Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries

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.

Nicholette D. Palmer | Christine A. Williams | P. Elliott | M. Fornage | M. Nalls | C. Gieger | M. Waldenberger | O. Franco | A. Uitterlinden | D. Levy | A. Peters | I. Deary | I. Ntalla | R. Mägi | T. Lehtimäki | E. Boerwinkle | C. Rotimi | M. Laakso | Z. Kutalik | K. Strauch | M. Boehnke | Hua Tang | Y. Kamatani | P. Ridker | D. Chasman | N. Samani | Morris J. Brown | J. Connell | P. Munroe | M. Caulfield | M. Farrall | Y. Teo | V. Gudnason | C. Bouchard | U. John | I. Borecki | Albert Vernon Smith | A. Chakravarti | C. Schmidt | J. Jonas | T. Wong | C. Lewis | A. Zonderman | M. Evans | E. Tai | B. Horta | O. Raitakari | S. Kardia | T. Meitinger | K. Lohman | Yongmei Liu | S. Kritchevsky | B. Psaty | D. Gu | B. Penninx | B. Howard | D. Arking | A. Kraja | M. Province | A. Metspalu | T. Esko | H. Snieder | L. Milani | K. Mohlke | H. Stringham | A. Jackson | K. Taylor | J. Rotter | P. Froguel | F. Hsu | R. Rueedi | C. Sitlani | T. Harris | T. Lakka | R. Rauramaa | J. Norris | Tangchun Wu | X. Shu | Jian-Min Yuan | W. Koh | W. Zheng | N. Sotoodehnia | D. Porteous | J. Starr | S. Sidney | D. Rao | C. Langefeld | D. Becker | L. Bielak | P. Peyser | N. Wareham | Jianjun Liu | T. Sofer | C. Laurie | K. Rice | Xiaofeng Zhu | C. Nelson | P. Magnusson | N. Pedersen | C. V. van Duijn | P. Franks | L. Cupples | M. Wojczynski | M. Kubo | Xiuqing Guo | N. Schupf | Q. Cai | M. Ikram | S. Harris | K. Christensen | C. Heng | H. Watkins | J. Kooner | C. Gu | N. Amin | C. Hayward | O. Polašek | Jennifer A. Smith | V. Vitart | Wei Zhao | J. Faul | M. Kähönen | L. Launer | P. Vollenweider | D. Weir | T. Rankinen | M. Feitosa | Y. Sung | T. Winkler | N. Franceschini | Ching-Yu Cheng | X. Sim | D. Vojinović | J. Marten | S. Musani | Changwei Li | A. Bentley | Michael R. Brown | K. Schwander | Melissa A. Richard | R. Noordam | H. Aschard | T. Bartz | R. Dorajoo | Virginia Fisher | F. Hartwig | A. Horimoto | A. Manning | S. Tajuddin | M. Alver | Mathilde Boissel | A. Campbell | Jin-Fang Chai | Xu Chen | J. Divers | Chuan Gao | A. Goel | Yanick P Hagemeijer | M. He | A. Kasturiratne | P. Komulainen | B. Kühnel | F. Laguzzi | J. Luan | N. Matoba | I. Nolte | S. Padmanabhan | Muhammad B. Riaz | A. Robino | M. A. Said | R. Scott | A. Stančáková | F. Takeuchi | B. Tayo | P. J. van der Most | T. V. Varga | Yajuan Wang | E. Ware | H. Warren | S. Weiss | W. Wen | L. Yanek | Weihua Zhang | Jinghua Zhao | Saima Afaq | M. Amini | T. Aung | U. Broeckel | M. Brumat | G. Burke | M. Canouil | S. Charumathi | Y. Ida Chen | A. Correa | L. de las Fuentes | R. de Mutsert | H. J. de Silva | Xuan Deng | Jingzhong Ding | Q. Duan | C. Eaton | G. Ehret | R. N. Eppinga | E. Evangelou | S. Felix | N. Forouhi | T. Forrester | Y. Friedlander | I. Gandin | He Gao | M. Ghanbari | B. Gigante | S. Hagenaars | G. Hallmans | Jiang He | S. Heikkinen | M. Hirata | T. Katsuya | C. Khor | T. Kilpeläinen | J. Krieger | J. Kuusisto | C. Langenberg | B. Lehne | Yize Li | Shiow J. Lin | Jingmin Liu | M. Loh | T. Louie | C. Mckenzie | Y. Milaneschi | Y. Momozawa | J. O'connell | N. Palmer | T. Perls | N. Poulter | L. Raffel | Kathryn Roll | L. Rose | F. Rosendaal | P. Schreiner | W. Scott | P. Sever | Yuan Shi | M. Sims | N. Tan | Yih-Chung Tham | S. Turner | Lihua Wang | Y. X. Wang | W. Wei | Jie Yao | Caizheng Yu | D. Bowden | J. Chambers | B. Freedman | P. Gasparini | N. Kato | K. Leander | Lifelines Cohort Study | A. Oldehinkel | James G. Scott | P. van der Harst | L. Wagenknecht | A. Wickremasinghe | A. Pereira | R. V. van Dam | W. Gauderman | D. Mook-Kanamori | T. Kelly | E. Fox | C. Kooperberg | W. Palmas | A. Morrison | Traci M Bartz | Peter J. van der Most | Traci M. Bartz | Colleen M. Sitlani | M. Brown | J. Yao | A. Smith | T. Varga | Maris Alver | S. Afaq | M. Boissel | Xiaofeng Zhu | P. van der harst | Michael R. Brown | A. Smith | M. Richard | L. Rose | Weihua Zhang | S. Turner | J. Scott | M. Kähönen | A. Uitterlinden | Wei Zhao | C. McKenzie | D. Rao | A. Goel | M. Kubo | C. V. van Duijn | B. Psaty | Brigitte Kühnel | J. Krieger | R. Scott | T. Wong | C. Nelson | S. Harris | R. Scott | T. Wong | A. Peters | A. R. Wickremasinghe | A. Jackson | K. Taylor | T. Wong | D. Levy | Wei Zhao | A. Correa | A. Campbell | Y. Hagemeijer | Jennifer A. Smith | K. Taylor | A. Peters | Y. Tham | T. Wong | Michael R. Brown | Jeffery R O'connell | D. Vojinovic

