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Gene-based association study reveals a distinct female genetic signal in primary hypertension

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Abstract

Hypertension is a polygenic disease that affects over 1.2 billion adults aged 30–79 worldwide. It is a major risk factor for renal, cerebrovascular, and cardiovascular diseases. The heritability of hypertension is estimated to be high; nevertheless, our understanding of its underlying mechanisms remains scarce and incomplete. This study covered the entries from European ancestry from the UK-Biobank (UKB), with 74,090 cases diagnosed with essential (primary) hypertension and 200,734 controls. We compared the findings from large-scale genome-wide association studies (GWAS) to the gene-based method of proteome-wide association studies (PWAS). We focused on 70 statistically significant associated genes, most of which failed to reach significance in variant-based GWAS. A total of 30% of the PWAS-associated genes were validated against independent cohorts, including the Finnish Biobank. Furthermore, gene-based analyses that were performed on both sexes revealed sex-dependent genetics with a stronger genetic component associated with females. Analysis of systolic and diastolic blood pressure measurements confirms a strong genetic effect associated with females. We demonstrated that gene-based approaches provide insight into the underlying biology of hypertension. Specifically, the expression profiles of the identified genes exposed the enrichment of endothelial cells from multiple organs. Furthermore, females' top-ranked significant genes are involved in cellular immunity. We conclude that studying hypertension and blood pressure via gene-based association methods improves interpretability and exposes sex-dependent genetic effects, which enhances clinical utility.

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Data and code availability

The UK-Biobank (UKB) application ID 26664 (Linial lab). PWAS is available through command-line interface as part of an open-source project (MIT license) at Brandes N. pwas. Github. 2020. https://github.com/nadavbra/pwas. Accessed 11 April 2020.

Abbreviations

BP:

Blood pressure

GWAS:

Genome-wide association study/studies

OR:

Odds ratio

OT:

Open targets

RAS:

Renin–angiotensin system

PWAS:

Proteome-wide association study/studies

SNP:

Single-nucleotide polymorphism

UKB:

UK-Biobank

References

  • Arteche-Lopez A, Alvarez-Mora MI, Sanchez Calvin MT, Lezana Rosales JM, Palma Milla C, Gomez Rodriguez MJ, Gomez Manjon I, Blazquez A, Juarez Rufian A, Ramos Gomez P, Sierra Tomillo O, Hidalgo Mayoral I, Perez de la Fuente R, Posada Rodriguez IJ, Gonzalez Granado LI, Martin MA, Quesada-Espinosa JF, Moreno-Garcia M (2021) Biallelic variants in genes previously associated with dominant inheritance: CACNA1A, RET and SLC20A2. Eur J Hum Genet 29:1520–1526. https://doi.org/10.1038/s41431-021-00919-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bohnen MS, Roman-Campos D, Terrenoire C, Jnani J, Sampson KJ, Chung WK, Kass RS (2017) The impact of heterozygous KCNK3 mutations associated with pulmonary arterial hypertension on channel function and pharmacological recovery. J Am Heart Assoc. https://doi.org/10.1161/JAHA.117.006465

    Article  PubMed  PubMed Central  Google Scholar 

  • Brandes N, Linial N, Linial M (2019) Quantifying gene selection in cancer through protein functional alteration bias. Nucl Acids Res 47:6642–6655. https://doi.org/10.1093/nar/gkz546

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Brandes N, Linial N, Linial M (2020) PWAS: proteome-wide association study-linking genes and phenotypes by functional variation in proteins. Genome Biol 21:173. https://doi.org/10.1186/s13059-020-02089-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Brandes N, Linial N, Linial M (2021) Genetic association studies of alterations in protein function expose recessive effects on cancer predisposition. Sci Rep 11:14901. https://doi.org/10.1038/s41598-021-94252-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Brandes N, Weissbrod O, Linial M (2022) Open problems in human trait genetics. Genome Biol 23:1–32

