Abstract P3043: Circulating Omega-3 Polyunsaturated Fatty Acids and Early Type 2 Diabetes Risk Phenotypes: Longitudinal Analyses in the PROspective Metabolism and ISlet cell Evaluation (PROMISE) Cohort
Bibliographic record
Abstract
Background: Literature on omega-3s and T2D risk has been heterogenous; however, most prior studies have used self-reported dietary intake or short-term supplementation regimens. Thus, further investigation is needed to assess longitudinal associations of circulating omega-3 with early T2D risk phenotypes. Objective: Assess longitudinal associations of circulating omega-3s with changes in insulin sensitivity (IS) and β-cell function (BCF) in the PROMISE cohort. Methods: Adults at-risk for T2D underwent four assessments over 9 years (n=472); blood samples were collected to determine insulin and glucose concentrations, and an OGTT was conducted. Baseline serum omega-3s (ALA, EPA, DPAn-3, DHA) were measured using gas chromatography-flame ionization detection. OGTT values were used to calculate validated IS (HOMA2-%S, ISI) and BCF (IGI/IR, ISSI-2) indices. Generalized estimating equations (GEE) analysis assessed the association between baseline omega-3s (mol%) with longitudinal change in IS and BCF indices after covariate adjustment. Results: Significant positive correlations were shown between EPA and DHA with IS measures (HOMA2-%S: EPA, r=0.18, DHA, r=0.23, all p<0.001; ISI: EPA, r=0.15, p<0.01, DHA, r=0.19, p<0.001) and between DHA and BCF indices (IGI/IR, r=0.14, p<0.01; ISSI-2, r=0.1, p<0.05). In adjusted GEE models, baseline EPA and DHA were positively associated with longitudinal change in IS (HOMA2-%S, p<0.001; ISI , p<0.01), and BCF (IGI/IR, p<0.05) ( Figure ) . Conclusions: Circulating omega-3s (specifically EPA and DHA) were positively associated with IS and BCF, which are important early T2D risk phenotypes. These findings add to growing evidence of the potential role omega-3s have in T2D primary prevention.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".