieger JE, Kritchevsky SB, Kubo M, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lewis CE, Li Y, Lin S, Liu J, Liu J, Loh M, Louie T, Mägi R, McKenzie CA, Meitinger T, Metspalu A, Milaneschi Y, Milani L, Mohlke KL, Momozawa Y, Nalls MA, Nelson CP, Sotoodehnia N, Norris JM, O'Connell JR, Palmer ND, Perls T, Pedersen NL, Peters A, Peyser PA, Poulter N, Raffel LJ, Raitakari OT, Roll K, Rose LM, Rosendaal FR, Rotter JI, Schmidt CO, Schreiner PJ, Schupf N, Scott WR, Sever PS, Shi Y, Sidney S, Sims M, Sitlani CM, Smith JA, Snieder H, Starr JM, Strauch K, Stringham HM, Tan NYQ, Tang H, Taylor KD, Teo YY, Tham YC, Turner ST, Uitterlinden AG, Vollenweider P, Waldenberger M, Wang L, Wang YX, Wei WB, Williams C, Yao J, Yu C, Yuan JM, Zhao W, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Deary IJ, Esko T, Farrall M, Franks PW, Freedman BI, Froguel P, Gasparini P, Gieger C, Jonas JB, Kamatani Y, Kato N, Kooner JS, Kutalik Z, Laakso M, Laurie CC, Leander K, Lehtimäki T, Study LC, Magnusson PKE, Oldehinkel AJ, Penninx BWJH, Polasek O, Porteous DJ, Rauramaa R, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wareham NJ, Watkins H, Weir DR, Wickremasinghe AR, Wu T, Zheng W, Bouchard C, Christensen K, Evans MK, Gudnason V, Horta BL, Kardia SLR, Liu Y, Pereira AC, Psaty BM, Ridker PM, van Dam RM, Gauderman WJ, Zhu X, Mook-Kanamori DO, Fornage M, Rotimi CN, Cupples LA, Kelly TN, Fox ER, Hayward C, van Duijn CM, Tai ES, Wong TY, Kooperberg C, Palmas W, Rice K, Morrison AC, Elliott P, Caulfield MJ, Munroe PB, Rao DC, Province MA, Levy D. Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries. PLoS One 2018; 13:e0198166. [PMID: 29912962 PMCID: PMC6005576 DOI: 10.1371/journal.pone.0198166] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 05/15/2018] [Indexed: 01/01/2023] Open
Abstract
Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
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Kral BG, Becker DM, Yanek LR, Vaidya D, Mathias RA, Becker LC, Kalyani RR. The relationship of family history and risk of type 2 diabetes differs by ancestry. DIABETES & METABOLISM 2018; 45:261-267. [PMID: 29875064 DOI: 10.1016/j.diabet.2018.05.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Revised: 05/07/2018] [Accepted: 05/14/2018] [Indexed: 01/15/2023]
Abstract
AIM Type 2 diabetes (T2DM) in a first-degree relative is a risk factor for incident diabetes. Americans of African ancestry (AA) have higher rates of T2DM than Americans of European ancestry (EA). Thus, we aimed to determine whether the presence, number and kinship of affected relatives are associated with race-specific T2DM incidence in a prospective study of participants from the Genetic Study of Atherosclerosis Risk (GeneSTAR), who underwent baseline screening including a detailed family history. METHODS Nondiabetic healthy siblings (n=1405) of patients with early-onset coronary artery disease (18-59 years) were enrolled (861 EA and 544 AA) and followed for incident T2DM (mean 14±6 years). RESULTS Baseline age was 46.2±7.3 years and 56% were female. T2DM occurred in 12.3% of EA and 19.1% of AA. Among EA, 32.6% had ≥1 affected first-degree relatives versus 53.1% in AA, P<0.0001. In fully adjusted Cox proportional hazard analyses, any family history was related to incident T2DM in EA (HR=2.53, 95% CI: 1.58-4.06) but not in AA (HR=1.01, 0.67-1.53). The number of affected relatives conferred incremental risk of T2DM in EA with HR=1.82 (1.08-3.06), 4.83 (2.15-10.85) and 8.46 (3.09-23.91) for 1, 2, and ≥3 affected, respectively. In AA only ≥3 affected increased risk (HR=2.45, 1.44-4.19). Specific kinship patterns were associated with incident T2DM in EA but not in AA. CONCLUSIONS The presence of any first-degree relative with T2DM does not discriminate risk in AA given the high race-specific prevalence of diabetes. Accounting for the number of affected relatives may more appropriately estimate risk for incident diabetes in both races.
