Browsing by Author "Kilpeläinen, T.O."

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Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci
(Stockton Press., 2021) de Las Fuentes, L.; Sung, Y. J.; Noordam, R.; Winkler, T.; Feitosa, M.F.; Schwander, K.; Bentley, A.R.; Brown, M.R.; Guo, X.; Manning, A.; Chasman, D.I.; Aschard, H.; Bartz, T. M.; Bielak, L.F.; Campbell, A.; Cheng, C.Y.; Dorajoo, R.; Hartwig, F. P.; Horimoto, A.R.V.R.; Li, C.; Li-Gao, R.; Liu, Y.; Marten, J.; Musani, S.K.; Ntalla, I.; Rankinen, T.; Richard, M.; Sim, X.; Smith, A.V.; Tajuddin, S.M.; Tayo, B.O.; Vojinovic, D.; Warren, H.R.; Xuan, D.; Alver, M.; Boissel, M.; Chai, J.F.; Chen, X.; Christensen, K.; Divers, J.; Evangelou, E.; Gao, C.; Girotto, G.; Harris, S.E.; He, M.; Hsu, F.C.; Kühnel, B.; Laguzzi, F.; Li, X.; Lyytikäinen, L. P.; Nolte, I. M.; Poveda, A.; Rauramaa, R.; Riaz, M.; Rueedi, R.; Shu, X.O.; Snieder, H.; Sofer, T.; Takeuchi, F.; Verweij, N.; Ware, E.B.; Weiss, S.; Yanek, L.R.; Amin, N.; Arking, D.E.; Arnett, D.K.; Bergmann, S.; Boerwinkle, E.; Brody, J.A.; Broeckel, U.; Brumat, M.; Burke, G.; Cabrera, C.P.; Canouil, M.; Chee, M.L.; Chen, Y. I.; Cocca, M.; Connell, J.; de Silva, H.J.; de Vries, P. S.; Eiriksdottir, G.; Faul, J.D.; Fisher, V.; Forrester, T.; Fox, E.F.; Friedlander, Y.; Gao, H.; Gigante, B.; Giulianini, F.; Gu, C.C.; Gu, D.; Harris, T. B.; He, J.; Heikkinen, S.; Heng, C. K.; Hunt, S.; Ikram, M. A.; Irvin, M.R.; Kähönen, M.; Kavousi, M.; Khor, C.C.; Kilpeläinen, T.O.; Koh, W.P.; Komulainen, P.; Kraja, A.T.; Krieger, J.E.; Langefeld, C. D.; Li, Y.; Liang, J.; Liewald, D.C.M.; Liu, C.T.; Liu, J.; Lohman, K.K.; Mägi, R.; McKenzie, C.A.; Meitinger, T.; Metspalu, A.; Milaneschi, Y.; Milani, L.; Mook-Kanamori, D.O.; Nalls, M.A.; Nelson, C.P.; Norris, J. M.; O'Connell, J.; Ogunniyi, A.; Padmanabhan, S.; Palmer, N.D.; Pedersen, N. L.; Perls, T.; Peters, A.; Petersmann, A.; Peyser, P. A.; Polasek, O.; Porteous, D. J.; Raffel, L. J.; Rice, T. K.; Rotter, J.I.; Rudan, I.; Rueda-Ochoa, O.L.; Sabanayagam, C.; Salako, B. L.; Schreiner, P.J.; Shikany, J.M.; Sidney, S.S.; Sims, M.; Sitlani, C.M.; Smith, J. A.; Starr, J. M.; Strauch, K.; Swertz, M. A.; Teumer, A.; Tham, Y. C.; Uitterlinden, A.G.; Vaidya, D.; van der Ende, M.Y.; Waldenberger, M.; Wang, L.; Wang, Y. X.; Wei, W.B.; Weir, D.R.; Wen, W.; Yao, J.; Yu, B.; Yu, C.; Yuan, J. M.; Zhao, W.; Zonderman, A.B.; Becker, D.M.; Bowden, D.W.; Deary, I. J.; Dörr, M.; Esko, T.; Freedman, B. I.; Froguel, P.; Gasparini, P.; Gieger, C.; Jonas, J.B.; Kammerer, C.M.; Kato, N.; Lakka, T. A.; Leander, K.; Lehtimäki, T.; Lifelines Cohort Study; Magnusson, P. K. E.; Marques-Vidal, P.; Penninx, B. W. J. H.; Samani, N. J.; van der Harst, P.; Wagenknecht, L. E.; Wu, T.; Zheng, W.; Zhu, X.; Bouchard, C.; Cooper, R. S.; Correa, A.; Evans, M. K.; Gudnason, V.; Hayward, C.; Horta, B. L.; Kelly, T. N.; Kritchevsky, S. B.; Levy, D.; Palmas, W. R.; Pereira, A. C.; Province, M. M.; Psaty, B. M.; Ridker, P. M.; Rotimi, C. N.; Tai, E. S.; van Dam, R. M.; van Duijn, C. M.; Wong, T. Y.; Rice, K.; Gauderman, W. J.; Morrison, A. C.; North, K. E.; Kardia, S. L. R.; Caulfield, M. J.; Elliott, P.; Munroe, P. B.; Franks, P. W.; Rao, D. C.; Fornage, M.
