Brain connectome-based prediction of cognitive performance in patients with type 2 diabetes

Motivation: Address the common issue of cognitive decline in type 2 diabetes (T2D) patients, lacking a simple cognitive assessment method. Goal(s): Use a connectome-based prediction model (CPM) to identify neurobiological patterns linked to cognitive performance in T2D patients. Approach: CPM was used with leave-one-out cross-validation on a training cohort of 592 T2D patients and validated the model on two independent sets. Results: CPM successfully predicted cognitive performance, showing replicability. We found differences in network strengths between T2D with and without MCI, indicated high diagnostic potential for MCI. In a treatment sample, the model indicated changes in network strength linked to cognitive improvement. Impact: The whole-brain functional network strengths could serve as a potential neural biomarker of global cognitive performance in T2D.