bioRxivNeurosciencePreprint
Microbiome-to-Nigrostriatal Vulnerability Mapping Prioritizes SCFA-Linked Gut-Brain Axes in Parkinson's Disease
Abstract
BackgroundParkinsons disease (PD) is increasingly recognized as a multisystem neurodegenerative disorder in which gastrointestinal dysfunction, microbial ecology, immune signaling, and nigrostriatal vulnerability intersect. Microbiome studies have identified PD-associated gut microbial alterations, but translating these observations into host-relevant biological axes requires integration across microbial functions, metabolites, host genes, and brain-region transcriptomic context. MethodsMiNi-PD was developed as a lightweight, fully in silico, table-level prioritization workflow integrating processed PD microbiome features, curated microbe-metabolite-host-gene associations from gutMGene v2.0, and processed substantia nigra and putamen transcriptomic support from GSE136666. The framework ranks microbe-metabolite-host-gene axes using exact-curated metabolite-mediated evidence, brain-region support, and a normalized Nigrostriatal Gut-Brain Convergence Score (NGBCS). ResultsStrict evidence filtering retained 639 primary exact-curated metabolite-mediated axes. Of these, 12 had FDR-level brain transcriptomic support and 65 had nominal-or-stronger support. IL1B emerged as the principal FDR-level host-gene convergence point. SCFA-linked metabolites dominated the primary exact-curated set, including 387 butyrate axes and 5 3-indolepropionic-acid axes. The FDR-supported axes reached the maximum NGBCS value of 5.0, while the top nominally supported axes reached the high-priority NGBCS value of 4.5. ConclusionMiNi-PD identifies a focused SCFA-linked gut-brain signature in PD, highlighting butyrate- and 3-indolepropionic-acid-associated links to IL1B as a biologically meaningful substantia nigra-supported inflammatory axis. The NGBCS framework provides an accessible and interpretable route for prioritizing metabolite-mediated gut-brain mechanisms for downstream validation.
- organism: human
- assay: metagenomics
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 0
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