Glucocorticoid Resistance in COVID-19: Endocrine–Inflammatory Associations in a Cross-Sectional Study

Round 1

Reviewer 1 Report

The article "Glucocorticoid Resistance in COVID-19: Endocrine and Inflammatory Mechanisms" has been submitted for review.
This study focuses on COVID-19, a complex multisystem disease characterized by profound immune dysregulation and a systemic inflammatory response. Although an overactivated immune response underlies this pathological cascade, the endocrine system, and particularly the hypothalamic-pituitary-adrenal (HPA) axis, plays a key yet often underappreciated role in regulating inflammation and maintaining homeostasis in critically ill patients.
Clinical data suggest that SARS-CoV-2 infection may be associated with transient or functional impairments of the HPA axis, particularly in the context of severe systemic inflammatory responses. It is well known that glucocorticoids regulate immune responses through complex genomic and nongenomic mechanisms that synergistically coordinate the suppression of inflammation and the maintenance of immune homeostasis. Therefore, the aim of this study was to determine the extent to which the inflammatory cytokine profile in COVID-19 is associated with changes in adrenal function and glucocorticoid sensitivity by analyzing serum cortisol levels and GRα 190 expression.
This article includes data from 101 individuals divided into appropriate groups. Modern research methods and adequate statistical analysis were employed. The abstract and conclusion are well presented and written. The work is well illustrated, with 8 tables and 3 figures. The reference list includes 55 sources, including recent ones.
Remarks. Despite the relevance of the study and the presented design, a number of caveats remain. Thus, the COVID-19 group included patients aged 18 years or older with confirmed active COVID-19 infection, as determined by a positive PCR test result. A table should be added with the clinical characteristics of the patients, including the presence of comorbidities, risk factors, bad habits, and stratification by severity. Moreover, the study included older patients with a wide range of disorders. It is indicated that the patients were in the age range 18 years or older. Table 1 shows the average age in the groups, which does not correspond to this range (69.8 years, 45.24 years, and 46.73 years). Table 2 presents the distribution of the groups by gender. This shows that the distribution is uneven; group 3 consists mainly of women (90%), while the previous groups are distributed differently. This raises questions regarding the comparability of the data, which should be corrected. There is no need to display tables with the normal distribution of features (Table 3). The data on blood component studies in COVID-19 patients (Tables 3, 4, and 5) are not entirely new. The article includes a lengthy discussion of the findings, necessitating a separate section—Discussion—for this information.

The article "Glucocorticoid Resistance in COVID-19: Endocrine and Inflammatory Mechanisms" has been submitted for review.
This study focuses on COVID-19, a complex multisystem disease characterized by profound immune dysregulation and a systemic inflammatory response. Although an overactivated immune response underlies this pathological cascade, the endocrine system, and particularly the hypothalamic-pituitary-adrenal (HPA) axis, plays a key yet often underappreciated role in regulating inflammation and maintaining homeostasis in critically ill patients.
Clinical data suggest that SARS-CoV-2 infection may be associated with transient or functional impairments of the HPA axis, particularly in the context of severe systemic inflammatory responses. It is well known that glucocorticoids regulate immune responses through complex genomic and nongenomic mechanisms that synergistically coordinate the suppression of inflammation and the maintenance of immune homeostasis. Therefore, the aim of this study was to determine the extent to which the inflammatory cytokine profile in COVID-19 is associated with changes in adrenal function and glucocorticoid sensitivity by analyzing serum cortisol levels and GRα 190 expression.
This article includes data from 101 individuals divided into appropriate groups. Modern research methods and adequate statistical analysis were employed. The abstract and conclusion are well presented and written. The work is well illustrated, with 8 tables and 3 figures. The reference list includes 55 sources, including recent ones.
Remarks. Despite the relevance of the study and the presented design, a number of caveats remain. Thus, the COVID-19 group included patients aged 18 years or older with confirmed active COVID-19 infection, as determined by a positive PCR test result. A table should be added with the clinical characteristics of the patients, including the presence of comorbidities, risk factors, bad habits, and stratification by severity. Moreover, the study included older patients with a wide range of disorders. It is indicated that the patients were in the age range 18 years or older. Table 1 shows the average age in the groups, which does not correspond to this range (69.8 years, 45.24 years, and 46.73 years). Table 2 presents the distribution of the groups by gender. This shows that the distribution is uneven; group 3 consists mainly of women (90%), while the previous groups are distributed differently. This raises questions regarding the comparability of the data, which should be corrected. There is no need to display tables with the normal distribution of features (Table 3). The data on blood component studies in COVID-19 patients (Tables 3, 4, and 5) are not entirely new. The article includes a lengthy discussion of the findings, necessitating a separate section—Discussion—for this information.

