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Machine Learning and Canine Chronic Enteropathies: A New Approach to Investigate FMT Effects
Giada Innocente1, Ilaria Patuzzi1, Tommaso Furlanello2
1Research & Development Division, EuBiome S.r.l., 35131 Padova, Italy.
Abstract:
Fecal microbiota transplantation (FMT) represents a very promising approach to decreasing disease activity in canine chronic enteropathies (CE). However, the relationship between remission mechanisms and microbiome changes has not been elucidated yet. The main objective of this study was to report the clinical effects of oral freeze-dried FMT in CE dogs, comparing the fecal microbiomes of three groups: pre-FMT CE-affected dogs, post-FMT dogs, and healthy dogs. Diversity analysis, differential abundance analysis, and machine learning algorithms were applied to investigate the differences in microbiome composition between healthy and pre-FMT samples, while Canine Chronic Enteropathy Clinical Activity Index (CCECAI) changes and microbial diversity metrics were used to evaluate FMT effects. In the healthy/pre-FMT comparison, significant differences were noted in alpha and beta diversity and a list of differentially abundant taxa was identified, while machine learning algorithms predicted sample categories with 0.97 (random forest) and 0.87 (sPLS-DA) accuracy. Clinical signs of improvement were observed in 74% (20/27) of CE-affected dogs, together with a statistically significant decrease in CCECAI (median value from 5 to 2 median). Alpha and beta diversity variations between pre- and post-FMT were observed for each receiver, with a high heterogeneity in the response. This highlighted the necessity for further research on a larger dataset that could identify different healing patterns of microbiome changes.
Insights
Fecal microbiota transplantation (FMT) shows promise for canine chronic enteropathies (CE). While FMT improved clinical signs in most dogs, microbiome changes varied, indicating a need for further research into healing patterns.
Area of Science:
- Veterinary Medicine
- Microbiome Research
- Gastroenterology
Background:
- Canine chronic enteropathies (CE) are complex gastrointestinal disorders.
- Fecal microbiota transplantation (FMT) is a potential therapeutic strategy for CE.
- The precise mechanisms linking microbiome alterations and CE remission remain unclear.
Purpose of the Study:
- To evaluate the clinical efficacy of oral freeze-dried FMT in dogs with CE.
- To compare fecal microbiome composition in healthy dogs, pre-FMT CE dogs, and post-FMT CE dogs.
- To investigate the relationship between microbiome changes and clinical improvement following FMT.
Main Methods:
- Fecal samples analyzed for microbiome diversity (alpha and beta diversity).
- Differential abundance analysis and machine learning identified distinct microbial profiles.
- Canine Chronic Enteropathy Clinical Activity Index (CCECAI) assessed clinical outcomes.
Main Results:
- Significant differences in microbiome diversity and composition were found between healthy and pre-FMT CE dogs.
- Machine learning accurately classified sample origins based on microbiome data.
- 74% of CE dogs showed clinical improvement post-FMT, with a significant CCECAI reduction.
- Individualized variations in microbiome shifts were observed post-FMT, indicating heterogeneous responses.
Conclusions:
- Oral freeze-dried FMT is clinically beneficial for canine chronic enteropathies.
- FMT induces significant changes in the canine gut microbiome.
- Further research with larger cohorts is needed to understand diverse microbiome-mediated healing patterns in CE.
