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: This study was based on two cohorts; one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the other from the Sino Longitudinal Study on Cognitive Decline (SILCODE). Each subject underwent [F-18] fluoro-2-deoxyglucose positron emission tomography (PET) and [F-18]florbetapir-PET imaging. Participants were binary-grouped based on p-amyloid (AB) status, and the positivity was defined as A beta+. 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: Forty-eight A beta+ NCs and 48 A beta- NCs were included in the ADNI cohort, and 25 A beta+ NCs and 30 A beta- NCs were included in the SILCODE cohort. The ARADRPs were identified from the combined cohorts and the two separate cohorts, characterized by relatively lower regional loadings in the posterior parts of the precuneus, posterior cingulate, and regions of the temporal gyms, as well as relatively higher values in the superior/middle frontal gyms and other areas. Patterns identified from the two separate cohorts showed some regional differences, including the temporal gyms, basal ganglia regions, anterior parts of the precuneus, and middle cingulate. Cross-validation suggested that the pattern expression score was significantly higher in the A beta+ group of both cohorts (p < 0.01), and contributed to the diagnosis of A beta+ NCs (with area under the curve values of 0.696-0.815). The correlation analysis revealed that the score was related to tau pathology measured in cere-brospinal fluid (p-tau: p < 0.02; t-tau: p < 0.03), but not A beta pathology assessed with [F-18]florbetapir-PET > 0.23). Conclusions: ARADRP exists for NCs, and the acquired pattern expression score shows a certain ability to discriminate A beta+ NCs from A beta- NCs. The SSM/PCA method is expected to be helpful in the ultra-early diagnosis of AD in clinical practice.