Author Response

Response to Reviewer 1

We thank the Reviewer for the careful evaluation of our manuscript and for the constructive suggestions. Each comment is reproduced below in bold, followed by our response.

Reviewer Comment: A table should be added with the clinical characteristics of the patients, including the presence of comorbidities, risk factors, bad habits, and stratification by severity.

Response: We thank the reviewer for this valuable suggestion. In response, a new table summarizing the clinical characteristics of patients with active COVID-19 has been added (Table 3). The table includes detailed stratification by disease severity (mild, moderate, severe, and critical), as well as comorbidities (hypertension, type 2 diabetes mellitus, ischemic heart disease, chronic lung disease including COPD/asthma, chronic kidney disease, chronic liver disease, and hematological disorders).

In addition, risk factors and lifestyle characteristics are presented, including current smoking status and alcohol consumption. Medication use at hospital admission is also reported, specifically antihypertensive and antidiabetic therapy. The manuscript has been revised accordingly (Section Results, page 9; Section Discussion, page 17).

 

Reviewer Comment: The COVID-19 group included patients aged 18 years or older; however, Table 1 shows mean ages (69.8, 45.24, 46.73 years), which does not correspond to this range.

Response: We appreciate the reviewer’s observation. The predefined inclusion criterion was age ≥18 years. However, the actual age distribution of enrolled participants reflected the clinical population admitted during the study period, resulting in higher mean age values, particularly in Group 1, which predominantly included older hospitalized patients with moderate to severe COVID-19. To improve clarity, we have explicitly reported the minimum and maximum age values for each group in Table 1.

 

Reviewer Comment: Table 2 presents the distribution of the groups by gender. This shows that the distribution is uneven; group 3 consists mainly of women (90%), while the previous groups are distributed differently. This raises questions regarding the comparability of the data, which should be corrected.

Response: We acknowledge the imbalance in sex distribution across groups, particularly in the reference group. To address this potential confounding factor, we performed multivariable generalized linear modeling with adjustment for age and sex. After adjustment, COVID-19 status remained independently associated with both cortisol and GRα levels. These analyses have been added to the Results section (pages 12, 14, 16, and 17 of the revised manuscript).

 

Reviewer Comment: There is no need to display tables with the normal distribution of features (Table 3).

Response: We thank the Reviewer for this suggestion. Table 3 has been removed to improve clarity and conciseness.

 

Reviewer Comment: The data on blood component studies (Tables 3, 4, and 5) are not entirely new.

Response: We appreciate the reviewer’s observation. In order to improve the focus and originality of the manuscript, we have removed the data on routine hematological parameters (previously presented in Tables 3, 4, and 5), as they are well established in the literature and do not add substantial novelty to the present analysis. The manuscript has been revised accordingly, and the remaining tables have been renumbered. The revised version now concentrates exclusively on the endocrine and immune–endocrine findings that represent the core objective of the study.

 

Reviewer Comment: The article includes a lengthy discussion of the findings, necessitating a separate section—Discussion—for this information.

Response: We appreciate this recommendation. The manuscript structure has been revised, and the Discussion section is now clearly separated from the Results.

