Chauhan, G;
Adams, HHH;
Satizabal, CL;
Bis, JC;
Teumer, A;
Sargurupremraj, M;
Hofer, E;
... Stroke Genetics Network (SiGN), the International Stroke Genetic, .; + view all
(2019)
Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.
Neurology
, 92
(5)
e486-e503.
10.1212/WNL.0000000000006851.
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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.
| Type: | Article |
|---|---|
| Title: | Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting. |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1212/WNL.0000000000006851 |
| Publisher version: | https://doi.org/10.1212/WNL.0000000000006851 |
| Language: | English |
| Additional information: | © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | 1000 Genomes reference panel, brain infarcts, body mass index, blood pressure, diastolic blood pressure, fluid-attenuated inversion recovery, genetic risk scores, genome-wide association studies, high-density lipoprotein, ischemic stroke, small vessel disease subtype of ischemic stroke, inverse-variance weighting, Log₁₀ of Bayesian factor, linkage disequilibrium, low-density lipoprotein, mean arterial pressure, pulse pressure, single nucleotide polymorphism, systolic blood pressure, small subcortical brain infarcts, small vessel disease, white matter hyperintensities |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10066593 |
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