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Liang J, Le TH, Velez Edwards DR, Tayo BO, Gaulton KJ, Smith JA, Lu Y, Jensen RA, Chen G, Yanek LR, Schwander K, Tajuddin SM, Sofer T, Kim W, Kayima J, McKenzie CA, Fox E, Nalls MA, Young JH, Sun YV, Lane JM, Cechova S, Zhou J, Tang H, Fornage M, Musani SK, Wang H, Lee J, Adeyemo A, Dreisbach AW, Forrester T, Chu PL, Cappola A, Evans MK, Morrison AC, Martin LW, Wiggins KL, Hui Q, Zhao W, Jackson RD, Ware EB, Faul JD, Reiner AP, Bray M, Denny JC, Mosley TH, Palmas W, Guo X, Papanicolaou GJ, Penman AD, Polak JF, Rice K, Taylor KD, Boerwinkle E, Bottinger EP, Liu K, Risch N, Hunt SC, Kooperberg C, Zonderman AB, Laurie CC, Becker DM, Cai J, Loos RJF, Psaty BM, Weir DR, Kardia SLR, Arnett DK, Won S, Edwards TL, Redline S, Cooper RS, Rao DC, Rotter JI, Rotimi C, Levy D, Chakravarti A, Zhu X, Franceschini N. Correction: Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations. PLoS Genet 2018; 14:e1007345. [PMID: 29750786 PMCID: PMC5947884 DOI: 10.1371/journal.pgen.1007345] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Keramati AR, Yanek LR, Iyer K, Taub MA, Ruczinski I, Becker DM, Becker LC, Faraday N, Mathias RA. Targeted deep sequencing of the PEAR1 locus for platelet aggregation in European and African American families. Platelets 2018; 30:380-386. [PMID: 29553866 DOI: 10.1080/09537104.2018.1447659] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Coronary artery disease (CAD) remains a major cause of mortality and morbidity worldwide. The aggregation of activated platelets on a ruptured atherosclerotic plaque is a critical step in most acute cardiovascular events like myocardial infarction. Platelet aggregation both at baseline and after aspirin is highly heritable. Genome-wide association studies (GWAS) have identified a common variant within the first intron of the platelet endothelial aggregation receptor1 (PEAR1), to be robustly associated with platelet aggregation. In this study, we used targeted deep sequencing to fine-map the prior GWAS peak and identify additional rare variants of PEAR1 that account for missing heritability in platelet aggregation within the GeneSTAR families. In this study, 1709 subjects (1043 European Americans, EA and 666 African Americans, AA) from families in the GeneSTAR study were included. In vitro platelet aggregation in response to collagen, ADP and epinephrine was measured at baseline and 14 days after aspirin therapy (81 mg/day). Targeted deep sequencing of PEAR1 in addition to 2kb of upstream and downstream of the gene was performed. Under an additive genetic model, the association of single variants of PEAR1 with platelet aggregation phenotypes were examined. Additionally, we examined the association between the burden of PEAR1 rare non-synonymous variants and platelet aggregation phenotypes. Of 532 variants identified through sequencing, the intron 1 variant, rs12041331, was significantly associated with all platelet aggregation phenotypes at baseline and after platelet inhibition with aspirin therapy. rs12566888, which is in linkage disequilibrium with rs12041331, was associated with platelet aggregation phenotypes but to a lesser extent. In the EA families, the burden of PEAR1 missense variants was associated with platelet aggregation after aspirin therapy when the platelets were stimulated with epinephrine (p = 0.0009) and collagen (p = 0.03). In AAs, the burden of PEAR1 missense variants was associated, to a lesser degree, with platelet aggregation in response to epinephrine (p = 0.02) and ADP (p = 0.04). Our study confirmed that the GWAS-identified variant, rs12041331, is the strongest variant associated with platelet aggregation both at baseline and after aspirin therapy in our GeneSTAR families in both races. We identified additional association of rare missense variants in PEAR1 with platelet aggregation following aspirin therapy. However, we observed a racial difference in the contribution of these rare variants to the platelet aggregation, most likely due to higher residual missing heritability of platelet aggregation after accounting for rs12041331 in the EAs compared to AAs.