Reviewer 2 Report

This manuscript explores immune–endocrine changes in COVID-19 by measuring serum cortisol alongside GRα as a marker of glucocorticoid sensitivity. The inclusion of three cohorts (acute infection, post-COVID, and healthy controls) is a sensible way to examine changes across disease phases. The study has a useful design and some strong signals, but it needs better control of confounding, a clearer reconciliation with ICU literature, and a more careful presentation of ROC findings before it can support the conclusions as written.

1) Group comparability and confounding

The three groups are not well balanced at baseline: the acute group is much older, and the control group is predominantly female. Because cortisol patterns and glucocorticoid signaling vary with age and sex, it is hard to attribute the observed differences to COVID-19 status alone.

Add adjusted analyses that include at least age and sex (and ideally major comorbidities and relevant medications).

If possible, run a sensitivity analysis with age/sex-matched subsets.

2) GRα findings vs ICU literature need a clearer explanation

You mention disagreement with Vassiliou et al. (2021), but the difference is not small—it is the opposite direction. Vassiliou reported increased GRα/GILZ signaling in steroid-free, critically ill ICU patients. In your study, Group 1 includes mixed severity and was sampled at hospital admission before treatment. That could explain the difference, but the paper needs to show it with data.

Present GRα results stratified by severity (mild/moderate/severe/critical).

If you have it, stratify by timing from symptom onset (or at least time from admission).

Clarify whether your “critical” subgroup resembles an ICU phenotype, and whether GRα changes direction with severity.

Address directly that your GRα readout is serum ELISA-based, while Vassiliou used cellular mRNA/signaling; these measures may not be comparable.

3) ROC/AUC claims should be toned down and supported with validation

The ROC result for GRα is very high (AUC 0.954; sensitivity 90%; specificity 100% for distinguishing acute cases from healthy controls). With this type of case–control comparison—especially with age/sex imbalance—performance can look better than it would in real clinical settings.

Report full ROC details clearly (exact groups compared, n used, CI, cut-off selection method).

Add internal validation (bootstrap or cross-validation).

Rephrase conclusions so this reads as an exploratory signal, not a clinically ready “near-perfect” biomarker.

Consider comparing acute COVID not only to healthy controls but also to a more clinically relevant group (e.g., non-COVID hospitalized patients), if available.

4) CIRCI wording is too definitive for single-point cortisol

You classify a large proportion of Group 1 as meeting CIRCI criteria based on random cortisol <10 μg/dL. CIRCI, however, is typically framed as a clinical syndrome and may require dynamic assessment (e.g., ACTH stimulation), depending on context. With a single cortisol measurement, diagnostic certainty is limited.

Avoid presenting CIRCI as a firm diagnosis unless dynamic testing is available.

Use more cautious wording (e.g., “low random cortisol consistent with thresholds used in CIRCI literature”).

Add a short limitations paragraph explaining what cannot be concluded from one-time cortisol values.

5) What does “serum GRα” mean biologically? (assay and sample handling need more detail)

Because GRα is classically an intracellular receptor, readers will want a clearer explanation of what a “serum GRα” ELISA detects and how it relates to receptor abundance or function. Also, storing samples at −18°C for cytokine/receptor assays may affect stability, depending on analyte and handling.

Provide kit details (manufacturer/catalog number), detection limits, and any validation or supporting literature for serum GRα as a proxy.

Describe freeze–thaw handling and confirm that all samples were processed and stored under identical conditions.

Keep mechanistic interpretation modest until the biological meaning of the serum measurement is clearer.

6) Causal language goes beyond the design

Some phrasing implies that inflammation “determines” impaired glucocorticoid signaling. With a cross-sectional observational design, the results support associations, not cause-and-effect.

Replace causal wording with association wording throughout (e.g., “is associated with,” “is consistent with,” “may contribute to”).

