Unraveling Mechanisms of Cryptogenic Stroke at the Genetic Level: A Systematic Literature Review

BackgroundA substantial proportion of ischemic strokes remain cryptogenic, which has important implications for secondary prevention. Identifying genetic variants related to mechanisms of stroke causes may provide a chance to clarify the actual causes of cryptogenic strokes. Methods and ResultsIn a 2-step process, 2 investigators independently and systematically screened studies that reported genetic variants in regard to stroke causes that were published between January 1991 and April 2021. Studies on monogenetic disorders, investigation of vascular risk factors as the primary end point, reviews, meta-analyses, and studies not written in English were excluded. We extracted information on study types, ancestries, corresponding single nucleotide polymorphisms, and sample and effect sizes. There were 937 studies screened, and 233 were eligible. We identified 35 single nucleotide polymorphisms and allele variants that were associated with an overlap between cryptogenic strokes and another defined cause. ConclusionsAssociations of single variants with an overlap between cryptogenic stroke and another defined cause were limited to a few polymorphisms. A limitation of all studies is a low granularity of clinical data, which is of major importance in a complex disease such as stroke. Deep phenotyping is in supposed contradiction with large sample sizes but needed for genome-wide analyses. Future studies should attempt to address this restriction to advance the promising approach of elucidating the cause of stroke at the genetic level. Especially in a highly heterogenous disease such as ischemic stroke, genetics are promising to establish a personalized approach in diagnostics and treatment in the sense of precision medicine.

Automated summary

In this study, researchers identified the genetic variants associated with cryptogenic strokes by screening relevant research. However, the associations were limited to a few polymorphisms. Future studies should address the limitation of low granularity in clinical data to advance the promising approach of elucidating stroke causes at the genetic level.