Resting-State Functional Connectivity Disruption as a Pathological Biomarker in Autosomal Dominant Alzheimer Disease

Abstract

Aim:

Identify a global resting-state functional connectivity (gFC) signature in mutation carriers (MC) from the Dominantly Inherited Alzheimer Network (DIAN). Assess the gFC with regard to amyloid (A), tau (T), and neurodegeneration (N) biomarkers, and estimated years to symptom onset (EYO).

Introduction:

Cross-sectional measures were assessed in MC (n = 171) and mutation noncarrier (NC) (n = 70) participants. A functional connectivity (FC) matrix that encompassed multiple resting-state networks was computed for each participant.

Methods:

A global FC was compiled as a single index indicating FC strength. The gFC signature was modeled as a nonlinear function of EYO. The gFC was linearly associated with other biomarkers used for assessing the AT(N) framework, including cerebrospinal fluid (CSF), positron emission tomography (PET) molecular biomarkers, and structural magnetic resonance imaging.

Results:

The gFC was reduced in MC compared with NC participants. When MC participants were differentiated by clinical dementia rating (CDR), the gFC was significantly decreased in MC CDR >0 (demented) compared with either MC CDR 0 (cognitively normal) or NC participants. The gFC varied nonlinearly with EYO and initially decreased at EYO = −24 years, followed by a stable period followed by a further decline near EYO = 0 years. Irrespective of EYO, a lower gFC associated with values of amyloid PET, CSF Aβ_1–42, CSF p-tau, CSF t-tau, 18F-fluorodeoxyglucose, and hippocampal volume.

Conclusions:

The gFC correlated with biomarkers used for defining the AT(N) framework. A biphasic change in the gFC suggested early changes associated with CSF amyloid and later changes associated with hippocampal volume.

Impact statement

This project focused on creating and evaluating a global functional connectivity (FC) signature that may serve as an outcome measure in clinical trials. This global FC signature encompassed multiple resting-state networks that included both inter- and intranetworks. Prior studies that focus on a single network may overlook important changes seen within and between networks. Our analysis is a logical progression from previous work that demonstrated that intra- and internetwork brain connections across multiple networks were affected with progression to cognitive impairment in autosomal dominant Alzheimer disease. This work revealed that FC disruption exhibits a nonlinear time course that was consistent with proposed biomarker models.