Title: Associations between Systemic Inflammatory Biomarkers and Metabolic Dysfunction
Associated Steatotic Liver Disease: A cross-sectional study of NHANES 2017-2020
Version: 2 Date: 25 Dec 2024
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The MASLD definition used in the study is detailed and includes specific cardiometabolic
risk factors. However, the relationship between MASLD and steatosis is complex. The authors
could provide additional clarification on how “light alcohol use” was defined in this study,
particularly given the potential ambiguity around alcohol consumption levels that might affect
liver pathology.
-Further elaboration on how the specific cutoff for CAP (285 dB/m) was chosen in the NHANES
cohort would strengthen the justification for this diagnostic criterion.
-The formulas provided for calculating systemic inflammatory biomarkers are generally clear,
but the description of some indices (e.g., PLR and NLR) could be improved for clarity. For
example, in the case of PLR, the formula involves lymphocyte count twice (LYM count * NEU
count / LYM count). This could be a typographical error or needs further explanation.
-SIPS includes binary scoring based on albumin and neutrophil counts. This approach, while
useful, may oversimplify complex inflammatory processes. Further discussion of how these
scores are clinically interpreted could add depth to the methodology.
-While the methods account for multiple confounders (e.g., age, sex, race, smoking status,
cardiovascular diseases), additional information on how these variables are operationalized (e.g.,
specific classification or cutoffs for smoking) would be helpful for reproducibility.
-A family history of metabolic disease could be a potentially important confounder given the
genetic predisposition to MASLD. If this data is available in NHANES, it could be worth
mentioning as a covariate in the models.
-While the authors propose several plausible mechanisms for the observed associations (e.g.,
oxidative stress, immune modulation, platelet activity), some of these explanations could benefit
from more detail and reference to specific studies. For example, while the potential role of
platelets in modulating liver endothelial cells is intriguing, it could be enhanced by referring to
specific studies that explore this mechanism in MASLD or related liver diseases.
-Additionally, while albumin (ALB) is discussed in the context of its relationship with both ALI
and PNI, further clarification could be provided on how albumin levels specifically contribute
to MASLD risk. For example, do elevated albumin levels reflect nutritional deficiencies or a
specific pro-inflammatory state that exacerbates steatosis and inflammation?
-The study shows that some biomarkers like NLR and PLR were associated with a decreased
risk of MASLD, while others like ALI, CAR, and PNI were linked to increased risk. While
these findings are important, they could be better explained. For example, how can elevated
NLR (which is often considered an inflammatory marker) be associated with a decreased risk
of MASLD? Are there specific mechanisms or patient characteristics that explain this inverse
relationship?
-The authors could also consider explaining why PLR and NLR, which are related to immune cell
responses, might be inversely associated with MASLD risk, especially in light of their observed
anti-inflammatory roles. It would be helpful to discuss potential pathophysiological explanations
or how these findings might vary in early vs. late stages of MASLD.
Title: Associations between Systemic Inflammatory Biomarkers and Metabolic Dysfunction
Associated Steatotic Liver Disease: A cross-sectional study of NHANES 2017-2020
Version: 2 Date: 25 Dec 2024
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The MASLD definition used in the study is detailed and includes specific cardiometabolic
risk factors. However, the relationship between MASLD and steatosis is complex. The authors
could provide additional clarification on how “light alcohol use” was defined in this study,
particularly given the potential ambiguity around alcohol consumption levels that might affect
liver pathology.
-Further elaboration on how the specific cutoff for CAP (285 dB/m) was chosen in the NHANES
cohort would strengthen the justification for this diagnostic criterion.
-The formulas provided for calculating systemic inflammatory biomarkers are generally clear,
but the description of some indices (e.g., PLR and NLR) could be improved for clarity. For
example, in the case of PLR, the formula involves lymphocyte count twice (LYM count * NEU
count / LYM count). This could be a typographical error or needs further explanation.
-SIPS includes binary scoring based on albumin and neutrophil counts. This approach, while
useful, may oversimplify complex inflammatory processes. Further discussion of how these
scores are clinically interpreted could add depth to the methodology.
-While the methods account for multiple confounders (e.g., age, sex, race, smoking status,
cardiovascular diseases), additional information on how these variables are operationalized (e.g.,
specific classification or cutoffs for smoking) would be helpful for reproducibility.
