Abstract C057: Associations between accelerated epigenetic age and patient-reported outcomes in cancer patients
Notice bibliographique
Résumé
Abstract Background: The relationship between epigenetic aging and cancer mortality has been well established; however, research is limited on how accelerated epigenetic age may be associated with other cancer-related health outcomes. Epigenetic clocks such as DNAm PhenoAge have recently emerged as biomarkers that can reliably predict morbidity and mortality by assessing DNA methylation at specific gene loci. When estimated epigenetic age surpasses chronological age, the discrepancy is termed epigenetic age acceleration (EAA). Various studies have linked higher EAA to risk factors such as low socioeconomic status, adverse childhood experiences, chronic stress, and HIV infection. Given that many of these factors are also associated with disparities in cancer-related health outcomes, investigating the relationship between accelerated aging and cancer-related symptoms could provide insight into the mechanisms that drive these differences. This study examined correlations between EAA and patient-reported outcomes (PROs) in cancer patients. Methods: The analytic data set was obtained by cross-referencing patient data collected as part of two concurrent studies conducted at Moffitt Cancer Center. In one study, cancer patients with and without HIV provided blood samples which were assayed using the Illumina MethylationEPIC BeadChip and translated through the EstimAge website to determine EAA via DNAm PhenoAge and PhenoAge acceleration. In the second study, a larger cohort of cancer patients completed the Edmonton Symptom Assessment Scale (ESAS), which asked them to rate the severity of 12 symptoms on a scale from 0 to 10. A total composite ESAS score was summed to represent overall symptom burden. Patients who provided both an assayed blood sample and a completed ESAS survey were included in this investigation. Spearman’s rank correlation coefficients were calculated to assess the association between PhenoAge acceleration and ESAS symptom severity. Results: Participants included in this study (n=22) were 77% male, 82% White, 9% Black, 4.5% Hispanic or Latino, and 36% HIV-positive. The three most prevalent primary cancers among participants were anal (32%, n=7), lung (14%, n=3), and pancreatic (14%, n=3). The median interval between ESAS completion and blood collection was 70 days (IQR=109). The average composite ESAS score was 35, and the average PhenoAge acceleration was 3.3 years. We observed a moderate correlation between PhenoAge acceleration and several symptoms that met the p<.05 threshold for statistical significance. Specifically, PhenoAge acceleration was moderately correlated with severity of drowsiness (ρ=.60, p<.01), reduced overall well-being (ρ=.49, p=.02), constipation (ρ=.47, p=.03), nausea (ρ=.44, p=.04), and shortness of breath (ρ=.44, p=.04). PhenoAge acceleration was also moderately associated with higher overall symptom burden (ρ=.45, p=.03). Conclusions: We observed that EAA in cancer patients, including those with a comorbid diagnosis of HIV, was associated with worse patient-reported outcomes across a range of symptoms. Citation Format: Sonia T. Brickey, KD L. Jacobs, Aasha I. Hoogland, Ryan M. Putney, Kristina E. Bowles, Heather Jim, Brian D. Gonzalez, Anna E. Coghill. Associations between accelerated epigenetic age and patient-reported outcomes in cancer patients [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr C057.
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 | 0,004 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».