Abstract 3228: Tobacco smoking and circulating immune-related biomarkers in monozygotic twins
Notice bibliographique
Résumé
Abstract Background: Tobacco smoking is a cause of a variety of cancers by various mechanisms. Paradoxically, smoking also increases the risk of atopy and asthma, which are inversely associated with some cancers such as glioma, colorectal cancer and non-Hodgkin lymphoma, but positively associated with others such as lung cancer. Tobacco smoking may affect the immune system, which may explain some of these associations. We assessed the association between smoking and levels of 27 serum immune/inflammatory markers and DNA methylation in healthy monozygotic (MZ) twins. Methods: 67 MZ twin pairs were identified from the Finnish Twin Cohort Study. Cotinine and immune related biomarkers were measured from fasting serum samples using LC-MS/MS and Luminex multiples assays. Current smoking status was defined by cotinine >3.08 ng/mL. Current smokers were further categorized into low vs high smoking level by the median cotinine (78.17 ng/mL) among smokers. Questionnaire reports of current and former smoking included duration, amount (cigarettes per day [CPD]) and years since quitting. Linear mixed models were used to assess the association between smoking variables and each individual biomarker. For each smoking variable P values were adjusted for multiple comparisons using Pact, taking into account correlations among biomarkers. For biomarkers significantly associated with smoking, we assessed whether blood DNA methylation of biomarker-related genes mediated the smoking-biomarker association. Results: The median age of the study population was 24.8 years (range 21.0-68.9 years) and 56.7% were female twins. 32.1% of the twins were current smokers according to cotinine levels. Current smoking, defined by either cotinine or self-reports, was significantly associated with CCL17, B-cell activating factor (BAFF) and haptoglobin (Hp) levels respectively, after adjusting for multiple comparisons. For instance, serum cotinine was associated with increasing CCL17 levels (Pact for trend test = 0.002): the geometric mean CCL17, adjusted for age and sex among current high-level smokers was approximately 8.2% higher than noncurrent smokers. Similar positive dose-response relationships were observed for self-reported smoking variables with the 3 biomarkers. However, we found no associations between former smoking and any of the 27 biomarkers. We also found that smoking-associated DNA methylation alterations in 3 CpG sites of BAFF affected circulating CCL17 (CpG site: cg11726530) and Hp (cg09158314 and cg21784254) levels, respectively. Conclusion: Current but not former smoking may be associated with alterations in circulating levels of CCL17, BAFF and Hp, suggesting that smoking may promote B-cell activation and affect Th2 immune response, which may play a role in carcinogenesis. Further, preliminary mediation analysis suggests that smoking-induced alterations in these biomarkers may partially mediate through DNA methylation. Citation Format: Jun Wang, David Conti, Marta Epeldegui, Miina Ollikainen, Amie E. Hwang, Ann S. Hamilton, Larry Magpantay, Rachel Tyndale, Thomas M. Mack, Otoniel Martinez-Maza, Jaakko Kaprio, Wendy Cozen. Tobacco smoking and circulating immune-related biomarkers in monozygotic twins [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3228.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».