Comparative Characteristics of the Immunometabolic Profile of Individuals with Newly Developed Metabolic Disorders and Classic Metabolic Syndrome

Round 1

Reviewer 1 Report

English language and clarity can be improved

Some sections contain long sentences, inconsistent verb tenses, and ambiguous phrasing.

Examples that could be revised:

• “What can be asserted is that...”

• “Interestingly, IR and adipocyte dysfunction are also observed…”

• “Another reason is the expected increased incidence…”

A professional language edit would improve clarity.

Tables need formatting refinements

Several tables include inconsistencies:

• Units not repeated across rows

• Misalignment of means and ranges

• Missing decimal places or inconsistent precision

Standardizing the format according to MDPI guidelines will improve readability.

Figures would benefit from scale harmonization

Figure 1 uses different y-axis scales for each cytokine, which limits visual comparison. Although cytokines differ in magnitude, harmonized or proportional axes would improve interpretability.

Abbreviations should be standardized

Some abbreviations appear before definition (e.g., IGT in early sections), while others are redefined multiple times. Consistent application is recommended.

Clarify inclusion/exclusion criteria

The manuscript states “precisely defined criteria,” but does not explicitly list:

• Exclusion of autoimmune diseases

• Exclusion of chronic inflammatory conditions

• Medication use (steroids, antidiabetics, statins)

Such details would help ensure comparability between groups.

Consider adding confidence intervals to regression or correlation results

Where correlations are statistically significant, confidence intervals would provide additional information about the robustness and precision of the estimates.

 Insufficient characterization of COVID-19 severity and timeline

The Post-COVID group is defined by a documented infection at least six months before the diagnosis of metabolic disorders. However, important variables that influence immune dysregulation—such as the severity of acute COVID-19, presence of hospitalization, oxygen requirement, treatment received (e.g., corticosteroids), and duration of symptoms—are not reported.
These factors are known to affect both the inflammatory response and the risk of post-acute metabolic dysfunction. Their absence limits the reader’s ability to contextualize the findings. Please consider:

• Adding available clinical severity data, OR

• Clearly stating that such information was not accessible and acknowledging it as a limitation.

Subgroup analyses are underpowered

Some subgroups include very few participants (e.g., T1DM n=8, IGT n=3–4). Despite this, the manuscript presents numerous subgroup comparisons and correlation analyses, which increases the risk of type I and type II errors. The authors should:

• Explicitly discuss the limited statistical power,

• Interpret subgroup differences with caution,

• Consider reducing the number of subgroup comparisons to avoid overinterpretation.

Need to control for confounding variables

Age, sex, BMI, and obesity prevalence differ across subgroups and between groups. Given that these variables directly influence cytokine levels, insulin resistance, lipid profiles, and adipokines, the absence of adjusted analyses limits the validity of the conclusions. The manuscript relies heavily on raw comparisons and bivariate correlations.

Recommendations:

• Include regression analyses adjusted for key confounders, OR

• State clearly that adjusted analyses were not feasible and discuss how this may affect the interpretation.

Interpretation sometimes exceeds the strength of the data

The discussion often attributes specific immunometabolic patterns to SARS-CoV-2 infection; however, this is an observational study without matched controls or adjustment. While the findings are biologically plausible, the text occasionally implies causality.

Examples include statements suggesting that COVID-19 caused adipose tissue dysfunction or triggered dysglycemia. These should be modified to language emphasizing associations rather than causation.

Need for deeper integration of immunological findings into a coherent model

The results section describes cytokine differences in detail, but the discussion could better integrate:

• How the pattern of TNF-α elevation in Post-COVID individuals relates to classic MetS inflammation

• Why IFN-γ and IL-17A appear lower in the Post-COVID group compared with classic MetS

• How low IL-10 levels across both groups reflect impaired anti-inflammatory signaling

A conceptual figure or expanded explanation would help illustrate how COVID-related metabolic dysfunction overlaps with, but also differs from, classic MetS.

