Exploring brain glucose metabolic patterns in cognitively normal adults at risk of Alzheimer’s disease: A cross-validation study with Chinese and ADNI cohorts

OBJECTIVE: Disease-related metabolic brain patterns have been verified for a variety of neurodegenerative diseases including Alzheimer's disease (AD). This study aimed to explore and validate the pattern derived from cognitively normal controls (NCs) in the Alzheimer's continuum. METHODS: F]florbetapir-PET imaging. Participants were binary-grouped based on β-amyloid (Aβ) status, and the positivity was defined as Aβ+. Voxel-based scaled subprofile model/principal component analysis (SSM/PCA) was used to generate the "at-risk AD-related metabolic pattern (ARADRP)" for NCs. The pattern expression score was obtained and compared between the groups, and receiver operating characteristic curves were drawn. Notably, we conducted cross-validation to verify the robustness and correlation analyses to explore the relationships between the score and AD-related pathological biomarkers. RESULTS: F]florbetapir-PET (p > 0.23). CONCLUSIONS: ARADRP exists for NCs, and the acquired pattern expression score shows a certain ability to discriminate Aβ+ NCs from Aβ- NCs. The SSM/PCA method is expected to be helpful in the ultra-early diagnosis of AD in clinical practice.

Authors

• Tao-Ran Li
• Qiu-Yue Dong
• Xue-Yan Jiang
• Gui-Xia Kang
• Xin Li
• Yun-Yan Xie
• Jie-Hui Jiang
• Ying Han

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