    Article  Google Scholar 

  • Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, Motyer A, Vukcevic D, Delaneau O, O’Connell J, Cortes A, Welsh S, Young A, Effingham M, McVean G, Leslie S, Allen N, Donnelly P, Marchini J (2018) The UK Biobank resource with deep phenotyping and genomic data. Nature 562:203–209. https://doi.org/10.1038/s41586-018-0579-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Carvalho-Silva D, Pierleoni A, Pignatelli M, Ong C, Fumis L, Karamanis N, Carmona M, Faulconbridge A, Hercules A, McAuley E (2019) Open Targets Platform: new developments and updates two years on. Nucl Acids Res 47:D1056–D1065

    Article  CAS  PubMed  Google Scholar 

  • Consortium G (2020) The GTEx consortium atlas of genetic regulatory effects across human tissues. Science 369:1318–1330

    Article  Google Scholar 

  • Dai Y, Hu R, Liu A, Cho KS, Manuel AM, Li X, Dong X, Jia P, Zhao Z (2022) WebCSEA: web-based cell-type-specific enrichment analysis of genes. Nucl Acids Res. https://doi.org/10.1093/nar/gkac392

    Article  PubMed  PubMed Central  Google Scholar 

  • Dale BL, Madhur MS (2016) Linking inflammation and hypertension via LNK/SH2B3. Curr Opin Nephrol Hypertens 25:87–93. https://doi.org/10.1097/MNH.0000000000000196

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Donertas HM, Fabian DK, Valenzuela MF, Partridge L, Thornton JM (2021) Common genetic associations between age-related diseases. Nat Aging 1:400–412. https://doi.org/10.1038/s43587-021-00051-5

    Article  PubMed  PubMed Central  Google Scholar 

  • Drummond GR, Vinh A, Guzik TJ, Sobey CG (2019) Immune mechanisms of hypertension. Nat Rev Immunol 19:517–532. https://doi.org/10.1038/s41577-019-0160-5

    Article  CAS  PubMed  Google Scholar 

  • Ehret GB, Caulfield MJ (2013) Genes for blood pressure: an opportunity to understand hypertension. Eur Heart J 34:951–961

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, Ntritsos G, Dimou N, Cabrera CP, Karaman I (2018) Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet 50:1412–1425

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Flynn E, Tanigawa Y, Rodriguez F, Altman RB, Sinnott-Armstrong N, Rivas MA (2021) Sex-specific genetic effects across biomarkers. Eur J Hum Genet 29:154–163. https://doi.org/10.1038/s41431-020-00712-w

    Article  CAS  PubMed  Google Scholar 

  • Geldsetzer P, Manne-Goehler J, Marcus ME, Ebert C, Zhumadilov Z, Wesseh CS, Tsabedze L, Supiyev A, Sturua L, Bahendeka SK, Sibai AM, Quesnel-Crooks S, Norov B, Mwangi KJ, Mwalim O, Wong-McClure R, Mayige MT, Martins JS, Lunet N, Labadarios D, Karki KB, Kagaruki GB, Jorgensen JMA, Hwalla NC, Houinato D, Houehanou C, Msaidie M, Guwatudde D, Gurung MS, Gathecha G, Dorobantu M, Damasceno A, Bovet P, Bicaba BW, Aryal KK, Andall-Brereton G, Agoudavi K, Stokes A, Davies JI, Barnighausen T, Atun R, Vollmer S, Jaacks LM (2019) The state of hypertension care in 44 low-income and middle-income countries: a cross-sectional study of nationally representative individual-level data from 1.1 million adults. Lancet 394:652–662. https://doi.org/10.1016/S0140-6736(19)30955-9

    Article  PubMed  Google Scholar 

  • Ghoussaini M, Mountjoy E, Carmona M, Peat G, Schmidt EM, Hercules A, Fumis L, Miranda A, Carvalho-Silva D, Buniello A (2021) Open targets genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics. Nucleic Acids Res 49:D1311–D1320

    Article  CAS  PubMed  Google Scholar 

  • Gleicher N, Barad DH (2007) Gender as risk factor for autoimmune diseases. J Autoimmun 28:1–6

