Abstract
Cerebral small vessel disease (cSVD) is a leading cause of ischaemic and haemorrhagic stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI but does not manifest as clinical stroke, is highly prevalent in the general population, particularly with increasing age. Advances in technologies and collaborative work have led to substantial progress in the identification of common genetic variants that are associated with cSVD-related stroke (ischaemic and haemorrhagic) and MRI-defined covert cSVD. In this Review, we provide an overview of collaborative studies — mostly genome-wide association studies (GWAS) — that have identified >50 independent genetic loci associated with the risk of cSVD. We describe how these associations have provided novel insights into the biological mechanisms involved in cSVD, revealed patterns of shared genetic variation across cSVD traits, and shed new light on the continuum between rare, monogenic and common, multifactorial cSVD. We consider how GWAS summary statistics have been leveraged for Mendelian randomization studies to explore causal pathways in cSVD and provide genetic evidence for drug effects, and how the combination of findings from GWAS with gene expression resources and drug target databases has enabled identification of putative causal genes and provided proof-of-concept for drug repositioning potential. We also discuss opportunities for polygenic risk prediction, multi-ancestry approaches and integration with other omics data.
Key points
-
Fifty-two independent genetic loci have been associated with cerebral small vessel disease (cSVD) at the genome-wide significance level, including loci associated with cSVD-related stroke and loci associated with covert, MRI-defined cSVD.
-
In silico functional explorations of the observed genetic associations point to a major role of blood pressure-related pathways and mechanisms independent of vascular risk factors, such as extracellular matrix structure and function.
-
Transcriptome-wide association studies have provided evidence for associations between one or several genes at a cSVD risk locus and the corresponding cSVD traits, enabling prioritization of putative causal genes for functional follow-up.
-
Mendelian randomization studies have been conducted to investigate the causal link between various factors and cSVD-related phenotypes; a dedicated systematic review and meta-analysis is required to confirm some causal relationships.
-
Preliminary results provide proof-of-concept that cSVD genomics can inform therapeutic strategies by providing genetic evidence for drug effects, indicating pathways with therapeutic relevance and revealing potential for drug repositioning.
-
Use of high-throughput molecular approaches, such as epigenomics, transcriptomics, proteomics and metabolomics, will enable integration of genetic associations with functional data to decipher the biological roles of genetic risk loci in cSVD.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Deep learning based on susceptibility-weighted MR sequence for detecting cerebral microbleeds and classifying cerebral small vessel disease
BioMedical Engineering OnLine Open Access 17 October 2023
-
Excessive salt intake accelerates the progression of cerebral small vessel disease in older adults
BMC Geriatrics Open Access 02 May 2023
-
Genomics of perivascular space burden unravels early mechanisms of cerebral small vessel disease
Nature Medicine Open Access 17 April 2023
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout



References
Seshadri, S. & Wolf, P. A. Lifetime risk of stroke and dementia: current concepts, and estimates from the Framingham study. Lancet Neurol. 6, 1106–1114 (2007).
Cuadrado-Godia, E. et al. Cerebral small vessel disease: a review focusing on pathophysiology, biomarkers, and machine learning strategies. J. Stroke 20, 302–320 (2018).
Wardlaw, J. M., Smith, C. & Dichgans, M. Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging. Lancet Neurol. 12, 483–497 (2013).
Greenberg, S. M. Small vessels, big problems. N. Engl. J. Med. 354, 1451–1453 (2006).
Feigin, V. L., Lawes, C. M. M., Bennett, D. A., Barker-Collo, S. L. & Parag, V. Worldwide stroke incidence and early case fatality reported in 56 population-based studies: a systematic review. Lancet Neurol. 8, 355–369 (2009).
Mozaffarian, D. et al. Heart disease and stroke statistics–2015 update: a report from the American Heart Association. Circulation 131, e29–e322 (2015).
Alber, J. et al. White matter hyperintensities in vascular contributions to cognitive impairment and dementia (VCID): knowledge gaps and opportunities. Alzheimers Dement. 5, 107–117 (2019).
Gladman, J. T. et al. Vascular contributions to cognitive impairment and dementia: research consortia that focus on etiology and treatable targets to lessen the burden of dementia worldwide. Alzheimers Dement. 5, 789–796 (2019).
Viswanathan, A., Rocca, W. A. & Tzourio, C. Vascular risk factors and dementia: how to move forward? Neurology 72, 368–374 (2009).
Kapasi, A., DeCarli, C. & Schneider, J. A. Impact of multiple pathologies on the threshold for clinically overt dementia. Acta Neuropathol. 134, 171–186 (2017).
Bos, D. et al. Cerebral small vessel disease and the risk of dementia: a systematic review and meta-analysis of population-based evidence. Alzheimers Dement. 14, 1482–1492 (2018).
Wardlaw, J. M., Smith, C. & Dichgans, M. Small vessel disease: mechanisms and clinical implications. Lancet Neurol. 18, 684–696 (2019). An in-depth overview of the current knowledge of mechanisms of small vessel disease.
Wardlaw, J. M. et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol. 12, 822–838 (2013).
Debette, S. & Markus, H. S. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 341, c3666 (2010).
Maxwell, S. S. et al. Genetic associations with brain microbleeds: systematic review and meta-analyses. Neurology 77, 158–167 (2011).