[1]  A. Parsian,et al.  Human chromosomes 11p15 and 4p12 and alcohol dependence: possible association with the GABRB1 gene. , 1999, American journal of medical genetics.

[2]  Jennifer H Barrett,et al.  Association studies. , 2002, Methods in molecular biology.

[3]  N. Hooper,et al.  The angiotensin-converting enzyme gene family: genomics and pharmacology. , 2002, Trends in pharmacological sciences.

[4]  Eric Boerwinkle,et al.  A meta-analysis of genome-wide linkage scans for hypertension: the National Heart, Lung and Blood Institute Family Blood Pressure Program. , 2003, American journal of hypertension.

[5]  Daniel W. Jones,et al.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. , 2003, Journal of the American Medical Association (JAMA).

[6]  Daniel W. Jones,et al.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. , 2003, JAMA.

[7]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .

[8]  P. Febbo,et al.  Literature Lab: a method of automated literature interrogation to infer biology from microarray analysis , 2007, BMC Genomics.

[9]  Peter Kraft,et al.  Exploiting Gene-Environment Interaction to Detect Genetic Associations , 2007, Human Heredity.

[10]  Yurii S. Aulchenko,et al.  BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btm108 Genetics and population analysis GenABEL: an R library for genome-wide association analysis , 2022 .

[11]  R. Castellon,et al.  Demystifying the ACE polymorphism: from genetics to biology. , 2007, Current pharmaceutical design.

[12]  Yurii S. Aulchenko,et al.  ProbABEL package for genome-wide association analysis of imputed data , 2010, BMC Bioinformatics.

[13]  S. Cichon,et al.  Genome-wide association study of alcohol dependence. , 2009, Archives of general psychiatry.