Potential analytical issues with cytokine outliers

Several cytokine values (particularly TNF-α up to 544 pg/mL and IL-17A up to 202 pg/mL) appear extremely high compared with typical ELISA ranges. The manuscript should specify:

• Whether extreme values were repeated or validated,

• Whether any samples were excluded,

• Whether distributions were examined for normality before comparisons.

This would strengthen confidence in the findings.

Author Response

Dear Editorial board,

Dear Reviewers,

On behalf of the entire author`s collective we thank the reviewers for their valuable comments. We have carefully reviewed all suggestions and revised the manuscript accordingly. Each comment has been addressed point-by-point, and the corresponding changes have been clearly indicated (in yellow) in the revised version.

• English language and clarity have been improved
• Tables have been formatted according to MDPI guidelines
• We intentionally presented each cytokine with an independent y-axis rather than using a single harmonized scale (in Figure 1) because the absolute concentrations of the measured cytokines differ markedly in magnitude. TNF-α levels were an order of magnitude higher than IFN-γ, IL-17A, and IL-10, and applying a uniform y-axis would have compressed the lower-range cytokines to the point that subgroup differences and variability would not be visually discernible. Using separate y-axes allows accurate visualization of relative differences between metabolic subgroups within each cytokine while preserving biological interpretability which is the main purpose of the study. A harmonized scale, although visually uniform, would obscure meaningful patterns and could be misleading by implying comparable absolute concentrations across cytokines, which is biologically inaccurate. To avoid misinterpretation, all axes are clearly labeled with units, and comparisons are intended within each cytokine panel rather than across cytokines.
• Abbreviations have been standardized
• Methods and materials section has been revised
• Inclusion/exclusion criteria have been clarified
• Due to the small sample size in several metabolic subgroups (n ≤ 10), 95% confidence intervals (CI) for correlation coefficients have also been reported to support interpretation.
• Available clinical severity data have been added where possible
• Subgroup analysis are revised and the number of correlation has been reduced
• Generalized linear models (GLMs) with a Gamma distribution and log link (Gamma-GLM) have been performed adjusted for age, sex and BMI. This model was selected due to the positively skewed distribution of all biochemical markers and its suitability for modelling multiplicative effects.
• The entire Results and Discussion section have been revised (so they are not marked in yellow)
• Conclusion section has also been corrected
• All samples were processed in duplicate (tested twice) to ensure technical reproducibility and none of them have been excluded from the analysis
• Distributions were examined using both the Kolmogorov–Smirnov and Shapiro–Wilk tests. As at least one group for each variable demonstrated a non-normal distribution, non-parametric statistical methods were applied.
• The list of references (numbering) has been completely changed due to the addition of further citations
• Limitations of the study have been pointed

 

 

The observed changes in both metabolic and immune parameters studied among the two groups in our study show many similarities, but some significant differences have also been identified. Together, these findings indicate that post-COVID metabolic dysfunction can be distinguished from classical Metabolic syndrome.

 

Thank you for the opportunity to review our manuscript again!

Best regards,

Dr. Victoria Tsvetkova

Corresponding author

Reviewer 2 Report

This study addresses a significant medical issue: the metabolic consequences of COVID-19. The study compares this with classic metabolic syndrome, allowing us to distinguish the specific effects of the virus from general pathogenic mechanisms. Despite its relevance, the study has several limitations, such as a small and unbalanced sample.

Line 22. Please state the aim of the study.

Lines 30-37. Please describe the differences between the groups and the identified correlations in more detail. Parameters found to be similar between the groups may be removed.

Elevated levels of pro-inflammatory cytokines are not a specific sign of a particular disease (e.g., COVID-19) but rather a universal marker of immune system activation and inflammatory processes. Their increased production is observed in a wide spectrum of conditions: autoimmune, infectious, oncological diseases, and other states (ischemic heart disease, neurodegenerative diseases, myocardial infarction, stroke, and others). Please revise the "Introduction" section accordingly.

