Review Reports - Association Between Sclerostin and Sarcopenia-Related Functional Decline in Older Women

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

INTRODUCTION

This section is well-written.

MATERIALS AND METHODS

The section is generally well structured and clear in reporting diagnostic criteria and statistical procedures. The methodological rigor is appreciable, especially the justification for sample size. However, there are two points where clarification would improve transparency and reproducibility:

Participants were prospectively enrolled, but it remains unclear whether DEXA, grip strength, and blood sampling were performed on the same day or within a defined time frame.
Exclusion criteria are adequate, but the analysis does not appear to account for common agents affecting bone or muscle turnover (e.g., vitamin D or calcium supplementation, statins, corticosteroids, aromatase inhibitors). I would suggest either reporting concomitant medications and supplements, or at least acknowledging this variable as a limitation. If available, an adjustment in the logistic regression model would meaningfully strengthen the conclusions.

RESULTS

The results section is generally well structured. The tables are concise and numerical values are not redundantly repeated across the narrative.

DISCUSSION

- The discussion notes that sclerostin correlates more with strength than with muscle mass, but it would be helpful to further emphasize the clinical significance of this distinction. For example, the potential implications for diagnosing and monitoring sarcopenia, as opposed to relying solely on ASM as a confirmatory measure, could be highlighted.

- I would suggest citing the following study in the discussion: Maccarone MC, Coraci D, Bernini A, Sarandria N, Valente MR, Frigo AC, Dionyssiotis Y, Masiero S. Sarcopenia prevalence and association with nutritional status in cohort of elderly patients affected by musculoskeletal concerns: a real-life analysis. Front Endocrinol (Lausanne). 2023 Jun 26;14:1194676. doi: 10.3389/fendo.2023.1194676; PMID: 37435492; PMCID: PMC10331423.

- Although some limitations are mentioned, it would be valuable to briefly discuss how future studies could control for variables such as physical activity, nutritional status, hormone therapy, and metabolic comorbidities, and how this might affect observed associations.

Author Response

We appreciate the insightful and helpful comments of the editor and reviewers very much. We have made as many changes as possible according to the reviewer’s recommendations and have prepared the responses in a point-by-point fashion. We hope that our revision is satisfactory to the standards of the editors and reviewers and look forward to hearing the ultimate decision.

Reviewer 1 comment

NTRODUCTION

This section is well-written.

Author’s response: Thank you very much. Appreciated your comment.

MATERIALS AND METHODS

Participants were prospectively enrolled, but it remains unclear whether DEXA, grip strength, and blood sampling were performed on the same day or within a defined time frame.

Author’s response: Thank you for this important comment. We would like to clarify that DXA scanning, handgrip strength assessment, and blood sampling were performed on the same day for majority of participants. In our outpatient clinic setting, once a participant agreed to enroll in the study, all study-related assessments were scheduled and completed during the same morning visit. This clarification has been added to the Methods section (lines 122-123).

Exclusion criteria are adequate, but the analysis does not appear to account for common agents affecting bone or muscle turnover (e.g., vitamin D or calcium supplementation, statins, corticosteroids, aromatase inhibitors). I would suggest either reporting concomitant medications and supplements, or at least acknowledging this variable as a limitation. If available, an adjustment in the logistic regression model would meaningfully strengthen the conclusions.

Author’s response: We thank the reviewer for this insightful comment. We agree that medications and supplements influencing bone or muscle metabolism may affect circulating sclerostin levels and sarcopenia-related outcomes. However, detailed information regarding concomitant medications and nutritional supplements was not systematically collected for all participants in this study. Therefore explicitly acknowledged this issue as a limitation in the Discussion (lines 269-272).

RESULTS

The results section is generally well structured. The tables are concise and numerical values are not redundantly repeated across the narrative.

Author’s response: We thank the reviewer for this positive assessment of the Results section.

DISCUSSION

Author’s response: We thank the reviewer for this valuable suggestion. We agree that the distinction between muscle strength and muscle mass has important clinical implications for the diagnosis and monitoring of sarcopenia. Accordingly, we have expanded the Discussion to emphasize the potential clinical relevance of sclerostin as a biomarker for monitoring muscle function, rather than muscle quantity alone (Lines 221–224).

Author’s response: We thank the reviewer for this helpful suggestion. We agree that this real-world study provides important context regarding the clinical relevance of sarcopenia, particularly in relation to functional and nutritional status. Accordingly, we have cited this study in the Discussion.