    Article  CAS  PubMed  Google Scholar 

  • Isgut M, Sun J, Quyyumi AA, Gibson G (2021) Highly elevated polygenic risk scores are better predictors of myocardial infarction risk early in life than later. Genome Med 13:1–16

    Article  Google Scholar 

  • Jeunemaitre X, Soubrier F, Kotelevtsev YV, Lifton RP, Williams CS, Charru A, Hunt SC, Hopkins PN, Williams RR, Lalouel JM et al (1992) Molecular basis of human hypertension: role of angiotensinogen. Cell 71:169–180. https://doi.org/10.1016/0092-8674(92)90275-h

    Article  CAS  PubMed  Google Scholar 

  • Ji LD, Tang NLS, Xu ZF, Xu J (2020) Genes regulate blood pressure, but “environments” cause hypertension. Front Genet 11:580443. https://doi.org/10.3389/fgene.2020.580443

    Article  PubMed  PubMed Central  Google Scholar 

  • Johnson T, Gaunt TR, Newhouse SJ, Padmanabhan S, Tomaszewski M, Kumari M, Morris RW, Tzoulaki I, O’Brien ET, Poulter NR, Sever P, Shields DC, Thom S, Wannamethee SG, Whincup PH, Brown MJ, Connell JM, Dobson RJ, Howard PJ, Mein CA, Onipinla A, Shaw-Hawkins S, Zhang Y, Davey Smith G, Day IN, Lawlor DA, Goodall AH, Cardiogenics C, Fowkes FG, Abecasis GR, Elliott P, Gateva V, Global BC, Braund PS, Burton PR, Nelson CP, Tobin MD, van der Harst P, Glorioso N, Neuvrith H, Salvi E, Staessen JA, Stucchi A, Devos N, Jeunemaitre X, Plouin PF, Tichet J, Juhanson P, Org E, Putku M, Sober S, Veldre G, Viigimaa M, Levinsson A, Rosengren A, Thelle DS, Hastie CE, Hedner T, Lee WK, Melander O, Wahlstrand B, Hardy R, Wong A, Cooper JA, Palmen J, Chen L, Stewart AF, Wells GA, Westra HJ, Wolfs MG, Clarke R, Franzosi MG, Goel A, Hamsten A, Lathrop M, Peden JF, Seedorf U, Watkins H, Ouwehand WH, Sambrook J, Stephens J, Casas JP, Drenos F, Holmes MV, Kivimaki M, Shah S, Shah T, Talmud PJ, Whittaker J, Wallace C, Delles C, Laan M, Kuh D, Humphries SE, Nyberg F, Cusi D, Roberts R, Newton-Cheh C, Franke L, Stanton AV et al (2011) Blood pressure loci identified with a gene-centric array. Am J Hum Genet 89:688–700. https://doi.org/10.1016/j.ajhg.2011.10.013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kauko A, Aittokallio J, Vaura F, Ji H, Ebinger JE, Niiranen T, Cheng S (2021) Sex differences in genetic risk for hypertension. Hypertension 78:1153–1155. https://doi.org/10.1161/HYPERTENSIONAHA.121.17796

    Article  CAS  PubMed  Google Scholar 

  • Kolifarhood G, Daneshpour M, Hadaegh F, Sabour S, MozafarSaadati H, Akbar Haghdoust A, Akbarzadeh M, Sedaghati-Khayat B, Khosravi N (2019) Heritability of blood pressure traits in diverse populations: a systematic review and meta-analysis. J Hum Hypertens 33:775–785. https://doi.org/10.1038/s41371-019-0253-4

    Article  PubMed  Google Scholar 

  • Kurniansyah N, Goodman MO, Kelly T, Elfassi T, Wiggins K, Bis J, Guo XO, Palmas W, Taylor KD, Lin H (2021) A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood. meDrxiv 1:1

    Google Scholar 

  • Leete J, Layton AT (2019) Sex-specific long-term blood pressure regulation: modeling and analysis. Comput Biol Med 104:139–148. https://doi.org/10.1016/j.compbiomed.2018.11.002

