Letter to the Editor: Skeletal muscle transcriptomics in metabolic dysfunction-associated steatotic liver disease - balancing promise with validation

Abstract

This letter underscores the clinical relevance of the study by Zhang et al published in the World Journal of Gastroenterology on exercise-responsive skeletal muscle genes in metabolic dysfunction-associated steatotic liver disease and commends its integrative design. We also note key limitations, including a permissive differential expression threshold that could be refined by applying more stringent criteria (e.g., |log2FC| ≥ 0.5 with false discovery rate < 0.05) and the fact that receiver operating characteristic analyses do not equate to clinical diagnostic validation. The exercise-related changes in LAMA4, PECAM1, PXDN, and THBS4 are intriguing and may reflect muscle-liver crosstalk; however, further human and functional validation is needed before clinical translation.

Key Words: Metabolic dysfunction-associated steatotic liver disease; Exercise-responsive genes; Skeletal muscle; Biomarkers; Muscle-liver crosstalk

Core Tip: Zhang et al identify exercise-responsive skeletal muscle genes that may help explain the metabolic benefits of exercise in metabolic dysfunction-associated steatotic liver disease. Their integrative approach is promising, but these candidate markers require validation in well-designed, multi-center prospective human cohorts with paired liver histology or imaging data, additional human validation and functional studies before they can be considered for clinical use.

TO THE EDITOR

I read with great interest the study by Zhang et al[1] published in the World Journal of Gastroenterology, which integrated multiple skeletal muscle transcriptomic datasets, weighted gene co-expression network analysis, least absolute shrinkage and selection operator modeling, and mouse validation to identify exercise-responsive genes linked to metabolic dysfunction-associated steatotic liver disease (MASLD). The authors deserve credit for moving the field beyond a single-molecule view of exercise biology and for proposing a refined set of candidate genes that may help explain how skeletal muscle contributes to improved hepatic metabolism[1]. Beyond this, the study also illustrates the growing need for systems-level interpretation of exercise biology, particularly in settings where transcriptomic signals alone may not fully capture mechanistic complexity. In that regard, the work would benefit from being situated more explicitly within the broader framework of multi-omics and multimodal integration[2,3].

The topic is highly relevant because MASLD is now recognized as the leading cause of global chronic liver disease, closely associated with obesity, insulin resistance, and type 2 diabetes mellitus[4,5]. Exercise remains one of the most effective non-pharmacological interventions for MASLD, and its benefits are not limited to weight control; regular physical activity also modulates systemic inflammation and inter-organ communication[6,7]. In this context, the search for exercise-responsive muscle-derived biomarkers is timely and clinically meaningful[1].

DESIGN STRENGTHS AND METHODOLOGICAL CONSIDERATIONS

The conceptual strength of the paper lies in its integrative design. By combining differential expression analysis, batch correction, co-expression network analysis, functional enrichment, external validation, and in vivo confirmation, the authors established a coherent pipeline from discovery to biological plausibility[1]. This multi-layered approach is particularly valuable in MASLD research, where disease heterogeneity and the complexity of exercise adaptation often limit the reproducibility of single-dataset findings[1,4]. At the same time, current expectations in systems biology increasingly favor explicit integration of multiple data layers, since transcriptomics alone may overlook regulatory, proteomic, and metabolomic determinants of phenotype[2,3].

At the same time, several methodological issues merit caution. First, the differential-expression threshold used in the discovery phase (|log2 fold change| ≥ 0.26) is relatively permissive. While this improves sensitivity but may also increase the risk of false-positive findings in publicly available transcriptomic data[1]. Future analyses would benefit from more stringent thresholds, such as |log2FC| ≥ 0.5 combined with false discovery rate < 0.05, to enhance robustness and reproducibility. The authors appropriately acknowledge this point, and their observation of only modest module-trait correlations further suggests that the identified signals reflect subtle but potentially important biological shifts rather than large-scale transcriptional changes[1].