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Sung YJ, Winkler TW, de Las Fuentes L, Bentley AR, Brown MR, Kraja AT, Schwander K, Ntalla I, Guo X, Franceschini N, Lu Y, Cheng CY, Sim X, Vojinovic D, Marten J, Musani SK, Li C, Feitosa MF, Kilpeläinen TO, Richard MA, Noordam R, Aslibekyan S, Aschard H, Bartz TM, Dorajoo R, Liu Y, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Tayo BO, Warren HR, Zhao W, Zhou Y, Matoba N, Sofer T, Alver M, Amini M, Boissel M, Chai JF, Chen X, Divers J, Gandin I, Gao C, Giulianini F, Goel A, Harris SE, Hartwig FP, Horimoto ARVR, Hsu FC, Jackson AU, Kähönen M, Kasturiratne A, Kühnel B, Leander K, Lee WJ, Lin KH, 'an Luan J, McKenzie CA, Meian H, Nelson CP, Rauramaa R, Schupf N, Scott RA, Sheu WHH, Stančáková A, Takeuchi F, van der Most PJ, Varga TV, Wang H, Wang Y, Ware EB, Weiss S, Wen W, Yanek LR, Zhang W, Zhao JH, Afaq S, Alfred T, Amin N, Arking D, Aung T, Barr RG, Bielak LF, Boerwinkle E, Bottinger EP, Braund PS, Brody JA, Broeckel U, Cabrera CP, Cade B, Caizheng Y, Campbell A, Canouil M, Chakravarti A, Chauhan G, Christensen K, Cocca M, Collins FS, Connell JM, de Mutsert R, de Silva HJ, Debette S, Dörr M, Duan Q, Eaton CB, Ehret G, Evangelou E, Faul JD, Fisher VA, Forouhi NG, Franco OH, Friedlander Y, Gao H, Gigante B, Graff M, Gu CC, Gu D, Gupta P, Hagenaars SP, Harris TB, He J, Heikkinen S, Heng CK, Hirata M, Hofman A, Howard BV, Hunt S, Irvin MR, Jia Y, Joehanes R, Justice AE, Katsuya T, Kaufman J, Kerrison ND, Khor CC, Koh WP, Koistinen HA, Komulainen P, Kooperberg C, Krieger JE, Kubo M, Kuusisto J, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lewis CE, Li Y, Lim SH, Lin S, Liu CT, Liu J, Liu J, Liu K, Liu Y, Loh M, Lohman KK, Long J, Louie T, Mägi R, Mahajan A, Meitinger T, Metspalu A, Milani L, Momozawa Y, Morris AP, Mosley TH, Munson P, Murray AD, Nalls MA, Nasri U, Norris JM, North K, Ogunniyi A, Padmanabhan S, Palmas WR, Palmer ND, Pankow JS, Pedersen NL, Peters A, Peyser PA, Polasek O, Raitakari OT, Renström F, Rice TK, Ridker PM, Robino A, Robinson JG, Rose LM, Rudan I, Sabanayagam C, Salako BL, Sandow K, Schmidt CO, Schreiner PJ, Scott WR, Seshadri S, Sever P, Sitlani CM, Smith JA, Snieder H, Starr JM, Strauch K, Tang H, Taylor KD, Teo YY, Tham YC, Uitterlinden AG, Waldenberger M, Wang L, Wang YX, Wei WB, Williams C, Wilson G, Wojczynski MK, Yao J, Yuan JM, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Chen YDI, de Faire U, Deary IJ, Esko T, Farrall M, Forrester T, Franks PW, Freedman BI, Froguel P, Gasparini P, Gieger C, Horta BL, Hung YJ, Jonas JB, Kato N, Kooner JS, Laakso M, Lehtimäki T, Liang KW, Magnusson PKE, Newman AB, Oldehinkel AJ, Pereira AC, Redline S, Rettig R, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wareham NJ, Watkins H, Weir DR, Wickremasinghe AR, Wu T, Zheng W, Kamatani Y, Laurie CC, Bouchard C, Cooper RS, Evans MK, Gudnason V, Kardia SLR, Kritchevsky SB, Levy D, O'Connell JR, Psaty BM, van Dam RM, Sims M, Arnett DK, Mook-Kanamori DO, Kelly TN, Fox ER, Hayward C, Fornage M, Rotimi CN, Province MA, van Duijn CM, Tai ES, Wong TY, Loos RJF, Reiner AP, Rotter JI, Zhu X, Bierut LJ, Gauderman WJ, Caulfield MJ, Elliott P, Rice K, Munroe PB, Morrison AC, Cupples LA, Rao DC, Chasman DI. A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure. Am J Hum Genet 2018; 102:375-400. [PMID: 29455858 PMCID: PMC5985266 DOI: 10.1016/j.ajhg.2018.01.015] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 01/18/2018] [Indexed: 12/18/2022] Open
Abstract
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 × 10-8) 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 × 10-8). 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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Nyquist PA, Yanek LR, Kral BG, Becker LC, Vaidya D, Becker DM. Abstract TMP91: White Matter Lesion Progression and Cognitive Function Over 5-Years in a Young Susceptible Population. Stroke 2018. [DOI: 10.1161/str.49.suppl_1.tmp91] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
Cerebrovascular disease (CVD) and vascular risk factors cluster in families of patients with early-onset coronary artery disease (CAD). In a prior cross-sectional study of 714 healthy middle-aged relatives, we found a high prevalence of early white matter hyperintensity lesions (WMHL) and associated lower cognitive function. Prior WMHL studies have included elderly or demented subjects. Rate of WMHL progression and cognitive decline in quiescent preclinical healthy middle-aged persons remains unknown.
