Chen Qionglei, Shi Jiayu, Yu Gaojie, Xie Huijia, Yu Shicheng, Xu Jin, Liu Jiaming, Sun Jing
Department of Geriatrics, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Department of Preventive Medicine, School of Public Health, Wenzhou Medical University, Wenzhou, China.
Front Aging Neurosci. 2024 Nov 27;16:1478557. doi: 10.3389/fnagi.2024.1478557. eCollection 2024.
Accumulating evidence suggested that Alzheimer's disease (AD) was associated with altered gut microbiota. However, the relationships between gut microbiota and specific cognitive domains of AD patients have yet been fully elucidated. The aim of this study was to explore microbial signatures associated with global cognition and specific cognitive domains in AD patients and to determine their predictive value as biomarkers.
A total of 64 subjects (18 mild AD, 23 severe AD and 23 healthy control) were recruited in the study. 16 s rDNA sequencing was performed for the gut bacteria composition, followed by liquid chromatography electrospray ionization tandem mass spectrometry (LC/MS/MS) analysis of short-chain fatty acids (SCFAs). The global cognition, specific cognitive domains (abstraction, orientation, attention, language, etc.) and severity of cognitive impairment, were evaluated by Montreal Cognitive Assessment (MoCA) scores. We further identified characteristic bacteria and SCFAs, and receiver operating characteristic (ROC) curve was used to determine the predictive value.
Our results showed that the microbiota dysbiosis index was significantly higher in the severe and mild AD patients compared to the healthy control (HC). Linear discriminant analysis (LDA) showed that 12 families and 17 genera were identified as key microbiota among three groups. The abundance of was positively associated with abstraction, and the abundance of was positively associated with attention, language, orientation in AD patients. Moreover, the levels of isobutyric acid and isovaleric acid were both significantly negatively correlated with abstraction, and level of propanoic acid was significantly positively associated with the attention. In addition, ROC models based on the characteristic bacteria , and could effectively distinguished between low and high orientation in AD patients (area under curve is 0.891), and and or the combination of SCFAs could distinguish abstraction in AD patients (area under curve is 0.797 and 0.839 respectively).
These findings revealed the signatures gut bacteria and metabolite SCFAs of AD patients and demonstrated the correlations between theses characteristic bacteria and SCFAs and specific cognitive domains, highlighting their potential value in early detection, monitoring, and intervention strategies for AD patients.
越来越多的证据表明，阿尔茨海默病（AD）与肠道微生物群的改变有关。然而，肠道微生物群与AD患者特定认知领域之间的关系尚未完全阐明。本研究的目的是探索与AD患者整体认知和特定认知领域相关的微生物特征，并确定它们作为生物标志物的预测价值。
本研究共招募了64名受试者（18名轻度AD患者、23名重度AD患者和23名健康对照）。对肠道细菌组成进行16s rDNA测序，随后采用液相色谱电喷雾电离串联质谱（LC/MS/MS）分析短链脂肪酸（SCFA）。通过蒙特利尔认知评估（MoCA）评分评估整体认知、特定认知领域（抽象、定向、注意力、语言等）以及认知障碍的严重程度。我们进一步鉴定了特征性细菌和SCFA，并使用受试者工作特征（ROC）曲线来确定预测价值。
我们的结果表明，与健康对照（HC）相比，重度和轻度AD患者的微生物群失调指数显著更高。线性判别分析（LDA）表明，在三组中鉴定出12个科和17个属为关键微生物群。在AD患者中，[具体细菌名称1]的丰度与抽象能力呈正相关，[具体细菌名称2]的丰度与注意力、语言、定向呈正相关。此外，异丁酸和异戊酸水平均与抽象能力显著负相关，丙酸水平与注意力显著正相关。此外，基于特征性细菌[具体细菌名称3]、[具体细菌名称4]和[具体细菌名称5]的ROC模型可以有效区分AD患者的低定向和高定向（曲线下面积为0.891），[具体细菌名称6]和[具体细菌名称7]或SCFA的组合可以区分AD患者的抽象能力（曲线下面积分别为0.797和0.839）。
这些发现揭示了AD患者肠道细菌和代谢物SCFA的特征，并证明了这些特征性细菌和SCFA与特定认知领域之间的相关性，突出了它们在AD患者早期检测、监测和干预策略中的潜在价值。
