Functional connectome‐based prediction of individual clinical and cognitive scores in midlife population with risk of dementia
Bolin Cao, Feng Deng, Qing Qi, Graciela Muniz‐Terrera, Paresh A Malhotra, Ivan Koychev, Karen Ritchie, John T O'Brien, Craig W Ritchie, Brian Lawlor, Lorina Naci- Psychiatry and Mental health
- Cellular and Molecular Neuroscience
- Geriatrics and Gerontology
- Neurology (clinical)
- Developmental Neuroscience
- Health Policy
- Epidemiology
Abstract
Background
It 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.
Method
Functional 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.
Result
FC 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).
Conclusion
Our 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.