    Article  PubMed  Google Scholar 

  • Levy D, Ehret GB, Rice K, Verwoert GC, Launer LJ, Dehghan A, Glazer NL, Morrison AC, Johnson AD, Aspelund T, Aulchenko Y, Lumley T, Kottgen A, Vasan RS, Rivadeneira F, Eiriksdottir G, Guo X, Arking DE, Mitchell GF, Mattace-Raso FU, Smith AV, Taylor K, Scharpf RB, Hwang SJ, Sijbrands EJ, Bis J, Harris TB, Ganesh SK, O’Donnell CJ, Hofman A, Rotter JI, Coresh J, Benjamin EJ, Uitterlinden AG, Heiss G, Fox CS, Witteman JC, Boerwinkle E, Wang TJ, Gudnason V, Larson MG, Chakravarti A, Psaty BM, van Duijn CM (2009) Genome-wide association study of blood pressure and hypertension. Nat Genet 41:677–687. https://doi.org/10.1038/ng.384

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Liu C, Kraja AT, Smith JA, Brody JA, Franceschini N, Bis JC, Rice K, Morrison AC, Lu Y, Weiss S, Guo X, Palmas W, Martin LW, Chen YD, Surendran P, Drenos F, Cook JP, Auer PL, Chu AY, Giri A, Zhao W, Jakobsdottir J, Lin LA, Stafford JM, Amin N, Mei H, Yao J, Voorman A, Consortium CHDE, Exome BPC, Go TDC, Consortium TDG, Larson MG, Grove ML, Smith AV, Hwang SJ, Chen H, Huan T, Kosova G, Stitziel NO, Kathiresan S, Samani N, Schunkert H, Deloukas P, Myocardial Infarction G, Consortia CAE, Li M, Fuchsberger C, Pattaro C, Gorski M, Consortium CK, Kooperberg C, Papanicolaou GJ, Rossouw JE, Faul JD, Kardia SL, Bouchard C, Raffel LJ, Uitterlinden AG, Franco OH, Vasan RS, O’Donnell CJ, Taylor KD, Liu K, Bottinger EP, Gottesman O, Daw EW, Giulianini F, Ganesh S, Salfati E, Harris TB, Launer LJ, Dorr M, Felix SB, Rettig R, Volzke H, Kim E, Lee WJ, Lee IT, Sheu WH, Tsosie KS, Edwards DR, Liu Y, Correa A, Weir DR, Volker U, Ridker PM, Boerwinkle E, Gudnason V, Reiner AP, van Duijn CM, Borecki IB, Edwards TL, Chakravarti A, Rotter JI, Psaty BM, Loos RJ, Fornage M, Ehret GB, Newton-Cheh C et al (2016) Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet 48:1162–1170. https://doi.org/10.1038/ng.3660

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lu J, Lu Y, Wang X, Li X, Linderman GC, Wu C, Cheng X, Mu L, Zhang H, Liu J, Su M, Zhao H, Spatz ES, Spertus JA, Masoudi FA, Krumholz HM, Jiang L (2017) Prevalence, awareness, treatment, and control of hypertension in China: data from 1.7 million adults in a population-based screening study (China PEACE Million Persons Project). Lancet 390:2549–2558. https://doi.org/10.1016/S0140-6736(17)32478-9

    Article  PubMed  Google Scholar 

  • MacArthur J, Bowler E, Cerezo M, Gil L, Hall P, Hastings E, Junkins H, McMahon A, Milano A, Morales J (2017) The new NHGRI-EBI catalog of published genome-wide association studies (GWAS Catalog). Nucl Acids Res 45:D896–D901

    Article  CAS  PubMed  Google Scholar 

  • Mohana VU, Swapna N, Surender RS, Vishnupriya S, Padma T (2012) Gender-related association of AGT gene variants (M235T and T174M) with essential hypertension—a case–control study. Clin Exp Hypertens 34:38–44. https://doi.org/10.3109/10641963.2011.618207

    Article  CAS  PubMed  Google Scholar 

  • Patel RS, Masi S, Taddei S (2017) Understanding the role of genetics in hypertension. Eur Heart J 38:2309–2312. https://doi.org/10.1093/eurheartj/ehx273

