Differences of individual gray matter networks between MCI patients who converted to AD within 3 Years and nonconverters

作者全名：Zhou, Baiwan; Zhao, Yueqi; Wu, Xiaojia

作者地址：[Zhou, Baiwan; Zhao, Yueqi; Wu, Xiaojia] Chongqing Med Univ, Affiliated Hosp 2, Dept Radiol, Chongqing, Peoples R China

通信作者：Wu, XJ (通讯作者)，Chongqing Med Univ, Affiliated Hosp 2, Dept Radiol, Chongqing, Peoples R China.

来源：HELIYON

ESI学科分类：　

WOS号：WOS:001228098600001

JCR分区：Q1

影响因子：3.4

年份：2024

卷号：10

期号：7

开始页：　

结束页：　

文献类型：Article

关键词：Mild cognitive impairment; Conversion; Neuroimaging; Connectome; Structural magnetic resonance imaging; Gradient; Topology; Support vector machine

摘要：Objective: Here we aimed to explore the differences in individual gray matter (GM) networks at baseline in mild cognitive impairment patients who converted to Alzheimer 's disease (AD) within 3 years (MCI-C) and nonconverters (MCI-NC). Materials and methods: Data from 461 MCI patients (180 MCI-C and 281 MCI-NC) were obtained from the Alzheimer 's Disease Neuroimaging Initiative (ADNI). For each subject, a GM network was constructed using 3D -T1 imaging and the Kullback -Leibler divergence method. Gradient and topological analyses of individual GM networks were performed, and partial correlations were calculated to evaluate relationships among network properties, cognitive function, and apolipoprotein E (APOE) <euro>4 alleles. Subsequently, a support vector machine (SVM) model was constructed to discriminate the MCI-C and MCI-NC patients at baseline. Results: The gradient analysis revealed that the principal gradient score distribution was more compressed in the MCI-C group than in the MCI-NC group, with scores for the left lingual gyrus, right fusiform gyrus and left middle temporal gyrus being increased in the MCI-C group (p < 0.05, FDR corrected). The topological analysis showed significant differences in nodal efficiency in four nodes between the two groups. Furthermore, the regional gradient scores or nodal efficiency were found to be significantly related to the neuropsychological test scores, and the left middle temporal gyrus gradient scores were positively associated with the number of APOE <euro>4 alleles (r = 0.192, p = 0.002). Ultimately, the SVM model achieved a balanced accuracy of 79.4% in classifying MCI-C and MCI-NC patients (p < 0.001). Conclusion: The whole-brain GM network hierarchy in the MCI-C group was more compressed than that in the MCI-NC group, suggesting more serious cognitive impairments in the MCI-C group. The left middle temporal gyrus gradient scores were related to both cognitive function and APOE <euro>4 alleles, thus serving as potential biomarkers distinguishing MCI-C from MCI-NC at baseline.

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