Medicine
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Item Implementation of a goal-directed Care Bundle for intracerebral hemorrhage: Results of embedded process evaluation in the INTERACT3 trial(Public Library of Science, 2024-12) Ouyang, M.; Anjum, A.; Cawley, F. G. M.; Wasay, M.; Ma, L.; Hu , X.; Chen, X.; Malavera, A.; Li, X.; Venturelli, P. M.; De Silva, H. A.; Thang, N. H.; Wahab, W. K.; Pandian, J. D.; Pontes-Neto, O. M.; Abanto , C.; Nigenda, V. C.; Arauz , A.; You , C.; Jan, S.; Song, L.; Anderson, C. S.; Liu, H.; INTERACT3 InvestigatorsThe third, stepped-wedge, cluster-randomized, Intensive Care Bundle with Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial (INTERACT3), has shown that a goal-directed multi-faceted Care Bundle incorporating protocols for the management of physiological variables was safe and effective for improving functional recovery in a broad range of patients with acute intracerebral hemorrhage (ICH). The INTERACT3 Care Bundle included time- and target-based protocols for the management of early intensive lowering of systolic blood pressure (SBP, target <140mmHg), glucose control (target 6.1-7.8 mmol/L in those without diabetes and 7.8-10.0 mmol/L in those with diabetes), anti-pyrexia treatment (target body temperature ≤37.5°C), and the rapid reversal of warfarin-related anticoagulation (target international normalized ratio <1.5). An embedded process evaluation was conducted to allow a better understanding of how the Care Bundle was implemented in different countries to enhance the transferability of this evidence in the international context. This study used a mixed-methods approach involving interviews, focus group discussions, and surveys to evaluate the implementation outcomes included fidelity, dose, reach, acceptability, appropriateness, adoption, and sustainability. Interviews (n = 27), focus group discussions (n = 3), and quantitative surveys (n = 48) were conducted in 7 low- and middle-income countries (LMICs) and 1 high-income country during 2019-2022. The Care Bundle was generally delivered as planned and well accepted by stakeholders, although some difficulties were reported in reaching the SBP and glycemic targets. Contextual factors including staff shortage, limited availability of antihypertensive drugs, and delayed systems of care processes, were common barriers to implementing the Care Bundle. Facilitating factors included good communication and collaboration with staff in emergency departments, the development of pathways within available resources, and regular training and monitoring. Our process evaluation provides useful insights into the contextual barriers which need to be addressed for effective scale up of the Care Bundle implementation in a global context.Item 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.Item The third intensive care bundle with blood pressure reduction in acute cerebral haemorrhage trial (INTERACT3): an international, stepped wedge cluster randomised controlled trial(Elsevier, 2023) Ma, L.; Hu, X.; Song, L.; Chen, X.; Ouyang, M.; Billot, L.; Li, Q.; Malavera, A.; Li, X.; Muñoz-Venturelli, P.; de Silva, A.; Thang, N.H.; Wahab, K.W.; Pandian, J.D.; Wasay, M.; Pontes-Neto, O.M.; Abanto, C.; Arauz, A.; Shi, H.; Tang, G.; Zhu, S.; She, X.; Liu, L.; Sakamoto, Y.; You, S.; Han, Q.; Crutzen, B.; Cheung, E.; Li, Y.; Wang, X.; Chen, C.; Liu, F.; Zhao, Y.; Li, H.; Liu, Y.; Jiang, Y.; Chen, L.; Wu, B.; Liu, M.; Xu, J.; You, C.; Anderson, C.S.; INTERACT3 InvestigatorsBACKGROUND: Early control of elevated blood pressure is the most promising treatment for acute intracerebral haemorrhage. We aimed to establish whether implementing a goal-directed care bundle incorporating protocols for early intensive blood pressure lowering and management algorithms for hyperglycaemia, pyrexia, and abnormal anticoagulation, implemented in a