ABSTRACT:Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10-8). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci
(Frontiers Research Foundation, 2023) de Las, F.L.; Schwande, K.L.; Brown, M.R.; Bentley, A.R.; Winkler, T.W.; Sung, Y.J.; Munroe, P.B.; Miller, C.L.; Aschard, H.; Aslibekyan, S.; Bartz, T.M.; Bielak, L.F.; Chai, J.F.; Cheng, C.Y.; Dorajoo, R.; Feitosa, M.F.; Guo, X.; Hartwig, F.P.; Horimoto, A.; Kolčić, I.; Lim, E.; Liu, Y.; Manning, A.K.; Marten, J.; Musani, S.K.; Noordam, R.; Padmanabhan, S.; Rankinen, T.; Richard, M.A.; Ridker, P.M.; Smith, A.V.; Vojinovic, D.; Zonderman, A.B.; Alver, M.; Boissel, M.; Christensen, K.; Freedman, B.I.; Gao, C.; Giulianini, F.; Harris, S.E.; He, M.; Hsu, F.C.; Kühnel, B.; Laguzzi, F.; Li, X.; Lyytikäinen, L.P.; Nolte, I.M.; Poveda, A.; Rauramaa, R.; Riaz, M.; Robino, A.; Sofer, T.; Takeuchi, F.; Tayo, B.O.; van der, M.P.J.; Verweij, N.; Ware, E.B.; Weiss, S.; Wen, W.; Yanek, L.R.; Zhan, Y.; Amin, N.; Arking, D.E.; Ballantyne, C.; Boerwinkle, E.; Brody, J.A.; Broeckel, U.; Campbell, A.; Canouil, M.; Chai, X.; Chen, Y.I.; Chen, X.; Chitrala, K.N.; Concas, M.P.; de Faire, U.; de Mutsert, R.; de Silva, H.J.; de Vries, P.S.; Do, A.; Faul, J.D.; Fisher, V.; Floyd, J.S.; Forrester, T.; Friedlander, Y.; Girotto, G.; Gu, C.C.; Hallmans, G.; Heikkinen, S.; Heng, C.K.; Homuth, G.; Hunt, S.; Ikram, M.A.; Jacobs, D.R.J.R.; Kavousi, M.; Khor, C.C.; Kilpeläinen, T.O.; Koh, W.P.; Komulainen, P.; Langefeld, C.D.; Liang, J.; Liu, K.; Liu, J.; Lohman, K.; Mägi, R.; Manichaikul, A.W.; McKenzie, C.A.; Meitinger, T.; Milaneschi, Y.; Nauck, M.; Nelson, C.P.; O'Connell, J.R.; Palmer, N.D.; Pereira, A.C.; Perls, T.; Peters, A.; Polašek, O.; Raitakari, O.T.; Rice, K.; Rice, T.K.; Rich, S.S.; Sabanayagam, C.; Schreiner, P.J.; Shu, X.; Sidney, S.; Sims, M.; Smith, J.A.; Starr, J.M.; Strauch, K.; Tai, E.S.; Taylor, K.D.; Tsai, M.Y.; Uitterlinden, A.G.; Heemst, D.V.; Waldenberger, M.; Wang, Y.; Wei, W.; Wilson, G.; Xuan, D.; Yao, J.; Yu, C.; Yuan, J.; Zhao, W.; Becker, D.M.; Bonnefond, A.; Bowden, D.W.; Cooper, R.S.; Deary, I.J.; Divers, J.; Esko, T.; Franks, P.W.; Froguel, P.; Gieger, C.; Jonas, J.B.; Kato, N.; Lakka, T.A.; Leander, K.; Lehtimäki, T.; Magnusson, P.K.E.; North, K.E.; Ntalla, I.; Penninx, B.; Samani, N.J.; Snieder, H.; Spedicati, B.; Harst, P.V.D.; Völzke, H.; Wagenknecht, L.E.; Weir, D.R.; Wojczynski, M.K.; Wu, T.; Zheng, W.; Zhu, X.; Bouchard, C.; Chasman, D.I.; Evans, M.K.; Fox, E.R.; Gudnason, V.; Hayward, C.; Horta, B.L.; Kardia, S.L.R.; Krieger, J.E.; Mook-Kanamori, D.O.; Peyser, P.A.; Province, M.M.; Psaty, B.M.; Rudan, I.; Sim, X.; Smith, B.H.; Dam, R.M.V.; Duijn, C.M.V.; Wong, T.Y.; Arnett, D.K.; Rao, D.C.; Gauderman, J.; Liu, C.; Morrison, A.C.; Rotter, J.I.; Fornage, M.