Author Response

Response to Reviewer 2

We thank the Reviewer for the careful evaluation of our manuscript and for the constructive comments. Each comment is reproduced below in bold, followed by our response.

Reviewer comment: 1) Group comparability and confounding

The three groups are not well balanced at baseline: the acute group is much older, and the control group is predominantly female. Because cortisol patterns and glucocorticoid signaling vary with age and sex, it is hard to attribute the observed differences to COVID-19 status alone.

Add adjusted analyses that include at least age and sex (and ideally major comorbidities and relevant medications).

If possible, run a sensitivity analysis with age/sex-matched subsets.

Response: We thank the Reviewer for this important comment regarding baseline imbalance and potential confounding. We agree that the three groups were not fully balanced with respect to age and sex distribution. In our study, patients in the acute COVID-19 group were significantly older than those in the post-COVID and reference groups, reflecting the established epidemiological pattern whereby older individuals are more susceptible to severe SARS-CoV-2 infection and hospitalization.

To directly explore the potential influence of age, we conducted age-stratified subgroup analyses (<60 years vs. ≥60 years) within each study group. A new table (Table 6) has been added to present serum cortisol, GRα concentrations, and inflammatory cytokine levels across age subgroups. Statistical comparisons between age categories within the same study group were performed using the Mann–Whitney U test. No statistically significant within-group age-related differences were observed. These results have been incorporated into the revised manuscript (Results section, Table 6; pages 11–13).

In addition, to further account for potential confounding by age and sex, we performed multivariable generalized linear modeling including age and sex as covariates. After adjustment, the associations between COVID-19 status and serum cortisol and GRα concentrations remained directionally consistent. For inflammatory cytokines (IL-17A, TNF-α, and IL-10), adjusted analyses did not demonstrate statistically significant independent group effects. These results have also been incorporated into the revised manuscript.

 

Reviewer comment: 2) GRα findings vs ICU literature need a clearer explanation

You mention disagreement with Vassiliou et al. (2021), but the difference is not small—it is the opposite direction. Vassiliou reported increased GRα/GILZ signaling in steroid-free, critically ill ICU patients. In your study, Group 1 includes mixed severity and was sampled at hospital admission before treatment. That could explain the difference, but the paper needs to show it with data.

Present GRα results stratified by severity (mild/moderate/severe/critical).

If you have it, stratify by timing from symptom onset (or at least time from admission).

Clarify whether your “critical” subgroup resembles an ICU phenotype, and whether GRα changes direction with severity.

Address directly that your GRα readout is serum ELISA-based, while Vassiliou used cellular mRNA/signaling; these measures may not be comparable.

Response: We thank the Reviewer for this thoughtful and important comment. We acknowledge that the findings reported by Vassiliou et al. (2021) differ in direction from our observations, and we agree that this discrepancy warrants clearer explanation.

Several key differences between the two studies should be considered. Vassiliou et al. investigated critically ill, steroid-free ICU patients and evaluated whole blood GRα and GILZ expression at the cellular mRNA level. In contrast, our study included patients with a spectrum of disease severity (mild, moderate, severe, and critical), and blood samples were obtained at hospital admission prior to initiation of treatment. Therefore, our cohort does not represent a homogeneous ICU phenotype and may reflect an earlier phase of the disease process.

Following the Reviewer’s suggestion, we have now presented serum GRα concentrations stratified according to disease severity (mild, moderate, severe, and critical). A new table (Table 7) has been added to the revised manuscript to summarize these results. While a tendency toward lower serum GRα levels with increasing disease severity was observed, differences between subgroups did not reach statistical significance. These findings are presented in the Results section (pages 15 and 16).

We agree that stratification by timing from symptom onset could further refine the interpretation of disease stage–related effects. However, precise and systematically recorded data regarding symptom onset were not available for all participants. All blood samples were collected at hospital admission prior to initiation of treatment, ensuring methodological consistency during the acute phase.