Duperron, M.-G. et al. Burden of dilated perivascular spaces, an emerging marker of cerebral small vessel disease, is highly heritable. Stroke 49, 282–287 (2018).
Dubost, F. et al. Enlarged perivascular spaces in brain MRI: automated quantification in four regions. NeuroImage 185, 534–544 (2019).
van Veluw, S. J. et al. Detection, risk factors, and functional consequences of cerebral microinfarcts. Lancet Neurol. 16, 730–740 (2017).
van Veluw, S. J. et al. Different microvascular alterations underlie microbleeds and microinfarcts. Ann. Neurol. 86, 279–292 (2019).
Baykara, E. et al. A novel imaging marker for small vessel disease based on skeletonization of white matter tracts and diffusion histograms: novel SVD imaging marker. Ann. Neurol. 80, 581–592 (2016).
Persyn, E. et al. Genome-wide association study of MRI markers of cerebral small vessel disease in 42,310 participants. Nat. Commun. 11, 2175 (2020).
Rutten-Jacobs, L. C. A. et al. Genetic study of white matter integrity in UK biobank (N=8448) and the overlap with stroke, depression, and dementia. Stroke 49, 1340–1347 (2018).
Debette, S., Schilling, S., Duperron, M.-G., Larsson, S. C. & Markus, H. S. Clinical significance of magnetic resonance imaging markers of vascular brain injury: a systematic review and meta-analysis. JAMA Neurol. 76, 81–94 (2019).
Georgakis, M. K., Duering, M., Wardlaw, J. M. & Dichgans, M. WMH and long-term outcomes in ischemic stroke: a systematic review and meta-analysis. Neurology 92, e1298–e1308 (2019).
Nelson, M. R. et al. The support of human genetic evidence for approved drug indications. Nat. Genet. 47, 856–860 (2015).
Okada, Y. et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 376–381 (2014).
Mancuso, M. et al. Monogenic cerebral small-vessel diseases: diagnosis and therapy. Consensus recommendations of the European Academy of Neurology. Eur. J. Neurol. 27, 909–927 (2020). Updated recommendations for the management of monogenic cSVD.
Marini, S., Anderson, C. D. & Rosand, J. Genetics of cerebral small vessel disease. Stroke 51, 12–20 (2020).
Falcone, G. J., Malik, R., Dichgans, M. & Rosand, J. Current concepts and clinical applications of stroke genetics. Lancet Neurol. 13, 405–418 (2014).
Traylor, M. et al. Genetic architecture of lacunar stroke. Stroke 46, 2407–2412 (2015).
Woo, D. et al. Meta-analysis of genome-wide association studies identifies 1q22 as a susceptibility locus for intracerebral hemorrhage. Am. J. Hum. Genet. 94, 511–521 (2014).
Marini, S. et al. 17p12 influences hematoma volume and outcome in spontaneous intracerebral hemorrhage. Stroke 49, 1618–1625 (2018).
Chung, J. et al. Genome-wide association study of cerebral small vessel disease reveals established and novel loci. Brain 142, 3176–3189 (2019).
Traylor, M. et al. Genetic basis of lacunar stroke: a pooled analysis of individual patient data and genome-wide association studies. Lancet Neurol. 20, 351–361 (2021). The largest GWAS of lacunar stroke in which a multi-trait approach is used with white matter hyperintensities to discover additional lacunar stroke loci.
von Berg, J. et al. Alternate approach to stroke phenotyping identifies a genetic risk locus for small vessel stroke. Eur. J. Hum. Genet. 28, 963–972 (2020).
Malik, R. et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat. Genet. 50, 524–537 (2018). The largest multi-ancestry GWAS meta-analysis of stroke and its subtypes; few loci were associated with small vessel stroke but follow-up bioinformatics analyses provided insights into the genetics of cSVD.
Traylor, M. et al. Genetic variation at 16q24.2 is associated with small vessel stroke. Ann. Neurol. 81, 383–394 (2017).
NINDS Stroke Genetics Network & International Stroke Genetics Consortium. Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study. Lancet Neurol. 15, 174–184 (2016).
Rajajee, V. et al. Diagnosis of lacunar infarcts within 6 hours of onset by clinical and CT criteria versus MRI. J. Neuroimaging 18, 66–72 (2008).
Turley, P. et al. Multi-trait analysis of genome-wide association summary statistics using MTAG. Nat. Genet. 50, 229–237 (2018).
Zhu, Z. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016).
Gusev, A. et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet. 48, 245–252 (2016).
Giambartolomei, C. et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014).
Sargurupremraj, M., Suzuki, H., Jian, X., Fornage, M. & Debette, S. Cerebral small vessel disease genomics and its implications across the lifespan. Nat. Commun. 11, 6285 (2020). The largest GWAS of WMHs, accounting for interaction with hypertension, providing important insights into the lifetime impact of genetic risk of cSVD.
Bin, B. H. et al. Molecular pathogenesis of spondylocheirodysplastic Ehlers-Danlos syndrome caused by mutant ZIP13 proteins. EMBO Mol. Med. 6, 1028–1042 (2014).
Ho, H. T., Dahlin, A. & Wang, J. Expression profiling of solute carrier gene families at the blood-CSF barrier. Front. Pharmacol. 3, 154 (2012).
