Extending understanding of the genetic architecture of cerebral small vessel disease using advanced imaging measures in UK Biobank

Abstract

AbstractCerebral small vessel disease (cSVD) is a leading cause of stroke and a major contributor to cognitive decline and dementia in the population (Debette JAMA Neurol 2019). 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. Large collaborative genomic studies through consortia like CHARGE or ISGC have led to substantial progress in the identification of common genetic variants that are associated with cSVD. In this presentation, we will provide an overview of such collaborative studies, prominently involving the unique UK Biobank resource, that have recently extended our understanding of the genetic architecture of cSVD, revealing over 70 independent loci associated with this condition, especially with MRI‐markers of cSVD (Bordes, Nat Rev Neurol 2022; Duperron, Nat Med AIP). In silico functional explorations of the observed genetic associations point to a major role of blood pressure‐related pathways, but also mechanisms independent of vascular risk factors, such as extracellular matrix, membrane transport, vascular development, myelination, and blood‐brain barrier. Leveraging next‐generation sequencing data in UK Biobank and other resources, these studies also shed new light on the continuum between monogenic and multifactorial cSVD, with several genes (HTRA1, COLA4) harboring both rare mutations and common variants contributing to the disease (Mishra, Brain 2019). Further, we recently showed that MRI‐cSVD risk loci identified in middle‐ and older age in UK Biobank and other cohorts are associated with white matter microstructure on diffusion imaging (DTI, NODDI) and perivascular space burden already in young adults in their twenties (e.g. at VCAN, OPA1, SLC13A3) suggesting that processes contributing to cSVD may find their root much earlier in life than previously thought (Duperron, Nat Med AIP; Sargurupremraj, Nat Commun. 2020). We provide preliminary insights on how these association patterns change across the adult lifespan and discuss how this can inform dementia prevention, including, in combination with other omics resources, for proof‐of‐concept genomics‐driven drug discovery (Duperron, Nat Med AIP; Mishra, Nature. 2022; Mishra, Brain. 2022).