Impact of Conventional Stroke Risk Factors on Early- and Late-Onset Ischemic Stroke: A Mendelian Randomization Study

Stroke incidence is decreasing in older ages but increasing in young adults. These divergent trends are at least partially attributable not only to diverging trends in stroke risk factors but may also be due to differences in the impact of stroke risk factors at different ages. To address this latter possibility, we used Mendelian randomization to assess differences in the association of stroke risk factors between early-onset ischemic stroke ([EOS]; onset 18-59 years) and late-onset ischemic stroke ([LOS]; onset ≥60 years).

We identified genetic variants from the GWAS Catalog for use as instrumental variables to proxy conventional stroke risk factors and then estimated the effects of these variants on risk factors in younger and older individuals in the UK Biobank. We then used these estimates to estimate the causal effects of stroke risk factors on EOS (n=6728 cases) and LOS (n=9272) cases from SiGN (Stroke Genetic Network) and the EOSC (Early-Onset Stroke Consortium). Lastly, we compared odds ratios between EOS and LOS, stratified by TOAST (Trial of ORG 10172 in Acute Stroke Treatment) subtypes, to determine if differences between estimates could be attributed to differences in stroke subtype distributions.

EOS was associated with higher levels of body mass index, blood pressure, type 2 diabetes, and lower levels of HDL (high-density lipoprotein) cholesterol (all P≤0.002), whereas LOS was associated with higher levels of systolic blood pressure (P=0.0001). The causal effect of body mass index on stroke was significantly stronger for EOS than for LOS (odds ratio, 1.26 versus 1.03; P=0.008). After the subtype-stratified analysis, the difference in causal effect sizes between EOS and LOS for body mass index diminished and was no longer significant.

These results support a causal relationship between body mass index, blood pressure, type 2 diabetes, and HDL cholesterol levels with EOS and blood pressure levels in LOS. Interventions that target these traits may reduce stroke risk.