Kusuhara, H. & Sugiyama, Y. Active efflux across the blood-brain barrier: role of the solute carrier family. NeuroRx 2, 73–85 (2005).
Geier, E. G. et al. Profiling solute carrier transporters in the human blood-brain barrier. Clin. Pharmacol. Ther. 94, 636–639 (2013).
Wang, W. W., Gallo, L., Jadhav, A., Hawkins, R. & Parker, C. G. The druggability of solute carriers. J. Med. Chem. 63, 3834–3867 (2020).
Liu, M., Xu, P., O’Brien, T. & Shen, S. Multiple roles of Ulk4 in neurogenesis and brain function. Neurogenesis 4, e1313646 (2017).
Liu, M. et al. Ulk4 deficiency leads to hypomyelination in mice. Glia 66, 175–190 (2018).
Humphreys, C. A., Smith, C. & Wardlaw, J. M. Correlations in post‐mortem imaging‐histopathology studies of sporadic human cerebral small vessel disease: a systematic review. Neuropathol. Appl. Neurobiol. https://doi.org/10.1111/nan.12737 (2021).
Rajani, R. M. et al. Characterisation of early ultrastructural changes in the cerebral white matter of CADASIL small vessel disease using high-pressure freezing/freeze-substitution. Neuropathol. Appl. Neurobiol. 47, 694–704 (2021).
Hadano, S. et al. A gene encoding a putative GTPase regulator is mutated in familial amyotrophic lateral sclerosis 2. Nat. Genet. 29, 166–173 (2001).
Bindesbøll, C. et al. NBEAL1 controls SREBP2 processing and cholesterol metabolism and is a susceptibility locus for coronary artery disease. Sci. Rep. 10, 4528 (2020).
Biffi, A. et al. Variants at APOE influence risk of deep and lobar intracerebral hemorrhage. Ann. Neurol. 68, 934–943 (2010).
Rannikmäe, K. et al. Common variation in COL4A1/COL4A2 is associated with sporadic cerebral small vessel disease. Neurology 84, 918–926 (2015).
Rannikmäe, K. et al. COL4A2 is associated with lacunar ischemic stroke and deep ICH: meta-analyses among 21,500 cases and 40,600 controls. Neurology 89, 1829–1839 (2017).
Pelletier, A. et al. Age-related modifications of diffusion tensor imaging parameters and white matter hyperintensities as inter-dependent processes. Front. Aging Neurosci. 7, 255 (2015).
Traylor, M. et al. Genome-wide meta-analysis of cerebral white matter hyperintensities in patients with stroke. Neurology 86, 146–153 (2016).
Armstrong, N. J. et al. Common genetic variation indicates separate causes for periventricular and deep white matter hyperintensities. Stroke 51, 2111–2121 (2020).
Fornage, M. et al. Genome-wide association studies of cerebral white matter lesion burden: the CHARGE consortium. Ann. Neurol. 69, 928–939 (2011).
Verhaaren, B. F. J. et al. Multiethnic genome-wide association study of cerebral white matter hyperintensities on MRI. Circ. Cardiovasc. Genet. 8, 398–409 (2015).
Knol, M. J. et al. Association of common genetic variants with brain microbleeds: a genome-wide association study. Neurology 95, e3331–e3343 (2020).
Chauhan, G. et al. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting. Neurology 95, e3331–e3343 (2019).
Gonzalez, C. E. et al. Peripheral sphingolipids are associated with variation in white matter microstructure in older adults. Neurobiol. Aging 43, 156–163 (2016).
Sun, N., Keep, R. F., Hua, Y. & Xi, G. Critical role of the sphingolipid pathway in stroke: a review of current utility and potential therapeutic targets. Transl. Stroke Res. 7, 420–438 (2016).
Ohi, K. et al. DEGS2 polymorphism associated with cognition in schizophrenia is associated with gene expression in brain. Transl. Psychiatry 5, e550 (2015).
Wallis, M. et al. Surprisingly good outcome in antenatal diagnosis of severe hydrocephalus related to CCDC88C deficiency. Eur. J. Med. Genet. 61, 189–196 (2018).
Jia, L., Piña-Crespo, J. & Li, Y. Restoring Wnt/β-catenin signaling is a promising therapeutic strategy for Alzheimer’s disease. Mol. Brain 12, 104 (2019).
Couffinhal, T., Dufourcq, P. & Duplàa, C. β-catenin nuclear activation. Circ. Res. 99, 1287–1289 (2006).
Guo, F. et al. Canonical Wnt signaling in the oligodendroglial lineage–puzzles remain. Glia 63, 1671–1693 (2015).
Zody, M. C. et al. Evolutionary toggling of the MAPT 17q21.31 inversion region. Nat. Genet. 40, 1076–1083 (2008).
Hyde, C. L. et al. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat. Genet. 48, 1031–1036 (2016).
Ikeda, M. et al. Genome-wide association study detected novel susceptibility genes for schizophrenia and shared trans-populations/diseases genetic effect. Schizophr. Bull. 45, 824–834 (2019).
Kouri, N. et al. Genome-wide association study of corticobasal degeneration identifies risk variants shared with progressive supranuclear palsy. Nat. Commun. 6, 7247 (2015).