hospital setting, could improve outcomes for patients with acute spontaneous intracerebral haemorrhage. METHODS: We performed a pragmatic, international, multicentre, blinded endpoint, stepped wedge cluster randomised controlled trial at hospitals in nine low-income and middle-income countries (Brazil, China, India, Mexico, Nigeria, Pakistan, Peru, Sri Lanka, and Viet Nam) and one high-income country (Chile). Hospitals were eligible if they had no or inconsistent relevant, disease-specific protocols, and were willing to implement the care bundle to consecutive patients (aged ≥18 years) with imaging-confirmed spontaneous intracerebral haemorrhage presenting within 6 h of the onset of symptoms, had a local champion, and could provide the required study data. Hospitals were centrally randomly allocated using permuted blocks to three sequences of implementation, stratified by country and the projected number of patients to be recruited over the 12 months of the study period. These sequences had four periods that dictated the order in which the hospitals were to switch from the control usual care procedure to the intervention implementation of the care bundle procedure to different clusters of patients in a stepped manner. To avoid contamination, details of the intervention, sequence, and allocation periods were concealed from sites until they had completed the usual care control periods. The care bundle protocol included the early intensive lowering of systolic blood pressure (target <140 mm Hg), strict glucose control (target 6·1-7·8 mmol/L in those without diabetes and 7·8-10·0 mmol/L in those with diabetes), antipyrexia treatment (target body temperature ≤37·5°C), and rapid reversal of warfarin-related anticoagulation (target international normalised ratio <1·5) within 1 h of treatment, in patients where these variables were abnormal. Analyses were performed according to a modified intention-to-treat population with available outcome data (ie, excluding sites that withdrew during the study). The primary outcome was functional recovery, measured with the modified Rankin scale (mRS; range 0 [no symptoms] to 6 [death]) at 6 months by masked research staff, analysed using proportional ordinal logistic regression to assess the distribution in scores on the mRS, with adjustments for cluster (hospital site), group assignment of cluster per period, and time (6-month periods from Dec 12, 2017). This trial is registered at Clinicaltrials.gov (NCT03209258) and the Chinese Clinical Trial Registry (ChiCTR-IOC-17011787) and is completed. FINDINGS: Between May 27, 2017, and July 8, 2021, 206 hospitals were assessed for eligibility, of which 144 hospitals in ten countries agreed to join and were randomly assigned in the trial, but 22 hospitals withdrew before starting to enrol patients and another hospital was withdrawn and their data on enrolled patients was deleted because regulatory approval was not obtained. Between Dec 12, 2017, and Dec 31, 2021, 10 857 patients were screened but 3821 were excluded. Overall, the modified intention-to-treat population included 7036 patients enrolled at 121 hospitals, with 3221 assigned to the care bundle group and 3815 to the usual care group, with primary outcome data available in 2892 patients in the care bundle group and 3363 patients in the usual care group. The likelihood of a poor functional outcome was lower in the care bundle group (common odds ratio 0·86; 95% CI 0·76-0·97; p=0·015). The favourable shift in mRS scores in the care bundle group was generally consistent across a range of sensitivity analyses that included additional adjustments for country and patient variables (0·84; 0·73-0·97; p=0·017), and with different approaches to the use of multiple imputations for missing data. Patients in the care bundle group had fewer serious adverse events than those in the usual care group (16·0% vs 20·1%; p=0·0098). INTERPRETATION: Implementation of a care bundle protocol for intensive blood pressure lowering and other management algorithms for physiological control within several hours of the onset of symptoms resulted in improved functional outcome for patients with acute intracerebral haemorrhage. Hospitals should incorporate this approach into clinical practice as part of active management for this serious condition. FUNDING: Joint Global Health Trials scheme from the Department of Health and Social Care, the Foreign, Commonwealth & Development Office, and the Medical Research Council and Wellcome Trust; West China Hospital; the National Health and Medical Research Council of Australia; Sichuan Credit Pharmaceutic and Takeda China.Item INTEnsive care bundle with blood pressure reduction in acute cerebral hemorrhage trial (INTERACT3): study protocol for a pragmatic stepped-wedge cluster-randomized controlled trial(BioMed Central, London, 2021) Song, L.; Hu, X.; Ma, L.; Chen, X.; Ouyang, M.; Billot, L.; Li, Q.; Muñoz-Venturelli, P.; Abanto, C.; Pontes-Neto, O.M.; Antonio, A.; Wasay, M.; de Silva, A.; Thang, N.H.; Pandian, J.D.; Wahab, K.W.; You, C.; Anderson, C.S.Background: Early intensive blood pressure (BP) lowering remains the most promising treatment for acute intracerebral hemorrhage (ICH), despite discordant results between clinical trials and potential variation in the treatment effects by approach to control BP. As the third in a series of clinical trials on this topic, the INTEnsive care bundle with blood pressure Reduction in Acute Cerebral hemorrhage Trial (INTERACT3) aims to determine the effectiveness of a goal-directed care bundle protocol of early physiological control (intensive BP lowering, glycemic control, and pyrexia treatment) and reversal of anticoagulation, in acute ICH. Methods: INTERACT3 is a pragmatic, international, multicenter, stepped-wedge (4 phases/3 steps), cluster-randomized controlled trial to determine the effectiveness of a multifaceted care package in adult (age ≥ 18 years) patients (target 8360) with acute ICH (< 6 h of onset) recruited from 110 hospitals (average of 19 consecutive patients per phase) in low- and middle-income countries. After a control phase, each hospital implements the intervention (intensive BP lowering, target systolic < 140 mmHg; glucose control, target 6.1-7.8 mmol/L and 7.8-10.0 mmol/L in those without and with diabetes mellitus, respectively; anti-pyrexia treatment to target body temperature ≤ 37.5 °C; and reversal of anticoagulation, target international normalized ratio < 1.5 within 1 h). Information will be obtained on demographic and baseline clinical characteristics, in-hospital management, and 7-day outcomes. Central trained blinded assessors will conduct telephone interviews to assess physical function and health-related quality of life at 6 months. The primary outcome is the modified Rankin scale (mRS) at 6 months analyzed using ordinal logistic regression. The sample size of 8360 subjects provides 90% power (α = 0.05) to detect a 5.6% absolute improvement (shift) in the primary outcome of the intervention versus control standard care, with various assumptions. Discussion: As the largest clinical trial in acute ICH, INTERACT3 is on schedule to provide an assessment of the effectiveness of a widely applicable goal-directed care bundle for a serious condition in which a clearly proven treatment has yet to be established.Item 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.Item 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.Item 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.Item Multi-ancestry genome-wide association study of lipid levels incorporating gene-alcohol interactions.