INTRODUCTION: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. METHODS: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: "Some College" (yes/no, for any education beyond high school) and "Graduated College" (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10-8) and suggestive (p < 1 × 10-6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals). RESULTS: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue. DISCUSSION: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.
Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids.
(Nature Publishing Group, 2019) Bentley, A.R.; Chasman, D. I.; Schwander, K.; Ntalla, I.; Kraja, A.T.; Winkler, T.W.; Brown, M. R.; Sung, Y. J.; Lim, E.; Huffman, J.E.; Vojinovic, D.; Sim, X.; Cheng, C.Y.; Lu, Y.; Liu, J.; Guo, X.; Deng, X.; Musani, S.K.; Li, C.; Feitosa, M.F.; Richard, M.A.; Noordam, R.; Baker, J.; Chen, G.; Aschard, H.; Bartz, T.M.; Ding, J.; Dorajoo, R.; Manning, A.K.; Rankinen, T.; Smith, A. V.; Tajuddin, S.M.; Zhao, W.; Graff, M.; Alver, M.; Boissel, M.; Chai, J. F.; Chen, X.; Divers, J.; Evangelou, E.; Gao, C.; Goel, A.; Hagemeijer, Y.; Harris, S. E.; Hartwig, F. P.; He, M.; Horimoto, A.R.V. R.; Hsu, F.C.; Hung, Y. J.; Jackson, A. U.; Kasturiratne, A.; Komulainen, P.; Kühnel, B.; Leander, K.; Lin, K. H.; Luan, J.; Lyytikäinen, L.P.; Matoba, N.; Nolte, I. M.; Pietzner, M.; Prins, B.; Riaz, M.; Robino, A.; Said, M. A.; Schupf, N.; Scott, R. A.; Sofer, T.; Stancáková, A.; Takeuchi, F.; Tayo, B. O.; van der Most, P. J.; Varga, T. V.; Wang, T. D.; Wang, Y.; Ware, E. B.; Wen, W.; Xiang, Y. B.; Yanek, L. R.; Zhang, W.; Zhao, J. H.; Adeyemo, A.; Afaq, S.; Amin, N.; Amini, M.; Arking, D.E.; Arzumanyan, Z.; Aung, T.; Ballantyne, C.; Barr, R. G.; Bielak, L. F.; Boerwinkle, E.; Bottinger, E.P.; Broeckel, U.; Chen, Y. I.; Charumathi, S.; Canouil, M.; Campbell, A.; Cade, B. E.; Brown, M.; Christensen, K.; de Las Fuentes, L.; Connell, J. M.; Concas, M. P.; COGENT-Kidney Consortium; de Silva, H.J.; de Vries, P. S.; Doumatey, A.; Duan, Q.; Eaton, C. B.; Eppinga, R.N.; Faul, J. D.; Floyd, J.S.; Gigante, B.; Gharib, S. A.; Forouhi, N.G.; Ghanbari, M.; Gao, H.; Gandin, I.; Friedlander, Y.; Forrester, T.; Hixson, J. E.; Hirata, M.; Justice, A. E.; Jonas, J. B.; Johnson, C.; Joehanes, R.; Jia, Y.; EPIC-InterAct