Kunkle, B. W. et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat. Genet. 51, 414–430 (2019).
Pain, O. et al. Novel insight into the etiology of autism spectrum disorder gained by integrating expression data with genome-wide association statistics. Biol. Psychiatry 86, 265–273 (2019).
Simón-Sánchez, J. et al. Genome-wide association study reveals genetic risk underlying Parkinson’s disease. Nat. Genet. 41, 1308–1312 (2009).
Davies, G. et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nat. Commun. 9, 2098 (2018).
Koolen, D. A. et al. A new chromosome 17q21.31 microdeletion syndrome associated with a common inversion polymorphism. Nat. Genet. 38, 999–1001 (2006).
Lee, J. J. et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50, 1112–1121 (2018).
Sanchez-Roige, S. et al. Genome-wide association study meta-analysis of the alcohol use disorders identification test (AUDIT) in two population-based cohorts. Am. J. Psychiatry 176, 107–118 (2019).
Ikram, M. A. et al. Common variants at 6q22 and 17q21 are associated with intracranial volume. Nat. Genet. 44, 539–544 (2012).
Jonsson, B. A. et al. Brain age prediction using deep learning uncovers associated sequence variants. Nat. Commun. 10, 5409 (2019).
Zhao, B. et al. Common genetic variation influencing human white matter microstructure. Science 372, eabf3736 (2021).
Barbu, M. C. et al. Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging. Transl. Psychiatry 10, 55 (2020). Analysis of unexplored relationships between gene expression and heritable in vivo measures of human brain structural connectivity by combining expression quantitative trait loci and genome-wide genotype data.
Boettger, L. M., Handsaker, R. E., Zody, M. C. & McCarroll, S. A. Structural haplotypes and recent evolution of the human 17q21.31 region. Nat. Genet. 44, 881–885 (2012).
Steinberg, K. M. et al. Structural diversity and African origin of the 17q21.31 inversion polymorphism. Nat. Genet. 44, 872–880 (2012).
Tabara, Y. et al. Association of Chr17q25 with cerebral white matter hyperintensities and cognitive impairment: the J-SHIPP study. Eur. J. Neurol. 20, 860–862 (2013).
Verhaaren, B. F. J. et al. Replication study of chr17q25 with cerebral white matter lesion volume. Stroke 42, 3297–3299 (2011).
Adib-Samii, P. et al. 17q25 locus is associated with white matter hyperintensity volume in ischemic stroke, but not with lacunar stroke status. Stroke 44, 1609–1615 (2013).
Jian, X. et al. Exome chip analysis identifies low-frequency and rare variants in MRPL38 for white matter hyperintensities on brain magnetic resonance imaging. Stroke 49, 1812–1819 (2018).
Hara, K. et al. Association of HTRA1 mutations and familial ischemic cerebral small-vessel disease. N. Engl. J. Med. 360, 1729–1739 (2009).
Dabertrand, F. et al. Potassium channelopathy-like defect underlies early-stage cerebrovascular dysfunction in a genetic model of small vessel disease. Proc. Natl Acad. Sci. USA 112, E796–E805 (2015).
Joutel, A., Haddad, I., Ratelade, J. & Nelson, M. T. Perturbations of the cerebrovascular matrisome: a convergent mechanism in small vessel disease of the brain? J. Cereb. Blood Flow. Metab. 36, 143–157 (2016). A description of the concept that cerebrovascular matrisome perturbations are a convergent pathological pathway in monogenic SVD and are likely to be relevant in cSVD.
Naba, A. et al. The matrisome: in silico definition and in vivo characterization by proteomics of normal and tumor extracellular matrices. Mol. Cell. Proteom. 11, M111.014647 (2012).
Mehta, P. & Piao, X. Adhesion G-protein coupled receptors and extracellular matrix proteins: roles in myelination and glial cell development. Dev. Dyn. 246, 275–284 (2017).
Monk, K. R., Oshima, K., Jörs, S., Heller, S. & Talbot, W. S. Gpr126 is essential for peripheral nerve development and myelination in mammals. Development 138, 2673–2680 (2011).
Chang, A. et al. Cortical remyelination: a new target for repair therapies in multiple sclerosis. Ann. Neurol. 72, 918–926 (2012).
Diamantopoulou, E. et al. Identification of compounds that rescue otic and myelination defects in the zebrafish adgrg6 (gpr126) mutant. eLife 8, e44889 (2019).
Paavola, K. J., Sidik, H., Zuchero, J. B., Eckart, M. & Talbot, W. S. Type IV collagen is an activating ligand for the adhesion G protein-coupled receptor GPR126. Sci. Signal. 7, ra76 (2014).
Rajani, R. M. et al. Reversal of endothelial dysfunction reduces white matter vulnerability in cerebral small vessel disease in rats. Sci. Transl. Med. 10, eaam9507 (2018).
Corder, E. H. et al. Protective effect of apolipoprotein E type 2 allele for late onset Alzheimer disease. Nat. Genet. 7, 180–184 (1994).
Jun, G. R. et al. Transethnic genome-wide scan identifies novel Alzheimer’s disease loci. Alzheimers Dement. 13, 727–738 (2017).
