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.

Keywords: 18F-fluorodeoxyglucose (FDG); amyloid; autosomal dominant Alzheimer disease; cerebrospinal fluid (CSF); estimated years to onset (EYO); hippocampus; positron emission tomography (PET); resting-state functional connectivity; tau.

FIG. 1.

PCA reveals a distributed pattern of FC changes across cortical and subcortical RSNs. Left: The mean FC matrix across all participants. An FC matrix from 248 regions of interest was computed for each participant. Positive correlations are shown in the upper triangle, and negatives are shown in the bottom triangle. Notched black lines on the top and to the right indicate RSNs. The black box outline is a visual aid highlighting the intranetwork FC values of the DMN. Middle: The mean FC-composite matrix across all participants. For each participant, an FC-composite matrix was generated by computing the mean intra- and internetwork FC matrix values (total of 78) for all 12 RSNs. Here the black box highlights the mean intranetwork FC value of the DMN. Right: The global FC signature is derived from the primary PCA pattern and reflects positively and negatively weighted mean FC-composite values. The strongest positive weights include the SM, SMlat, CO, AUD, VIS, and MEM. The strongest negative weights included the FP, MEM, DAN, and DMN. The black box outline highlights the weight of the mean intranetwork FC value of the DMN. AUD, auditory; CO, cingulo-opercular; DAN, dorsal attention; DMN, default mode network; FC, functional connectivity; FP, frontoparietal; MEM, memory; PCA, principal component analysis; RSNs, resting-state networks; SAL, salience; SM, sensorimotor; SMlat, sensorimotor-lateral; SUB, subcortical; VAN, ventral attention; VIS, visual. Color images are available online.

FIG. 2.

(A) The global FC signature as a function of mutation status, CDR, and EYO. (A) Violin and box plots of the global FC signature for NC (gray) and MC (yellow), MC CDR 0 (green), and MC CDR >0 (red) participants. NC had a higher global FC signature compared with MC. MC CDR >0 had significant decreases in the global FC signature compared with NC and MC CDR 0 participants. A black bar represents a significant group difference. (B) Line plot showing the association between global FC signature and mutation EYO for MC participants. The global FC signature was associated with EYO in MC (p < 0.05). The dashed line (black) is the mean global FC signature in NC participants, and the dark gray band is the confidence interval defined as two standard errors of the mean. (C) Coefficient of determination (R²) for the global FC signature and the intranetwork values of 12 RSNs. The length of the vertical bar represents the strength of that FC value for predicting EYO. (D) The global FC signature for MC individuals exhibits a biphasic behavior with regard to mutation EYO in ±5-year bins. When the global FC signature was fit to the bin means (yellow curve), two logistic curves were observed (magenta and cyan). A two-stage process was observed, with early and late changes seen in the global FC signature. CDR, clinical dementia rating; EYO, expected years to symptom onset; MC, mutation carrier; NC, noncarrier. Color images are available online.

FIG. 3.

The global FC signature as a function of Alzheimer disease (AD) biomarkers in mutation-positive (MC) individuals. Analyses investigated amyloid (A; green), Tau (T; purple), and neurodegenerative (N; orange) biomarkers. Scatter plots show that the global FC signature was (A) positively associated with CSF Aβ_1–42, negatively associated with mean PiB SUVR, negatively associated with CSF p-tau₁₈₁ and total tau, and positively associated with both precuneus FDG uptake and hippocampal volume. (B) The correlation matrix of all biomarkers, including global FC signature (left), was inverted to compute the partial correlation matrix (middle). Network map of relationships was plotted among the global FC signature, and AD biomarkers based on the partial correlation matrix. The fully (light edges) and minimally (dark edges) connected graphs are shown. All associations were corrected for age. CSF, cerebrospinal fluid; FDG, 18F-fluorodeoxyglucose; PiB, Pittsburgh compound B; p-tau₁₈₁, phosphorylated tau₁₈₁; SUVR, standardized uptake value ratios. Color images are available online.