Background: Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) were considered to be a continuum of Alzheimer's disease (AD) spectrum. The abnormal topological architecture and rich-club organization in the brain functional network can reveal the pathology of the AD spectrum. However, few studies have explored the disrupted patterns of diverse club organizations and the combination of rich-and diverse-club organizations in SCD and aMCI. Methods: We collected resting-state functional magnetic resonance imaging data of 19 SCDs, 29 aMCIs, and 28 healthy controls (HCs) from the Alzheimer's Disease Neuroimaging Initiative. Graph theory analysis was used to analyze the network metrics and rich-and diverse-club organizations simultaneously. Results: Compared with HC, the aMCI group showed altered small-world and network efficiency, whereas the SCD group remained relatively stable. The aMCI group showed reduced rich-club connectivity compared with the HC. In addition, the aMCI group showed significantly increased feeder connectivity and decreased local connectivity of the diverse club compared with the SCD group. The overlapping nodes of the rich club and diverse club showed a significant difference in nodal efficiency and shortest path length (L p) between groups. Notably, the L p values of overlapping nodes in the SCD and aMCI groups were significantly associated with episodic memory. Conclusion: The present study demonstrates that the network properties of SCD and aMCI have varying degrees of damage. The combination of the rich club and the diverse club can provide a novel insight into the pathological mechanism of the AD spectrum. The altered patterns in overlapping nodes might be potential biomarkers in the diagnosis of the AD spectrum.

Salience network (SN), playing a vital role in advanced cognitive function, is regarded to be impaired in subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The purpose of the study was to explore the importance of structural and functional features of SN in the diagnosis of SCD and aMCI. Structural and resting-state functional magnetic resonance imaging were collected from SCD, aMCI, and healthy control (HC). Cortex thickness, gray matter (GM) volume, spontaneous brain activity, functional connectivity (FC) within SN, and its relationship with cognitive function were analyzed. Moreover, the receiver operating characteristic analysis was performed to assess diagnostic efficacy of altered indictors for SCD and aMCI. Compared to HC, both SCD and aMCI showed decreased GM volume, decreased spontaneous brain activity, and increased FC within SN, while aMCI showed additional decreased cortex thickness. Furthermore, the altered FC in SCD and aMCI was significantly correlated with cognitive function. Particularly, the best-fitting classification models of SCD and aMCI were based on the combined multiple indicators. In conclusion, structure and function of SN were disrupted in SCD and aMCI, which involved in cognitive decline. The combined multiple indicators of SN provided powerful biomarkers for the diagnosis of SCD and aMCI.

Background: Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are regarded as part of the pre-clinical Alzheimer's disease (AD) spectrum. The insular subregional networks are thought to have diverse intrinsic connectivity patterns that are involved in cognitive and emotional processing. We set out to investigate convergent and divergent altered connectivity patterns of the insular subregions across the spectrum of pre-clinical AD and evaluated how well these patterns can differentiate the pre-clinical AD spectrum.Method: Functional connectivity (FC) analyses in insular subnetworks were carried out among 38 patients with SCD, 56 patients with aMCI, and 55 normal controls (CNs). Logistic regression analyses were used to construct models for aMCI and CN, as well as SCD and CN classification. Finally, we conducted correlation analyses to measure the relationship between FCs of altered insular subnetworks and cognition.Results: Patients with SCD presented with reduced FC in the bilateral cerebellum posterior lobe and increased FC in the medial frontal gyrus and the middle temporal gyrus. On the other hand, patients with aMCI largely presented with decreased FC in the bilateral inferior parietal lobule, the cerebellum posterior lobe, and the anterior cingulate cortex, as well as increased FC in the medial and inferior frontal gyrus, and the middle and superior temporal gyrus. Logistic regression analyses indicated that a model composed of FCs among altered insular subnetworks in patients with SCD was able to appropriately classify 83.9% of patients with SCD and CN, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.876, 81.6% sensitivity, and 81.8% specificity. A model consisting of altered insular subnetwork FCs in patients with aMCI was able to appropriately classify 86.5% of the patients with aMCI and CNs, with an AUC of 0.887, 80.4% sensitivity, and 83.6% specificity. Furthermore, some of the FCs among altered insular subnetworks were significantly correlated with episodic memory and executive function.Conclusions: Patients with SCD and aMCI are likely to share similar convergent and divergent altered intrinsic FC patterns of insular subnetworks as the pre-clinical AD spectrum, and presented with abnormalities among subnetworks. Based on these abnormalities, individuals can be correctly differentiated in the pre-clinical AD spectrum. These results suggest that alterations in insular subnetworks can be utilized as a potential biomarker to aid in conducting a clinical diagnosis of the spectrum of pre-clinical AD.