Predicting neurodegenerative disease using pre-pathology gut microbiota composition: a longitudinal study in mice modeling Alzheimer’s disease pathologies

Abstract

The gut microbiota-brain axis is suspected to contribute to the development of Alzheimer’s Disease (AD), a neurodegenerative disease characterized by amyloid-β plaque deposition, neurofibrillary tangles, and neuroinflammation. To evaluate the role of the gut microbiota-brain axis in AD, we characterized the gut microbiota of 3xTg-AD mice modeling amyloidosis and tauopathy and wild type (WT) genetic controls. Fecal samples were collected fortnightly from 4 to 52 weeks, and the V4 region of the 16S rRNA gene was amplified and sequenced on an Illumina MiSeq. RNA was extracted from the colon and hippocampus, converted to cDNA, and used to measure immune gene expression using RT-qPCR. Diversity metrics were calculated using QIIME 2, and a Random Forest classifier was applied to predict bacterial features that are important in predicting mouse genotype. Gut microbiota were compositionally distinct early in life between 3xTg-AD mice and WT mice (PERMANOVA 8 weeks, p = 0.001, 24 weeks, p = 0.039, and 52 weeks, p = 0.058). We demonstrate that mouse genotype was correctly predicted 90–100% using fecal microbiome composition. Finally, we demonstrate that Bacteroides species relative abundance increased over time in 3xTg-AD mice. Taken together, we demonstrate that changes bacterial gut microbiota composition at pre-pathology timepoints are predictive of development of AD pathologies.

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