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

Author

Chauhan, G., Adams, H.H.H., Satizabal, C.L., Bis, J.C., Teumer, A., Sargurupremraj, M., Hofer, E., Trompet, S., Hilal, S., Smith, A.V., Jian, X.Q., Malik, R., Traylor, M., Pulit, S.L., Amouyel, P., Mazoyer, B., Zhu, Y.C., Kaffashian, S., Schilling, S., Beecham, G.W., Montine, T.J., Schellenberg, G.D., Kjartansson, O., Gudnason, V., Knopman, D.S., Griswold, M.E., Windham, B.G., Gottesman, R.F., Mosley, T.H., Schmidt, R., Saba, Y., Schmidt, H., Takeuchi, F., Yamaguchi, S., Nabika, T., Kato, N., Rajan, K.B., Aggarwal, N.T., Jager, P.L. de, Evans, D.A., Psaty, B.M., Rotter, J.I., Rice, K., Lopez, O.L., Liao, J.M., Chen, C., Cheng, C.Y., Wong, T.Y., Ikram, M.K., Lee, S.J. van der, Amin, N., Chouraki, V., DeStefano, A.L., Aparicio, H.J., Romero, J.R., Maillard, P., DeCarli, C., Wardlaw, J.M., Hernandez, M.D.V., Luciano, M., Liewald, D., Deary, I.J., Starr, J.M., Bastin, M.E., Maniega, S.M., Slagboom, P.E., Beekman, M., Deelen, J., Uh, H.W., Lemmens, R., Brodaty, H., Wright, M.J., Ames, D., Boncoraglio, G.B., Hopewell, J.C., Beecham, A.H., Blanton, S.H., Wright, C.B., Sacco, R.L., Wen, W., Thalamuthu, A., Armstrong, N.J., Chong, E., Schofield, P.R., Kwok, J.B., Grond, J. van der, Stott, D.J., Ford, I., Jukema, J.W., Vernooij, M.W., Hofman, A., Uitterlinden, A.G., Lugt, A. van der, Wittfeld, K., Grabe, H.J., Hosten, N., Sarnowski, B. von, Volker, U., Levi, C., Jimenez-Conde, J., Sharma, P., Sudlow, C.L.M., Rosand, J., Woo, D., Cole, J.W., Meschia, J.F., Slowik, A., Thijs, V., Lindgren, A., Melander, O., Grewal, R.P., Rundek, T., Rexrode, K., Rothwell, P.M., Arnett, D.K., Jern, C., Johnson, J.A., Benavente, O.R., Wasssertheil-Smoller, S., Lee, J.M., Wong, Q., Mitchell, B.D., Rich, S.S., McArdle, P.F., Geerlings, M.I., Graaf, Y. van der, Bakker, P.I.W. de, Asselbergs, F.W., Srikanth, V., Thomson, R., McWhirter, R., Moran, C., Callisaya, M., Phan, T., Rutten-Jacobs, L.C.A., Bevan, S., Tzourio, C., Mather, K.A., Sachdev, P.S., Duijn, C.M. van, Worrall, B.B., Dichgans, M., Kittner, S.J., Markus, H.S., Ikram, M.A., Fornage, M., Launer, L.J., Seshadri, S., Longstreth, W.T., Debette, S., Stroke Genetics Network SiGN, ISGC, METASTROKE, ADGC, and CHARGE Consortium

Subjects
Meta-analysis, Mendelian Randomization, Blood Pressure, Polymorphisms, Genome-wide Association, Silent, Insights, Small Vessel Disease, Matter Hyperintensity Volume, Ischemic Stroke, Doenças Cardio e Cérebro-vasculares
Abstract

Collaborators (845): Astrid M. Vicente Free PMC article:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6369905/ 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. info:eu-repo/semantics/publishedVersion