-A family history of metabolic disease could be a potentially important confounder given the
genetic predisposition to MASLD. If this data is available in NHANES, it could be worth
mentioning as a covariate in the models.
-While the authors propose several plausible mechanisms for the observed associations (e.g.,
oxidative stress, immune modulation, platelet activity), some of these explanations could benefit
from more detail and reference to specific studies. For example, while the potential role of
platelets in modulating liver endothelial cells is intriguing, it could be enhanced by referring to
specific studies that explore this mechanism in MASLD or related liver diseases.
-Additionally, while albumin (ALB) is discussed in the context of its relationship with both ALI
and PNI, further clarification could be provided on how albumin levels specifically contribute
to MASLD risk. For example, do elevated albumin levels reflect nutritional deficiencies or a
specific pro-inflammatory state that exacerbates steatosis and inflammation?
-The study shows that some biomarkers like NLR and PLR were associated with a decreased
risk of MASLD, while others like ALI, CAR, and PNI were linked to increased risk. While
these findings are important, they could be better explained. For example, how can elevated
NLR (which is often considered an inflammatory marker) be associated with a decreased risk
of MASLD? Are there specific mechanisms or patient characteristics that explain this inverse
relationship?
-The authors could also consider explaining why PLR and NLR, which are related to immune cell
responses, might be inversely associated with MASLD risk, especially in light of their observed
anti-inflammatory roles. It would be helpful to discuss potential pathophysiological explanations
or how these findings might vary in early vs. late stages of MASLD.
Please review this paper.
user
Title: Associations between Systemic Inflammatory Biomarkers and Metabolic Dysfunction
Associated Steatotic Liver Disease: A cross-sectional study of NHANES 2017-2020
Version: 2 Date: 25 Dec 2024
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The MASLD definition used in the study is detailed and includes specific cardiometabolic
risk factors. However, the relationship between MASLD and steatosis is complex. The authors
could provide additional clarification on how “light alcohol use” was defined in this study,
particularly given the potential ambiguity around alcohol consumption levels that might affect
liver pathology.
-Further elaboration on how the specific cutoff for CAP (285 dB/m) was chosen in the NHANES
cohort would strengthen the justification for this diagnostic criterion.
-The formulas provided for calculating systemic inflammatory biomarkers are generally clear,
but the description of some indices (e.g., PLR and NLR) could be improved for clarity. For
example, in the case of PLR, the formula involves lymphocyte count twice (LYM count * NEU
count / LYM count). This could be a typographical error or needs further explanation.
-SIPS includes binary scoring based on albumin and neutrophil counts. This approach, while
useful, may oversimplify complex inflammatory processes. Further discussion of how these
scores are clinically interpreted could add depth to the methodology.
-While the methods account for multiple confounders (e.g., age, sex, race, smoking status,
cardiovascular diseases), additional information on how these variables are operationalized (e.g.,
specific classification or cutoffs for smoking) would be helpful for reproducibility.
-A family history of metabolic disease could be a potentially important confounder given the
genetic predisposition to MASLD. If this data is available in NHANES, it could be worth
mentioning as a covariate in the models.
-While the authors propose several plausible mechanisms for the observed associations (e.g.,
oxidative stress, immune modulation, platelet activity), some of these explanations could benefit
from more detail and reference to specific studies. For example, while the potential role of
platelets in modulating liver endothelial cells is intriguing, it could be enhanced by referring to
specific studies that explore this mechanism in MASLD or related liver diseases.
-Additionally, while albumin (ALB) is discussed in the context of its relationship with both ALI
and PNI, further clarification could be provided on how albumin levels specifically contribute
to MASLD risk. For example, do elevated albumin levels reflect nutritional deficiencies or a
specific pro-inflammatory state that exacerbates steatosis and inflammation?
-The study shows that some biomarkers like NLR and PLR were associated with a decreased
risk of MASLD, while others like ALI, CAR, and PNI were linked to increased risk. While
these findings are important, they could be better explained. For example, how can elevated
NLR (which is often considered an inflammatory marker) be associated with a decreased risk
of MASLD? Are there specific mechanisms or patient characteristics that explain this inverse
relationship?
-The authors could also consider explaining why PLR and NLR, which are related to immune cell
responses, might be inversely associated with MASLD risk, especially in light of their observed
anti-inflammatory roles. It would be helpful to discuss potential pathophysiological explanations
or how these findings might vary in early vs. late stages of MASLD.
assistant