Sex-driven modifiers of Alzheimer’s risk: a multi-modality brain imaging study
Rahman, Aneela et al. (2021), Sex-driven modifiers of Alzheimer’s risk: a multi-modality brain imaging study, Dryad, Dataset, https://doi.org/10.5061/dryad.zgmsbcc6g
Objective: To investigate sex differences in late-onset Alzheimer’s disease (AD) risks by means of multi-modality brain biomarkers [β-amyloid load via 11C-PiB PET, and neurodegeneration via 18F-FDG PET and structural MRI].
Methods: We examined 121 cognitively normal participants [85 women and 36 men] ages 40-65, with clinical, laboratory, neuropsychological, lifestyle exams, and MRI, FDG- and PiB-PET exams. Several clinical (e.g. age, education, APOE status, family history), medical (e.g., depression, diabetes, 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 LASSO 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. Adjusting 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, FWE-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 using 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-preventative interventions in women is early in the endocrine aging process.