  • Padmanabhan S, Caulfield M, Dominiczak AF (2015) Genetic and molecular aspects of hypertension. Circ Res 116:937–959. https://doi.org/10.1161/CIRCRESAHA.116.303647

    Article  CAS  PubMed  Google Scholar 

  • Porcu E, Rueger S, Lepik K, E QC, Consortium B, Santoni FA, Reymond A, Kutalik Z (2019) Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits. Nat Commun 10:3300. https://doi.org/10.1038/s41467-019-10936-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rodriguez-Iturbe B, Johnson RJ (2019) Genetic polymorphisms in hypertension: Are we missing the immune connection? Am J Hypertens 32:113–122. https://doi.org/10.1093/ajh/hpy168

    Article  CAS  PubMed  Google Scholar 

  • Rossi GP, Ceolotto G, Caroccia B, Lenzini L (2017) Genetic screening in arterial hypertension. Nat Rev Endocrinol 13:289–298

    Article  CAS  PubMed  Google Scholar 

  • Rudemiller NP, Lund H, Priestley JR, Endres BT, Prokop JW, Jacob HJ, Geurts AM, Cohen EP, Mattson DL (2015) Mutation of SH2B3 (LNK), a genome-wide association study candidate for hypertension, attenuates Dahl salt-sensitive hypertension via inflammatory modulation. Hypertension 65:1111–1117. https://doi.org/10.1161/HYPERTENSIONAHA.114.04736

    Article  CAS  PubMed  Google Scholar 

  • Sandberg K, Ji H (2012) Sex differences in primary hypertension. Biol Sex Differ 3:1–21

    Article  Google Scholar 

  • Sinnott-Armstrong N, Tanigawa Y, Amar D, Mars N, Benner C, Aguirre M, Venkataraman GR, Wainberg M, Ollila HM, Kiiskinen T (2021) Genetics of 35 blood and urine biomarkers in the UK Biobank. Nat Genet 53:185–194

    Article  CAS  PubMed  Google Scholar 

  • Sjostedt E, Zhong W, Fagerberg L, Karlsson M, Mitsios N, Adori C, Oksvold P, Edfors F, Limiszewska A, Hikmet F, Huang J, Du Y, Lin L, Dong Z, Yang L, Liu X, Jiang H, Xu X, Wang J, Yang H, Bolund L, Mardinoglu A, Zhang C, von Feilitzen K, Lindskog C, Ponten F, Luo Y, Hokfelt T, Uhlen M, Mulder J (2020) An atlas of the protein-coding genes in the human, pig, and mouse brain. Science. https://doi.org/10.1126/science.aay5947

    Article  PubMed  Google Scholar 

  • Surendran P, Drenos F, Young R, Warren H, Cook JP, Manning AK, Grarup N, Sim X, Barnes DR, Witkowska K, Staley JR, Tragante V, Tukiainen T, Yaghootkar H, Masca N, Freitag DF, Ferreira T, Giannakopoulou O, Tinker A, Harakalova M, Mihailov E, Liu C, Kraja AT, Fallgaard Nielsen S, Rasheed A, Samuel M, Zhao W, Bonnycastle LL, Jackson AU, Narisu N, Swift AJ, Southam L, Marten J, Huyghe JR, Stancakova A, Fava C, Ohlsson T, Matchan A, Stirrups KE, Bork-Jensen J, Gjesing AP, Kontto J, Perola M, Shaw-Hawkins S, Havulinna AS, Zhang H, Donnelly LA, Groves CJ, Rayner NW, Neville MJ, Robertson NR, Yiorkas AM, Herzig KH, Kajantie E, Zhang W, Willems SM, Lannfelt L, Malerba G, Soranzo N, Trabetti E, Verweij N, Evangelou E, Moayyeri A, Vergnaud AC, Nelson CP, Poveda A, Varga TV, Caslake M, de Craen AJ, Trompet S, Luan J, Scott RA, Harris SE, Liewald DC, Marioni R, Menni C, Farmaki AE, Hallmans G, Renstrom F, Huffman JE, Hassinen M, Burgess S, Vasan RS, Felix JF, Consortium CH-HF, Uria-Nickelsen M, Malarstig A, Reily DF, Hoek M, Vogt T, Lin H, Lieb W, EchoGen C, Traylor M, Markus HF, Consortium M, Highland HM, Justice AE, Marouli E, Consortium G et al (2016) Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension. Nat Genet 48:1151–1161. https://doi.org/10.1038/ng.3654

