TY - JOUR
T1 - Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting
AU - Stroke Genetics Network (SiGN)
AU - International Stroke Genetics Consortium (ISGC)
AU - METASTROKE, Alzheimer’s Disease Genetics Consortium (ADGC)
AU - Neurology Working Group of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium
AU - Chauhan, Ganesh
AU - Adams, Hieab H.H.
AU - Satizabal, Claudia L.
AU - Bis, Joshua C.
AU - Teumer, Alexander
AU - Sargurupremraj, Muralidharan
AU - Hofer, Edith
AU - Trompet, Stella
AU - Hilal, Saima
AU - Smith, Albert Vernon
AU - Jian, Xueqiu
AU - Malik, Rainer
AU - Traylor, Matthew
AU - Pulit, Sara L.
AU - Amouyel, Philippe
AU - Mazoyer, Bernard
AU - Zhu, Yi Cheng
AU - Kaffashian, Sara
AU - Schilling, Sabrina
AU - Beecham, Gary W.
AU - Montine, Thomas J.
AU - Schellenberg, Gerard D.
AU - Kjartansson, Olafur
AU - Guðnason, Vilmundur
AU - Knopman, David S.
AU - Griswold, Michael E.
AU - Windham, B. Gwen
AU - Gottesman, Rebecca F.
AU - Mosley, Thomas H.
AU - Schmidt, Reinhold
AU - Saba, Yasaman
AU - Schmidt, Helena
AU - Takeuchi, Fumihiko
AU - Yamaguchi, Shuhei
AU - Nabika, Toru
AU - Kato, Norihiro
AU - Rajan, Kumar B.
AU - Aggarwal, Neelum T.
AU - De Jager, Philip L.
AU - Evans, Denis A.
AU - Psaty, Bruce M.
AU - Rotter, Jerome I.
AU - Rice, Kenneth
AU - Lopez, Oscar L.
AU - Liao, Jiemin
AU - Chen, Christopher
AU - Cheng, Ching Yu
AU - Wong, Tien Y.
AU - Ikram, Mohammad K.
AU - van der Lee, Sven J.
N1 - Publisher Copyright:
© 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.
PY - 2019/1/29
Y1 - 2019/1/29
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85065551999&partnerID=8YFLogxK
U2 - 10.1212/WNL.0000000000006851
DO - 10.1212/WNL.0000000000006851
M3 - Article
C2 - 30651383
AN - SCOPUS:85065551999
SN - 0028-3878
VL - 92
SP - E486-E503
JO - Neurology
JF - Neurology
IS - 5
ER -