Importantly, GRα in our study was measured using a serum ELISA-based assay reflecting circulating protein concentrations rather than intracellular receptor expression. This differs fundamentally from the cellular mRNA–based assessment of GRα and GILZ expression performed by Vassiliou et al. These methodological and biological differences may partly explain the divergent findings and limit direct comparability between the two studies. These distinctions have been clarified in the revised Discussion section (pages 20 and 21), and additional methodological details have been added to the Methods section (page 6).

 

Reviewer comment: 3) ROC/AUC claims should be toned down and supported with validation

The ROC result for GRα is very high (AUC 0.954; sensitivity 90%; specificity 100% for distinguishing acute cases from healthy controls). With this type of case–control comparison—especially with age/sex imbalance—performance can look better than it would in real clinical settings.

Report full ROC details clearly (exact groups compared, n used, CI, cut-off selection method).

Add internal validation (bootstrap or cross-validation).

Rephrase conclusions so this reads as an exploratory signal, not a clinically ready “near-perfect” biomarker.

Consider comparing acute COVID not only to healthy controls but also to a more clinically relevant group (e.g., non-COVID hospitalized patients), if available.

Response: We thank the reviewer for this important comment.
In the revised manuscript, we have:
• clearly reported full ROC details (groups compared, sample sizes, SE, 95% CI, and cut-off determination using the Youden index), which are now presented in the Results section (pages 14,15);
• toned down the language to present GRα as an exploratory biomarker signal rather than a clinically validated diagnostic tool;
• explicitly acknowledged that the observed performance may be overestimated and requires validation in larger, prospectively designed cohorts.

Due to the relatively modest sample size and subgroup stratification, bootstrap-based internal validation was not performed, as resampling under these conditions may yield unstable estimates. 

We acknowledge that comparison with hospitalized patients without COVID-19 would enhance the clinical applicability of the findings; however, due to design constraints, inclusion of such a control group was not feasible in the present study.

 

Reviewer comment: 4) CIRCI wording is too definitive for single-point cortisol

You classify a large proportion of Group 1 as meeting CIRCI criteria based on random cortisol <10 μg/dL. CIRCI, however, is typically framed as a clinical syndrome and may require dynamic assessment (e.g., ACTH stimulation), depending on context. With a single cortisol measurement, diagnostic certainty is limited.

Avoid presenting CIRCI as a firm diagnosis unless dynamic testing is available.

Use more cautious wording (e.g., “low random cortisol consistent with thresholds used in CIRCI literature”).

Add a short limitations paragraph explaining what cannot be concluded from one-time cortisol values.

Response: We agree that CIRCI represents a clinical syndrome and that diagnostic certainty is limited in the absence of dynamic adrenal function testing (e.g., ACTH stimulation). In the acute hospital setting at admission, where timely diagnostic and therapeutic interventions were prioritized, additional dynamic hormonal testing was not feasible.

In the revised manuscript, we have removed wording that might imply a definitive diagnosis of CIRCI and replaced it with more cautious terminology (e.g., “low random cortisol consistent with thresholds reported in the CIRCI literature”). We have clarified that the applied threshold was used for descriptive and analytical purposes only and not to establish a clinical diagnosis.

Additionally, a brief paragraph has been added to the Limitations section explicitly stating that a single time-point cortisol measurement does not allow confirmation of CIRCI, assessment of adrenal reserve, or differentiation from transient stress-related hormonal fluctuations (page 8).

 

Reviewer comment: 5) What does “serum GRα” mean biologically? (assay and sample handling need more detail)

Because GRα is classically an intracellular receptor, readers will want a clearer explanation of what a “serum GRα” ELISA detects and how it relates to receptor abundance or function. Also, storing samples at −18°C for cytokine/receptor assays may affect stability, depending on analyte and handling.

Provide kit details (manufacturer/catalog number), detection limits, and any validation or supporting literature for serum GRα as a proxy.

Describe freeze–thaw handling and confirm that all samples were processed and stored under identical conditions.

