Microbial biomarker discovery in Parkinson’s disease through a network-based approach

Abstract

Abstract 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.