Elucidating the etiology of cryptogenic stroke with human genetics

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Ischemic stroke is a major cause of disability and mortality. Following occurrence of an ischemic stroke event, efforts are focused on identifying the underlying etiology so as to apply targeted secondary prevention. Despite the advancements in diagnosis, the etiology of ischemic stroke remains unknown in up to one third of the events. Clinical trials have shown no benefits of treatments beyond aspirin for secondary prevention in patients with cryptogenic stroke. Thus, these patients remain without a specific prophylactic treatment, although they carry a similar risk of recurrence as patients with other stroke subtypes. Observational studies have proposed several mechanisms as potential explanations for cryptogenic stroke including occult non-stenotic atherosclerotic lesions and paroxysmal atrial fibrillation. Still, such studies are biased because of confounding and reverse causation. Human genetics provide a window for a deeper exploration of the etiology of cryptogenic stroke. Specifically, combining multiple sources of genomic data enables the exploration of correlations between two or more phenotypes at the genetic level, the discovery of novel genetic loci involved in the pathophysiology of multiple diseases, the assessment of causal associations between risk factors and disease outcomes, and the identification of novel drug targets. In previous studies we applied these methodologies to inform the etiology of stroke subtypes including large artery, cardioembolic, and small vessel stroke. The current application aims at providing novel insights into the etiology of cryptogenic stroke by leveraging large-scale human genetic data. Specifically, I will explore (i) the genetic overlap of cryptogenic stroke with other ischemic stroke subtypes; (ii) genes commonly predisposing to cryptogenic stroke and other ischemic stroke subtypes; (iii) the associations of genetic predisposition to carotid atherosclerosis, atrial fibrillation, and cerebral small vessel disease with cryptogenic stroke; (iv) the associations of conventional vascular risk factors with cryptogenic stroke; and (v) the effects of genetic proxies for anticoagulant drug targets on cryptogenic stroke. To achieve these aims, I will use human genetic data from 16,851 cases of ischemic stroke and 32,473 stroke-free controls in the SiGN project (Boston, USA) and combine them with novel data from 3,759 ischemic stroke cases from the Munich Stroke Cohort to maximize power. Several different computational methods will be used including GWAS analyses, LD regression analyses, polygenic risk scores, pairwise GWASs, and Mendelian randomization. This project with enhance our understanding of cryptogenic stroke by generating new hypotheses about its etiology and will inform the design of future trials testing the efficacy of new diagnostic approaches for identifying the cause of cryptogenic stroke, as well as trials testing secondary preventive approaches in patients with cryptogenic stroke.