Literature DB >> 33603002

Trans-ethnic meta-analysis identifies new loci associated with longitudinal blood pressure traits.

Mateus H Gouveia1, Amy R Bentley1, Hampton Leonard2,3, Karlijn A C Meeks1, Kenneth Ekoru1, Guanjie Chen1, Michael A Nalls2,3, Eleanor M Simonsick4, Eduardo Tarazona-Santos5, Maria Fernanda Lima-Costa6, Adebowale Adeyemo1, Daniel Shriner7,8, Charles N Rotimi9,10.   

Abstract

Genome-wide association studies (GWAS) have identified thousands of genetic loci associated with cross-sectional blood pressure (BP) traits; however, GWAS based on longitudinal BP have been underexplored. We performed ethnic-specific and trans-ethnic GWAS meta-analysis using longitudinal and cross-sectional BP data of 33,720 individuals from five cohorts in the US and one in Brazil. In addition to identifying several known loci, we identified thirteen novel loci with nine based on longitudinal and four on cross-sectional BP traits. Most of the novel loci were ethnic- or study-specific, with the majority identified in African Americans (AA). Four of these discoveries showed additional evidence of association in independent datasets, including an intergenic variant (rs4060030, p = 7.3 × 10-9) with reported regulatory function. We observed a high correlation between the meta-analysis results for baseline and longitudinal average BP (rho = 0.48). BP trajectory results were more correlated with those of average BP (rho = 0.35) than baseline BP(rho = 0.18). Heritability estimates trended higher for longitudinal traits than for cross-sectional traits, providing evidence for different genetic architectures. Furthermore, the longitudinal data identified up to 20% more BP known associations than did cross-sectional data. Our analyses of longitudinal BP data in diverse ethnic groups identified novel BP loci associated with BP trajectory, indicating a need for further longitudinal GWAS on BP and other age-related traits.

Entities:  

Mesh:

Year:  2021        PMID: 33603002      PMCID: PMC7893038          DOI: 10.1038/s41598-021-83450-3

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.996


  61 in total

1.  Cohort profile: the Bambui (Brazil) Cohort Study of Ageing.

Authors:  Maria Fernanda Lima-Costa; Josélia O A Firmo; Elizabeth Uchoa
Journal:  Int J Epidemiol       Date:  2010-08-30       Impact factor: 7.196

2.  Socioeconomic Position, But Not African Genomic Ancestry, Is Associated With Blood Pressure in the Bambui-Epigen (Brazil) Cohort Study of Aging.

Authors:  M Fernanda Lima-Costa; Juliana Vaz de Mello Mambrini; Maria Lea Corrêa Leite; Sérgio Viana Peixoto; Josélia Oliveira Araújo Firmo; Antônio Ignácio de Loyola Filho; Mateus H Gouveia; Thiago P Leal; Alexandre Costa Pereira; James Macinko; Eduardo Tarazona-Santos
Journal:  Hypertension       Date:  2015-12-28       Impact factor: 10.190

3.  Multi-Ethnic Study of Atherosclerosis: objectives and design.

Authors:  Diane E Bild; David A Bluemke; Gregory L Burke; Robert Detrano; Ana V Diez Roux; Aaron R Folsom; Philip Greenland; David R Jacob; Richard Kronmal; Kiang Liu; Jennifer Clark Nelson; Daniel O'Leary; Mohammed F Saad; Steven Shea; Moyses Szklo; Russell P Tracy
Journal:  Am J Epidemiol       Date:  2002-11-01       Impact factor: 4.897

4.  ST7 is a novel low-density lipoprotein receptor-related protein (LRP) with a cytoplasmic tail that interacts with proteins related to signal transduction pathways.

Authors:  Michele A Battle; Veronica M Maher; J Justin McCormick
Journal:  Biochemistry       Date:  2003-06-24       Impact factor: 3.162

5.  Heritability of blood pressure traits in diverse populations: a systematic review and meta-analysis.

Authors:  Goodarz Kolifarhood; Maryam Daneshpour; Farzad Hadaegh; Siamak Sabour; Hossein Mozafar Saadati; Ali Akbar Haghdoust; Mahdi Akbarzadeh; Bahareh Sedaghati-Khayat; Nasim Khosravi
Journal:  J Hum Hypertens       Date:  2019-09-24       Impact factor: 3.012

6.  Life course trajectories of systolic blood pressure using longitudinal data from eight UK cohorts.

Authors:  Andrew K Wills; Debbie A Lawlor; Fiona E Matthews; Avan Aihie Sayer; Eleni Bakra; Yoav Ben-Shlomo; Michaela Benzeval; Eric Brunner; Rachel Cooper; Mika Kivimaki; Diana Kuh; Graciela Muniz-Terrera; Rebecca Hardy
Journal:  PLoS Med       Date:  2011-06-14       Impact factor: 11.069

7.  Efficient haplotype matching and storage using the positional Burrows-Wheeler transform (PBWT).

Authors:  Richard Durbin
Journal:  Bioinformatics       Date:  2014-01-09       Impact factor: 6.937

8.  A global reference for human genetic variation.

Authors:  Adam Auton; Lisa D Brooks; Richard M Durbin; Erik P Garrison; Hyun Min Kang; Jan O Korbel; Jonathan L Marchini; Shane McCarthy; Gil A McVean; Gonçalo R Abecasis
Journal:  Nature       Date:  2015-10-01       Impact factor: 49.962

9.  The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019.

Authors:  Annalisa Buniello; Jacqueline A L MacArthur; Maria Cerezo; Laura W Harris; James Hayhurst; Cinzia Malangone; Aoife McMahon; Joannella Morales; Edward Mountjoy; Elliot Sollis; Daniel Suveges; Olga Vrousgou; Patricia L Whetzel; Ridwan Amode; Jose A Guillen; Harpreet S Riat; Stephen J Trevanion; Peggy Hall; Heather Junkins; Paul Flicek; Tony Burdett; Lucia A Hindorff; Fiona Cunningham; Helen Parkinson
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

10.  Genetics of cognitive trajectory in Brazilians: 15 years of follow-up from the Bambuí-Epigen Cohort Study of Aging.

Authors:  Mateus H Gouveia; Cibele C Cesar; Meddly L Santolalla; Hanaisa P Sant Anna; Marilia O Scliar; Thiago P Leal; Nathalia M Araújo; Giordano B Soares-Souza; Wagner C S Magalhães; Ignacio F Mata; Cleusa P Ferri; Erico Castro-Costa; Sam M Mbulaiteye; Sarah A Tishkoff; Daniel Shriner; Charles N Rotimi; Eduardo Tarazona-Santos; Maria Fernanda Lima-Costa
Journal:  Sci Rep       Date:  2019-12-02       Impact factor: 4.379

View more
  3 in total

1.  The genetic architecture of blood pressure variability: A genome-wide association study of 9370 participants from UK Biobank.

Authors:  Pingping Jia; Na Zhan; Baker K K Bat; Qi Feng; Kelvin K F Tsoi
Journal:  J Clin Hypertens (Greenwich)       Date:  2022-08-08       Impact factor: 2.885

2.  Bayesian analysis of longitudinal traits in the Korea Association Resource (KARE) cohort.

Authors:  Wonil Chung; Hyunji Hwang; Taesung Park
Journal:  Genomics Inform       Date:  2022-06-30

3.  Bayesian mixed models for longitudinal genetic data: theory, concepts, and simulation studies.

Authors:  Wonil Chung; Youngkwang Cho
Journal:  Genomics Inform       Date:  2022-03-31
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.