[14]  D. Levy,et al.  Association of common variants in NPPA and NPPB with circulating natriuretic peptides and blood pressure , 2009, Nature Genetics.

[15]  H. Becher,et al.  Laryngeal cancer risk associated with smoking and alcohol consumption is modified by genetic polymorphisms in ERCC5, ERCC6 and RAD23B but not by polymorphisms in five other nucleotide excision repair genes , 2009, International journal of cancer.

[16]  Marc W. Kirschner,et al.  Tankyrase inhibition stabilizes axin and antagonizes Wnt signalling , 2009, Nature.

[17]  Julie Bryant,et al.  Protein Networks and Pathway Analysis , 2009, Methods in Molecular Biology.

[18]  Raimund Erbel,et al.  Two New Loci for Body-Weight Regulation Identified in a Joint Analysis of Genome-Wide Association Studies for Early-Onset Extreme Obesity in French and German Study Groups , 2010, PLoS genetics.

[19]  Henrik,et al.  Association analyses of 249,796 individuals reveal eighteen new loci associated with body mass index , 2012 .

[20]  A. Morris,et al.  American Journal of Epidemiology Practice of Epidemiology a Comparison of Sample Size and Power in Case-only Association Studies of Gene-environment Interaction , 2022 .

[21]  Marc A Schuckit,et al.  Genome-wide association study of alcohol dependence implicates a region on chromosome 11. , 2010, Alcoholism, clinical and experimental research.

[22]  Josée Dupuis,et al.  Meta‐analysis of gene‐environment interaction: joint estimation of SNP and SNP × environment regression coefficients , 2011, Genetic epidemiology.

[23]  S. Cichon,et al.  Involvement of the atrial natriuretic peptide transcription factor GATA4 in alcohol dependence, relapse risk and treatment response to acamprosate , 2011, The Pharmacogenomics Journal.

[24]  Timothy J. Durham,et al.  Systematic analysis of chromatin state dynamics in nine human cell types , 2011, Nature.

[25]  L. Fauchier,et al.  A genome-wide association study identifies two loci associated with heart failure due to dilated cardiomyopathy. , 2011, European heart journal.

[26]  Joseph K. Pickrell,et al.  DNaseI sensitivity QTLs are a major determinant of human expression variation , 2011, Nature.

[27]  Dong Hwan Kim,et al.  Association between IL10, IL10RA, and IL10RB SNPs and ischemic stroke with hypertension in Korean population , 2012, Molecular Biology Reports.

[28]  P. Majumder,et al.  Genetic variants of TNFα, IL10, IL1β, CTLA4 and TGFβ1 modulate the indices of alcohol-induced liver injury in East Indian population. , 2012, Gene.

[29]  Eurie L. Hong,et al.  Annotation of functional variation in personal genomes using RegulomeDB , 2012, Genome research.

[30]  A. Martí,et al.  Statistical and Biological Gene-Lifestyle Interactions of MC4R and FTO with Diet and Physical Activity on Obesity: New Effects on Alcohol Consumption , 2012, PloS one.

[31]  Vincent Jaquet,et al.  MALAT-1, a non protein-coding RNA is upregulated in the cerebellum, hippocampus and brain stem of human alcoholics. , 2012, Alcohol.

[32]  Manolis Kellis,et al.  HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants , 2011, Nucleic Acids Res..

[33]  Dan Xie,et al.  Dynamic trans-Acting Factor Colocalization in Human Cells , 2013, Cell.

[34]  M. Peters,et al.  Systematic identification of trans eQTLs as putative drivers of known disease associations , 2013, Nature Genetics.

[35]  Pak Chung Sham,et al.  GWAS3D: detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications , 2013, Nucleic Acids Res..

[36]  H. Deng,et al.  Association of rare PTP4A1-PHF3-EYS variants with alcohol dependence , 2013, Journal of Human Genetics.

[37]  Pedro G. Ferreira,et al.  Transcriptome and genome sequencing uncovers functional variation in humans , 2013, Nature.