Published
2019

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

Author

Chauhan, G., Adams, H., Satizabal, C., Bis, J., Teumer, A., Sargurupremraj, M., Hofer, E., Trompet, S., Hilal, S., Smith, A., Jian, X., Malik, R., Traylor, M., Pulit, S., Amouyel, P., Mazoyer, B., Zhu, Y., Kaffashian, S., Schilling, S., Beecham, G., Montine, T., Schellenberg, G., Kjartansson, O., Guethnason, V., Knopman, D., Griswold, M., Windham, B., Gottesman, R., Mosley, T., Schmidt, R., Saba, Y., Schmidt, H., Takeuchi, F., Yamaguchi, S., Nabika, T., Kato, N., Rajan, K., Aggarwal, N., De Jager, P., Evans, D., Psaty, B., Rotter, J., Rice, K., Lopez, O., Liao, J., Chen, C., Cheng, C., Wong, T., Ikram, M., van der Lee, S., Amin, N., Chouraki, V., DeStefano, A., Aparicio, H., Romero, J., Maillard, P., DeCarli, C., Wardlaw, J., Hernandez, M., Luciano, M., Liewald, D., Deary, I., Starr, J., Bastin, M., Munoz Maniega, S., Slagboom, P., Beekman, M., Deelen, J., Uh, H., Lemmens, R., Brodaty, H., Wright, M., Ames, D., Boncoraglio, G., Hopewell, J., Beecham, A., Blanton, S., Wright, C., Sacco, R., Wen, W., Thalamuthu, A., Armstrong, N., Chong, E., Schofield, P., Kwok, J., van der Grond, J., Stott, D., Ford, I., Jukema, J., Vernooij, M., Hofman, A., Uitterlinden, A., van der Lugt, A., Wittfeld, K., Grabe, H., Hosten, N., von Sarnowski, B., Volker, U., Levi, C., Jimenez-Conde, J., Sharma, P., Sudlow, C., Rosand, J., Woo, D., Cole, J., Meschia, J., Slowik, A., Thijs, V., Lindgren, A., Melander, O., Grewal, R., Rundek, T., Rexrode, K., Rothwell, P., Arnett, D., Jern, C., Johnson, J., Benavente, O., Wasssertheil-Smoller, S., Lee, J., Wong, Q., Mitchell, B., Rich, S., McArdle, P., Geerlings, M., van der Graaf, Y., de Bakker, P., Asselbergs, F., Srikanth, V., Thomson, R., McWhirter, R., Moran, C., Callisaya, M., Phan, T., Rutten-Jacobs, L., Bevan, S., Tzourio, C., Mather, K., Sachdev, P., van Duijn, C., Worrall, B., Dichgans, M., Kittner, S., Markus, H., Fornage, M., Launer, L., Seshadri, S., Longstreth, W., Debette, S., Stroke Genetics Network, t., the Neurology Working Group of the Cohorts for, H., and Aging Research in Genomic Epidemiology, C.

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 x 10(-8); and LINC00539/ZDHHC20, p = 5.82 x 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 x 10(-25); p [SSBI] = 5.23 x 10(-14) for hypertension), smoking (p [BI] = 4.4 x 10(-10); p [SSBI] = 1.2 x 10(-4)), diabetes (p [BI] = 1.7 x 10(-8); p [SSBI] = 2.8 x 10(-3)), previous cardiovascular disease (p [BI] = 1.0 x 10(-18); p [SSBI] = 2.3 x 10(-7)), stroke (p [BI] = 3.9 x 10(-69); p [SSBI] = 3.2 x 10(-24)), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 x 10(-157); p [SSBI] = 3.16 x 10(-106)), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p

Published
2019

3. White Matter Lesion Progression Genome-Wide Search for Genetic Influences

Author

Hofer, E., Cavalieri, M., Bis, J.C., DeCarli, C., Fornage, M., Sigurdsson, S., Srikanth, V., Trompet, S., Verhaaren, B.F.J., Wolf, C., Yang, Q., Adams, H.H.H., Amouyel, P., Beiser, A., Buckley, B.M., Callisaya, M., Chauhan, G., Craen, A.J.M. de, Dufouil, C., Duijn, C.M. van, Ford, I., Freudenberger, P., Gottesman, R.F., Gudnason, V., Heiss, G., Hofman, A., Lumley, T., Martinez, O., Mazoyer, B., Moran, C., Niessen, W.J., Phan, T., Psaty, B.M., Satizabal, C.L., Sattar, N., Schilling, S., Shibata, D.K., Slagboom, P.E., Smith, A., Stott, D.J., Taylor, K.D., Thomson, R., Toglhofer, A.M., Tzourio, C., Buchem, M. van, Wang, J., Westendorp, R.G.J., Windham, B.G., Vernooij, M.W., Zijdenbos, A., Beare, R., Debette, S., Ikram, M.A., Jukema, J.W., Launer, L.J., Longstreth, W.T., Mosley, T.H., Seshadri, S., Schmidt, H., Schmidt, R., and Cohorts Heart Aging Res Genomic Ep

Subjects
Adult, Male, Aging, Clinical Sciences, Cardiorespiratory Medicine and Haematology, Cardiovascular, Cohort Studies, Leukoencephalopathies, Clinical Research, Genetics, Humans, magnetic resonance imaging, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Prospective Studies, Aetiology, Aged, Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium, Neurology & Neurosurgery, white matter lesions, Prevention, Human Genome, Neurosciences, Middle Aged, biological factors, White Matter, Disease Progression, Female, cerebral small vessel diseases, Genome-Wide Association Study
Abstract

Background and purposeWhite matter lesion (WML) progression on magnetic resonance imaging is related to cognitive decline and stroke, but its determinants besides baseline WML burden are largely unknown. Here, we estimated heritability of WML progression, and sought common genetic variants associated with WML progression in elderly participants from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.MethodsHeritability of WML progression was calculated in the Framingham Heart Study. The genome-wide association study included 7773 elderly participants from 10 cohorts. To assess the relative contribution of genetic factors to progression of WML, we compared in 7 cohorts risk models including demographics, vascular risk factors plus single-nucleotide polymorphisms that have been shown to be associated cross-sectionally with WML in the current and previous association studies.ResultsA total of 1085 subjects showed WML progression. The heritability estimate for WML progression was low at 6.5%, and no single-nucleotide polymorphisms achieved genome-wide significance (P

Published
2015

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