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Cited by 94Intracerebral and Subarachnoid Hemorrhage ResearchCerebrovascular and genetic disordersGenetic Associations and Epidemiology

Association of common genetic variants with brain microbleeds: a genome-wide association study

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Knol, Maria J., Lu, Dongwei, Traylor, Matthew, Adams, Hieab H.H., Romero, José Rafael J., Smith, Albert V., Fornage, Myriam, Hofer, Edith +56 more·2020·Neurology
DOI 10.1212/wnl.0000000000010852PMC PMC7836652
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Abstract

Objective To identify common genetic variants associated with the presence of brain microbleeds (BMBs). Methods We performed genome-wide association studies in 11 population-based cohort studies and 3 case–control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of APOE ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs. Results BMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR]any BMB [95% confidence interval (CI)] 1.33 [1.21–1.45]; p = 2.5 × 10−10). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19–1.50]; p = 1.0 × 10−6) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86–1.25]; p = 0.68). APOE ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB. Conclusions Genetic variants in the APOE region are associated with the presence of BMB, most likely due to the APOE ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.

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  1. [1]Wardlaw JM, Smith EE, Biessels GJ, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol 2013; 12: 822– 838. 23867200 PMC3714437
  2. [2]Poels MM, Vernooij MW, Ikram MA, et al. Prevalence and risk factors of cerebral microbleeds: an update of the Rotterdam Scan Study. Stroke 2010; 41: S103– S106. 20876479
  3. [3]Debette S, Schilling S, Duperron MG, Larsson SC, Markus HS. Clinical significance of magnetic resonance imaging markers of vascular brain injury: a systematic review and meta-analysis. JAMA Neurol 2019; 76: 81– 94. 30422209 PMC6439887
  4. [4]Wilson D, Ambler G, Lee KJ, et al. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies. Lancet Neurol 2019; 18: 653– 665. 31130428 PMC6562236
  5. [5]Wang Z, Soo YO, Mok VC. Cerebral microbleeds: is antithrombotic therapy safe to administer? Stroke 2014; 45: 2811– 2817. 25028449
  6. [6]Vernooij MW, van der Lugt A, Ikram MA, et al. Prevalence and risk factors of cerebral microbleeds: the Rotterdam Scan Study. Neurology 2008; 70: 1208– 1214. 18378884
  7. [7]van Rooden S, van der Grond J, van den Boom R, et al. Descriptive analysis of the Boston criteria applied to a Dutch-type cerebral amyloid angiopathy population. Stroke 2009; 40: 3022– 3027. 19556530
  8. [8]Akoudad S, Portegies ML, Koudstaal PJ, et al. Cerebral microbleeds are associated with an increased risk of stroke: the Rotterdam Study. Circulation 2015; 132: 509– 516. 26137955
  9. [9]Biffi A, Sonni A, Anderson CD, et al. Variants at APOE influence risk of deep and lobar intracerebral hemorrhage. Ann Neurol 2010; 68: 934– 943. 21061402 PMC3058266
  10. [10]Traylor M, Tozer DJ, Croall ID, et al. Genetic variation in PLEKHG1 is associated with white matter hyperintensities (n = 11,226). Neurology 2019; 92: e749– e757. 30659137 PMC6396967
  11. [11]Verhaaren BF, Debette S, Bis JC, et al. Multiethnic genome-wide association study of cerebral white matter hyperintensities on MRI. Circ Cardiovasc Genet 2015; 8: 398– 409. 25663218 PMC4427240
  12. [12]Maxwell SS, Jackson CA, Paternoster L, et al. Genetic associations with brain microbleeds: systematic review and meta-analyses. Neurology 2011; 77: 158– 167. 21715706 PMC3140069