Maddison, D. C. & Giorgini, F. The kynurenine pathway and neurodegenerative disease. Semin. Cell Dev. Biol. 40, 134–141 (2015).
Strang, K. H., Golde, T. E. & Giasson, B. I. MAPT mutations, tauopathy, and mechanisms of neurodegeneration. Lab. Invest. 99, 912–928 (2019).
Harold, D. et al. Interaction between the ADAM12 and SH3MD1 genes may confer susceptibility to late-onset Alzheimer’s disease. Am. J. Med. Genet. B Neuropsychiatr. Genet. 144B, 448–452 (2007).
Okbay, A. et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat. Genet. 48, 624–633 (2016).
Wu, Y. et al. Identification of the primate-specific gene BTN3A2 as an additional schizophrenia risk gene in the MHC loci. EBioMedicine 44, 530–541 (2019).
Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).
Evangelou, E. et al. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat. Genet. 50, 1412–1425 (2018).
Xue, A. et al. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nat. Commun. 9, 2941 (2018).
Willer, C. J. et al. Discovery and refinement of loci associated with lipid levels. Nat. Genet. 45, 1274–1283 (2013).
Wootton, R. E. et al. Evidence for causal effects of lifetime smoking on risk for depression and schizophrenia: a Mendelian randomisation study. Psychol. Med. 50, 2435–2443 (2020).
Liberzon, A. et al. Molecular signatures database (MSigDB) 3.0. Bioinformatics 27, 1739–1740 (2011).
Holliday, E. G. et al. Genetic overlap between diagnostic subtypes of ischemic stroke. Stroke 46, 615–619 (2015).
Mishra, A. et al. Association of variants in HTRA1 and NOTCH3 with MRI-defined extremes of cerebral small vessel disease in older subjects. Brain 142, 1009–1023 (2019). In this study, whole-exome sequencing in a population-based setting provided evidence that a composite, extreme MRI-derived phenotype for cSVD is useful for identification of rare variants, adding to evidence that NOTCH3 mutations that cause CADASIL are more common than previously suspected.
Narayan, S. K., Gorman, G., Kalaria, R. N., Ford, G. A. & Chinnery, P. F. The minimum prevalence of CADASIL in northeast England. Neurology 78, 1025–1027 (2012).
Razvi, S. S. M., Davidson, R., Bone, I. & Muir, K. W. The prevalence of cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy (CADASIL) in the west of Scotland. J. Neurol. Neurosurg. Psychiatry 76, 739–741 (2005).
Verdura, E. et al. Heterozygous HTRA1 mutations are associated with autosomal dominant cerebral small vessel disease. Brain 138, 2347–2358 (2015).
Siitonen, M. et al. Multi-infarct dementia of Swedish type is caused by a 3’UTR mutation of COL4A1. Brain 140, e29 (2017).
Lemmens, R. et al. Novel COL4A1 mutations cause cerebral small vessel disease by haploinsufficiency. Hum. Mol. Genet. 22, 391–397 (2013).
Li, J. et al. Replication of top loci from COL4A1/2 associated with white matter hyperintensity burden in patients with ischemic stroke. Stroke 51, 3751–3755 (2020).
Malik, R. et al. Genome-wide meta-analysis identifies 3 novel loci associated with stroke: MEGASTROKE and UK Biobank GWAS. Ann. Neurol. 84, 934–939 (2018).
Simon, A. J. et al. Mutations in STN1 cause Coats plus syndrome and are associated with genomic and telomere defects. J. Exp. Med. 213, 1429–1440 (2016).
Schmidt, H. et al. Genetic variants of the NOTCH3 gene in the elderly and magnetic resonance imaging correlates of age-related cerebral small vessel disease. Brain 134, 3384–3397 (2011).
Rutten, J. W. et al. Archetypal NOTCH3 mutations frequent in public exome: implications for CADASIL. Ann. Clin. Transl. Neurol. 3, 844–853 (2016).
Rutten, J. W. et al. Broad phenotype of cysteine-altering NOTCH3 variants in UK Biobank: CADASIL to nonpenetrance. Neurology 95, e1835–e1843 (2020).
Cho, B. P. H. et al. NOTCH3 variants are more common than expected in the general population and associated with stroke and vascular dementia: an analysis of 200 000 participants. J. Neurol. Neurosurg. Psychiatry 92, 694–701 (2021). Using UK Biobank data, this study provides evidence that NOTCH3 mutations that cause CADASIL are more common than expected in the general population and describes their phenotypic spectrum.
Chauhan, G. et al. Identification of additional risk loci for stroke and small vessel disease: a meta-analysis of genome-wide association studies. Lancet Neurol. 15, 695–707 (2016). This study identified a novel risk locus for any stroke and subclinical cerebral small vessel disease in a population-based setting, with experimental follow-up in mice and zebrafish implicating FOXF2.
French, C. R. et al. Mutation of FOXC1 and PITX2 induces cerebral small-vessel disease. J. Clin. Invest. 124, 4877–4881 (2014).
Whitesell, T. R. et al. foxc1 is required for embryonic head vascular smooth muscle differentiation in zebrafish. Dev. Biol. 453, 34–47 (2019).
Siegenthaler, J. A. et al. Foxc1 is required by pericytes during fetal brain angiogenesis. Biol. Open 2, 647–659 (2013).
