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Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

Authors :
Chauhan, Ganesh
Adams, Hieab HH
Satizabal, Claudia L
Bis, Joshua C
Teumer, Alexander
Sargurupremraj, Muralidharan
Hofer, Edith
Trompet, Stella
Hilal, Saima
Smith, Albert Vernon
Jian, Xueqiu
Malik, Rainer
Traylor, Matthew
Pulit, Sara L
Amouyel, Philippe
Mazoyer, Bernard
Zhu, Yi-Cheng
Kaffashian, Sara
Schilling, Sabrina
Beecham, Gary W
Montine, Thomas J
Schellenberg, Gerard D
Kjartansson, Olafur
Guðnason, Vilmundur
Knopman, David S
Griswold, Michael E
Windham, B Gwen
Gottesman, Rebecca F
Mosley, Thomas H
Schmidt, Reinhold
Saba, Yasaman
Schmidt, Helena
Takeuchi, Fumihiko
Yamaguchi, Shuhei
Nabika, Toru
Kato, Norihiro
Rajan, Kumar B
Aggarwal, Neelum T
De Jager, Philip L
Evans, Denis A
Psaty, Bruce M
Rotter, Jerome I
Rice, Kenneth
Lopez, Oscar L
Liao, Jiemin
Chen, Christopher
Cheng, Ching-Yu
Wong, Tien Y
Ikram, Mohammad K
van der Lee, Sven J
Amin, Najaf
Chouraki, Vincent
DeStefano, Anita L
Aparicio, Hugo J
Romero, Jose R
Maillard, Pauline
DeCarli, Charles
Wardlaw, Joanna M
Hernández, Maria Del C Valdés
Luciano, Michelle
Liewald, David
Deary, Ian J
Starr, John M
Bastin, Mark E
Muñoz Maniega, Susana
Slagboom, P Eline
Beekman, Marian
Deelen, Joris
Uh, Hae-Won
Lemmens, Robin
Brodaty, Henry
Wright, Margaret J
Ames, David
Boncoraglio, Giorgio B
Hopewell, Jemma C
Beecham, Ashley H
Blanton, Susan H
Wright, Clinton B
Sacco, Ralph L
Wen, Wei
Thalamuthu, Anbupalam
Armstrong, Nicola J
Chong, Elizabeth
Schofield, Peter R
Kwok, John B
van der Grond, Jeroen
Stott, David J
Ford, Ian
Jukema, J Wouter
Vernooij, Meike W
Hofman, Albert
Uitterlinden, André G
van der Lugt, Aad
Wittfeld, Katharina
Grabe, Hans J
Hosten, Norbert
von Sarnowski, Bettina
Völker, Uwe
Levi, Christopher
Jimenez-Conde, Jordi
Sharma, Pankaj
Sudlow, Cathie LM
Rosand, Jonathan
Woo, Daniel
Cole, John W
Meschia, James F
Slowik, Agnieszka
Thijs, Vincent
Lindgren, Arne
Melander, Olle
Grewal, Raji P
Rundek, Tatjana
Rexrode, Kathy
Rothwell, Peter M
Arnett, Donna K
Jern, Christina
Johnson, Julie A
Benavente, Oscar R
Wasssertheil-Smoller, Sylvia
Lee, Jin-Moo
Wong, Quenna
Mitchell, Braxton D
Rich, Stephen S
McArdle, Patrick F
Geerlings, Mirjam I
van der Graaf, Yolanda
de Bakker, Paul IW
Asselbergs, Folkert W
Srikanth, Velandai
Thomson, Russell
McWhirter, Rebekah
Moran, Chris
Callisaya, Michele
Phan, Thanh
Rutten-Jacobs, Loes CA
Bevan, Steve
Tzourio, Christophe
Mather, Karen A
Sachdev, Perminder S
van Duijn, Cornelia M
Worrall, Bradford B
Dichgans, Martin
Kittner, Steven J
Markus, Hugh S
Ikram, Mohammad A
Fornage, Myriam
Launer, Lenore J
Seshadri, Sudha
Longstreth, WT
Debette, Stéphanie
Stroke Genetics Network (SiGN), the International Stroke Genetics Consortium (ISGC), METASTROKE, Alzheimer's Disease Genetics Consortium (ADGC), and the Neurology Working Group of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium
Teumer, Alexander [0000-0002-8309-094X]
Pulit, Sara L [0000-0002-2502-3669]
Muñoz Maniega, Susana [0000-0001-5185-6384]
Beekman, Marian [0000-0003-0585-6206]
Schofield, Peter R [0000-0003-2967-9662]
Kwok, John B [0000-0001-9574-6195]
Grabe, Hans J [0000-0003-3684-4208]
Thijs, Vincent [0000-0002-6614-8417]
de Bakker, Paul IW [0000-0001-7735-7858]
Asselbergs, Folkert W [0000-0002-1692-8669]
Rutten-Jacobs, Loes CA [0000-0003-3223-885X]
Tzourio, Christophe [0000-0002-6517-2984]
Apollo - University of Cambridge Repository
Source :
Datacite, Apollo
Publication Year :
2019
Publisher :
Neurology, 2019.

Abstract

OBJECTIVE: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. METHODS: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. RESULTS: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. CONCLUSION: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.

Details

Language :
English
Database :
OpenAIRE
Journal :
Datacite, Apollo
Accession number :
edsair.dedup.wf.001..c0014a5e0b81879f143786fe63c8548f