Title: Gender difference in the association between serum uric acid and metabolic dysfunction-
associated steatotic liver disease in patients with newly diagnosed type 2 diabetes
Version: 1 Date: 17 Mar 2025
Reviewer's report:
This study investigates gender-specific associations between serum uric acid (SUA) and
metabolic dysfunction-associated steatotic liver disease (MASLD) in newly diagnosed type
2 diabetes (T2DM) patients. The findings highlight that SUA is an independent predictor of
MASLD in males but not in females, with BMI influencing the association in females. The topic
is clinically relevant, addressing a gap in understanding sex-specific risk factors for MASLD
in T2DM populations. The manuscript is well-structured, but several areas require revision to
enhance clarity, consistency, and scientific rigor.
1.  Tables and text interchangeably use "NAFLD" and "MASLD" (e.g., Tables 1–4 label
outcomes as "Prevalence Rat of NAFLD").  Consistently replace "NAFLD" with "MASLD"
throughout the manuscript to align with the updated diagnostic framework.
2. MASLD diagnosis relies on ultrasound, which may underdetect mild steatosis.  Explicitly
discuss how this limitation might bias results (e.g., underestimation of MASLD prevalence) and
suggest future studies using more sensitive methods (e.g., FibroScan, MRI-PDFF).
3.  Key variables (e.g., waist circumference, diet, physical activity, alcohol intake) were
not adjusted for.  Acknowledge these limitations in the discussion and propose them as
considerations for future research.
4. The discussion briefly mentions hormonal influences (e.g., estrogen, androgen imbalance)
but lacks depth.   Expand on potential biological mechanisms (e.g., estrogen’s hepatoprotective
role, obesity-related hormonal dysregulation) to explain gender-specific findings.
5. Clarification of SUA Cut-offs:  The rationale for SUA stratification thresholds (e.g., median
split) is unclear.   Justify the choice of cut-offs in the methods (e.g., clinical relevance,
population-specific percentiles).
6.  The abstract’s conclusion does not explicitly state that the female association is limited to non-
overweight/obese individuals.   For example  Revise to: "In females, SUA-MASLD associations
depend on BMI, with significance only in non-overweight/obese individuals."
7.  Inconsistent presentation of median values (e.g., ALT and AST in Table 1 for females lack
interquartile ranges).   Standardize data presentation (e.g., report medians with IQR for all non-
normally distributed variables).
8. Additional Minor Revisions:
- Correct typographical errors (e.g., "Prevalence Rat" # "Prevalence Rate").
- Ensure all abbreviations (e.g., MASLD) are defined at first mention.
- Clarify whether "newly diagnosed T2DM" refers to drug-naïve patients or those recently
diagnosed (methods section).
Recommendation: minor revision.
Title: Gender difference in the association between serum uric acid and metabolic dysfunction-
associated steatotic liver disease in patients with newly diagnosed type 2 diabetes
Version: 1 Date: 17 Mar 2025
Reviewer's report:
This study investigates gender-specific associations between serum uric acid (SUA) and
metabolic dysfunction-associated steatotic liver disease (MASLD) in newly diagnosed type
2 diabetes (T2DM) patients. The findings highlight that SUA is an independent predictor of
MASLD in males but not in females, with BMI influencing the association in females. The topic
is clinically relevant, addressing a gap in understanding sex-specific risk factors for MASLD
in T2DM populations. The manuscript is well-structured, but several areas require revision to
enhance clarity, consistency, and scientific rigor.
1.  Tables and text interchangeably use "NAFLD" and "MASLD" (e.g., Tables 1–4 label
outcomes as "Prevalence Rat of NAFLD").  Consistently replace "NAFLD" with "MASLD"
throughout the manuscript to align with the updated diagnostic framework.
2. MASLD diagnosis relies on ultrasound, which may underdetect mild steatosis.  Explicitly
discuss how this limitation might bias results (e.g., underestimation of MASLD prevalence) and
suggest future studies using more sensitive methods (e.g., FibroScan, MRI-PDFF).
3.  Key variables (e.g., waist circumference, diet, physical activity, alcohol intake) were
not adjusted for.  Acknowledge these limitations in the discussion and propose them as
considerations for future research.