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Surendran P, Feofanova EV, Lahrouchi N, Ntalla I, Karthikeyan S, Cook J, Chen L, Mifsud B, Yao C, Kraja AT, Cartwright JH, Hellwege JN, Giri A, Tragante V, Thorleifsson G, Liu DJ, Prins BP, Stewart ID, Cabrera CP, Eales JM, Akbarov A, Auer PL, Bielak LF, Bis JC, Braithwaite VS, Brody JA, Daw EW, Warren HR, Drenos F, Nielsen SF, Faul JD, Fauman EB, Fava C, Ferreira T, Foley CN, Franceschini N, Gao H, Giannakopoulou O, Giulianini F, Gudbjartsson DF, Guo X, Harris SE, Havulinna AS, Helgadottir A, Huffman JE, Hwang SJ, Kanoni S, Kontto J, Larson MG, Li-Gao R, Lindstrom J, Lotta LA, Lu Y, Luan J, Mahajan A, Malerba G, Masca NGD, Mei H, Menni C, Mook-Kanamori DO, Mosen-Ansorena D, Muller-Nurasyid M, Pare G, Paul DS, Perola M, Poveda A, Rauramaa R, Richard M, Richardson TG, Sepulveda N, Sim X, Smith AV, Smith JA, Staley JR, Stanakova A, Sulem P, Theriault S, Thorsteinsdottir U, Trompet S, Varga TV, Velez Edwards DR, Veronesi G, Weiss S, Willems SM, Yao J, Young R, Yu B, Zhang W, Zhao JH, Zhao W, Zhao W, Evangelou E, Aeschbacher S, Asllanaj E, Blankenberg S, Bonnycastle LL, Bork-Jensen J, Brandslund I, Braund PS, Burgess S et al (2020) Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals. Nat Genet 52:1314–1332. https://doi.org/10.1038/s41588-020-00713-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Takeuchi F, Akiyama M, Matoba N, Katsuya T, Nakatochi M, Tabara Y, Narita A, Saw WY, Moon S, Spracklen CN, Chai JF, Kim YJ, Zhang L, Wang C, Li H, Li H, Wu JY, Dorajoo R, Nierenberg JL, Wang YX, He J, Bennett DA, Takahashi A, Momozawa Y, Hirata M, Matsuda K, Rakugi H, Nakashima E, Isono M, Shirota M, Hozawa A, Ichihara S, Matsubara T, Yamamoto K, Kohara K, Igase M, Han S, Gordon-Larsen P, Huang W, Lee NR, Adair LS, Hwang MY, Lee J, Chee ML, Sabanayagam C, Zhao W, Liu J, Reilly DF, Sun L, Huo S, Edwards TL, Long J, Chang LC, Chen CH, Yuan JM, Koh WP, Friedlander Y, Kelly TN, Bin Wei W, Xu L, Cai H, Xiang YB, Lin K, Clarke R, Walters RG, Millwood IY, Li L, Chambers JC, Kooner JS, Elliott P, van der Harst P, International Genomics of Blood Pressure C, Chen Z, Sasaki M, Shu XO, Jonas JB, He J, Heng CK, Chen YT, Zheng W, Lin X, Teo YY, Tai ES, Cheng CY, Wong TY, Sim X, Mohlke KL, Yamamoto M, Kim BJ, Miki T, Nabika T, Yokota M, Kamatani Y, Kubo M, Kato N (2018) Interethnic analyses of blood pressure loci in populations of East Asian and European descent. Nat Commun 9:5052. https://doi.org/10.1038/s41467-018-07345-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Vaura F, Kauko A, Suvila K, Havulinna AS, Mars N, Salomaa V, FinnGen CS, Niiranen T (2021) Polygenic risk scores predict hypertension onset and cardiovascular risk. Hypertension 77:1119–1127

