Gene-environment interactions between clonal hematopoiesis of indeterminate potential and air pollution in non-small cell lung cancer among non-smokers.
Notice bibliographique
Résumé
10514 Background: Small particulate matter air pollution (≤ 2.5µm diameter; PM2.5) is a recognized driver of non-small cell lung cancer (NSCLC) among non-smokers. PM2.5 recruits pro-inflammatory macrophages to the lungs, which facilitate the clonal expansion of mutated epithelial cells and eventual transformation to NSCLC. Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related condition caused by the acquisition of somatic mutations in hematopoietic stem cells. CHIP and its accompanying pro-inflammatory phenotype have been linked with various age-related diseases, including incident NSCLC; however, the mechanisms underlying this relationship are unknown. In this study, we aimed to explore the interaction between CHIP and exposure to PM2.5 in the development of incident NSCLC. Methods: This study was conducted using data from participants in the UK Biobank (n = 451,095). CHIP status was determined from peripheral blood whole exome sequencing data, and defined as the presence of a somatic driver mutation in the blood at variant allele frequency (VAF) ≥2% (PMID: 36652671). Incident NSCLC was determined from UK cancer registry data, and PM2.5 exposure was determined based on ambient regional measures from 2010. Cox proportional hazard models were used to evaluate associations between CHIP, PM2.5, and NSCLC. Proteomics data was measured using OLINK proteomics in a subset of UK Biobank participants (n = 44,625). Results: CHIP was prevalent in 3.4% of UK Biobank participants (n = 15,633; never smokers: 3.0%, n = 6,916/227,133). There were 1983 incident cases of NSCLC (never smokers: n = 307). CHIP status was associated with incident NSCLC when adjusting for smoking status (HR = 1.73, 95% CI: 1.48–2.02) and analyzing exclusively non-smokers (HR = 2.01, 95% CI: 1.34-3.00). PM2.5 levels were not associated with NSCLC in non-smokers (HR = 1.00, 95% CI: 0.89–1.12 per µg/m3 increase in PM2.5); however, there was a significant interaction between PM2.5 and CHIP (HR = 1.46, 95% CI: 1.02–2.11, pint = 0.04), suggesting that it is the interplay between the two that drives incident NSCLC risk. We found no association between PM2.5 levels and increased CHIP prevalence or CHIP VAF. PM2.5 and CHIP were also found to interact to increase systemic inflammatory markers C-reactive peptide (pint = 0.01) and IL-6 (pint = 0.002). Conclusions: PM2.5 and CHIP act as a novel gene x environment interaction pair that play a key role in NSCLC etiology among non-smokers. Rather than acting in isolation to increase risk of NSCLC, PM2.5 intensifies the relationship between CHIP and NSCLC, presumably by exacerbating systemic inflammation and the hyper-inflammatory lung microenvironment. With PM2.5 levels in the UK among the lowest in the world, we posit that the CHIP x PM2.5 interaction contributes substantially to the global burden of NSCLC in non-smokers.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 ».