Keep mechanistic interpretation modest until the biological meaning of the serum measurement is clearer.

Response: GRα is classically described as an intracellular receptor; therefore, circulating protein levels measured in serum may not directly reflect intracellular receptor abundance or functional glucocorticoid signaling. This clarification has been incorporated into the revised manuscript, and the mechanistic interpretation has been moderated accordingly.

Detailed assay characteristics have been added to the Methods section, including the manufacturer (Elabscience Biotechnology Co., Ltd., catalog no. E-EL-H1998), detection range (0.313–20 ng/mL), analytical sensitivity (0.188 ng/mL), and reported intra- and inter-assay variability (CV <10%), as specified by the manufacturer.

During the revision process, a technical inaccuracy in reporting measurement units (pg/mL instead of ng/mL) was identified and corrected consistently throughout the manuscript, including all tables and graphical representations. This correction does not affect the statistical analyses or the study conclusions.

Following re-examination of the laboratory documentation, we identified a reporting error regarding the storage temperature. After standard centrifugation, the separated serum and plasma samples were stored at −80 °C until analysis. The previously stated −18 °C storage condition was incorrect and has now been corrected throughout the manuscript.

Storage duration did not exceed the manufacturer’s recommended timeframe, repeated freeze–thaw cycles were strictly avoided, and all samples from the three study groups were processed, stored, and analyzed under identical laboratory conditions.

We acknowledge that commercially available ELISA assays quantify circulating immunoreactive GRα protein forms, and current evidence supporting serum GRα as a direct proxy for tissue-level receptor function remains limited. Accordingly, the biological interpretation has been further moderated, and the findings are presented as exploratory.

 

Reviewer comment: 6) Causal language goes beyond the design

Some phrasing implies that inflammation “determines” impaired glucocorticoid signaling. With a cross-sectional observational design, the results support associations, not cause-and-effect.

Replace causal wording with association wording throughout (e.g., “is associated with,” “is consistent with,” “may contribute to”).

Response: We agree that the cross-sectional observational design does not allow causal inference. In the revised manuscript, we have carefully reviewed the entire text and replaced causal expressions (e.g., “determines,” “leads to,” “results in”) with association-based terminology such as “is associated with,” “is consistent with,” “may contribute to,” and “may reflect.” These revisions were applied consistently throughout the manuscript, including the Abstract, Discussion, and Conclusion sections. The title has also been adjusted to better reflect the observational nature of the study and to avoid causal implications.

Round 2

Reviewer 1 Report

The authors made numerous edits to the text of the article. Overall, the article has been significantly improved. The abstract is well written and fully reflects the data obtained. However, some comments remain: Clinical characteristics should be presented, including for Group 2 (those who recovered from COVID-19). There is no need to provide Table 4 (Kruskal-Wallis differences). It is sufficient to indicate in the text that such comparisons have been made. Table 5 should be simplified by making three columns (Group 1, 2, 3) and a separate column for p values ​​(p1-2, p1-3, p2-3). Otherwise, the table will become too cumbersome. The three figures (Serum GRα concentrations in the three studied groups) should be combined into one figure so that the parameters are side by side and the differences are clearly visible.

The authors made numerous edits to the text of the article. Overall, the article has been significantly improved. The abstract is well written and fully reflects the data obtained. However, some comments remain: Clinical characteristics should be presented, including for Group 2 (those who recovered from COVID-19). There is no need to provide Table 4 (Kruskal-Wallis differences). It is sufficient to indicate in the text that such comparisons have been made. Table 5 should be simplified by making three columns (Group 1, 2, 3) and a separate column for p values ​​(p1-2, p1-3, p2-3). Otherwise, the table will become too cumbersome. The three figures (Serum GRα concentrations in the three studied groups) should be combined into one figure so that the parameters are side by side and the differences are clearly visible.

Author Response

Comment 1: Clinical characteristics should be presented, including for Group 2 (those who recovered from COVID-19).