Reyahi, A. et al. Foxf2 is required for brain pericyte differentiation and development and maintenance of the blood-brain barrier. Dev. Cell 34, 19–32 (2015).
He, W. et al. FOXF2 acts as a crucial molecule in tumours and embryonic development. Cell Death Dis. 11, 424 (2020).
Smith, G. D. & Ebrahim, S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int. J. Epidemiol. 32, 1–22 (2003).
Georgakis, M. K. et al. Genetically determined blood pressure, antihypertensive drug classes, and risk of stroke subtypes. Neurology 95, e353–e361 (2020).
Yuan, S., Tang, B., Zheng, J. & Larsson, S. C. Circulating lipoprotein lipids, apolipoproteins and ischemic stroke. Ann. Neurol. 88, 1229–1236 (2020).
Georgakis, M. K. et al. Genetic determinants of blood lipids and cerebral small vessel disease: role of high-density lipoprotein cholesterol. Brain 143, 597–610 (2020).
Falcone, G. J. et al. Genetically elevated LDL associates with lower risk of intracerebral hemorrhage. Ann. Neurol. 88, 56–66 (2020).
Valdes-Marquez, E. et al. Relative effects of LDL-C on ischemic stroke and coronary disease: a Mendelian randomization study. Neurology 92, e1176–e1187 (2019).
Pan, Y., Li, H., Wang, Y. & Meng, X. Causal effect of Lp(a) [lipoprotein(a)] level on ischemic stroke and Alzheimer disease: a Mendelian randomization study. Stroke 50, 3532–3539 (2019).
Georgakis, M. K. et al. Diabetes mellitus, glycemic traits, and cerebrovascular disease: a Mendelian randomization study. Neurology 96, e1732–e1742 (2021).
Larsson, S. C. et al. Type 2 diabetes, glucose, insulin, BMI, and ischemic stroke subtypes: Mendelian randomization study. Neurology 89, 454–460 (2017).
Liu, J., Rutten-Jacobs, L., Liu, M., Markus, H. S. & Traylor, M. Causal impact of type 2 diabetes mellitus on cerebral small vessel disease: a Mendelian randomization analysis. Stroke 49, 1325–1331 (2018).
Lu, H., Wu, P. F., Li, R. Z., Zhang, W. & Huang, G. X. Sleep duration and stroke: a Mendelian randomization study. Front. Neurol. 11, 976 (2020).
Dale, C. E. et al. Causal associations of adiposity and body fat distribution with coronary heart disease, stroke subtypes, and type 2 diabetes mellitus: a Mendelian randomization analysis. Circulation 135, 2373–2388 (2017).
Marini, S. et al. Mendelian randomization study of obesity and cerebrovascular disease. Ann. Neurol. 87, 516–524 (2020).
Qian, Y. et al. Coffee consumption and risk of stroke: a Mendelian randomization study. Ann. Neurol. 87, 525–532 (2020).
Wang, M. et al. Higher tea consumption is associated with decreased risk of small vessel stroke. Clin. Nutr. 40, 1430–1435 (2021).
Qian, Y. et al. Role of cigarette smoking in the development of ischemic stroke and its subtypes: a Mendelian randomization study. Clin. Epidemiol. 11, 725–731 (2019).
Larsson, S. C., Burgess, S. & Michaëlsson, K. Smoking and stroke: a mendelian randomization study. Ann. Neurol. 86, 468–471 (2019).
Harshfield, E. L., Georgakis, M. K., Malik, R., Dichgans, M. & Markus, H. S. Modifiable lifestyle factors and risk of stroke: a Mendelian randomization analysis. Stroke 52, 931–936 (2021).
Wang, T. et al. Birth weight and stroke in adult life: genetic correlation and causal inference with genome-wide association data sets. Front. Neurosci. 14, 479 (2020).
Cai, H. et al. Major depression and small vessel stroke: a Mendelian randomization analysis. J. Neurol. 266, 2859–2866 (2019).
Maners, J. et al. A Mendelian randomization of γ’ and total fibrinogen levels in relation to venous thromboembolism and ischemic stroke. Blood 136, 3062–3069 (2020).
Georgakis, M. K. et al. Genetically determined levels of circulating cytokines and risk of stroke. Circulation 139, 256–268 (2019). This study demonstrates how Mendelian randomization can be used to provide evidence for causal involvement of circulating biomarkers for stroke (MCP-1), leveraging summary data from GWAS.
Lin, J., Wang, Y. & Pan, Y. Inflammatory biomarkers and risk of ischemic stroke and subtypes: a 2-sample Mendelian randomization study. Neurol. Res. 42, 118–125 (2020).
Yuan, S., Lin, A., He, Q. Q., Burgess, S. & Larsson, S. C. Circulating interleukins in relation to coronary artery disease, atrial fibrillation and ischemic stroke and its subtypes: a two-sample Mendelian randomization study. Int. J. Cardiol. 313, 99–104 (2020).
Larsson, S. C., Traylor, M. & Markus, H. S. Homocysteine and small vessel stroke: a Mendelian randomization analysis. Ann. Neurol. 85, 495–501 (2019).
