Systemic Drivers and Molecular Mechanisms of Sarcopenia in Aetiology‐Specific End‐Stage Liver Disease
Notice bibliographique
Résumé
BACKGROUND: Patients with end-stage liver disease (ESLD) often present with sarcopenia, defined as loss of skeletal muscle mass and quality, which is associated with reduced quality of life and increased mortality. However, the molecular mechanisms driving sarcopenia in ESLD are not fully understood and there are currently no therapeutic interventions. This study aimed to identify potential circulating factors contributing to sarcopenia progression in ESLD by assessing their role in driving transcriptomic alterations in skeletal muscle. METHODS: Quadriceps muscle tissue, plasma and serum were obtained from ESLD patients (n = 24) and age/sex-matched healthy controls (HC; n = 18) (Clinical Trial ID: NCT04734496, Ethical Approval 18/WM/0167). Total RNA from snap-frozen vastus lateralis muscle biopsies underwent RNA sequencing (Illumina). Serum concentrations of 60 cytokines were profiled by Luminex and ELISA, with comparisons made both between ESLD and HC, and across ESLD aetiologies (alcohol-related, NAFLD, viral hepatitis, other). In vitro, primary human myotubes (from non-ESLD aged donors, NRES #16/SS/0172) were treated with 10% ESLD or HC plasma (24 h, n = 6 per group) followed by RNA sequencing (BGI Genomics). Differentially expressed genes (p < 0.05, fold-change > 1.5) were identified via Qlucore and DESeq2, and pathway analysis performed using Ingenuity (Qiagen). The impact of physiological concentrations of candidate cytokines (IL-1α, GDF-15 and HGF) on myotube thickness, differentiation and mitochondrial function was assessed by immunofluorescence microscopy, RT-qPCR and metabolic flux assays. RESULTS: In ESLD muscle, 387 and 225 genes were significantly up- and downregulated compared to HC, respectively, with cellular senescence identified as a top dysregulated function. Upstream regulator analysis predicted activation of hepatocyte growth factor (HGF) and interleukin-1 signalling. Subgroup analysis revealed distinct transcriptomic profiles based on disease aetiology. Serum profiling identified 15 cytokines significantly elevated (p < 0.05) and five reduced (p < 0.05) in ESLD, including increased HGF and reduced interleukin-1 receptor antagonist. Stratified analysis also revealed aetiology specific cytokine profiles, with only GDF-15 significantly (p < 0.0001) elevated in all groupsTwenty-four-hour ESLD plasma treatment induced 423 differentially expressed genes in human myotubes, which were again associated with significant activation of senescence pathways, with IL-1 identified as a key upstream driver. In vitro, IL-1α, GDF-15, and HGF significantly reduced myotube thickness, nuclear fusion index and perturbed metabolism (increased glycolysis, impaired oxidative phosphorylation). CONCLUSIONS: Collectively, these findings suggest that sarcopenia in ESLD is driven by aetiology-specific mechanisms, highlighting the potential for targeted therapies to improve muscle mass and function.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».