  13. [13]Li HQ, Cai WJ, Hou XH, et al. Genome-wide association study of cerebral microbleeds on MRI. Neurotox Res 2020; 37: 146– 155. 31209788
  14. [14]Psaty BM, O'Donnell CJ, Gudnason V, et al. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: design of prospective meta-analyses of genome-wide association studies from 5 cohorts. Circ Cardiovasc Genet 2009; 2: 73– 80. 20031568 PMC2875693
  15. [15]Traylor M, Zhang CR, Adib-Samii P, et al. Genome-wide meta-analysis of cerebral white matter hyperintensities in patients with stroke. Neurology 2016; 86: 146– 153. 26674333 PMC4731688
  16. [17]Nandigam RN, Viswanathan A, Delgado P, et al. MR imaging detection of cerebral microbleeds: effect of susceptibility-weighted imaging, section thickness, and field strength. AJNR Am J Neuroradiol 2009; 30: 338– 343. 19001544 PMC2760298
  17. [18]Cheng AL, Batool S, McCreary CR, et al. Susceptibility-weighted imaging is more reliable than T2*-weighted gradient-recalled echo MRI for detecting microbleeds. Stroke 2013; 44: 2782– 2786. 23920014
  18. [19]Goos JD, van der Flier WM, Knol DL, et al. Clinical relevance of improved microbleed detection by susceptibility-weighted magnetic resonance imaging. Stroke 2011; 42: 1894– 1900. 21566235
  19. [20]Ding J, Sigurethsson S, Jonsson PV, et al. Space and location of cerebral microbleeds, cognitive decline, and dementia in the community. Neurology 2017; 88: 2089– 2097. 28468844 PMC5447401
  20. [21]Kantarci K, Gunter JL, Tosakulwong N, et al. Focal hemosiderin deposits and beta-amyloid load in the ADNI cohort. Alzheimers Dement 2013; 9: S116– S123. 23375568 PMC3770782
  21. [22]Qiu C, Cotch MF, Sigurdsson S, et al. Retinal and cerebral microvascular signs and diabetes: the Age, Gene/Environment Susceptibility–Reykjavik Study. Diabetes 2008; 57: 1645– 1650. 18332097
  22. [23]Roob G, Lechner A, Schmidt R, Flooh E, Hartung HP, Fazekas F. Frequency and location of microbleeds in patients with primary intracerebral hemorrhage. Stroke 2000; 31: 2665– 2669. 11062292
  23. [24]Graff-Radford J, Simino J, Kantarci K, et al. Neuroimaging correlates of cerebral microbleeds: the ARIC Study (Atherosclerosis Risk in Communities). Stroke 2017; 48: 2964– 2972. 29018129 PMC5685663
  24. [25]Wilson D, Ambler G, Shakeshaft C, et al. Cerebral microbleeds and intracranial haemorrhage risk in patients anticoagulated for atrial fibrillation after acute ischaemic stroke or transient ischaemic attack (CROMIS-2): a multicentre observational cohort study. Lancet Neurol 2018; 17: 539– 547. 29778365 PMC5956310
  25. [26]Cordonnier C, Potter GM, Jackson CA, et al. Improving interrater agreement about brain microbleeds: development of the Brain Observer MicroBleed Scale (BOMBS). Stroke 2009; 40: 94– 99. 19008468
  26. [27]Romero JR, Preis SR, Beiser A, et al. Risk factors, stroke prevention treatments, and prevalence of cerebral microbleeds in the Framingham Heart Study. Stroke 2014; 45: 1492– 1494. 24713533 PMC4048617
  27. [28]Wardlaw JM, Bastin ME, Valdes Hernandez MC, et al. Brain aging, cognition in youth and old age and vascular disease in the Lothian Birth Cohort 1936: rationale, design and methodology of the imaging protocol. Int J Stroke 2011; 6: 547– 559. 22111801
  28. [29]Altmann-Schneider I, van der Grond J, Slagboom PE, et al. Lower susceptibility to cerebral small vessel disease in human familial longevity: the Leiden Longevity Study. Stroke 2013; 44: 9– 14. 23160879
  29. [30]Altmann-Schneider I, Trompet S, de Craen AJ, et al. Cerebral microbleeds are predictive of mortality in the elderly. Stroke 2011; 42: 638– 644. 21233474
