Functional connectome‐based prediction of individual clinical and cognitive scores in midlife population with risk of dementia

Abstract

AbstractBackgroundIt is well acknowledged that Alzheimer’s Disease (AD) neuropathology start decades before clinical manifestations, but the brain mechanism of sporadic AD in midlife remains unclear. Resting‐state functional connectivity (FC) is increasingly used to understand early brain changes in Alzheimer’s disease (AD) (Sperling, 2011; van den Heuvel & Sporns, 2019). We asked whether risk for late‐life dementia impacts functional connectivity in cognitively healthy middle‐aged individuals.MethodFunctional Magnetic Resonance Imaging and detailed neuropsychological assessments were obtained for 585 (207/378 female/male) cognitively healthy individuals, aged 40‐59 years (mean = 50.9), from the PREVENT‐Dementia study. Dementia risk was calculated with the Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) score. A novel connectome‐based predictive method called NBS‐Predict was used to investigate the association between FC and CAIDE score and its role in cognition.ResultFC significantly predicted CAIDE scores across the whole cohort (r = 0.207, p < 0.001). FC within and between the cingulo‐opercular network (CON) and sensorimotor network (SMN), as well as between CON and fronto‐parietal network (FPN), and between SMN with default mode network (DMN), and FPN contributed the most (Figure 1). Furthermore, we found that, in the high dementia risk group (CAIDE > 6) only, FC, mainly in DMN‐SMN and DMN‐CON (Figure 2), significantly predicted multisensory processing cognitive score (r = 0.114, p<0.05).ConclusionOur results show that FC can be used to detect early brain changes associated with risk of future dementia in cognitively healthy individuals. This method has implications of the early detection of dementia in preclinical populations.