AUTHOR=Wang Siyu , Sun Haiting , Hu Guanjie , Xue Chen , Qi Wenzhang , Rao Jiang , Zhang Fuquan , Zhang Xiangrong , Chen Jiu 

TITLE=Altered Insular Subregional Connectivity Associated With Cognitions for Distinguishing the Spectrum of Pre-clinical Alzheimer's Disease

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=Volume 13 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2021.597455

DOI=10.3389/fnagi.2021.597455

ISSN=1663-4365

ABSTRACT=Background: Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are regarded as preclinical Alzheimer’s disease (AD) spectrum. The insular subregional networks are considered to present different intrinsic connectivity patterns, which are involved in cognitive and emotional processing. This study aimed at investigating convergent and divergent altered connectivity patterns of insular subregions across preclinical AD spectrum and to further test how well this could distinguish the preclinical AD spectrum.
Method: Functional connectivity (FC) analyses in insular subnetworks were conducted among 38 SCD, 56 aMCI, and 55 normal controls (CN). Logistic regression analyses were utilized to build models for aMCI and CN, and SCD and CN classification. Finally, correlation analyses were applied to measure the relationship between FC of altered insular subnetworks and cognitions. 
Results: SCD patients majorly presented descended FC in bilateral cerebellum posterior lobe and increased FC in medial frontal gyrus and middle temporal gyrus while aMCI patients mainly presented decreased FC in bilateral inferior parietal lobule, cerebellum posterior lobe, and anterior cingulate cortex, and increased FC in medial and inferior frontal gyrus, middle and superior temporal gyrus. Logistic regression analyses showed that a model composed of connectivities among altered insular subnetworks in SCD patients correctly classified 83.9% of SCD and CN, with an area under the ROC curve (AUC) of 0.876, 81.6% sensitivity, and 81.8% specificity. A model composed of altered insular subnetwork connectivities in aMCI patients correctly classified 86.5% of aMCI and CN, with an AUC of 0.887, 80.4% sensitivity, and 83.6% specificity. Furthermore, some of connectivities among altered insular subnetworks were significantly correlated with episodic memory and executive function. 
Conclusions: SCD and aMCI patients may share convergent and divergent altered intrinsic connectivity patterns of insular subnetworks as the preclinical AD spectrum, and presented differences in abnormalities among subnetworks. These abnormalities correctly distinguish the individuals in preclinical AD spectrum. It further suggests that the alterations in insular subnetworks can be utilized as a potential biomarker to assist in clinical diagnosis of preclinical AD spectrum.