Author’s response: We thank the reviewer for this valuable suggestion. We have revised the Discussion section to include a brief description of how future studies could control for key confounding factors and how these variables may influence the observed associations (lines 292–299).

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,
First of all, I would like to congratulate you on conducting a study that examines the role of a biochemical parameter in the diagnosis of sarcopenia. However, there are methodological weaknesses and limitations in the presentation of the data.

First, it is unclear why the algorithm developed by the EWGSOP2 was not used for the diagnosis of sarcopenia. There are certain differences between the EWGSOP2 criteria and those of the Korean Working Group on Sarcopenia. Therefore, the diagnostic algorithm needs to be clearly defined and justified.

Second, the diagnostic value of the sclerostin molecule in the diagnosis or discrimination of sarcopenia has not been adequately articulated. A ROC analysis should be performed. Moreover, the presentation and interpretation of the logistic regression analysis are incorrect, and the interpretations are flawed; biostatistical support is required in this regard.

Finally, the statistical output appears to have been generated using the JAMOVI software; however, the authors state that SPSS was used. If this is an error, it should be corrected accordingly.

Author Response

Author’s response: We thank the reviewer for this important comment. We would like to clarify that the primary aim of this study was not to evaluate or compare diagnostic algorithms for sarcopenia, but rather to examine differences in circulating sclerostin levels between individuals classified as having sarcopenia and those without sarcopenia in an older female population.

Accordingly, the application of a stepwise diagnostic algorithm such as EWGSOP2 was not central to the study design. Instead, sarcopenia was defined using the Korean Working Group on Sarcopenia (KWGS) criteria, which are widely used and validated in Korean older adults, to enable group-based comparative analyses aligned with the study objective. Although the EWGSOP2 and KWGS guidelines differ in their diagnostic algorithms, the core components required for sarcopenia diagnosis—namely muscle strength and muscle mass—are fundamentally consistent across both guidelines.

Author’s response: We thank the reviewer for these detailed and constructive comments. In response, we have performed an additional ROC analysis to further evaluate the discriminatory ability of circulating sclerostin levels for sarcopenia. The ROC analysis demonstrated a modest discriminatory performance, with an area under the curve (AUC) of 0.688, and these results have been added to the Results section.

In addition, we have carefully revised the presentation and interpretation of the logistic regression analysis. The analysis has been explicitly clarified as univariate, and the corresponding interpretations have been modified to emphasize association rather than diagnostic or predictive performance. These revisions were made to ensure appropriate statistical reporting and interpretation in line with the study objective.

Finally, the statistical output appears to have been generated using the JAMOVI software; however, the authors state that SPSS was used. If this is an error, it should be corrected accordingly.

Author’s response: We thank the reviewer for pointing out this issue. We would like to clarify that the primary statistical analyses were conducted using SPSS software, as described in the Methods section. However, selected figures were generated using JAMOVI for visualization purposes, as it provides clearer graphical outputs for presentation.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Please present the results of the ROC analysis, including the graph, p-value, and your chosen optimum cutoff value, in the text and show them in tables. Also, repeat the logistic regression analysis based on your newly found cutoff value. Include the odds ratio and confidence intervals for the logistic regression results.

Author Response

We sincerely thank the reviewer for this constructive comment and for providing us with the opportunity to further strengthen the statistical rigor of our study. We appreciate the reviewer’s insightful suggestion, which allowed us to perform a more in-depth analysis of the diagnostic performance of serum sclerostin.

Reviewer comment

Author response: We performed receiver operating characteristic (ROC) analysis to evaluate the discriminative ability of serum sclerostin for sarcopenia and osteoporosis and determined optimal cutoff values for each outcome using the Youden index (124.6 pg/mL for sarcopenia and 83.2 pg/mL for osteoporosis). The cutoff values, 95% CI, and OR are now presented in the Results section and summarized in Table 3.

In addition, we conducted univariable logistic regression analyses using both continuous serum sclerostin levels and ROC-derived cutoff values. In the continuous analysis, serum sclerostin was significantly associated with sarcopenia, but not with osteoporosis. When applying the ROC-derived cutoff values, higher serum sclerostin levels were significantly associated with increased odds of sarcopenia (OR = 5.39, 95% CI = 2.04–14.19, p < 0.001) and were inversely associated with osteoporosis (OR = 0.26, 95% CI = 0.07–0.96, p = 0.043). These findings are summarized in Table 3. For the reviewer’s reference, the ROC curves for sarcopenia and osteoporosis are provided below.

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

Comments on the Quality of English Language