Mulvey, B., Lagunas, T. & Dougherty, J. D. Massively parallel reporter assays: defining functional psychiatric genetic variants across biological contexts. Biol. Psychiatry 89, 76–89 (2021).
Sanseau, P. et al. Use of genome-wide association studies for drug repositioning. Nat. Biotechnol. 30, 317–320 (2012).
Gill, D. et al. Use of genetic variants related to antihypertensive drugs to inform on efficacy and side effects. Circulation 140, 270–279 (2019). In this study, genetic variants were used to explore the efficacy and side effects of different antihypertensive drug classes for stroke prevention, providing proof-of-concept that genomic data can provide genetic support for drug effects.
Wardlaw, J. M. et al. ESO guideline on covert cerebral small vessel disease. Eur. Stroke J. 6, CXI–CLXII (2021).
Abraham, G. & Inouye, M. Genomic risk prediction of complex human disease and its clinical application. Curr. Opin. Genet. Dev. 33, 10–16 (2015).
Habes, M. et al. The brain chart of aging: machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans. Alzheimers Dement. 17, 89–102 (2021).
Abraham, G. et al. Genomic prediction of coronary heart disease. Eur. Heart J. 37, 3267–3278 (2016).
Escott-Price, V., Shoai, M., Pither, R., Williams, J. & Hardy, J. Polygenic score prediction captures nearly all common genetic risk for Alzheimer’s disease. Neurobiol. Aging 49, 214.e7–214.e11 (2017).
Lambert, S. A., Abraham, G. & Inouye, M. Towards clinical utility of polygenic risk scores. Hum. Mol. Genet. 28, R133–R142 (2019).
Khera, A. V. et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 50, 1219–1224 (2018).
Abraham, G. et al. Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke. Nat. Commun. 10, 5819 (2019). Abraham et al. developed a new polygenic risk score (PRS) approach based on the combination of PRS from various traits (metaGRS) and applied it to predict ischaemic stroke in the UK biobank.
Khera, A. V. et al. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N. Engl. J. Med. 375, 2349–2358 (2016).
Mok, V. et al. Race-ethnicity and cerebral small vessel disease–comparison between Chinese and White populations. Int. J. Stroke 9(Suppl A100), 36–42 (2014).
Keene, K. L. et al. Genome-wide association study meta-analysis of stroke in 22 000 individuals of African descent identifies novel associations with stroke. Stroke 51, 2454–2463 (2020).
Carty, C. L. et al. Meta-analysis of genome-wide association studies identifies genetic risk factors for stroke in African Americans. Stroke 46, 2063–2068 (2015).
Márquez-Luna, C., Loh, P. R. & Price, A. L. Multiethnic polygenic risk scores improve risk prediction in diverse populations. Genet. Epidemiol. 41, 811–823 (2017).
Montaner, J. et al. Multilevel omics for the discovery of biomarkers and therapeutic targets for stroke. Nat. Rev. Neurol. 16, 247–264 (2020).
Woo, D. et al. Top research priorities for stroke genetics. Lancet Neurol. 17, 663–665 (2018).
Adams, H. P. Jr et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke 24, 35–41 (1993).
Ay, H. et al. A computerized algorithm for etiologic classification of ischemic stroke: the Causative Classification of Stroke System. Stroke 38, 2979–2984 (2007).
Lin, M. K. et al. HTRA1, an age-related macular degeneration protease, processes extracellular matrix proteins EFEMP1 and TSP1. Aging Cell 17, e12710 (2018).
Zagryazhskaya-Masson, A. et al. Intersection of TKS5 and FGD1/CDC42 signaling cascades directs the formation of invadopodia. J. Cell Biol. 219, e201910132 (2020).
Leonardo, C. C., Eakin, A. K., Ajmo, J. M. & Gottschall, P. E. Versican and brevican are expressed with distinct pathology in neonatal hypoxic-ischemic injury. J. Neurosci. Res. 86, 1106–1114 (2008).
Menezes, M. J. et al. The extracellular matrix protein laminin α2 regulates the maturation and function of the blood-brain barrier. J. Neurosci. 34, 15260–15280 (2014).
Fukada, T. et al. The zinc transporter SLC39A13/ZIP13 is required for connective tissue development; its involvement in BMP/TGF-β signaling pathways. PLoS ONE 3, e3642 (2008).
Yoneshiro, T. et al. BCAA catabolism in brown fat controls energy homeostasis through SLC25A44. Nature 572, 614–619 (2019).
Bowden, J. & Holmes, M. V. Meta-analysis and Mendelian randomization: a review. Res. Synth. Methods 10, 486–496 (2019).
Burgess, S. & Thompson, S. G. Avoiding bias from weak instruments in Mendelian randomization studies. Int. J. Epidemiol. 40, 755–764 (2011).
Hemani, G., Bowden, J. & Davey Smith, G. Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum. Mol. Genet. 27, R195–R208 (2018).
Pierce, B. L., Ahsan, H. & Vanderweele, T. J. Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int. J. Epidemiol. 40, 740–752 (2011).
Acknowledgements
We thank S. Schilling for her editorial assistance. S.D. is supported by a grant overseen by the French National Research Agency (ANR) as part of the “Investment for the Future Programme” ANR-18-RHUS-0002, by the EU Joint Programme–Neurodegenerative Disease Research (JPND), and by funding from the European Research Council (ERC) and the European Union Horizon 2020 research and innovation programme under grant agreement numbers 643417, 640643, 667375, and 754517.