(School of Hygiene and Public Health of Johns Hopkins University,Baltimore., 2019) de Vries, P. S.; Brown, M. R.; Bentley, A. R.; Sung, Y. J.; Winkler, T. W.; Ntalla, I.; Schwander, K.; Kraja, A. T.; Guo, X.; Franceschini, N.; Cheng, C. Y.; Sim, X.; Vojinovic, D.; Huffman, J. E.; Musani, S. K.; Li, C.; Feitosa, M.F.; Richard, M.A.; Noordam, R.; Aschard, H.; Bartz, T. M.; Bielak, L. F.; Deng, X.; Dorajoo, R.; Lohman, K.K.; Manning, A. K.; Rankinen, T.; Smith, A. V.; Tajuddin, S. M.; Evangelou, E.; Graff, M.; Alver, M.; Boissel, M.; Chai, J. F.; Chen, X.; Divers, J.; Gandin, I.; Gao, C.; Goel, A.; Hagemeijer, Y.; Harris, S. E.; Hartwig, F. P.; He, M.; Horimoto, A. R. V. R.; Hsu, F. C.; Jackson, A. U.; Kasturiratne, A.; Komulainen, P.; Kühnel, B.; Laguzzi, F.; Lee, J. H.; Luan, J.; Lyytikäinen, L. P.; Matoba, N.; Nolte, I. M.; Pietzner, M.; Riaz, M.; Said, M. A.; Scott, R. A.; Sofer, T.; Stancáková, A.; Takeuchi, F.; Tayo, B. O.; van der Most, P. J.; Varga, T. V.; Wang, Y.; Ware, E. B.; Wen, W.; Yanek, L. R.; Zhang, W.; Zhao, J. H.; Afaq, S.; Amin, N.; Amini, M.; Arking, D. E.; Aung, T.; Ballantyne, C.; Boerwinkle, E.; Broeckel, U.; Campbell, A.; Canouil, M.; Charumathi, S.; Chen, Y. I.; Connell, J. M.; de Faire, U.; de Las Fuentes, L.; de Mutsert, R.; de Silva, H.J.; Ding, J.; Dominiczak, A. F.; Duan, Q.; Eaton, C. B.; Eppinga, R.N.; Faul, J. D.; Fisher, V.; Forrester, T.; Franco, O. H.; Friedlander, Y.; Ghanbari, M.; Giulianini, F.; Grabe, H. J.; Grove, M. L.; Gu, C. C.; Harris, T. B.; Heikkinen, S.; Heng, C. K.; Hirata, M.; Hixson, J. E.; Howard, B. V.; Ikram, M. A.; InterAct Consortium; Jr. Jacobs, D. R.; Johnson, C.; Jonas, J. B.; Kammerer, C. M.; Katsuya, T.; Khor, C. C.; Kilpeläinen, T. O.; Koh, W. P.; Koistinen, H. A.; 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.; Lemaitre, R. N.; Li, Y.; Liang, J.; Liu, J.; Liu, K.; Loh, M.; Louie, T.; Mägi, R.; Manichaikul, A. W.; McKenzie, C. A.; Meitinger, T.; Metspalu, A.; Milaneschi, Y.; Milani, L.; Mohlke, K. L.; Jr. Mosley, T. H.; Nelson, C. P.; Mukamal, K. J.; Nalls, M. A.; Nauck, M.; Sotoodehnia, N.; O'Connell, J. R.; Palmer, N. D.; Pazoki, R.; Pedersen, N. L.; Peters, A.; Peyser, P. A.; Polasek, O.; Poulter, N.; Raffel, L. J.; Raitakari, O. T.; Reiner, A. P.; Rice, T. K.; Rich, S. S.; Robino, A.; Robinson, J. G.; Rose, L. M.; Rudan, I.; Schmidt, C. O.; Schreiner, P. J.; Scott, W. R.; Sever, P.; Shi, Y.; Sidney, S.; Sims, M.; Smith, B. H.; Smith, J. A.; Snieder, H.; Starr, J. M.; Strauch, K.; Tan, N.; Taylor, K. D.; Teo, Y. Y.; Tham, Y. C.; Uitterlinden, A. G.; van Heemst, D.; Vuckovic, D.; Waldenberger, M.; Wang, L.; Wang, Y.; Wang, Z.; Wei, W. B.; Williams, C.; Sr Wilson, G.; Wojczynski, M. K.; Yao, J.; Yu, B.; Yu, C.; Yuan, J. M.; Zhao, W.; Zonderman, A. B.; Becker, D. M.; Boehnke, M.; Bowden, D. W.; Chambers, J. C.; Deary, I. J.; Esko, T.; Farrall, M.; Franks, P. W.; Freedman, B. I.; Froguel, P.; Gasparini, P.; Gieger, C.; Horta, B. L.; Kamatani, Y.; Kato, N.; Kooner, J. S.; Laakso, M.; Leander, K.; Lehtimäki, T.; Lifelines Cohort, Groningen,; The Netherlands (Lifelines Cohort Study); Magnusson, P. K. E.; Penninx, B.; Pereira, A. C.; Rauramaa, R.; Samani, N.J.; Scott, J.; Shu, X. O.; van der Harst, P.; Wagenknecht, L. E.; Wang, Y. X.; Wareham, N. J.; Watkins, H.; Weir, D. R.; Wickremasinghe, A.R.; Zheng, W.; Elliott, P.; North, K. E.; Bouchard, C.; Evans, M. K.; Gudnason, V.; Liu, C. T.; Liu, Y.; Psaty, B. M.; Ridker, P. M.; van Dam, R. M.; Kardia, S. L. R.; Zhu, X.; Rotimi, C. N.; Mook-Kanamori, D. O.; Fornage, M.; Kelly, T. N.; Fox, E. R.; Hayward, C.; van Duijn, C. M.; Tai, E. S.; Wong, T. Y.; Liu, J.; Rotter, J. I.; Gauderman, W. J.; Province, M. A.; Munroe, P. B.; Rice, K.; Chasman, D. I.; Cupples, L. A.; Rao, D. C.; Morrison, A. C.An individual'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 multi-ancestry 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 five ancestry groups. Genetic main and interaction effects were jointly assessed by 