  30. [33]Ward LD, Kellis M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res 2012; 40: D930– D934. 22064851 PMC3245002
  31. [34]Xue A, Wu Y, Zhu Z, et al. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nat Commun 2018; 9: 2941. 30054458 PMC6063971
  32. [35]Warren HR, Evangelou E, Cabrera CP, et al. Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk. Nat Genet 2017; 49: 403. 28135244 PMC5972004
  33. [36]Yengo L, Sidorenko J, Kemper KE, et al. Meta-analysis of genome-wide association studies for height and body mass index in approximately 700000 individuals of European ancestry. Hum Mol Genet 2018; 27: 3641– 3649. 30124842 PMC6488973
  34. [37]Surakka I, Horikoshi M, Magi R, et al. The impact of low-frequency and rare variants on lipid levels. Nat Genet 2015; 47: 589– 597. 25961943 PMC4757735
  35. [38]Traylor M, Malik R, Nalls MA, et al. Genetic variation at 16q24.2 is associated with small vessel stroke. Ann Neurol 2017; 81: 383– 394. 27997041 PMC5366092
  36. [39]Rannikmäe K, Sivakumaran V, Millar H, et al. COL4A2 is associated with lacunar ischemic stroke and deep ICH: meta-analyses among 21,500 cases and 40,600 controls. Neurology 2017; 89: 1829– 1839. 28954878 PMC5664302
  37. [41]Malik R, Chauhan G, Traylor M, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet 2018; 50: 524– 537. 29531354 PMC5968830
  38. [42]Malik R, Rannikmae K, Traylor M, et al. Genome-wide meta-analysis identifies 3 novel loci associated with stroke. Ann Neurol 2018; 84: 934– 939. 30383316 PMC6644297
  39. [43]Jansen IE, Savage JE, Watanabe K, et al. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk. Nat Genet 2019; 51: 404– 413. 30617256 PMC6836675
  40. [44]Georgakis MK, Malik R, Anderson CD, Parhofer KG, Hopewell JC, Dichgans M. Genetic determinants of blood lipids and cerebral small vessel disease: role of high-density lipoprotein cholesterol. Brain 2020; 143: 597– 610. 31968102 PMC7009571
  41. [45]Wieberdink RG, Poels MM, Vernooij MW, et al. Serum lipid levels and the risk of intracerebral hemorrhage: the Rotterdam Study. Arterioscler Thromb Vasc Biol 2011; 31: 2982– 2989. 21921260
  42. [46]Ding J, Sigurdsson S, Garcia M, et al. Risk factors associated with incident cerebral microbleeds according to location in older people: the Age, Gene/Environment Susceptibility (AGES)–Reykjavik Study. JAMA Neurol 2015; 72: 682– 688. 25867544 PMC4698002
  43. [47]Bonaventure A, Kurth T, Pico F, et al. Triglycerides and risk of hemorrhagic stroke vs. ischemic vascular events: the Three-City Study. Atherosclerosis 2010; 210: 243– 248. 19963214
  44. [48]Sturgeon JD, Folsom AR, Longstreth WT Jr, Shahar E, Rosamond WD, Cushman M. Risk factors for intracerebral hemorrhage in a pooled prospective study. Stroke 2007; 38: 2718– 2725. 17761915
  45. [49]Traylor M, Rutten-Jacobs LC, Thijs V, et al. Genetic associations with white matter hyperintensities confer risk of lacunar stroke. Stroke 2016; 47: 1174– 1179. 27073246 PMC4839546
  46. [50]Chung J, Marini S, Pera J, et al. Genome-wide association study of cerebral small vessel disease reveals established and novel loci. Brain 2019; 142: 3176– 3189. 31430377 PMC6763741
  47. [51]Caselli RJ, Reiman EM, Osborne D, et al. Longitudinal changes in cognition and behavior in asymptomatic carriers of the APOE e4 allele. Neurology 2004; 62: 1990– 1995. 15184602
  48. [52]Charidimou A, Kakar P, Fox Z, Werring DJ. Cerebral microbleeds and recurrent stroke risk: systematic review and meta-analysis of prospective ischemic stroke and transient ischemic attack cohorts. Stroke 2013; 44: 995– 1001. 23493732