Review criteria
For our literature review, we searched PubMed for papers published between January 2007 and March 2021. We focused on this period because we chose to focus on genome-wide association studies (GWAS), which were not available at earlier time points in the field of cerebral small vessel disease (cSVD). We considered only genetic associations with common cSVD phenotypes that reached genome-wide significance (P < 5 × 10−8). When several genome-wide significant associations on the same locus were reported in several GWAS, we present the lead single nucleotide polymorphism (SNP) and association statistics of the GWAS performed on the largest sample size (largest number of cases for binary traits) but still report references of the other publications. Where several genome-wide significant associations with different SNPs have been identified in the same locus, we report only those that correspond to independent signals (linkage disequilibrium r² < 0.1); for correlated SNPs (r² > 0.1), we selected the SNP with the lowest P value (if reported in the same study) or that from the GWAS performed on the largest sample size (if reported in two different studies). Results of candidate gene association studies were included if the studies were large (n > 500), robust methodology was used and the findings complement or support GWAS findings. Only peer-reviewed papers in English were considered. For Mendelian randomization studies, we searched the literature for publications that relate to cSVD phenotypes and include Mendelian randomization in the title or abstract. We also systematically screened all published GWAS of cSVD-related phenotypes for Mendelian randomization analyses.
Author information
Authors and Affiliations
Contributions
C.B. researched data for the article. All authors made substantial contributions to discussion of the content, wrote the article and edited and/or reviewed the manuscript before submission.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Peer review information
Nature Reviews Neurology thanks A. Joutel, R. Kalaria and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Related links
CoSTREAM: http://www.costream.eu/
Discovery: https://discoverystudy.org/
MarkVCID: https://markvcid.partners.org/
SHIVA: https://rhu-shiva.com/
Glossary
- White matter hyperintensity (WMH) of presumed vascular origin
-
An abnormality of variable size in the white matter seen on MRI as a hyperintensity on T2-weighted images, such as fluid-attenuated inversion recovery, but as isointense or hypointense on T1-weighted images (although not as hypointense as cerebrospinal fluid).
- Lacunes of presumed vascular origin
-
A subcortical, round, fluid-filled cavity (3–15 mm diameter, of similar signal to cerebrospinal fluid) consistent with a previous acute small subcortical infarct or haemorrhage in the territory of one perforating arteriole.
- Cerebral microbleeds
-
A small area (usually 2–5 mm in diameter) that appears as a signal void with associated blooming on T2*-weighted MRI or susceptibility-weighted imaging, which is likely to mostly reflect vascular leakage of blood cells.
- Perivascular spaces
-
Fluid-filled spaces that surround perforating vessels in the brain, with a signal intensity similar to that of cerebrospinal fluid on all MRI sequences (diameter generally smaller than 3 mm).
- Genetic variants
-
A specific region of the genome that differs between individuals in the population.
- Alleles
-
Two or more versions of a polymorphic genetic site; for single nucleotide polymorphisms, alleles correspond to two alternative nucleotides at the given position.
- Fractional anisotropy
-
A scalar measure derived from diffusion tensor imaging that quantifies the overall directionality of water diffusion in brain tissue. The measure is greatest in organized white matter tracts and lowest in the case of free water movement, such as in cerebrospinal fluid. Reduced fractional anisotropy in white matter is seen in cerebral small vessel disease.
- Mean diffusivity
-
A scalar measure obtained from diffusion tensor imaging that quantifies the magnitude of water diffusion regardless of the direction. It is used to study microstructural properties and the structural integrity of brain tissue. Increased mean diffusivity in white matter is seen in cerebral small vessel disease.
- Linkage disequilibrium
-
The non-random association of alleles at two nearby genetic loci, reflecting haplotypes that descend from a common ancestor.
- Inversion polymorphism
-
A type of DNA structural variant that changes the orientation of a genomic segment.
- Single nucleotide polymorphisms
-
A single nucleotide variation in the DNA sequence.
- Pleiotropy
-
A phenomenon in which genes or genetic variants affect multiple, apparently unrelated, phenotypes.
Rights and permissions
About this article
Cite this article
Bordes, C., Sargurupremraj, M., Mishra, A. et al. Genetics of common cerebral small vessel disease. Nat Rev Neurol 18, 84–101 (2022). https://doi.org/10.1038/s41582-021-00592-8
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41582-021-00592-8
This article is cited by
-
Deep learning based on susceptibility-weighted MR sequence for detecting cerebral microbleeds and classifying cerebral small vessel disease
BioMedical Engineering OnLine (2023)
-
Excessive salt intake accelerates the progression of cerebral small vessel disease in older adults
BMC Geriatrics (2023)
-
Brain and spinal cord arteriolosclerosis and its associations with cerebrovascular disease risk factors in community-dwelling older adults
Acta Neuropathologica (2023)
-
Presumed periventricular venous infarction on magnetic resonance imaging and its association with increased white matter edema in CADASIL
European Radiology (2023)
-
Progress on Prevention and Treatment of Cerebral Small Vascular Disease Using Integrative Medicine
Chinese Journal of Integrative Medicine (2023)