Systemic Drivers and Molecular Mechanisms of Sarcopenia in Aetiology‐Specific End‐Stage Liver Disease
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".