Lines 66-68. Please describe IR and adipocyte dysfunction during and after SARS-CoV-2 infection in more detail. Cite relevant studies. What mechanism underlies this association? Please note why the study was conducted on a group of patients who had recovered from COVID-19.

Line 411. Here, cases of diabetes development following COVID-19 should also be described in more detail. Please provide references describing such cases.

'Results' section. Is the significant gender imbalance in the groups related to the effect of SARS-CoV-2 infection on the development of metabolic disorders in men? Please provide literature data on this issue. The gender imbalance may skew the data, considering gender differences in metabolism and immune response.

Please add a section on the study limitations. This section should note the small sample size. The lack of data on the severity of the past COVID-19 illness is also a limitation, as it prevents an assessment of how disease severity influences metabolic changes.

Author Response

Dear Editorial board,

Dear Reviewers,

On behalf of the entire author`s collective we thank the reviewers for their valuable comments. We have carefully reviewed all suggestions and revised the manuscript accordingly. Each comment has been addressed point-by-point, and the corresponding changes have been clearly indicated (in yellow) in the revised version.

• English language and clarity have been improved
• Tables have been formatted according to MDPI guidelines
• We intentionally presented each cytokine with an independent y-axis rather than using a single harmonized scale (in Figure 1) because the absolute concentrations of the measured cytokines differ markedly in magnitude. TNF-α levels were an order of magnitude higher than IFN-γ, IL-17A, and IL-10, and applying a uniform y-axis would have compressed the lower-range cytokines to the point that subgroup differences and variability would not be visually discernible. Using separate y-axes allows accurate visualization of relative differences between metabolic subgroups within each cytokine while preserving biological interpretability which is the main purpose of the study. A harmonized scale, although visually uniform, would obscure meaningful patterns and could be misleading by implying comparable absolute concentrations across cytokines, which is biologically inaccurate. To avoid misinterpretation, all axes are clearly labeled with units, and comparisons are intended within each cytokine panel rather than across cytokines.
• Abbreviations have been standardized
• Methods and materials section has been revised
• Inclusion/exclusion criteria have been clarified
• Due to the small sample size in several metabolic subgroups (n ≤ 10), 95% confidence intervals (CI) for correlation coefficients have also been reported to support interpretation.
• Available clinical severity data have been added where possible
• Subgroup analysis are revised and the number of correlation has been reduced
• Generalized linear models (GLMs) with a Gamma distribution and log link (Gamma-GLM) have been performed adjusted for age, sex and BMI. This model was selected due to the positively skewed distribution of all biochemical markers and its suitability for modelling multiplicative effects.
• The entire Results and Discussion section have been revised (so they are not marked in yellow)
• Conclusion section has also been corrected
• All samples were processed in duplicate (tested twice) to ensure technical reproducibility and none of them have been excluded from the analysis
• Distributions were examined using both the Kolmogorov–Smirnov and Shapiro–Wilk tests. As at least one group for each variable demonstrated a non-normal distribution, non-parametric statistical methods were applied.
• The list of references (numbering) has been completely changed due to the addition of further citations
• Limitations of the study have been pointed

 

 

The observed changes in both metabolic and immune parameters studied among the two groups in our study show many similarities, but some significant differences have also been identified. Together, these findings indicate that post-COVID metabolic dysfunction can be distinguished from classical Metabolic syndrome.

 

Thank you for the opportunity to review our manuscript again!

Best regards,

Dr. Victoria Tsvetkova

Corresponding author

Round 2

Reviewer 2 Report

The new additions to the manuscript made a big difference. The quality of the paper had improved, and all my questions were addressed. No more comments.

The new additions to the manuscript made a big difference. The quality of the paper had improved, and all my questions were addressed. No more comments.