Polygenic Stroke Risk and Autoimmune Disease: Associations and Clinical Modifiers

Area of Science:

• Genetics
• Immunology
• Neurology

Background:

• Polygenic risk scores (PRSs) aid complex disease prediction.
• Autoimmune diseases may alter stroke risk and genetic prediction utility.
• Distinct inflammatory profiles can influence disease susceptibility.

Purpose of the Study:

• To assess if PRSs differentially improve 10-year stroke prediction in individuals with and without autoimmune diseases.
• To quantify the added value of genetic information in distinct clinical subgroups.
• To explore interactions between genetic and immune-mediated risk factors for stroke.

Main Methods:

• Utilized UK Biobank data to identify individuals with prevalent autoimmune diseases.
• Modeled 10-year incident stroke using logistic regression, gradient boosting, and XGBoost.
• Compared prediction error between non-genetic and PRS-inclusive models to quantify PRS contribution.

Main Results:

• Elevated baseline stroke risk in autoimmune disease patients reduced the incremental predictive benefit of PRSs.
• Confirmed established links between immune-mediated disease and cerebrovascular risk.
• Identified subgroups where PRS inclusion improved or worsened stroke prediction accuracy.

Conclusions:

• Genetic risk prediction's utility is context-dependent, influenced by clinical factors like autoimmune status.
• This approach quantifies interactions between genetic and immune-mediated risk.
• Highlights the need to consider individual clinical profiles when applying PRSs for disease risk assessment.