Sex-driven modifiers of Alzheimer risk: A multimodality brain imaging study. (14th July 2020)

• Record Type: Journal Article
• Authors: Rahman, Aneela; Schelbaum, Eva; Hoffman, Katherine; Diaz, Ivan; Hristov, Hollie; Andrews, Randolph; Jett, Steven; Jackson, Hande; Lee, Andrea; Sarva, Harini; Pahlajani, Silky; Matthews, Dawn; Dyke, Jonathan; de Leon, Mony J.; Isaacson, Richard S.; Brinton, Roberta D.; Mosconi, Lisa
• Is Part Of: Neurology. Volume 95:Number 2(2020)
• Publication Date: 2020-07-14
• Subjects: Neurology -- Periodicals; Neurology -- Periodicals; Neurologie -- Périodiques; 616.8
• DOI: 10.1212/WNL.0000000000009781
• Languages: English
• ISSNs: 0028-3878

Abstract

Abstract : Objective: To investigate sex differences in late-onset Alzheimer disease (AD) risks by means of multimodality brain biomarkers (β-amyloid load via 11 C-Pittsburgh compound B [PiB] PET, neurodegeneration via 18 F-fluorodeoxyglucose [FDG] PET and structural MRI). Methods: We examined 121 cognitively normal participants (85 women and 36 men) 40 to 65 years of age with clinical, laboratory, neuropsychological, lifestyle, MRI, FDG- and PiB-PET examinations. Several clinical (e.g., age, education, APOE status, family history), medical (e.g., depression, diabetes mellitus, hyperlipidemia), hormonal (e.g., thyroid disease, menopause), and lifestyle AD risk factors (e.g., smoking, diet, exercise, intellectual activity) were assessed. Statistical parametric mapping and least absolute shrinkage and selection operator regressions were used to compare AD biomarkers between men and women and to identify the risk factors associated with sex-related differences. Results: Groups were comparable on clinical and cognitive measures. After adjustment for each modality-specific confounders, the female group showed higher PiB β-amyloid deposition, lower FDG glucose metabolism, and lower MRI gray and white matter volumes compared to the male group ( p < 0.05, family-wise error corrected for multiple comparisons). The male group did not show biomarker abnormalities compared to the female group. Results were independent of age and remained significant with the use of age-matched groups. Second to female sex, menopausal status was the predictor most consistently and strongly associated with the observed brain biomarker differences, followed by hormone therapy, hysterectomy status, and thyroid disease. Conclusion: Hormonal risk factors, in particular menopause, predict AD endophenotype in middle-aged women. These findings suggest that the window of opportunity for AD preventive interventions in women is early in the endocrine aging process.