Abstract 2003: Poor diet quality is associated with immune aging in survivors of pediatric acute lymphoblastic leukemia
Bibliographic record
Abstract
Abstract Rationale and objectives: Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer. Despite a 90% five-year survival rate, survivors of childhood ALL often suffer from late effects, including cardiometabolic disorders. Contributing factors such as inflammation and oxidative stress, combined with drug treatments, can induce premature aging and cellular senescence with a significant impact on cardiometabolic disorders. Premature aging can lead to decreased thymic T-cell production, resulting in decreased circulation of T-cell receptor excision circles (TRECs). Because diet has been associated with cardiometabolic disorders, we hypothesized that the quality of diet in children who had survived ALL was related to the immune aging biomarker TREC, in concert with inflammatory status. Methods: Adolescent and young adult survivors of pediatric ALL of the PETALE cohort (n=241, 22.1 ± 6.3 years at diagnosis, 49.4% male) were examined in their profile for TREC levels (by qPCR) and for adherence to 6 diet quality indices. Results: Adjusted linear regressions revealed that the Healthy Diet Indicator (HDI) was associated with TREC levels (β=50.0, p=0.005, adjusted p=0.03). After performing a conceptual relational analysis (CAR) for data mining of various biomarkers of inflammation, oxidative stress, endotoxemia, and endothelial or adipose dysfunction; interleukin-6 (IL-6) and C-reactive protein (CRP) were found to be negatively associated with TREC levels (β= -80 and -80.1, p=0.017 and 0.026, respectively) but not with HDI. Further analysis revealed that IL-6 and CRP levels were moderators, but not mediators, of the association between HDI and TREC. Conclusion: This study supports the positive impact of a healthy diet on premature immune aging and the moderating role of inflammation in this association. Citation Format: Abderrahim Benmoussa, Tibila Kientega, Sophia Morel, Guillaume Cardin, Sophie Bérard, Mickael wajnberg, Petko Valtchev, Alexandre Blondin-Masse, Daniel Curnier, Maja Krajinovic, Caroline Laverdière, Daniel Sinnett, Emile Levy, Sophie Marcoux, Francis Rodier, Valérie Marcil. Poor diet quality is associated with immune aging in survivors of pediatric acute lymphoblastic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2003.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".