Response: Thank you for this important comment. Clinical characteristics for patients in Group 2 (post-COVID) have now been added and presented in Table 3 (page 9). The descriptive text in the Results section (page 10) and the Discussion (pages 17 and 18) has been updated to include information on disease severity (where available), comorbidities, and risk factors in this group. The incomplete availability of disease severity documentation in Group 2 is explicitly acknowledged in the revised manuscript: severity data were available for 11 patients, whereas for the remaining 24 participants the acute COVID-19 infection had been managed in the outpatient setting and detailed clinical documentation regarding disease severity was not available. This limitation is also noted in the Limitations section (page 8).

Comment 2: There is no need to provide Table 4 (Kruskal-Wallis differences). It is sufficient to indicate in the text that such comparisons have been made.

Response: We appreciate this suggestion. Table 4 has been removed from the revised manuscript. The results of the Kruskal–Wallis tests are now described directly in the Results section, where the corresponding statistical values are reported in the text. As a consequence, all subsequent tables have been renumbered accordingly.

Comment 3: Table 5 should be simplified by making three columns (Group 1, 2, 3) and a separate column for p values (p1-2, p1-3, p2-3). Otherwise, the table will become too cumbersome.

Response: Thank you for this helpful suggestion. Table 5 has been simplified according to the reviewer’s recommendation. The table now includes three columns representing Groups 1, 2, and 3, along with a separate column for pairwise p-values (p1–2, p1–3, p2–3). 

Comment 4: The three figures (Serum GRα concentrations in the three studied groups) should be combined into one figure so that the parameters are side by side and the differences are clearly visible.

Response: Thank you for this suggestion. The three separate figures have now been combined into a single figure showing serum GRα concentrations in the three study groups side-by-side using a box-and-whisker plot. 

Reviewer 2 Report

None

Thank you for the careful revision and for the detailed responses. My major concerns have been addressed, and the manuscript is now much clearer and more balanced in its interpretation. I think the paper is close to being ready. Before submission, I would just suggest one final check on two small points:

1. The sample storage temperature should be fully consistent across the manuscript and any related records. Since the original version mentioned −18°C and the revised version now states −80°C, it would be good to ensure this is fully reconciled and, if needed, briefly clarify that the earlier value was a reporting error rather than a procedural issue.
2. Please make sure the Limitations section states clearly that:

1. cortisol was measured at a single time point / blood sampling time was not standardized by time of day, and
2. the exclusion of vaccinated participants limits the generalizability of the findings.

Overall, the revision has substantially improved the paper, and in my view it is now suitable for resubmission once these minor points are checked.

Author Response

Comment 1: The sample storage temperature should be fully consistent across the manuscript and any related records. Since the original version mentioned −18°C and the revised version now states −80°C, it would be good to ensure this is fully reconciled and, if needed, briefly clarify that the earlier value was a reporting error rather than a procedural issue.

Response: Thank you for pointing out this important issue. We carefully reviewed the manuscript to ensure full consistency regarding the sample storage temperature. The correct storage temperature used in the study was −80 °C, which is now clearly stated in the Methods section (Section 2.3). The previously mentioned value of −18 °C in the earlier manuscript version resulted from a reporting error rather than a procedural issue. The manuscript has been checked to ensure that the reported storage temperature is fully consistent with the actual laboratory procedures and study documentation.

Comment 2: Please make sure the Limitations section states clearly that:
a) cortisol was measured at a single time point / blood sampling time was not standardized by time of day, and
b) the exclusion of vaccinated participants limits the generalizability of the findings.

Response: Thank you for this helpful suggestion. The Limitations section has been revised and expanded to explicitly state that serum cortisol was measured at a single time point and that blood sampling was not standardized according to the time of the day, which may influence cortisol concentrations due to its physiological diurnal variation. In addition, we have clarified that vaccinated individuals were excluded from the study population, which may limit the generalizability of the findings to populations with prior SARS-CoV-2 vaccination.