Alterations of Structural Network Efficiency in Early-Onset and Late-Onset Alzheimer's Disease

Abstract

Background and purpose: Early- and late-onset Alzheimer's disease (EOAD and LOAD, respectively) share the same neuropathological hallmarks of amyloid and neurofibrillary tangles but have distinct cognitive features. We compared structural brain connectivity between the EOAD and LOAD groups using structural network efficiency and evaluated the association of structural network efficiency with the cognitive profile and pathological markers of Alzheimer's disease (AD).

Methods: The structural brain connectivity networks of 80 AD patients (47 with EOAD and 33 with LOAD) and 57 healthy controls were reconstructed using diffusion-tensor imaging. Graph-theoretic indices were calculated and intergroup differences were evaluated. Correlations between network parameters and neuropsychological test results were analyzed. The correlations of the amyloid and tau burdens with network parameters were evaluated for the patients and controls.

Results: Compared with the age-matched control group, the EOAD patients had increased global path length and decreased global efficiency, averaged local efficiency, and averaged clustering coefficient. In contrast, no significant differences were found in the LOAD patients. Locally, the EOAD patients showed decreases in local efficiency and the clustering coefficient over a wide area compared with the control group, whereas LOAD patients showed such decreases only within a limited area. Changes in network parameters were significantly correlated with multiple cognitive domains in EOAD patients, but only with Clinical Dementia Rating Sum-of-Boxes scores in LOAD patients. Finally, the tau burden was correlated with changes in network parameters in AD signature areas in both patient groups, while there was no correlation with the amyloid burden.

Conclusions: The impairment of structural network efficiency and its effects on cognition may differ between EOAD and LOAD.

Keywords: Alzheimer disease; diffusion-tensor imaging; early-onset Alzheimer's disease; late-onset Alzheimer's disease; white-matter connectivity.

Fig. 1. Comparison of network measures. Group comparisons of global path length (A), global efficiency (B), averaged local efficiency (C), and averaged clustering coefficient (D). Error bars indicate standard deviations. Analysis of covariance (ANCOVA) with the covariates of age, sex, and education duration was used to identify significant differences between each Alzheimer’s disease group and its age-matched control group. ANCOVA with covariates of sex and education duration was used to identify significant differences between early-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease (LOAD) patients. ^*Indicates significant difference at the 0.05 level. OC, old controls; YC, young controls.

Fig. 2. Topography of the brain regions with significant group effects of the network parameters. ANCOVA with covariates of age, sex, and education duration was used. Colored nodes indicate significant group difference at the false-discovery-rate-corrected p<0.05 level. Nodes colored orange indicate significant decreases in network parameters in the AD group relative to the age-matched controls (A, B, and D). None of the nodes shows significant group differences in the opposite direction. Nodes showing higher network parameters in LOAD and EOAD patients are colored red and blue, respectively (C). AD, Alzheimer’s disease; ANCOVA, analysis of covariance; ANG, angular gyrus; CAL, calcarine; CUN, cuneus; DCG, median cingulate and paracingulate gyrus; EOAD, early-onset AD; HES, Heschl gyrus; HIP, hippocampus; IPL, inferior parietal lobule; ITG, inferior temporal gyrus; LING, lingual gyrus; LOAD, late-onset AD; MOG, middle occipital gyrus; MTG, middle temporal gyrus; OC, old controls; OLF, olfactory cortex; ORBsupmed, superior frontal gyrus, medial orbital; PCUN, precuneus; PHG, parahippocampal gyrus; PoCG, postcentral gyrus; PUT, putamen; REC, gyrus rectus; ROL, Rolandic operculum; SMA, supplementary motor area; SMG, supramarginal gyrus; SOG, superior occipital gyrus; SPG, superior parietal gyrus; STG, superior temporal gyrus; TPOmid, Temporal pole, middle temporal gyrus; TPOsup, Temporal pole, superior temporal gyrus; YC, young controls.

Fig. 3. Relationships between network parameters and [¹⁸F]THK5351 (THK) retention in EOAD and LOAD patients. Spearman correlation analysis was used to identify significant relationships of THK retention with local efficiency (A) and clustering coefficient (B) in EOAD and LOAD patients. Colored nodes indicate significant differences at the false-discovery-rate-corrected p<0.05 level. ANG, angular gyrus; EOAD, early-onset Alzheimer’s disease; IFGtriang, triangular part of the inferior frontal gyrus; IOG, inferior occipital gyrus; IPL, inferior parietal lobule; ITG, inferior temporal gyrus; LOAD, late-onset Alzheimer’s disease; MTG, middle temporal gyrus; PCG, posterior cingulate gyrus; PCUN, precuneus; SFGdor, dorsolateral superior frontal gyrus; SMG, supramarginal gyrus; SPG, superior parietal gyrus; TPOmid, Temporal pole, middle temporal gyrus.