Identifying microbial biomarkers of neurodegeneration: a comparative study in Alzheimer's and Parkinson's disease.
AI interpretation is pending for this paper.
What the AI sees
Not AI summarized yet.
Research significance
Pending deeper interpretation.
Source abstract
INTRODUCTION: Neurodegenerative disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD) have been increasingly linked to alterations of the gut microbiota, although reported microbial signatures remain heterogeneous and often lack taxonomic resolution. METHODS: In the present study, we applied full-length 16S rRNA gene sequencing to characterize gut microbiota composition in 152 individuals, including patients with AD (n = 37), PD (n = 65), and age-matched healthy controls (n = 50), using a unified bioinformatic and statistical framework with adjustment for relevant demographic covariates. RESULTS: Alzheimer's disease was associated with a modest but significant reduction in microbial richness and Shannon diversity compared with controls, whereas no alpha diversity differences were observed in PD. Beta diversity analyses revealed significant compositional differences across diagnostic groups, driven primarily by PD and modulated by sex but not age. Species-level differential abundance analysis identified a PD-associated microbial signature characterized by reduced abundances of short-chain fatty acid-producing bacteria, including Faecalibacterium prausnitzii, Agathobacter rectalis, Roseburia intestinalis, and Faecalicatena fissicatena, together with increased abundance of Ruminococcus sp. JE7A12. In contrast, AD exhibited minimal species-level changes, with only Bacteroidales bacterium CF showing reduced abundance compared with controls. DISCUSSION: Overall, these findings indicate that Parkinson's disease is characterized by a targeted disruption of beneficial butyrate-producing bacteria, whereas Alzheimer's disease exhibits subtler and less consistent microbiome alterations. Our results underscore the importance of species-level resolution for identifying disease-associated microbial signatures.