Joint Analysis of Metabolite Markers of Fish Intake and Persistent Organic Pollutants in Relation to Type 2 Diabetes Risk in Swedish Adults
Bibliographic record
Abstract
BACKGROUND: There is conflicting evidence regarding the association between fish intake and type 2 diabetes (T2D) incidence, possibly owing to measurement errors in self-reported intake and coexposure to persistent organic pollutants (POPs) present in fish. OBJECTIVE: The aim of this study was to identify plasma metabolites associated with fish intake and to assess their association with T2D risk, independently of POPs, in Swedish adults. METHODS: In a case-control study nested in the Swedish Västerbotten Intervention Programme, fasting plasma samples from 421 matched T2D case-control pairs of men and women aged 30-60 y at baseline and 10-y follow-up samples from a subset of 149 pairs were analyzed using untargeted metabolomics. Moreover, 16 plasma POPs were analyzed for the 149 pairs who had repeated samples available. Fish-related plasma metabolites were identified using multivariate modelling and partial correlation analysis. Reproducibility of metabolites and metabolite patterns, derived via principal component analysis (PCA), was assessed by intraclass correlation. A unique component of metabolites unrelated to POPs was dissected by integrating metabolites and POPs using 2-way orthogonal partial least squares regression. ORs of T2D were estimated using conditional logistic regression. RESULTS: We identified 31 metabolites associated with fish intake that had poor to good reproducibility. A PCA-derived metabolite pattern strongly correlated with fish intake (ρ = 0.37, P < 0.001) but showed no association with T2D risk. Integrating fish-related metabolites and POPs led to a unique metabolite component independent of POPs, which tended to be inversely associated with T2D risk (OR: 0.75; 95% CI: 0.54, 1.02, P = 0.07). This component mainly consisted of metabolites reflecting fatty fish intake. CONCLUSIONS: Our results suggest that fatty fish intake may be beneficial for T2D prevention, after removing the counteractive effects of coexposure to POPs in Swedish adults. Integrating metabolite markers and POP exposures appears a promising approach to advance the understanding of associations between fish intake and T2D incidence.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".