Abstract
Migration is associated with a substantial change in environmental exposures and health outcomes. We aimed to investigate the shift in gut microbiota composition and the associations with cardiometabolic outcomes in the RODAM-Pros cohort spanning multiple research sites across continents. We determined gut microbiota composition of 1,177 Ghanaian participants in rural Ghana, urban Ghana, and Amsterdam, the Netherlands, using 16S rRNA sequencing. We observed a clear gradient in gut microbiota composition and alpha and beta diversity from rural Ghana to urban Ghana, to Amsterdam. We used pairwise XGBoost machine learning classification models to identify which microbes were most distinct between locations in prevalence and abundance. The associations between these microbes and the locations could partly be explained by differences in confounders such as dietary intake. Groups of microbes that emerged or disappeared along the migration axis were associated with cardiometabolic outcomes, including higher body mass index, higher HbA1c and higher diastolic blood pressure. Concluding, we identified associations between a shift in gut microbiota composition and cardiometabolic risk along the migration axis, underscoring the relevance of gut health in the context of migration-associated adverse health outcomes.
| Original language | English |
|---|---|
| Article number | 2471960 |
| Journal | Gut Microbes |
| Volume | 17 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Gut microbiota
- machine learning
- migration
- urbanization
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