Plasma <i>n</i> -3 Polyunsaturated Fatty Acid Levels and Colorectal Cancer Risk in the UK Biobank: Evidence of Nonlinearity, as Well as Tumor Site- and Sex-Specificity
Bibliographic record
Abstract
BACKGROUND: The relationship between omega-3 polyunsaturated fatty acid (n-3 PUFA) intake and colorectal cancer risk is unclear. Blood n-3 PUFA concentration is a biomarker of dietary n-3 PUFA intake. We examined the relationship between plasma n-3 PUFA concentrations and colorectal cancer risk in UK Biobank (UKBB) participants. METHODS: We analyzed the relationship between tertiles (T) of plasma total n-3 PUFAs and n-3 PUFA docosahexaenoic acid (DHA) levels, and overall colorectal cancer (also stratified by tumor location and sex) risk. Cox proportional hazards regression models were adjusted for clinical covariates. Nonlinearity was tested by restricted cubic splines. RESULTS: There were 2,602 incident colorectal cancer cases in 234,598 UKBB participants with baseline plasma fatty acid data (mean follow-up 13.4 years). There was an inverse association between the plasma total n-3 PUFA level [T2 HR = 0.88 (95% confidence interval, 0.80-0.97) compared with the T1 reference; T3 = 0.91 (0.83-1.00)], as well as the plasma DHA concentration [T2 = 0.89 (0.80-0.98); T3 = 0.91 (0.82-1.00)], and colorectal cancer risk. The relationship was nonlinear [P for nonlinearity = 0.14 (total n-3 PUFAs) and 0.008 (DHA)], with a plateau effect at the highest n-3 PUFA concentrations. The relationship was more pronounced for proximal colon cancer [T2 = 0.82 (0.69-0.97); T3 = 0.76 (0.64-0.90) for DHA] and was evident for males [T2 = 0.84 (0.74-0.95); T3 = 0.89 (0.78-1.00)], but not for females. CONCLUSIONS: Higher plasma n-3 PUFAs are associated with reduced colorectal cancer risk in the UKBB. IMPACT: Nonlinearity, as well as tumor site and sex specificities, of the inverse relationship between plasma n-3 PUFA levels and colorectal cancer risk, if confirmed in other diverse populations, has significant implications for nutritional prevention guidelines.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".