To determine the combined polygenic effect of the major vascular risk factors on treatment failure and secondary vascular events after stroke.
Stroke patients are at risk for secondary events, but risk factor control is often insufficient. High genetic predisposition to vascular risks such as hypertension, diabetes, and hyperlipidemia impedes effective risk factor management. The combined impact of these polygenic effects on clinical management after stroke is unknown.
In our genetic association study in stroke patients from the UK Biobank, we created polygenic risk scores (PRS) for systolic blood pressure, diabetes, and LDL from genome-wide association summary statistics. We added them to a metaPRS of overall genetic risk for all three risk factors, categorized into low, intermediate, and high (<20th, 20-80th, >80th percentiles). Baseline outcomes were uncontrolled (at least one of: systolic blood pressure >140mmHg, HbA1c >7.0%, or LDL >100mg/dl) and resistant risk factors (uncontrolled despite treatment). Cross-sectional outcomes were recurrent stroke, myocardial infarction, and all-cause death. We performed logistic regressions adjusted to age, sex, and genetic principal components to assess the impact of metaPRS on outcomes.
In 6,290 stroke patients (mean age 61, female sex 42%), high polygenic risk was associated with 37% increase in uncontrolled (OR 1.37, 95% CI 1.16-1.63) and a 2-fold increase in resistant risk factors (OR 2.09, 95% CI 1.77-2.48). Poor risk factor control translated into clinical outcomes: high polygenic risk was associated with a 21% increase of recurrent stroke (OR 1.21, 95% CI 0.99-1.48), 58% increase of myocardial infarction (OR 1.58,95% CI 1.13-2.23), 31% increase of death (OR 1.31,95% CI 1.07-1.60).
In our study, aggregate polygenic vascular risk correlates with poor risk factor control and treatment resistance in stroke patients, but also with recurrent stroke, myocardial infarction, and death. Further research should evaluate the benefit of tailored therapies for stroke survivors with adverse genomic profiles.