There is evidence that gray matter networks are disrupted in Mild Cognitive Impairment (MCI) and associated with cognitive impairment and faster disease progression. However, it remains unknown how these alterations are related to the presence of Apolipoprotein E isoform E4 (ApoE4), the most prominent genetic risk factor for late-onset Alzheimer’s disease (AD). To investigate this topic at the individual level, we explore the impact of ApoE4 and the disease progression on the Single-Subject Gray Matter Networks (SSGMNets) using the graph theory approach. Our data sample comprised 200 MCI patients selected from the ADNI database, classified as non-Converters and Converters (will progress into AD). Each group included 50 ApoE4-positive (‘Carriers', ApoE4 + ) and 50 ApoE4-negative ('non-Carriers', ApoE4-). The SSGMNets were estimated from structural MRIs at two-time points: baseline and conversion. We investigated whether altered network topological measures at baseline and their rate of change (RoC) between baseline and conversion time points were associated with ApoE4 and disease progression. We also explored the correlation of SSGMNets attributes with general cognition score (MMSE), memory (ADNI-MEM), and CSF-derived biomarkers of AD (Aβ42, T-tau, and P-tau). Our results showed that ApoE4 and the disease progression modulated the global topological network properties independently but not in their RoC. MCI converters showed a lower clustering index in several regions associated with neurodegeneration in AD. The SSGMNets' topological organization was revealed to be able to predict cognitive and memory measures. The findings presented here suggest that SSGMNets could indeed be used to identify MCI ApoE4 Carriers with a high risk for AD progression.

有证据表明，灰质网络在轻度认知障碍 (MCI) 中受到破坏，并与认知障碍和疾病进展更快有关。然而，尚不清楚这些改变与载脂蛋白 E 亚型 E4 (ApoE4) 的存在有何关系，ApoE4 是迟发性阿尔茨海默病 (AD) 最突出的遗传风险因素。为了在个体层面研究该主题，我们使用图论方法探讨了 ApoE4 和疾病进展对单受试者灰质网络 ( SSGMNets ) 的影响。我们的数据样本包括从 ADNI 数据库中选出的 200 名 MCI 患者，分为非转化者和转化者（将进展为 AD）。每组包括 50 个 ApoE4 -阳性（“携带者”，ApoE4 + ）和 50 个 ApoE4 -阴性（'非携带者'，ApoE4-）。SSGMNets是在两个时间点从结构 MRI 估计的：基线和转换。我们调查了基线时改变的网络拓扑测量及其在基线和转换时间点之间的变化率 (RoC) 是否与 ApoE4 和疾病进展相关。我们还探讨了SSGMNets属性与一般认知评分 (MMSE)、记忆力 (ADNI-MEM) 和脑脊液衍生的 AD 生物标志物（Aβ42、T-tau 和 P-tau）之间的相关性。我们的结果表明 ApoE4 和疾病进展独立调节全局拓扑网络属性，但不在其 RoC 中。MCI 转换器在与 AD 神经变性相关的几个区域中显示出较低的聚类指数。SSGMNets的拓扑结构被发现能够预测认知和记忆测量。此处提供的研究结果表明，SSGMNets确实可用于识别具有 AD 进展高风险的 MCI ApoE4 携带者。