  49. [53]Copenhaver BR, Hsia AW, Merino JG, et al. Racial differences in microbleed prevalence in primary intracerebral hemorrhage. Neurology 2008; 71: 1176– 1182. 18838665 PMC2676986
  50. [54]Kakar P, Charidimou A, Werring DJ. Cerebral microbleeds: a new dilemma in stroke medicine. JRSM Cardiovasc Dis 2012; 1: 2048004012474754. 24175079 PMC3738371

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Authors
Knol, M. J., Lu, D., Traylor, M., Adams, H. H. H., Romero, J. R. J., Smith, A. V., Fornage, M., Hofer, E., Liu, J., Hostettler, I. C., Luciano, M., Trompet, S., Giese, A.-K., Hilal, S., van den Akker, E. B., Vojinovic, D., Li, S., Sigurdsson, S., van der Lee, S. J., Jack, C. R., Wilson, D., Yilmaz, P., Satizabal, C. L., Liewald, D. C. M., van der Grond, J., Chen, C., Saba, Y., van der Lugt, A., Bastin, M. E., Windham, B. G., Cheng, C. Y., Pirpamer, L., Kantarci, K., Himali, J. J., Yang, Q., Morris, Z., Beiser, A. S., Tozer, D. J., Vernooij, M. W., Amin, N., Beekman, M., Koh, J. Y., Stott, D. J., Houlden, H., Schmidt, R., Gottesman, R. F., MacKinnon, A. D., DeCarli, C., Gudnason, V., Deary, I. J., van Duijn, C. M., Slagboom, P. E., Wong, T. Y., Rost, N. S., Jukema, J. W., Mosley, T. H., Werring, D. J., Schmidt, H., Wardlaw, J. M., Ikram, M. A., Seshadri, S., Launer, L. J., Markus, H. S., & Initiative, F. T. A. D. N.
Affiliations
University of Cambridge (GB)
Corresponding author
  • Launer, Lenore J.
  • Markus, Hugh S.
ORCID
Venue
Neurology
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2020-12-15
Volume
95
Issue
24
Pages
e3331-e3343
ISSN
  • 0028-3878 (ISSN-L)
  • 1526-632X
DOI
10.1212/wnl.0000000000010852
PMC
PMC7836652
OpenAlex
W3085741005
Cited by
94
References
4
Citations by year
2026: 15 · 2025: 15 · 2024: 25 · 2023: 18 · 2022: 17 · 2021: 3 · 2020: 1
FWCI
4.16
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Neurology (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
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  • Minerva Access (University of Melbourne) (submittedVersion, cc-by-nc-nd)
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  • Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, public-domain)
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  • DRYAD (public-domain)
Funders
  • Barts Charity (MGU0284)
  • National Institute for Health and Care Research (NF-SI-0512-10019, NF-SI-0617-10006, NF-SI-0512-10113, NF-SI-0617-10154)
  • British Heart Foundation (RG/16/4/32218)
  • European Commission (667375)
  • Agence Nationale de la Recherche (ANR-17-EURE-0019)
  • ZonMw (916.19.151)
  • Medical Research Council (MC_PC_14089, MC_EX_MR/M009203/1, MR/R024065/1)
  • National Institute on Aging (U01AG052409, R01AG054076, RF1AG059421, P30AG066546)
Topics
  • Health Sciences › Medicine › Neurology › Intracerebral and Subarachnoid Hemorrhage Research
  • Health Sciences › Medicine › Neurology › Cerebrovascular and genetic disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
cerebral microbleeds, APOE ε4, APOE ε2, cerebral small vessel disease, genetic susceptibility, lobar microbleeds, deep intracerebral hemorrhage, lacunar stroke, genome-wide association study
MeSH terms
Aged, Aged, 80 and over, Alleles, Apolipoproteins E, Cerebral Hemorrhage, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Risk, Cohort Studies, Case-Control Studies, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Apolipoprotein E4, Apolipoprotein E2, Genome-Wide Association Study, Cerebral Small Vessel Diseases, White Matter

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