Consortium; Ikram, M.A.; Katsuya, T.; Khor, C.C.; Kilpeläinen, T.O.; Koh, W. P.; Kolcic, I.; Kooperberg, C.; Krieger, J.E.; Kritchevsky, S.B.; Kubo, M.; Kuusisto, J.; Lakka, T. A.; Langefeld, C.D.; Langenberg, C.; Launer, L. J.; Lehne, B.; Lewis, C. E.; Li, Y.; Liang, J.; Lin, S.; Liu, C.T.; Liu, J.; Liu, K.; Loh, M.; Lohman, K.K.; Louie, T.; Luzzi, A.; Mägi, R.; Mahajan, A.; Manichaikul, A.W.; McKenzie, C.A.; Meitinger, T.; Metspalu, A.; Milaneschi, Y.; Milani, L.; Mohlke, K. L.; Momozawa, Y.; Morris, A. P.; Murray, A. D.; Nalls, M. A.; Nauck, M.; Nelson, C. P.; North, K. E.; O'Connell, J.R.; Palmer, N.D.; Papanicolau, G.J.; Pedersen, N. L.; Peters, A.; Peyser, P. A.; Polasek, O.; Poulter, N.; Raitakari, O.T.; Reiner, A. P.; Renström, F.; Rice, T.K.; Rich, S.S.; Robinson, J.G.; Rose, L. M.; Rosendaal, F. R.; Rudan, I.; Schmidt, C.O.; Schreiner, P. J.; Scott, W.R.; Sever, P.; Shi, Y.; Sidney, S.; Sims, M.; Smith, J. A.; Snieder, H.; Starr, J. M.; Strauch, K.; Stringham, H. M.; Tan, N. Y. Q.; Tang, H.; Taylor, K. D.; Teo, Y. Y.; Tham, Y. C.; Tiemeier, H.; Turner, S. T.; Uitterlinden, A. G.; Understanding Society Scientific Group; van Heemst, D.; Waldenberger, M.; Wang, H.; Wang, L.; Wang, L.; Wei, W. B.; Williams, C. A.; Wilson, G. Sr.; Wojczynski, M. K.; Yao, J.; Young, K.; Yu, C.; Yuan, J. M.; Zhou, J.; Zonderman, A. B.; Becker, D. M.; Boehnke, M.; Bowden, D. W.; Chambers, J. C.; Cooper, R. S.; de Faire, U.; Deary, I. J.; Elliott, P.; Esko, T.; Farrall, M.; Franks, P. W.; Freedman, B. I.; Froguel, P.; Gasparini, P.; Gieger, C.; Horta, B. L.; Juang, J. J.; Kamatani, Y.; Kammerer, C. M.; Kato, N.; Kooner, J. S.; Laakso, M.; Laurie, C. C.; Lee, I. T.; Lehtimäki, T.; Lifelines Cohort; Magnusson, P. K. E.; Oldehinkel, A. J.; Penninx, B. W. J. H.; Pereira, A. C.; Rauramaa, R.; Redline, S.; Samani, N. J.; Scott, J.; Shu, X. O.; van der Harst, P.; Wagenknecht, L. E.; Wang, J. S.; Wang, Y. X.; Wareham, N. J.; Watkins, H.; Weir, D. R.; Wickremasinghe, A.R.; Wu, T.; Zeggini, E.; Zheng, W.; Bouchard, C.; Evans, M. K.; Gudnason, V.; Kardia, S. L. R.; Liu, Y.; Psaty, B. M.; Ridker, P. M.; van Dam, R. M.; Mook-Kanamori, D. O.; Fornage, M.; Province, M. A.; Kelly, T. N.; Fox, E. R.; Hayward, C.; van Duijn, C. M.; Tai, E. S.; Wong, T. Y.; Loos, R. J. F.; Franceschini, N.; Rotter, J. I.; Zhu, X.; Bierut, L. J.; Gauderman, W. J.; Rice, K.; Munroe, P. B.; Morrison, A. C.; Rao, D. C.; Cupples, L. A.; Rotimi, C. N.
