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Background <p>This study aimed to identify risk factors and develop statistical models to predict cerebral amyloid angiopathy (CAA).</p> Methods <p>Associations between demographic, cognition, cardiovascular, and AD-related neuropathology and CAA were analyzed using data from three longitudinal cohorts of aging and dementia. Logistic regression with LASSO was used for feature selection. Predictive performance was assessed using ROC-AUC and decision curve analysis (DCA). Predictor importance was quantified using Shapley Variable Importance Cloud (ShapleyVIC), which provides a robust estimate of individual feature contribution in prediction.</p> Results <p>Stratified analyses showed that the strength of association between episodic memory or tau pathology and CAA was greater in males, while the amyloid pathology-CAA association was stronger in females. Among APOE ε4 carriers, the amyloid/tau pathology-CAA associations were pronounced. Episodic memory and amyloid/tau pathology were identified as key factors in our predictive model. DCA demonstrated the model’s clinical utility, and SHAP values confirmed the importance of individual features.</p> Conclusion <p>We identified sex- and APOE-specific risk factors for CAA and developed models to support CAA risk stratification.</p>

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Sex and APOE ε4 genotype modify risk factor associations with cerebral amyloid angiopathy: a multi-cohort autopsy study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月4日

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  • Liwei Ma,
  • Yihan Wang,
  • Benjamin Goudey,
  • Liang Jin,
  • Yijun Pan

摘要

Background

This study aimed to identify risk factors and develop statistical models to predict cerebral amyloid angiopathy (CAA).

Methods

Associations between demographic, cognition, cardiovascular, and AD-related neuropathology and CAA were analyzed using data from three longitudinal cohorts of aging and dementia. Logistic regression with LASSO was used for feature selection. Predictive performance was assessed using ROC-AUC and decision curve analysis (DCA). Predictor importance was quantified using Shapley Variable Importance Cloud (ShapleyVIC), which provides a robust estimate of individual feature contribution in prediction.

Results

Stratified analyses showed that the strength of association between episodic memory or tau pathology and CAA was greater in males, while the amyloid pathology-CAA association was stronger in females. Among APOE ε4 carriers, the amyloid/tau pathology-CAA associations were pronounced. Episodic memory and amyloid/tau pathology were identified as key factors in our predictive model. DCA demonstrated the model’s clinical utility, and SHAP values confirmed the importance of individual features.

Conclusion

We identified sex- and APOE-specific risk factors for CAA and developed models to support CAA risk stratification.