4. The discussion briefly mentions hormonal influences (e.g., estrogen, androgen imbalance)
but lacks depth.   Expand on potential biological mechanisms (e.g., estrogen’s hepatoprotective
role, obesity-related hormonal dysregulation) to explain gender-specific findings.
5. Clarification of SUA Cut-offs:  The rationale for SUA stratification thresholds (e.g., median
split) is unclear.   Justify the choice of cut-offs in the methods (e.g., clinical relevance,
population-specific percentiles).
6.  The abstract’s conclusion does not explicitly state that the female association is limited to non-
overweight/obese individuals.   For example  Revise to: "In females, SUA-MASLD associations
depend on BMI, with significance only in non-overweight/obese individuals."
7.  Inconsistent presentation of median values (e.g., ALT and AST in Table 1 for females lack
interquartile ranges).   Standardize data presentation (e.g., report medians with IQR for all non-
normally distributed variables).
8. Additional Minor Revisions:
- Correct typographical errors (e.g., "Prevalence Rat" # "Prevalence Rate").
- Ensure all abbreviations (e.g., MASLD) are defined at first mention.
- Clarify whether "newly diagnosed T2DM" refers to drug-naïve patients or those recently
diagnosed (methods section).
Recommendation: minor revision.
Please review this paper.
user
Title: Gender difference in the association between serum uric acid and metabolic dysfunction-
associated steatotic liver disease in patients with newly diagnosed type 2 diabetes
Version: 1 Date: 17 Mar 2025
Reviewer's report:
This study investigates gender-specific associations between serum uric acid (SUA) and
metabolic dysfunction-associated steatotic liver disease (MASLD) in newly diagnosed type
2 diabetes (T2DM) patients. The findings highlight that SUA is an independent predictor of
MASLD in males but not in females, with BMI influencing the association in females. The topic
is clinically relevant, addressing a gap in understanding sex-specific risk factors for MASLD
in T2DM populations. The manuscript is well-structured, but several areas require revision to
enhance clarity, consistency, and scientific rigor.
1.  Tables and text interchangeably use "NAFLD" and "MASLD" (e.g., Tables 1–4 label
outcomes as "Prevalence Rat of NAFLD").  Consistently replace "NAFLD" with "MASLD"
throughout the manuscript to align with the updated diagnostic framework.
2. MASLD diagnosis relies on ultrasound, which may underdetect mild steatosis.  Explicitly
discuss how this limitation might bias results (e.g., underestimation of MASLD prevalence) and
suggest future studies using more sensitive methods (e.g., FibroScan, MRI-PDFF).
3.  Key variables (e.g., waist circumference, diet, physical activity, alcohol intake) were
not adjusted for.  Acknowledge these limitations in the discussion and propose them as
considerations for future research.
4. The discussion briefly mentions hormonal influences (e.g., estrogen, androgen imbalance)
but lacks depth.   Expand on potential biological mechanisms (e.g., estrogen’s hepatoprotective
role, obesity-related hormonal dysregulation) to explain gender-specific findings.
5. Clarification of SUA Cut-offs:  The rationale for SUA stratification thresholds (e.g., median
split) is unclear.   Justify the choice of cut-offs in the methods (e.g., clinical relevance,
population-specific percentiles).
6.  The abstract’s conclusion does not explicitly state that the female association is limited to non-
overweight/obese individuals.   For example  Revise to: "In females, SUA-MASLD associations
depend on BMI, with significance only in non-overweight/obese individuals."
7.  Inconsistent presentation of median values (e.g., ALT and AST in Table 1 for females lack
interquartile ranges).   Standardize data presentation (e.g., report medians with IQR for all non-
normally distributed variables).
8. Additional Minor Revisions:
- Correct typographical errors (e.g., "Prevalence Rat" # "Prevalence Rate").
- Ensure all abbreviations (e.g., MASLD) are defined at first mention.
- Clarify whether "newly diagnosed T2DM" refers to drug-naïve patients or those recently
diagnosed (methods section).
Recommendation: minor revision.
assistant