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.
A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure
(IRL Press at Oxford University Press., 2019) Sung, Y.J.; de Las Fuentes, L.; Winkler, T.W.; Chasman, D.I.; Bentley, A.R.; Kraja, A.T.; Ntalla, I.; Warren, H.R.; Guo, X.; Schwander, K.; Manning, A.K.; Brown, M.R.; Aschard, H.; Feitosa, M.F.; Franceschini, N.; Lu, Y.; Cheng, C.Y.; Sim, X.; Vojinovic, D.; Marten, J.; Musani, S.K.; Kilpeläinen, T.O.; Richard, M.A.; Aslibekyan, S.; Bartz, T.M.; Dorajoo, R.; Li, C.; Liu, Y.; Rankinen, T.; Smith, A.V.; Tajuddin, S.M.; Tayo, B.O.; Zhao, W.; Zhou, Y.; Matoba, N.; Sofer, T.; Alver, M.; Amini, M.; Boissel, M.; Chai, J.F.; Chen, X.; Divers, J.; Gandin, I.; Gao, C.; Giulianini, F.; Goel, A.; Harris, S.E.; Hartwig, F.P.; He, M.; Horimoto, A.R.V.R.; Hsu, F.C.; Jackson, A.U.; Kammerer, C.M.; Kasturiratne, A.; Komulainen, P.; Kühnel, B.; Leander, K.; Lee, W.J.; Lin, K.H.; Luan, J.; Lyytikäinen, L.P.; McKenzie, C.A.; Nelson, C.P.; Noordam, R.; Scott, R.A.; Sheu, W.H.H.; Stančáková, A.; Takeuchi, F.; van der Most, P.J.; Varga, T.V.; Waken, R.J.; Wang, H.; Wang, Y.; Ware, E.B.; Weiss, S.; Wen, W.; Yanek, L.R.; Zhang, W.; Zhao, J.H.; Afaq, S.; Alfred, T.; Amin, N.; Arking, D.E.; Aung, T.; Barr, R.G.; Bielak, L.F.; Boerwinkle, E.; Bottinger, E.P.; Braund, P.S.; Brody, J.A.; Broeckel, U.; Cade, B.; Campbell, A.; Canouil, M.; Chakravarti, A.; Cocca, M.; Collins, F.S.; Connell, J.M.; de Mutsert, R.; de Silva, H.J.; Dörr, M.; Duan, Q.; Eaton, C.B.; Ehret, G.; Evangelou, E.; Faul, J.D.; Forouhi, N.G.; Franco, O.H.; Friedlander, Y.; Gao, H.; Gigante, B.; Gu, C.C.; Gupta, P.; Hagenaars, S.P.; Harris, T.B.; He, J.; Heikkinen, S.; Heng, C.K.; Hofman, A.; Howard, B.V.; Hunt, S.C.; Irvin, M.R.; Jia, Y.; Katsuya, T.; Kaufman, J.; Kerrison, N.D.; Khor, C.C.; Koh, W.P.; Koistinen, H.A.; Kooperberg, C.B.; Krieger, J.E.; Kubo, M.; Kutalik, Z.; Kuusisto, J.; Lakka, T.A.; Langefeld, C.D.; Langenberg, C.; Launer, L.J.; Lee, J.H.; Lehne, B.; Levy, D.; Lewis, C.E.; Li, Y.; Lifelines Cohort Study; Lim, S.H.; Liu, C.T.; Liu, J.; Liu, J.; Liu, Y.; Loh, M.; Lohman, K.K.; Louie, T.; Mägi, R.; Matsuda, K.; Meitinger, T.; Metspalu, A.; Milani, L.; Momozawa, Y.; Mosley, T.H. Jr; Nalls, M.A.; Nasri, U.; O'Connell, J.R.; Ogunniyi, A.; Palmas, W.R.; Palmer, N.D.; Pankow, J.S.; Pedersen, N.L.; Peters, A.; Peyser, P.A.; Polasek, O.; Porteous, D.; Raitakari, O.T.; Renström, F.; Rice, T.K.; Ridker, P.M.; Robino, A.; Robinson, J.G.; Rose, L.M.; Rudan, I.; Sabanayagam, C.; Salako, B.L.; Sandow, K.; Schmidt, C.O.; Schreiner, P.J.; Scott, W.R.; Sever, P.; Sims, M.; Sitlani, C.M.; Smith, B.H.; Smith, J.A.; Snieder, H.; Starr, J.M.; Strauch, K.; Tang, H.; Taylor, K.D.; Teo, Y.Y.; Tham, Y.C.; Uitterlinden, A.G.; Waldenberger, M.; Wang, L.; Wang, Y.X.; Wei, W.B.; Wilson, G.; Wojczynski, M.K.; Xiang, Y.B.; Yao, J.; Yuan, J.M.; Zonderman, A.B.; Becker, D.M.; Boehnke, M.; Bowden, D.W.; Chambers, J.C.; Chen, Y.I.; Weir, D.R.; de Faire, U.; Deary, I.J.; Esko, T.; Farrall, M.; Forrester, T.; Freedman, B.I.; Froguel, P.; Gasparini, P.; Gieger, C.; Horta, B.L.; Hung, Y.J.; Jonas, J.B.; Kato, N.; Kooner, J.S.; Laakso, M.; Lehtimäki, T.; Liang, K.W.; Magnusson, P.K.E.; VOldehinkel, A.J.; Pereira, A.C.; Perls, T.; Rauramaa, R.; Redline, S.; Rettig, R.; Samani, N.J.; Scott, J.; Shu, X.O.; van der Harst, P.; Wagenknecht, L.E.; Wareham, N.J.; Watkins, H.; Wickremasinghe, A.R.; Wu, T.; Kamatani, Y.; Laurie, C.C.; Bouchard, C.; Cooper, R.S.; Evans, M.K.; Gudnason, V.; Hixson, J.; Kardia, S.L.R.; Kritchevsky, S.B.; Psaty, B.M.; van Dam, R.M.; Arnett, D.K.; Mook-Kanamori, D.O.; Fornage, M.; Fox, E.R.; Hayward, C.; van Duijn, C.M.; Tai, E.S.; Wong, T.Y.; Loos, R.J.F.; Reiner, A.P.; Rotimi, C.N.; Bierut, L.J.; Zhu, X.; Cupples, L.A.; Province, M.A.; Rotter, J.I.; Franks, P.W.; Rice, K.; Elliott, P.; Caulfield, M.J.; Gauderman, W.J.; Munroe, P.B.; Rao, D.C.; Morrison, A.C.
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.
Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.
(Nature Publications, 2019) Kilpeläinen, T.O.; Bentley, A.R.; Noordam, R.; Sung, Y. J.; Schwander, K.; Winkler, T. W.; Jakupović, H.; Chasman, D. I.; Manning, A.; Ntalla, I.; Aschard, H.; Brown, M. R.; de Las Fuentes, L.; Franceschini, N.; Guo, X.; Vojinovic, D.; Aslibekyan, S.; Feitosa, M. F.; Kho, M.; Musani, S. K.; Richard, M.; Wang, H.; Wang, Z.; Bartz, T. M.; Bielak, L. F.; Campbell, A.; Dorajoo, R.; Fisher, V.; Hartwig, F. P.; Horimoto, A. R. V. R.; Li, C.; Lohman, K. K.; Marten, J.; Sim, X.; Smith, A. V.; Tajuddin, S. M.; Alver, M.; Amini, M.; Boissel, M.; Chai, J. F.; Chen, X.; Divers, J.; Evangelou, E.; Gao, C.; Graff, M.; Harris, S. E.; He, M.; Hsu, F. C.; Jackson, A. U.; Zhao, J. H.; Kraja, A. T.; Kühnel, B.; Laguzzi, F.; Lyytikäinen, L. P.; Nolte, I. M.; Rauramaa, R.; Riaz, M.; Robino, A.; Rueedi, R.; Stringham, H. M.; Takeuchi, F.; van der