Dynamic network connectivity alteration predicts cognitive decline in Alzheimer’s disease spectrum

Abstract

AbstractBackgroundBrian network integrity plays a pivotal role in the regulation of high‐order cognitive function and emotion for human brain. Disrupted functional coupling within‐ and between resting‐state networks (RSNs) are selectively vulnerable for neurodegenerative disease, such as Alzheimer’s disease. However, dynamic network alteration and its molecular pathological basis following the disease course in the AD spectrum still remain unclear. Currently, we integrated a new method combination of large‐scale network analysis and canonical correlation analysis (CCA) to explore dynamic spatiotemporal patterns within‐ and between RSNs and their significance in the AD spectrum.MethodWe analyzed data from the Alzheimer’s Disease Neuroimaging Initiative 1, GO and 2 datasets. A total of 160participants (59 cognitively normal (CN) participants, 49 patients with early mild cognitive impairment (EMCI), 28 patients with late mild cognitive impairment (LMCI) and 24 AD patients) completed fMRI scan, 3T MRI brain scan, CSF biomarkers and genes which strongly tied to AD risk detection and cognitive function assessment (MMSE and ADAS‐Cog scores). We studied group differences in within‐ and between RSNs. For cognitive function, genes and biomarkers, we did canonical correlation analysis between gene scores, cognitive scores , the biomarker levels and network variables across disease spectrum.ResultWe identified that all RSNs represented the increase connectivity within networks by enhancing inner cohesive ability, while seven out of ten RSNs were characterized by the decreased connectivity between networks, which indicates weaken connector ability among networks from the early stage to dementia. This dichotomous mode presenting large‐scale dynamic network abnormality was significantly correlated with the levels of molecular biomarkers (amyloid‐β, Tau, p‐Tau), cognitive performance, as well as accumulating effects of AD‐related ten genetic risk factors. This study implicated that spatiotemporal pattern of large‐scale network connectivity failure was not cascading, but represented a bouncing mode with the progression of cognitive decline. Taken together, we identified the determinants of the spread of disrupted network incoherence, molecular correlates, and summative effects of genetic variants on the RSNs.ConclusionThese findings provide novel insights for better understanding the mechanism underlying large‐scale network disruption linking molecular biomarkers and phenotypic variations in the AD spectrum.