Abstract 1880: Associations of coffee drinking with systemic immune and inflammatory markers
Bibliographic record
Abstract
Abstract Background: Coffee drinking has been inversely associated with mortality as well as cancers of the endometrium, colon, skin and liver. Improved insulin sensitivity and reduced inflammation are among the hypothesized mechanisms by which coffee drinking may affect cancer risk. The association between coffee drinking and systemic levels of immune and inflammatory markers has not been well characterized. Objective: To explore the associations of coffee drinking with levels of a wide range of immune and inflammatory markers. Design: Luminex bead-based assays were used to measure serum levels of 77 immune and inflammatory markers in 1728 older non-Hispanic Whites from three case-control studies nested within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Usual coffee intake was self-reported using a semi-quantitative food frequency questionnaire. We used weighted multivariable logistic regression models to examine the associations between coffee drinking and dichotomized marker levels. We conducted statistical trend tests by assigning each coffee category its median value and modeling as a continuous variable. We applied a 20% false discovery rate criterion to the P-values for trend. Results: Ten of the 77 examined markers were nominally associated (P-value<0.05) with coffee drinking. The five markers that withstood correction for multiple comparisons included various aspects of the host response namely chemotaxis of monocytes/macrophages (IFNγ, CX3CL1/fractalkine, CCL4/MIP-1β), pro-inflammatory cytokines (sTNFRII) and regulators of cell growth (FGF-2). Heavy coffee drinkers had lower circulating levels of IFNγ (OR = 0.35; 95% CI 0.16, 0.75; P-trend = 0.0003), CX3CL1/fractalkine (OR = 0.25; 95% CI 0.10, 0.64; P-trend = 0.0031), CCL4/MIP-1β (OR = 0.48; 95% CI 0.24, 0.99; P-trend = 0.0050), FGF-2 (OR = 0.62; 95% CI 0.28, 1.38; P-trend = 0.0080) and sTNFRII (OR = 0.34; 95% CI 0.15, 0.79; P-trend = 0.0112) than non-coffee drinkers. Conclusions: Coffee drinking was associated with lower circulating levels of inflammatory markers, which may partially mediate previously observed associations of coffee drinking with lower mortality and morbidity. Validation studies, ideally controlled feeding trials, and prospective studies, such as nested case-control studies, are needed to confirm these associations. Citation Format: Erikka Loftfield, Meredith S. Shiels, Barry I. Graubard, Hormuzd A. Katki, Anil Chaturvedi, Britton Trabert, Ligia Pinto, Troy Kemp, Fatma M. Shebl, Susan T. Mayne, Nicolas Wentzensen, Mark P. Purdue, Allan Hildesheim, Rashmi Sinha, Neal D. Freedman. Associations of coffee drinking with systemic immune and inflammatory markers. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1880. doi:10.1158/1538-7445.AM2015-1880
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.005 | 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".