    Article  CAS  PubMed  Google Scholar 

  • Warren HR, Evangelou E, Cabrera CP, Gao H, Ren M, Mifsud B, Ntalla I, Surendran P, Liu C, Cook JP (2017) Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk. Nat Genet 49:403–415

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Warren H, Edwards T, Vaez A, Keaton J, Kamali Z, Xie T, Ani A, Evangelou E, Hellwege J, Yengo L et al (2022) Genome-wide analysis in over 1 million individuals reveals over 2000 independent genetic signals for blood pressure. Preprint. https://doi.org/10.21203/rs.3.rs-1409164/v1

  • Wolf-Maier K, Cooper RS, Banegas JR, Giampaoli S, Hense H-W, Joffres M, Kastarinen M, Poulter N, Primatesta P, Rodríguez-Artalejo F (2003) Hypertension prevalence and blood pressure levels in 6 European countries, Canada, and the United States. JAMA 289:2363–2369

    Article  PubMed  Google Scholar 

  • Wong TY, Mitchell P (2007) The eye in hypertension. Lancet 369:425–435. https://doi.org/10.1016/S0140-6736(07)60198-6

    Article  PubMed  Google Scholar 

  • Yao C, Chen G, Song C, Keefe J, Mendelson M, Huan T, Sun BB, Laser A, Maranville JC, Wu H, Ho JE, Courchesne P, Lyass A, Larson MG, Gieger C, Graumann J, Johnson AD, Danesh J, Runz H, Hwang SJ, Liu C, Butterworth AS, Suhre K, Levy D (2018) Genome-wide mapping of plasma protein QTLs identifies putatively causal genes and pathways for cardiovascular disease. Nat Commun 9:3268. https://doi.org/10.1038/s41467-018-05512-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Dr. Nadav Brandes for the support in using the UKB parser, the PWAS algorithm and commenting on the initial draft. We thank Dr. Guy Kelman for his help in the implementation of PWAS. We thank Dr. Ronen Durst and Idit Gabay for commenting on the initial draft. We thank Amos Stern from the Linial lab for useful discussion. We appreciate the constant support of the system team of the School of Computer Science at the Hebrew University.

Funding

ISF Grant 2753/20 (M.L) on Sex-dependent genetics.

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Authors and Affiliations

  1. The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel

    Roei Zucker & Michael Kovalerchik

  2. Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel

    Michal Linial

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  1. Roei Zucker
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Correspondence to Michal Linial.

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Ethical committee approval: The Hebrew University #13082019 from the University Committee for the Use of Human Subjects in research (dated 07/2002).

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Supplementary file 1 (PDF 801 KB)

Table S1

: Summary statistics of GWAS for hypertension extracted from OT (Source of Fig. 1). (XLSX 79 KB)

Table S2

: A list of PWAS top genes with their statistics including top 70 significant genes (Source for Fig. 3) (XLSX 80 KB)

Table S3

: A list of PWAS identified genes for DBP (199 genes) and SBP (220 gene) and their statistics (Source for Fig. 4). (XLSX 100 KB)

Table S4

: A list of hypertension gene results from FinnGen used for validations and their statistics (Source for Table 1). (XLSX 43 KB)

Table S5

: Listing and scoring of 1665 genes from GWAS for hypertension as compiled by OT (Source for Table 1). (XLSX 89 KB)

Table S6

: List variants along with their p-values in males and females (total 377, source Fig. 5). (XLSX 72 KB)

Table S7

: Listing the significant PWAS genes by sex for I10 (Source for Fig. 6). (XLSX 22 KB)

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Zucker, R., Kovalerchik, M. & Linial, M. Gene-based association study reveals a distinct female genetic signal in primary hypertension. Hum Genet 142, 863–878 (2023). https://doi.org/10.1007/s00439-023-02567-9

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