[38]  I. Borecki,et al.  A correlated meta-analysis strategy for data mining "OMIC" scans. , 2012, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[39]  Genetic Variants in the Fat Mass- and Obesity-Associated (FTO) Gene are Associated with Alcohol Dependence , 2013, Journal of Molecular Neuroscience.

[40]  M. Miles,et al.  Ethanol Regulation of Serum Glucocorticoid Kinase 1 Expression in DBA2/J Mouse Prefrontal Cortex , 2013, PloS one.

[41]  Tom R. Gaunt,et al.  Loci influencing blood pressure identified using a cardiovascular gene-centric array. , 2013, Human molecular genetics.

[42]  D. Rao,et al.  Gene-alcohol interactions identify several novel blood pressure loci including a promising locus near SLC16A9 , 2013, Front. Genet..

[43]  Juan M. Vaquerizas,et al.  DNA-Binding Specificities of Human Transcription Factors , 2013, Cell.

[44]  V. Hervieu,et al.  Cause-specific telomere factors deregulation in hepatocellular carcinoma , 2013, Journal of experimental & clinical cancer research : CR.

[45]  W. Iacono,et al.  A Genome-Wide Association Study of Behavioral Disinhibition , 2013, Behavior genetics.

[46]  D. Lawlor,et al.  Exploring causal associations between alcohol and coronary heart disease risk factors: findings from a Mendelian randomization study in the Copenhagen General Population Study. , 2013, European heart journal.

[47]  Heping Zhang,et al.  Common PTP4A1-PHF3-EYS variants are specific for alcohol dependence. , 2014, The American journal on addictions.

[48]  M. Rietschel,et al.  Genetic Variation in the Atrial Natriuretic Peptide Transcription Factor GATA4 Modulates Amygdala Responsiveness in Alcohol Dependence , 2014, Biological Psychiatry.

[49]  Margaret A. Broadwater,et al.  Adolescent, but Not Adult, Binge Ethanol Exposure Leads to Persistent Global Reductions of Choline Acetyltransferase Expressing Neurons in Brain , 2014, PloS one.

[50]  Xueli Yang,et al.  A Gene-Based Analysis of Variants in the Serum/Glucocorticoid Regulated Kinase (SGK) Genes with Blood Pressure Responses to Sodium Intake: The GenSalt Study , 2014, PloS one.

[51]  Association of GATA4 sequence variation with alcohol dependence , 2014, Addiction biology.

[52]  Christian Gieger,et al.  Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci. , 2014, American journal of human genetics.

[53]  Peter J. Bickel,et al.  Comparative analysis of regulatory information and circuits across distant species , 2014, Nature.

[54]  Hong-Wen Deng,et al.  ALDH2 is associated to alcohol dependence and is the major genetic determinant of “daily maximum drinks” in a GWAS study of an isolated rural chinese sample , 2014, American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics.

[55]  Zoltán Kutalik,et al.  Quality control and conduct of genome-wide association meta-analyses , 2014, Nature Protocols.

[56]  L A Farrer,et al.  Genome-wide association study of alcohol dependence:significant findings in African- and European-Americans including novel risk loci , 2014, Molecular Psychiatry.

[57]  Eric Boerwinkle,et al.  Pleiotropic genes for metabolic syndrome and inflammation. , 2014, Molecular genetics and metabolism.

[58]  I. Klein,et al.  Thyroid disease and the cardiovascular system. , 2014, Endocrinology and metabolism clinics of North America.

[59]  Oscar Harari,et al.  Genome-wide survival analysis of age at onset of alcohol dependence in extended high-risk COGA families. , 2014, Drug and alcohol dependence.

[60]  Richard Leslie,et al.  GRASP: analysis of genotype-phenotype results from 1390 genome-wide association studies and corresponding open access database , 2014, Bioinform..

[61]  Dmitry Pushkarev,et al.  Whole-genome haplotyping using long reads and statistical methods , 2014, Nature Biotechnology.

[62]  J. Antunes-Rodrigues,et al.  Angiotensin type 1 receptor mediates chronic ethanol consumption-induced hypertension and vascular oxidative stress. , 2015, Vascular pharmacology.