Methods:
We studied WMHL and cognitive function over 5 years in 20 healthy relatives, age 50-59, of patients with CAD <60 years of age (one subject per family). Persons with any physical or neurological abnormality were excluded. At baseline and follow-up, subjects underwent 3-Tesla brain magnetic resonance imaging. WMHL volumes were determined using automated segmented volumes measured from FLAIR and MPRAGE using a previously described automated pipeline. Cognitive function was measured with the: Delayed Recall, Digit Symbol Substitution, Verbal Fluency, Digit Span, and Grooved Pegboard tests.
Results:
Our 20 participants were: 50% male, 45% African American (AA), average age was 54.1 (SD 1.57) years, 45% with HTN, 15% smokers, and 50% obese. WMHL prevalence was 92%. The average change in WMHL volume was 819 mm
3
(P<0.0008); this was significant for men (p=0.006), women (p= 0.062), AAs (p= 0.019), and European Americans (EA) (p= 0.018). Decline occurred in all cognitive function tests (average P across all tests was <0.001) in all races and sexes. Vascular risk factors did not change from baseline to follow-up.
Conclusion:
These striking findings are among the first to demonstrate significant quantitative WMHL volume progression and cognitive decline in a healthy middle-aged population over just 5 years, in AA and EA and both sexes. This small pilot study suggests that early quiescent brain white matter lesion progression and early multidimensional cognitive decline can be detected in healthy susceptible populations using state-of-the-art quantitative volumetric imaging techniques.
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Chen MH, Yanek LR, Backman JD, Eicher JD, Huffman JE, Ben-Shlomo Y, Beswick AD, Yerges-Armstrong LM, Shuldiner AR, O'Connell JR, Mathias RA, Becker DM, Becker LC, Lewis JP, Johnson AD, Faraday N. Exome-chip meta-analysis identifies association between variation in ANKRD26 and platelet aggregation. Platelets 2017; 30:164-173. [PMID: 29185836 DOI: 10.1080/09537104.2017.1384538] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Previous genome-wide association studies (GWAS) have identified several variants associated with platelet function phenotypes; however, the proportion of variance explained by the identified variants is mostly small. Rare coding variants, particularly those with high potential for impact on protein structure/function, may have substantial impact on phenotype but are difficult to detect by GWAS. The main purpose of this study was to identify low frequency or rare variants associated with platelet function using genotype data from the Illumina HumanExome Bead Chip. Three family-based cohorts of European ancestry, including ~4,000 total subjects, comprised the discovery cohort and two independent cohorts, one of European and one of African American ancestry, were used for replication. Optical aggregometry in platelet-rich plasma was performed in all the discovery cohorts in response to adenosine diphosphate (ADP), epinephrine, and collagen. Meta-analyses were performed using both gene-based and single nucleotide variant association methods. The gene-based meta-analysis identified a significant association (P = 7.13 × 10-7) between rare genetic variants in ANKRD26 and ADP-induced platelet aggregation. One of the ANKRD26 SNVs - rs191015656, encoding a threonine to isoleucine substitution predicted to alter protein structure/function, was replicated in Europeans. Aggregation increases of ~20-50% were observed in heterozygotes in all cohorts. Novel genetic signals in ABCG1 and HCP5 were also associated with platelet aggregation to ADP in meta-analyses, although only results for HCP5 could be replicated. The SNV in HCP5 intersects epigenetic signatures in CD41+ megakaryocytes suggesting a new functional role in platelet biology for HCP5. This is the first study to use gene-based association methods from SNV array genotypes to identify rare variants related to platelet function. The molecular mechanisms and pathophysiological relevance for the identified genetic associations requires further study.