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 Stage 1 and Stage 2, 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 (PCSK5, VEGFB, and A1CF) with a putative role in lipid metabolism based on existing evidence from cellular and experimental models.Item Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries(Public Library of Science, 2018) Feitosa, M.F.; Kraja, A.T.; Chasman, D.I.; Sung, Y.J.; Winkler, T.W.; Ntalla, I.; Guo, X.; Franceschini, N.; Cheng, C.Y.; Sim, X.; Vojinovic, D.; Marten, J.; Musani, S.K.; Li, C.; Bentley, A.R.; Brown, M.R.; Scwander, K.; Richard, M.A.; Noordam, R.; Aschard, H.; Bartz, T.M.; Bielak, L.F.; Dorajoo, R.; Fishaer, V.; Hartwig, F.P.; Horimoto, A.R.V.R.; Lohman, K.K.; Manning, A.K.; Rankinen, T.; Smith, A.V.; Tajiddin, S.M.; Wojczynski, M.K.; Alver, M.; Boissel, M.; Cai, Q.; Campbell, A.; Chai, J.F.; Chen, X.; Divers, J.; Gao, C.; Goel, A.; Hagemeijer, Y.; Harris, S.E.; He, M.; Hsu, F.C.; Jackson, A.U.; Kahonen, M.; Kasturiratne, A.; Komulainen, P.; Kuhnel, B.; Laguzzi, F.; Luan, J.; Matoba, N.; Nolte, I.M.; Padmanabhan, S.; Riaz, M.; Rueedi, R.; Robino, A.; Said, M.A.; Scott, R.A.; Soffer, T.; Stancakova, A.; Takeuchi, F.; Tayo, B.O.; van de Most, P.J.; Varga, T.V.; Vitart, V.; Wang, Y.; Ware, E.B.; Warren, H.R.; Weiss, S.; Wen, W.; Yanek, L.R.; Zhang, W.; Zhao, J.H.; Afaq, S.; Amin, N.; Amini, M.; Arking, D.E.; Aung, T.; Boerwinkle, E.; Borecki, I.; Broecki, I.; Broeckel, U.; Brown, M.; Brumat, M.; Burke, G.L.; Canouil, M.; Chakravarthi, A.; Charumathi, S.; Ida Chen, Y.D.; Connel, J.M.; Correa, A.; de Las Fuentes, L.; de Mutsert, R.; de Silva, H.J.; Deng, X.; Ding, J.; Duan, Q.; Eaton, C.B.; Ehret, G.; Eppinga, R.N.; Evangelou, E.; Faul, J.D.; Felix, S.B.; Forouhi, N.G.; Forrester, T.; Franco, O.H.; Friedlander, Y.; Gandin, I.; Gao, H.; Ghanbari, M.; Gigante, B.; Gu, C.C.; Gu, D.; Hagenaars, S.P.; Halmans, G.; Harris, T.B.; He, J.; Heikkinen, S.; Heng, C.K.; Hirata, M.; Howard, B.V.; Ikram, M.A.; InterAct Consortium; John, U.; Katsuya, T.; Lakka, T.A.; Langefeld, C.D.; Langenberg, C.; Launer, L.J.; Lehne, B.; Lewis, C.E.; Li, Y.; Lin, S.; Lin, U.; Liu, J.; Liu, J.; Loh, M.; Louie, T.; Magi, R.; McKenzie, C.A.; Meitinger, T.; Metspalu, A.; Milaneschi, Y.; Milani, L.; mohlke, K.L.; Momozawa, Y.; Nalls, M.A.; Nelson, C.P.; Sotoodehnia, N.; Norris, J.M.; O'Connel, J.R.; Palmer, N.D.; Perls, T.; Pedersen, N.L.; Peters, A.; Peyser, P.A.; Poulter, N.; Raffel, L.J.; Raitakari, O.T.; Roll, K.; Rose, L.M.; Rosendaal, F.R.; Rotter, J.I.; Schimidit, C.O.; Schreiner, P.J.; Schupf, N.; Scott, W.R.; Sever, P.S.; Shi, Y.; Sidney, S.; Sims, M.; Sitlani, C.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.; Turner, S.C.; Uitterlinden, A.G.; Vollenweider, P.; Waldenberger, M.; Wang, L.; Wang, Y.X.; Wei, W.B.; Williams, C.; Yao, J.; Yuan, J.M.; Zhao, W.; Zonderman, A.B.; Becker, D.M.; Boehnke, M.; Bowden, D.W.; Chambers, J.C.; Deary, I.J.; Esco, T.; Farall, M.; Frankd, P.W.; Freedman, B.I.; Froguel, P.; Gasparini, P.; Gieger, C.; Jonas, J.B.; Kamatani, Y.; Kato, N.; Kooner, J.S.; Kutalik, Z.; Laakso, M.; Laurie, C.C.; Leander, K.; Lehtimaki, T.; Study, L.C.; Magnusson, P.K.E.; Olderhinkel, A.J.; Penninx, B.W.J.H.; Polasek, O.; Porteous, D.J.; Rauramaa, R.; Ssamani, N.J.; Scott, J.; Shu, X.O.; van der Harst, P.; Wagenknecht, L.E.; Wareham, N.J.; Watkins, H.; Weir, D.R.; Wickremasinghe, A.R.; Wu, T.; Zheng, W.; Bouchard, C.; Christensen, K.; Evans, M.K.; Gudnason, V.; Horta, B.L.; Kardia, S.L.R.; Liu, Y.; Pereira, A.C.; Psaty, B.M.; Ridker, P.M.; van Dam, R.M.; Gauderman, W.J.; Zhu, X.; Mook-Kanamori, D.O.; Fornage, M.; Rotimi, C.N.; Cupples, L.A.; Kelly, T.N.; Fox, E.R.; Hayward, C.; van Duijn, C.M.; Tai, E.S.; Wong, T.Y.; Kooperberg, C.; Palmas, W.; Rice, K.; Morrison, A.C.; Elliott, P.; Caulfield, M.J.; Munroe, P.B.; Rao, D.C.; Province, M.A.; Levy, D.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