Literature DB >> 22476227

Ethnic differences in genetic predisposition to hypertension.

Norihiro Kato1.   

Abstract

Recently, large-scale meta-analyses of genome-wide association (GWA) studies have identified a number of loci significantly associated with systolic and/or diastolic blood pressure (BP). Most of the GWA studies reported to date were conducted in populations of European descent. Given the appreciable ethnic differences in clinical presentation of hypertension, studies in non-European populations allow us to assess the relevance of the findings in Europeans to other ethnic groups and to potentially discover novel variants. Before the GWA scan era, the presence of racial or ethnic differences has been widely recognized for response to antihypertensive therapies, salt sensitivity and impact of obesity on developing hypertension. Despite a limited number of genetic loci that have been proven to show substantial ethnic differences, we can assume four possible genetic mechanisms--(1) absence of target variants in other ethnic groups; (2) presence of allelic heterogeneity; (3) difference in linkage disequilibrium structure; and (4) gene-gene and gene-environment interactions. Considering such a number of potential sources of heterogeneity, we should be cautious about claiming the presence of genuine ethnic differences in genetic susceptibility to BP-related traits or hypertension. Approximately a quarter of BP-associated loci that have been reported in four meta-analyses of GWA studies (i.e., 8 out of 34 loci) appear to be common across three ethnic groups--Europeans, east Asians and south Asians. 'Transethnic' BP meta-analysis will be useful not only for revealing novel susceptibility loci and pathophysiological pathways but also for facilitating the fine mapping of common causal variants.

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Year:  2012        PMID: 22476227     DOI: 10.1038/hr.2012.44

Source DB:  PubMed          Journal:  Hypertens Res        ISSN: 0916-9636            Impact factor:   3.872


  19 in total

1.  Impact of interactions between risk alleles on clinical endpoints in hypertension.

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2.  Twenty years of evolving trends in racial disparities for adult kidney transplant recipients.

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Journal:  Kidney Int       Date:  2016-08-20       Impact factor: 10.612

3.  Development of a risk prediction score for hypertension incidence using Japanese health checkup data.

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Journal:  Hypertens Res       Date:  2021-12-27       Impact factor: 5.528

4.  Tag polymorphisms of solute carrier family 12 member 3 gene modify the risk of hypertension in northeastern Han Chinese.

Authors:  Y L Wang; Y Qi; J N Bai; Z M Qi; J R Li; H Y Zhao; Y F Wang; C Z Lu; Y Xiao; N Jia; B Wang; W Q Niu
Journal:  J Hum Hypertens       Date:  2014-01-16       Impact factor: 3.012

5.  Dietary salt reduction and cardiovascular disease rates in India: a mathematical model.

Authors:  Sanjay Basu; David Stuckler; Sukumar Vellakkal; Shah Ebrahim
Journal:  PLoS One       Date:  2012-09-06       Impact factor: 3.240

6.  Prevalence and risk factors for resistant hypertension among hypertensive patients from a developing country.

Authors:  W A Nuwan Kumara; Thisara Perera; Mekhala Dissanayake; Priyanga Ranasinghe; Godwin R Constantine
Journal:  BMC Res Notes       Date:  2013-09-21

Review 7.  Insights into the genetic basis of type 2 diabetes.

Authors:  Norihiro Kato
Journal:  J Diabetes Investig       Date:  2013-05-06       Impact factor: 4.232

8.  Echocardiographic assessment of left ventricular geometric patterns in hypertensive patients in Nigeria.

Authors:  Rasaaq A Adebayo; Olaniyi J Bamikole; Michael O Balogun; Anthony O Akintomide; Victor O Adeyeye; Luqman A Bisiriyu; Tuoyo O Mene-Afejuku; Ebenezer A Ajayi; Olugbenga O Abiodun
Journal:  Clin Med Insights Cardiol       Date:  2013-10-23

9.  Interactive contribution of serine/threonine kinase 39 gene multiple polymorphisms to hypertension among northeastern Han Chinese.

Authors:  Hongye Zhao; Yue Qi; Yuefei Wang; Yanli Wang; Changzhu Lu; Yu Xiao; Bin Wang; Wenquan Niu
Journal:  Sci Rep       Date:  2014-05-30       Impact factor: 4.379

10.  Analysing the socioeconomic determinants of hypertension in South Africa: a structural equation modelling approach.

Authors:  Annibale Cois; Rodney Ehrlich
Journal:  BMC Public Health       Date:  2014-05-01       Impact factor: 3.295

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