Zhao Zhe, Chen Jing, Zhao Danhua, Chen Baoyu, Wang Qi, Li Yuan, Chen Junyi, Bai Chaobo, Guo Xintong, Hu Nan, Zhang Bingwei, Zhao Rongsheng, Yuan Junliang
Department of Pharmacy, Peking University Third Hospital, 100191, Beijing, China.
Institute for Drug Evaluation, Peking University Health Science Center, 100191, Beijing, China.
NPJ Parkinsons Dis. 2024 Oct 26;10(1):203. doi: 10.1038/s41531-024-00802-2.
Associations between the gut microbiota and Parkinson's disease (PD) have been widely investigated. However, the replicable biomarkers for PD diagnosis across multiple populations remain elusive. Herein, we performed a meta-analysis to investigate the pivotal role of the gut microbiome in PD and its potential diagnostic implications. Six 16S rRNA gene amplicon sequence datasets from five independent studies were integrated, encompassing 550 PD and 456 healthy control samples. The analysis revealed significant alterations in microbial composition and alpha and beta diversity, emphasizing altered gut microbiota in PD. Specific microbial taxa, including Faecalibacterium, Roseburia, and Coprococcus_2, known as butyrate producers, were notably diminished in PD, potentially contributing to intestinal inflammation. Conversely, genera such as Akkermansia and Bilophila exhibited increased relative abundances. A network-based algorithm called NetMoss was utilized to identify potential biomarkers of PD. Afterwards, a classification model incorporating 11 optimized genera demonstrated high performance. Further functional analyses indicated enrichment in pathways related to neurodegeneration and metabolic pathways. These findings illuminate the intricate relationship between the gut microbiota and PD, offering insights into potential therapeutic interventions and personalized diagnostic strategies.
肠道微生物群与帕金森病(PD)之间的关联已得到广泛研究。然而,跨多个人群用于PD诊断的可重复生物标志物仍然难以捉摸。在此,我们进行了一项荟萃分析,以研究肠道微生物群在PD中的关键作用及其潜在的诊断意义。整合了来自五项独立研究的六个16S rRNA基因扩增子序列数据集,涵盖550个PD样本和456个健康对照样本。分析揭示了微生物组成以及α和β多样性的显著变化,强调了PD患者肠道微生物群的改变。特定的微生物分类群,包括作为丁酸盐产生菌的粪杆菌属、罗斯氏菌属和粪球菌属_2,在PD中显著减少,可能导致肠道炎症。相反,诸如阿克曼氏菌属和嗜胆菌属等属的相对丰度增加。使用一种名为NetMoss的基于网络的算法来识别PD的潜在生物标志物。随后,一个包含11个优化属的分类模型表现出高性能。进一步的功能分析表明与神经退行性变和代谢途径相关的通路富集。这些发现阐明了肠道微生物群与PD之间的复杂关系,为潜在的治疗干预和个性化诊断策略提供了见解。
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