A journey from India to Canada : the westernization of the gut microbiome is associated with dietary acculturation in Indian migrants
Bibliographic record
Abstract
The growing immigrant population in North America are experiencing westernization at a rapid rate. Amidst the backdrop of rising immigration, health disparities are emerging in immigrants, including several modern diseases linked with the westernized lifestyle. Young Indian immigrants and Indo-Canadians face a significantly higher risk of inflammatory bowel disease (IBD) in westernized countries. While the root causes of IBD are not entirely understood, a main characteristic is an imbalanced gut microbiome no longer in symbiosis with its host. However, Indian populations are underrepresented in microbiome studies, making it challenging to determine the influences of their gut microbiome in this increased IBD risk. To understand why Indians are more vulnerable to IBD in Canada, it is essential to first investigate their gut microbiome. This thesis explores the gut microbiome transition in Indian migrants in Canada by characterizing their microbial composition, and the impact of their dietary patterns on the microbiome. Using 16S and shotgun sequencing data obtained from stool samples of healthy subjects, our study compares the microbiome of Indians residing in India, Indian immigrants, and Indo-Canadians, with Euro-Canadians and Euro-Immigrants as westernized controls. Our findings reveal significant differences in microbiota composition among these groups, with Indian residents showing a distinctive gut microbiota rich in Prevotella spp., whereas Indo-Canadians resembled more of an industrialized gut, with higher Bacteroides spp. abundance. While Indo-Immigrants had a gut microbiota that was distinct from Indians and westernized cohorts, some subjects displayed moderate levels of Prevotella spp. abundances, which may be due to their mixed diet that included both traditional Indian and westernized foods. This study concludes that Indo-Canadians undergo a marked transition towards an industrialized microbiome within just one generation, both through functional changes and the loss of Prevotella spp. This microbiota transition was associated with a large change in dietary habits, in particular a decrease in a high carbohydrate, high fibre diet, and an increase in ultra-processed foods. Overall, the data shown offers insight into how migration and lifestyle changes affect both microbial composition and functions in the gut, and their implications for understanding immigrant-health outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".