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Joshi PK, Pirastu N, Kentistou KA, Fischer K, Hofer E, Schraut KE, Clark DW, Nutile T, Barnes CLK, Timmers PRHJ, Shen X, Gandin I, McDaid AF, Hansen TF, Gordon SD, Giulianini F, Boutin TS, Abdellaoui A, Zhao W, Medina-Gomez C, Bartz TM, Trompet S, Lange LA, Raffield L, van der Spek A, Galesloot TE, Proitsi P, Yanek LR, Bielak LF, Payton A, Murgia F, Concas MP, Biino G, Tajuddin SM, Seppälä I, Amin N, Boerwinkle E, Børglum AD, Campbell A, Demerath EW, Demuth I, Faul JD, Ford I, Gialluisi A, Gögele M, Graff M, Hingorani A, Hottenga JJ, Hougaard DM, Hurme MA, Ikram MA, Jylhä M, Kuh D, Ligthart L, Lill CM, Lindenberger U, Lumley T, Mägi R, Marques-Vidal P, Medland SE, Milani L, Nagy R, Ollier WER, Peyser PA, Pramstaller PP, Ridker PM, Rivadeneira F, Ruggiero D, Saba Y, Schmidt R, Schmidt H, Slagboom PE, Smith BH, Smith JA, Sotoodehnia N, Steinhagen-Thiessen E, van Rooij FJA, Verbeek AL, Vermeulen SH, Vollenweider P, Wang Y, Werge T, Whitfield JB, Zonderman AB, Lehtimäki T, Evans MK, Pirastu M, Fuchsberger C, Bertram L, Pendleton N, Kardia SLR, Ciullo M, Becker DM, Wong A, Psaty BM, van Duijn CM, Wilson JG, Jukema JW, Kiemeney L, Uitterlinden AG, Franceschini N, North KE, Weir DR, Metspalu A, Boomsma DI, Hayward C, Chasman D, Martin NG, Sattar N, Campbell H, Esko T, Kutalik Z, Wilson JF. Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity. Nat Commun 2017; 8:910. [PMID: 29030599 PMCID: PMC5715013 DOI: 10.1038/s41467-017-00934-5] [Citation(s) in RCA: 86] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Accepted: 08/08/2017] [Indexed: 01/03/2023] Open
Abstract
Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents’ survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan. Variability in human longevity is genetically influenced. Using genetic data of parental lifespan, the authors identify associations at HLA-DQA/DRB1 and LPA and find that genetic variants that increase educational attainment have a positive effect on lifespan whereas increasing BMI negatively affects lifespan.
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Nyquist PA, Yanek LR, Kral BG, Becker LC, Vaidya D, Becker DM. White Matter Lesion Progression and Cognitive Function Over 5 Years in a Young Susceptible Population. Neuroepidemiology 2017; 49:62-63. [PMID: 28850949 DOI: 10.1159/000480238] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2017] [Accepted: 08/09/2017] [Indexed: 12/14/2022] Open
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Liang J, Le TH, Edwards DRV, Tayo BO, Gaulton KJ, Smith JA, Lu Y, Jensen RA, Chen G, Yanek LR, Schwander K, Tajuddin SM, Sofer T, Kim W, Kayima J, McKenzie CA, Fox E, Nalls MA, Young JH, Sun YV, Lane JM, Cechova S, Zhou J, Tang H, Fornage M, Musani SK, Wang H, Lee J, Adeyemo A, Dreisbach AW, Forrester T, Chu PL, Cappola A, Evans MK, Morrison AC, Martin LW, Wiggins KL, Hui Q, Zhao W, Jackson RD, Ware EB, Faul JD, Reiner AP, Bray M, Denny JC, Mosley TH, Palmas W, Guo X, Papanicolaou GJ, Penman AD, Polak JF, Rice K, Taylor KD, Boerwinkle E, Bottinger EP, Liu K, Risch N, Hunt SC, Kooperberg C, Zonderman AB, Laurie CC, Becker DM, Cai J, Loos RJF, Psaty BM, Weir DR, Kardia SLR, Arnett DK, Won S, Edwards TL, Redline S, Cooper RS, Rao DC, Rotter JI, Rotimi C, Levy D, Chakravarti A, Zhu X, Franceschini N. Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations. PLoS Genet 2017; 13:e1006728. [PMID: 28498854 PMCID: PMC5446189 DOI: 10.1371/journal.pgen.1006728] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 05/26/2017] [Accepted: 03/30/2017] [Indexed: 02/07/2023] Open
Abstract
Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.
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Ng MCY, Graff M, Lu Y, Justice AE, Mudgal P, Liu CT, Young K, Yanek LR, Feitosa MF, Wojczynski MK, Rand K, Brody JA, Cade BE, Dimitrov L, Duan Q, Guo X, Lange LA, Nalls MA, Okut H, Tajuddin SM, Tayo BO, Vedantam S, Bradfield JP, Chen G, Chen WM, Chesi A, Irvin MR, Padhukasahasram B, Smith JA, Zheng W, Allison MA, Ambrosone CB, Bandera EV, Bartz TM, Berndt SI, Bernstein L, Blot WJ, Bottinger EP, Carpten J, Chanock SJ, Chen YDI, Conti DV, Cooper RS, Fornage M, Freedman BI, Garcia M, Goodman PJ, Hsu YHH, Hu J, Huff CD, Ingles SA, John EM, Kittles R, Klein E, Li J, McKnight B, Nayak U, Nemesure B, Ogunniyi A, Olshan A, Press MF, Rohde R, Rybicki BA, Salako B, Sanderson M, Shao Y, Siscovick DS, Stanford JL, Stevens VL, Stram A, Strom SS, Vaidya D, Witte JS, Yao J, Zhu X, Ziegler RG, Zonderman AB, Adeyemo A, Ambs S, Cushman M, Faul JD, Hakonarson H, Levin AM, Nathanson KL, Ware EB, Weir DR, Zhao W, Zhi D, Arnett DK, Grant SFA, Kardia SLR, Oloapde OI, Rao DC, Rotimi CN, Sale MM, Williams LK, Zemel BS, Becker DM, Borecki IB, Evans MK, Harris TB, Hirschhorn JN, Li Y, Patel SR, Psaty BM, Rotter JI, Wilson JG, Bowden DW, Cupples LA, Haiman CA, Loos RJF, North KE. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium. PLoS Genet 2017; 13:e1006719. [PMID: 28430825 PMCID: PMC5419579 DOI: 10.1371/journal.pgen.1006719] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 05/05/2017] [Accepted: 03/29/2017] [Indexed: 11/20/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10−8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations. Genome-wide association studies (GWAS) have identified >300 genetic regions that influence body size and shape as measured by body mass index (BMI) and waist-to-hip ratio (WHR), respectively, but few have been identified in populations of African ancestry. We conducted large scale high coverage GWAS and replication of these traits in 52,895 and 23,095 individuals of African ancestry, respectively, followed by additional replication in European populations. We identified 10 genome-wide significant loci in all individuals, and an additional seven loci by analyzing men and women separately. We combined African and European ancestry GWAS and were able to narrow down 43 out of 74 African ancestry associated genetic regions to contain small number of putative causal variants. Our results highlight the improvement of applying high density genome coverage and combining multiple ancestries in the identification and refinement of location of genetic regions associated with adiposity traits.