Second, while receiver operating characteristic analyses are useful for ranking candidate genes, they should not be interpreted as equivalent to clinical diagnostic performance[1]. The reported area under the curve values were derived from transcriptomic datasets rather than from prospective patient-level testing. Consequently, a multicenter, prospective human cohort design with paired liver histology or imaging data would be essential for clinical validation before these candidates can be translated into clinical practice[1,4]. In particular, multi-center, prospective study designs incorporating standardized clinical phenotyping would substantially strengthen translational relevance.

BIOLOGICAL INTERPRETATION OF THE CANDIDATE GENES

The most intriguing aspect of the study is the reciprocal behavior of the four exercise-responsive genes highlighted in the validation experiments: LAMA4, PECAM1, and PXDN increased with exercise, whereas THBS4 decreased[1]. This pattern suggests that endurance training may regulate extracellular matrix organization, vascular signaling, and matricellular remodeling in skeletal muscle, processes that could plausibly influence muscle-liver crosstalk and metabolic adaptation[1,8-10]. This observation could be expanded by considering biomarker specificity, biological heterogeneity, and the difference between “detectable” markers and clinically actionable biomarkers. In that sense, the work would be strengthened by framing circulating candidates within established liquid-biopsy paradigms, where systemic detectability must be complemented by rigorous validation of specificity and disease association[11].

Among these genes, PECAM1 and THBS4 are especially interesting because both were detectable in the circulation in the animal experiments, raising the possibility that they may act as muscle-derived secreted signals or reflect broader exercise-induced tissue remodeling[1]. However, secretion alone does not establish causality. It remains unclear whether these proteins directly mediate hepatic improvement or simply mirror upstream adaptations in contractile tissue, the endothelium, or the extracellular matrix[1,8,10].

Furthermore, this study also adds to the broader literature on exercise-responsive factors such as interleukin-6, irisin, and fibroblast growth factor 21, which have previously been implicated in skeletal muscle communication with the liver and adipose tissue[12-14]. In this regard, the present work broadens the field from classical myokines to a more distributed network of muscle-expressed genes involved in structural remodeling and inter-organ signaling[1,10,12-14].

TRANSLATIONAL OUTLOOK

From a translational perspective, the work is promising but remains preliminary. Because the human discovery cohorts included individuals with obesity and type 2 diabetes mellitus, the observed signatures may represent shared metabolic adaptations rather than MASLD-specific biology. Future studies should test whether this gene set remains informative across sex, age, adiposity, training modality, and disease stage[1,4,7,15,16]. A more structured validation strategy would also improve the practical value of the findings, for example by using longitudinal cohorts, pre/post exercise sampling, stratification by metabolic status, and parallel assessment of imaging and proteomic endpoints. A practical next step would be to assess whether these candidate genes or their protein products can be detected in human serum and whether their levels track with exercise response. Moreover, prospective multi-center human studies incorporating paired liver histology, imaging, and circulating biomarkers are needed to validate clinical applicability and to evaluate whether these markers could support precision exercise prescription in MASLD patients. Longitudinal human exercise trials with proteomic validation would be particularly valuable for clarifying whether these genes can serve as reliable response biomarkers or therapeutic targets[1,6,7]. In addition, a mechanistically informed translational discussion should consider oxidative-stress pathways and antioxidant responses as plausible downstream effectors of exercise benefit, particularly in light of established links between exercise, redox balance, and hepatometabolic improvement[17].

CONCLUSION

In summary, Zhang et al[1] provide a thoughtful and technically solid framework for understanding how skeletal muscle may participate in the beneficial effects of exercise in MASLD[1]. Their data support LAMA4, PECAM1, PXDN, and THBS4 as attractive candidates for future mechanistic and translational work. However, the field now requires methodologically rigorous studies incorporating stricter statistical thresholds and multicenter prospective clinical validation cohorts, together with serum-based feasibility settings to determine whether these markers can be used to guide precision exercise prescriptions or integrated therapeutic strategies[1]. A broader systems-biology perspective, including multi-omics integration and liquid-biopsy-style validation, would further strengthen the translational reach of this commentary[2,3,11,18].