Meta-analysis identifies common gut microbiota associated with multiple sclerosis - Qingqi Lin; Yair Dorsett; Ali Mirza; Helen Tremlett; Laura Piccio; Erin E. Longbrake; Siobhan Ni Choileain; David A. Hafler; Laura M. Cox; Howard L. Weiner; Takashi Yamamura; Kun Chen; et al. (Genome Medicine, 2024)
Abstract Background Previous studies have identified a diverse group of microbial taxa that differ between patients with multiple sclerosis (MS) and the healthy population. However, interpreting findings on MS-associated microbiota is challenging, as there is no true consensus. It is unclear whether there is gut microbiota commonly altered in MS across studies. Methods To answer this, we performed a meta-analysis based on the 16S rRNA gene sequencing data from seven geographically and technically diverse studies comprising a total of 524 adult subjects (257 MS and 267 healthy controls). Analysis was conducted for each individual study after reprocessing the data and also by combining all data together. The blocked Wilcoxon rank-sum test and linear mixed-effects regression were used to identify differences in microbial composition and diversity between MS and healthy controls. Network analysis was conducted to identify bacterial correlations. A leave-one-out sensitivity analysis was performed to ensure the robustness of the findings. Results The microbiome community structure was significantly different between studies. Re-analysis of data from individual studies revealed a lower relative abundance of Prevotella in MS across studies, compared to controls. Meta-analysis found that although alpha and beta diversity did not differ between MS and controls, a higher abundance of Actinomyces and a lower abundance of Faecalibacterium were reproducibly associated with MS. Additionally, network analysis revealed that the recognized negative Bacteroides-Prevotella correlation in controls was disrupted in patients with MS. Conclusions Our meta-analysis identified common gut microbiota associated with MS across geographically and technically diverse studies.