Most, P. J.; Varga, T. V.; Verweij, N.; Ware, E. B.; Wen, W.; Li, X.; Yanek, L. R.; Amin, N.; Arnett, D. K.; Boerwinkle, E.; Brumat, M.; Cade, B.; Canouil, M.; Chen, Y. I.; Concas, M. P.; Connell, J.; de Mutsert, R.; de Silva, H.J.; de Vries, P.S.; Demirkan, A.; Ding, J.; Eaton, C. B.; Faul, J. D.; Friedlander, Y.; Gabriel, K. P.; Ghanbari, M.; Giulianini, F.; Gu, C. C.; Gu, D.; Harris, T. B.; He J, J.; Heikkinen, S.; Heng, C. K.; Hunt, S. C.; Ikram, M. A.; Jonas, J. B.; Koh, W. P.; Komulainen, P.; Krieger, J. E.; Kritchevsky, S. B.; Kutalik, Z.; Kuusisto, J.; Langefeld, C. D.; Langenberg, C.; Launer, L. J.; Leander, K.; Lemaitre, R. N.; Lewis, C. E.; Liang, J.; Lifelines Cohort Study; Liu, J.; Mägi, R.; Manichaikul, A.; Meitinger, T.; Metspalu, A.; Milaneschi, Y.; Mohlke, K. L.; Mosley, T. H.; Murray, A. D.; Nalls, M. A.; Nang, E. K.; Nelson, C. P.; Nona, S.; Norris, J. M.; Nwuba, C. V.; O'Connell, J.; Palmer, N. D.; Papanicolau, G. J.; Pazoki, R.; Pedersen, N. L.; Peters, A.; Peyser, P. A.; Polasek, O.; Porteous, D. J.; Poveda, A.; Raitakari, O. T.; Rich, S. S.; Risch, N.; Robinson, J. G.; Rose, L. M.; Rudan, I.; Schreiner, P. J.; Scott, R. A.; Sidney, S. S.; Sims, M.; Smith, J. A.; Snieder, H.; Sofer, T.; Starr, J. M.; Sternfeld, B.; Strauch, K.; Tang, H.; Taylor, K. D.; Tsai, M. Y.; Tuomilehto, J.; Uitterlinden, A. G.; van der Ende, M. Y.; van Heemst, D.; Voortman, T.; Waldenberger, M.; Wennberg, P.; Wilson, G.; Xiang, Y. B.; Yao, J.; Yu, C.; Yuan, J. M.; Zhao, W.; Zonderman, A. B.; Becker, D. M.; Boehnke, M.; Bowden, D. W.; de Faire, U.; Deary, I. J.; Elliott, P.; Esko, T.; Freedman, B. I.; Froguel, P.; Gasparini, P.; Gieger, C.; Kato, N.; Laakso, M.; Lakka, T. A.; Lehtimäki, T.; Magnusson, P. K. E.; Oldehinkel, A. J.; Penninx, B. W. J. H.; Samani, N. J.; Shu, X. O.; van der Harst, P.; Van Vliet-Ostaptchouk, J. V.; Vollenweider, P.; Wagenknecht, L. E.; Wang, Y. X.; Wareham, N. J.; Weir, D. R.; Wu, T.; Zheng, W.; Zhu, X.; Evans, M. K.; Franks, P. W.; Gudnason, V.; Hayward, C.; Horta, B. L.; Kelly, T. N.; Liu, Y.; North, K. E.; Pereira, A. C.; Ridker, P. M.; Tai, E. S.; van Dam, R. M.; Fox, E. R.; Kardia, S. L. R.; Liu, C. T.; Province, M. A.; Mook-Kanamori, D. O.; Redline, S.; van Duijn, C. M.; Rotter, J. I.; Kooperberg, C. B.; Gauderman, W. J.; Psaty, B. M.; Rice, K.; Munroe, P. B.; Fornage, M.; Cupples, L. A.; Rotimi, C. N.; Morrison, A. C.; Rao, D. C.; Loos, R. J. F.
Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.