Probability of Alzheimer's disease in breast cancer survivors based on gray-matter structural network efficiency

Abstract

Introduction: Breast cancer chemotherapy is associated with accelerated aging and potentially increased risk for Alzheimer's disease (AD).

Methods: We calculated the probability of AD diagnosis from brain network and demographic and genetic data obtained from 47 female AD converters and 47 matched healthy controls. We then applied this algorithm to data from 78 breast cancer survivors.

Results: The classifier discriminated between AD and healthy controls with 86% accuracy (P < .0001). Chemotherapy-treated breast cancer survivors demonstrated significantly higher probability of AD compared to healthy controls (P < .0001) and chemotherapy-naïve survivors (P = .007), even after stratifying for apolipoprotein e4 genotype. Chemotherapy-naïve survivors also showed higher AD probability compared to healthy controls (P = .014).

Discussion: Chemotherapy-treated breast cancer survivors who have a particular profile of brain structure may have a higher risk for AD, especially those who are older and have lower cognitive reserve.

Keywords: Alzheimer's disease; Breast cancer; Chemotherapy; Connectome; MRI.

Fig. 1

Random forest classification of Alzheimer's disease (AD) converters and healthy female controls. Mean decrease in Gini index of features retained by the final model. Higher mean decrease in Gini index indicates greater importance of that feature in the model. +/− indicates the direction of the relationship of the feature with AD class, for example, lower total brain volume was associated with AD class. Abbreviation: APOE4 = apolipoprotein ɛ4 genotype.

Fig. 2

Alzheimer's disease (AD) probability. The chemotherapy group demonstrated significantly higher AD probability compared to chemotherapy-naïve and healthy female (HF) groups even after stratifying for apolipoprotein (APOE) ɛ4 genotype.