Identification of DNA methylation signature of frailty in postmenopausal women and extracellular vesicle mediated epigenetic age reversal in skeletal myoblasts
Notice bibliographique
Résumé
As the Canadian population continues to age, healthcare systems are expected to be burdened with an increasing incidence of age-related illnesses. Current strategies are aimed at promoting healthy living and aging in place, but the underlying biology of frailty is not yet understood at the depth required for therapeutic intervention. DNA methylation (DNAm) studies implicate epigenetic maintenance systems as some of the molecular contributors leading to cellular dysfunction. By leveraging changes at particular DNAm loci, biological clocks have been created to predict an i4ndividual’s apparent age. Parabiosis experiments with extracellular content from young donors have successfully reduced the severity of age-related diseases in treated old organisms, indicating that extracellular signaling plays a crucial role in aging. How epigenetic dysregulation and extracellular communication interact in the context of frailty is still not understood, and even less so in the often under-studied population of older women. We sought to better understand the DNA methylation signature of frailty and transmission of epigenetic age through extracellular cargo in the woman-centered WARMHearts Study (Clinical Trial #NCT02863211). In this study, we: 1) isolated and profiled genome-wide DNA methylation from frail and robust women between 55-79 years old (Md = 64, IQR [59-68]) to identify frailty-linked DNAm loci, and 2) co-cultured robust/slow-aging extracellular vesicles (EVs), and frail/fast-aging EVs with chronologically young and old primary human skeletal myoblasts to explore the effect of circulating EVs from individuals of similar chronological age. Our results demonstrate that epigenetic clocks based on biomarkers of health and inflammation are better at predicting frailty than those trained only on chronological age data. We also found 9 cytosine-guanine dimers (CpG) that were differentially methylated (p < 1 x 10-6, |Δβ|> 0.01, N = 56), 8 CpGs that were variably methylated (p < 1 x 10-6, N = 56), and 43 regions with multiple CpGs within 1 kb that were differentially methylated (FDR < 0.05, N = 56) with frailty. The myoblast co-culture experiments demonstrated epigenetic age acceleration only in young myoblasts treated with robust plasma (p = 0.024, GrimAgeAccel = 1.79), although our collaborators in the Saleem Lab found significant phenotypic alterations in cell viability and senescence with robust EVs. Our data demonstrates that inflammation, cancer, and cardiometabolic disease drive frailty-associated alterations in DNAm in postmenopausal women. We also found that our EV treatment does not show significant alterations in epigenetic aging rates, likely from the amount of baseline drift in cultured cells from variable passaging and plating density. This thesis demonstrates that epigenetic aging and gene-regulation contribute to frailty in postmenopausal women, even after controlling for tobacco smoking, income, and chronological age.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 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) | 0,001 | 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 ».