[63]  Dengyong Zhang,et al.  Down-regulated FSTL5 promotes cell proliferation and survival by affecting Wnt/β-catenin signaling in hepatocellular carcinoma. , 2015, International journal of clinical and experimental pathology.

[64]  Ross M. Fraser,et al.  Genetic studies of body mass index yield new insights for obesity biology , 2015, Nature.

[65]  Manolis Kellis,et al.  FTO Obesity Variant Circuitry and Adipocyte Browning in Humans. , 2015, The New England journal of medicine.

[66]  Kaanan P. Shah,et al.  A gene-based association method for mapping traits using reference transcriptome data , 2015, Nature Genetics.

[67]  L. Lan,et al.  Transcription-coupled homologous recombination after oxidative damage. , 2016, DNA repair.

[68]  Ashutosh Kumar Singh,et al.  Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015 , 2016, Lancet.

[69]  B. Maisch,et al.  Alcoholic cardiomyopathy , 2016, Herz.

[70]  Fabian L. Wauthier,et al.  Multiple novel gene-by-environment interactions modify the effect of FTO variants on body mass index , 2016, Nature Communications.

[71]  S. Yusuf,et al.  Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case-control study , 2016, The Lancet.

[72]  C. Xie,et al.  Polymorphisms in PDLIM 5 gene are associated with alcohol dependence , type 2 diabetes , and hypertension , 2016 .

[73]  Mark D. Huffman,et al.  Heart Disease and Stroke Statistics—2016 Update: A Report From the American Heart Association , 2016, Circulation.

[74]  V. de Laurenzi,et al.  The prosurvival protein BAG3: a new participant in vascular homeostasis , 2016, Cell Death and Disease.

[75]  He Zhang,et al.  Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension , 2016, Nature Genetics.

[76]  Claude Bouchard,et al.  Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci , 2016, Nature Genetics.

[77]  Claude Bouchard,et al.  An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene‐Lifestyle Interactions Working Group , 2016, Genetic epidemiology.

[78]  Xiaofeng Zhu,et al.  The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals , 2016, Nature Genetics.

[79]  Jian-Si Li,et al.  Multiple Mechanisms are Involved in Salt-Sensitive Hypertension-Induced Renal Injury and Interstitial Fibrosis , 2017, Scientific Reports.

[80]  N. Risch,et al.  Genome-wide association analyses using electronic health records identify new loci influencing blood pressure variation , 2016, Nature Genetics.

[81]  He Gao,et al.  Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk , 2017, Nature Genetics.

[82]  C. Jodice,et al.  Alcohol use disorder and GABAB receptor gene polymorphisms in an Italian sample: haplotype frequencies, linkage disequilibrium and association studies , 2017, Annals of human biology.

[83]  Xiaofeng Zhu,et al.  Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations , 2017, PLoS genetics.

[84]  C. Xie,et al.  Polymorphisms in PDLIM5 gene are associated with alcohol dependence, type 2 diabetes, and hypertension. , 2017, Journal of psychiatric research.

[85]  Yue Zhou,et al.  Fibulin-4 reduces extracellular matrix production and suppresses chondrocyte differentiation via DKK1- mediated canonical Wnt/β-catenin signaling. , 2017, International journal of biological macromolecules.

[86]  Chi-Hua Chen,et al.  Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders , 2016, Nature Genetics.

[87]  Daniel W. Jones,et al.  Potential U.S. Population Impact of the 2017 American College of Cardiology/American Heart Association High Blood Pressure Guideline , 2017 .

[88]  P. Munroe,et al.  Multiancestry Study of Gene–Lifestyle Interactions for Cardiovascular Traits in 610 475 Individuals From 124 Cohorts: Design and Rationale , 2017, Circulation. Cardiovascular genetics.

[89]  Daniel W. Jones,et al.  Potential US Population Impact of the 2017 ACC/AHA High Blood Pressure Guideline , 2018, Circulation.

[90]  Kyle J. Gaulton,et al.  Correction: Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations , 2018, PLoS Genetics.