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Eicher JD, Chen MH, Pitsillides AN, Lin H, Veeraraghavan N, Brody JA, Metcalf GA, Muzny DM, Gibbs RA, Becker DM, Becker LC, Faraday N, Mathias RA, Yanek LR, Boerwinkle E, Cupples LA, Johnson AD. Whole exome sequencing in the Framingham Heart Study identifies rare variation in HYAL2 that influences platelet aggregation. Thromb Haemost 2017; 117:1083-1092. [PMID: 28300864 DOI: 10.1160/th16-09-0677] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Accepted: 02/12/2017] [Indexed: 12/30/2022]
Abstract
Inhibition of platelet reactivity is a common therapeutic strategy in secondary prevention of cardiovascular disease. Genetic and environmental factors influence inter-individual variation in platelet reactivity. Identifying genes that contribute to platelet reactivity can reveal new biological mechanisms and possible therapeutic targets. Here, we examined rare coding variation to identify genes associated with platelet reactivity in a population-based cohort. To do so, we performed whole exome sequencing in the Framingham Heart Study and conducted single variant and gene-based association tests against platelet reactivity to collagen, adenosine diphosphate (ADP), and epinephrine agonists in up to 1,211 individuals. Single variant tests revealed no significant associations (p<1.44×10-7), though we observed a suggestive association with previously implicated MRVI1 (rs11042902, p = 1.95×10-7). Using gene-based association tests of rare and low-frequency variants, we found significant associations of HYAL2 with increased ADP-induced aggregation (p = 1.07×10-7) and GSTZ1 with increased epinephrine-induced aggregation (p = 1.62×10-6). HYAL2 also showed suggestive associations with epinephrine-induced aggregation (p = 2.64×10-5). The rare variants in the HYAL2 gene-based association included a missense variant (N357S) at a known N-glycosylation site and a nonsense variant (Q406*) that removes a glycophosphatidylinositol (GPI) anchor from the resulting protein. These variants suggest that improper membrane trafficking of HYAL2 influences platelet reactivity. We also observed suggestive associations of AR (p = 7.39×10-6) and MAPRE1 (p = 7.26×10-6) with ADP-induced reactivity. Our study demonstrates that gene-based tests and other grouping strategies of rare variants are powerful approaches to detect associations in population-based analyses of complex traits not detected by single variant tests and possible new genetic influences on platelet reactivity.
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Hannawi Y, Yanek LR, Kral BG, Vaidya D, Becker LC, Becker DM, Nyquist PA. Abstract TMP93: Hypertension is Associated with Disruption of White Matter Tracts in Healthy Middle-aged Persons at Risk for Vascular Disease. Stroke 2017. [DOI: 10.1161/str.48.suppl_1.tmp93] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Fractional anisotropy (FA) measured by Diffusion Tensor Imaging (DTI) is a sensitive biomarker of white matter (WM) integrity and offers a means to detect early axonal disruption and attendant cognitive impairment secondary to vascular disease.
Hypothesis:
We hypothesized that hypertension (HTN), of all known risk factors, is most closely linked to early WM tract injury in apparently healthy high risk relatives of patients with early-onset coronary artery disease (CAD).
Methods:
DTI was acquired on a Phillips 3T MRI scanner (slice thickness 2.2 mm, field of view 212X212 mm and b-value 700 mm
2
/s) for relatives of CAD patients. The brain was segmented into 181 regions using the Eve Atlas, Large Deformation Diffeomorphic Metric Mapping paradigm, and 48 regions representing the deep WM were selected for analysis. Mean regional FA (rFA) was assessed using t-tests in persons with and without smoking, HTN, diabetes. Continuous variable association with rFA was tested using Spearman correlations. Covariate-adjusted GEE linear regression (corrected for nonindependence of families) was performed for regions meeting the Bonferroni threshold of 0.001 (0.05/48).
Results:
116 subjects had DTI data (mean age 49.5±11, 57% males, 40.5% African Americans, 23% smokers, 36% hypertensives, 12% diabetics). rFA was not significantly associated with diabetes or current smoking. Moreover, rFA was not significantly correlated with glucose level, LDL, total cholesterol or body mass index. However, patients with HTN showed a significantly lower rFA compared to normotensives in the left (L) genu of corpus callosum, L external capsule, right (R) cingulum, L fornix/ stria terminalis, L and R column and body of fornix, and R sagittal stratum. After adjusting for age, sex and race, this relation remained significant in the R sagittal stratum (P=0.012) and R cingulum (P=0.001). Systolic blood pressure (SBP) correlated with rFA after adjustment in the L superior longitudinal fasciculus as well (unadjusted rho=-0.309, p=0.00073, adjusted beta =-1.08+-0.47, P=0.02).
Conclusions:
Of all of the risk factors, as hypothesized, HTN and SBP were significantly associated with early WM tract injury in areas related to cognition in middle-aged persons at risk for vascular disease.
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