Diagnosing Monogenic Stroke at Younger Age

Abstract

Background: An increasing number of monogenic conditions underlying stroke are being identified. We explored the possibilities of increasing the diagnostic yield of monogenic stroke in a population under 56 years of age.

Methods: Fifty probands ≤55 years at their first stroke episode were characterized clinically and investigated by whole genome sequencing. Probands had one or more of: (1) one or more first to second degree relatives with stroke under 60 years or same stroke-causing condition/disease; (2) no hypertension, hypercholesterolemia, diabetes, heart disease, or smoking; or (3) either multiple stroke episodes or multiple arterial dissections. Variants with minor allele frequency under 0.01, identified by using our stroke gene panels, were assessed. The stroke subtypes, including large artery atherosclerotic, large artery nonatherosclerotic (tortuosity, dolichoectasia, aneurysm, nonatherosclerotic dissection, or occlusion), cerebral small vessel disease, cardioembolic (arrhythmia, heart defect, or cardiomyopathy), coagulation dysfunctions (venous thrombosis, arterial thrombosis, or bleeding tendency), intracerebral hemorrhage, vascular malformations (cavernoma or arteriovenous malformations), metabolic disorders, or cryptogenic embolic, were used for genotype-phenotype correlation. In a final step, we combined genetic and clinical information to determine if the genetic variant likely was the cause of stroke in the patients.

Results: Whole genome sequencing of younger patients with stroke identified 17 clinically matching genetic variants in 15 of 50 (30%) patients, while a stronger clinical correlation with stroke was established in only 6 (12%) of them. Stroke-related genetic variants were identified in 4 of 5 (80%) patients with cardioembolic stroke subtype, 3 of 4 (75%) with intracerebral hemorrhage, 7 of 18 (39%) with cryptogenic embolic stroke, 1 of 6 (17%) with small vessel disease, and 3 of 15 (20%) of patients with nonatherosclerotic large artery stroke, including 1 of 11 (9%) with cervical dissection stroke.

Conclusions: Careful clinical interpretation of whole genome data using stroke gene panels can detect monogenic causes of early stroke, allowing individualized follow-up and opening new possibilities for potential treatment.

Keywords: blood coagulation disorders; genetic association studies; heart diseases; stroke; whole genome sequencing.