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Early-onset Alzheimer's disease (EOAD) involves multiple cognitive domains and shows more rapid progression than late-onset Alzheimer's disease (LOAD). However, the difference in pathogenesis between EOAD and LOAD is still unclear. Accordingly, we applied intrinsic network analysis to explore the potential neuropathological mechanism underlying distinct clinical phenotypes. According to the cut-off age of 65, we included 20 EOAD patients, 20 LOAD patients, and 36 age-matched controls (19 young and 17 old controls). We employed resting-state functional MRI and network centrality analysis to explore the local (degree centrality (DC)) and global (eigenvector centrality (EC)) functional integrity. Two-sample t-test analysis was performed, with gray matter volume, age, gender, and education as covariates. Furthermore, we performed a correlation analysis between network metrics and cognition. Compared to young controls, EOAD patients exhibited lower DC in the middle temporal gyrus (MTG), parahippocampal gyrus (PHG), superior temporal gyrus (STG), and lower EC in the MTG, PHG, and postcentral gyrus. In contrast, LOAD patients exhibited lower DC in the STG and anterior cingulum gyrus and higher DC in the middle frontal gyrus compared to old controls. No significant difference in EC was observed in LOAD patients. Furthermore, both DC and EC correlated with cognitive performance. Our study demonstrated divergent functional network impairments in EOAD and LOAD patients. EOAD patients showed more complex network damage involving both local and global centrality properties, while LOAD patients mainly featured local functional connectivity changes. Such centrality impairments are related to poor cognition, especially regarding memory performance.

The APOE ε4 allele is associated with impaired intrinsic functional connectivity in neural networks, especially in the default mode network (DMN). However, effective connectivity (EC) reflects the direct causal effects of one brain region to another, which has rarely been investigated. Recently, Granger causality analysis (GCA) proved suitable for the study of directionality in neuronal interactions. Using GCA, we examined the differences in the EC between the anterior medial prefrontal cortex/posterior cingulate cortex (aMPFC/PCC) and the whole brain in 17 ε4 carrying and 32 non-carrying cognitively intact elderly individuals. Furthermore, correlation analyses were performed between the abnormal EC and cognition/neuropathological indices. Compared with the non-carriers, the results showed that the ε4 carriers exhibited decreased EC from the PCC to the whole brain in the middle temporal gyrus (MTG), the anterior cingulate cortex (ACC), and the precuneus (PCu). Meanwhile, the ε4 carriers demonstrated increased EC from the whole brain to the aMPFC in the inferior parietal lobe (IPL) and the postcentral gyrus (PCG). The correlation analyses suggested that the EC from the IPL/PCG to the aMPFC was related to episodic memory in non-carriers, while the decreased EC from the PCC to the ACC was associated with increased levels of t-tau in the ε4 carriers. In ε4 carriers, a negative influence can be traced from the PCC to both the anterior and posterior DMN subsystems; meanwhile, the anterior DMN subsystem receives compensatory effects from the parietal cortex. Early increases in AD-related pathologies in the PCC may act as first factors during this pathological process.

Amnestic mild cognitive impairment can be further classified as single-domain aMCI (SD-aMCI) with isolated memory deficit, or multi-domain aMCI (MD-aMCI) if memory deficit is combined with impairment in other cognitive domains. Prior studies reported these clinical subtypes presumably differ in etiology. Thus, we aimed to explore the possible mechanisms between different aMCI subtypes by assessing alteration in brain activity and brain vasculature, and their relations with CSF AD biomarkers. 49 healthy controls, 32 SD-aMCI, and 32 MD-aMCI, who had undergone structural scans, resting-state functional MRI (rsfMRI) scans and neuropsychological evaluations, were identified. Regional homogeneity (ReHo) was employed to analyze regional synchronization. Periventricular white matter hyperintensities (PWMH) and deep WMH (DWMH) volume of each participant was quantitatively assessed. AD biomarkers from CSF were also measured. SD-aMCI showed decreased ReHo in medial temporal gyrus (MTG), and increased ReHo in lingual gyrus (LG) and superior temporal gyrus (STG) relative to controls. MD-aMCI showed decreased ReHo, mostly located in precuneus (PCu), LG and postcentral gyrus (PCG), relative to SD-aMCI and controls. As for microvascular disease, MD-aMCI patients had more PWMH burden than SD-aMCI and controls. Correlation analyses indicated mean ReHo in differenced regions were related with memory, language, and executive function in aMCI patients. However, no significant associations between PWMH and behavioral data were found. The Aβ level was related with the ReHo value of STG in SD-aMCI. MD-aMCI displayed different patterns of abnormal regional synchronization and more severe PWMH burden compared with SD-aMCI. Therefore aMCI is not a uniform disease entity, and MD-aMCI group may show more complicated pathologies than SD-aMCI group.

Apolipoprotein E (APOE) e4 allele is the best established genetic risk factor for sporadic Alzheimer’s disease (AD). However, there is a need to understand the effects of this genotype on the brain by simultaneously assessing intrinsic brain network and cerebral spinal fluid (CSF) biomarkers changes in healthy older e4 carriers. Thirteen cognitively intact, elderly APOE e4 carriers and 22 e3 homozygotes were included in the present study. Eigenvector centrality mapping (ECM) was used to identify brain network hub organization based on resting-state functional MRI (rsfMRI). We evaluated comprehensive cognitive ability and tested levels of Aβ1–42, total-tau (t-tau) and phosphorylated-tau (p-tau181) in CSF. Comparisons of ECM between two groups were conducted, followed by correlations analyses between EC values with significant group differences and cognitive ability/CSF biomarkers. APOE e4 carriers showed significantly decreased EC values in left medial temporal lobe (MTL), left lingual gyrus (LG) and increased EC values in left middle frontal gyrus (MFG) as compared to non-carriers. Correlation analysis demonstrated that left LG EC value correlated with Rey Auditory Verbal Learning Test total learning (RAVLT, r = 0.57, p

APOE is one of the strongest genetic factors associated with information processing speed (IPS). Herein, we explored the neural substrates underlying APOE-related IPS alteration by measuring lobar distribution of white matter hyperintensities (WMH), cortical grey matter volume (GMV) and thickness. Using the ADNI database, we evaluated 178 cognitively normal elderly individuals including 34 APOE e2 carriers, 54 APOE e4 carriers and 90 e3 homozygotes. IPS was determined using Trail Making Tests (TMT). We quantified lobar distribution of WMH, cortical GM lobar volume, cortical thickness among three groups. Finally, we used Pearson's correlation and general linear models to examine structural MRI markers in relation to IPS. There were significant differences of IPS among groups, with e4 carriers displaying the worst performance. Across groups, significant differences in frontal and parietal WMH load were observed (the highest in e4 carriers); however, no significant differences in cortical GMV and thickness were found. Pearson's correlation analysis showed parietal WMH volume was significantly related with IPS, especially in e4 carriers. Subsequently a general linear model demonstrated that parietal WMH volume, age and the interaction between parietal WMH volume and age, was significantly associated with IPS, even after adjusting total intracranial volume (TIV), gender and vascular risk factors. Disruption of WM structure, rather than atrophy of GM, plays a more critical role in APOE e4 allele-specific IPS. Moreover, specific WMH loci are closely associated with IPS; increased parietal WMH volume, especially in e4 carriers, was independently contributed to slower IPS.