Spatial Computational Hepatic Molecular Biomarker Reveals LSEC Role in Midlobular Liver Zonation Fibrosis in DILI and NASH Liver Injury
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis is a solid and interesting manuscript. Augmenting the analytical basis for differentiating DILI and NASH (and other distinct pathologies) is a worthy goal.
The informatics analysis appears to be solidified by internal predictivity tests, which is a reasonable start. The impact of the analysis might be illustratively advanced by illustrating how the patterns could aid in interpretating other interesting aspects of liver disease or etiology. The authors might think of an example or two that could strengthen their case.
Perhaps of relevance is the fact that there have been a fair number of recent studies examining NASH-related and DILI-related differentiation in gut microbiome profiles, as a potential basis for differential diagnoses. It has seemed a bit murky whether liver pathology influences gut microbiota by altering the composition of blood exchanged via the portal vein, or whether the microbiota may exacerbate liver dysfunction. Perhaps both; I believe I have seen evidence that gut microbiota may amplify drug hepatotoxicity as a factor in DILI, for example.
Such analyses are distinct from those pursued in this manuscript, but may be inter-complementary. The manuscrript may benefit from brief comments on the interplay between these two distint, and potentially diagnostically complementary modes of assessment.
Author Response
Point-by-point response
Dear Reviewer, I would like to convey my sincere thanks for reviewing my manuscript. All the points raised by you are valuable and important for making this manuscript a quality research document for the readers. The following are the point-by-point responses, and all these recommendations are accepted and included in the revised updated draft.
Reviewer`s comments:
This is a solid and interesting manuscript. Augmenting the analytical basis for differentiating DILI and NASH (and other distinct pathologies) is a worthy goal.
The informatics analysis appears to be solidified by internal predictivity tests, which is a reasonable start. The impact of the analysis might be illustratively advanced by illustrating how the patterns could aid in interpretating other interesting aspects of liver disease or etiology. The authors might think of an example or two that could strengthen their case.
Response; Thanks for reviewing and highlighting this important point. Examples are added in the revised manuscript (highlighted gray in discussion section)
Perhaps of relevance is the fact that there have been a fair number of recent studies examining NASH-related and DILI-related differentiation in gut microbiome profiles, as a potential basis for differential diagnoses. It has seemed a bit murky whether liver pathology influences gut microbiota by altering the composition of blood exchanged via the portal vein, or whether the microbiota may exacerbate liver dysfunction. Perhaps both; I believe I have seen evidence that gut microbiota may amplify drug hepatotoxicity as a factor in DILI, for example.
Such analyses are distinct from those pursued in this manuscript, but may be inter-complementary. The manuscrript may benefit from brief comments on the interplay between these two distint, and potentially diagnostically complementary modes of assessment.
Response; Thanks for bringing this important missing aspect of the study here. Comments on gut microbiome are added in the revised manuscript (highlighted in gray color in discussion section)
Reviewer 2 Report
Comments and Suggestions for AuthorsThe authors present a very interesting manuscript with novel findings. However, it should be substantially improved to reach publication status.
1. In introduction section, NAFLD should be substituted for MASLD (ref: Rinella ME, J Hepatol 2023)
2. Also in introduction section, the following reviews regarding LSECs should be added: Gao J, Mol Med Rep 2024; Velliou RI, Cell Mol Life Sci 2023; Nasiri-Ansari N, Cells 2022
3. In results section, in the beggining of each paragraph, a small sentence explains what the authors did and reach each result. T.ex. in 2.1 'Image analytics and experimental workflow, illustrated in Fig.1 D, is designed to classify Hematoxylin and Eosin (H&E) histopathology images under five categories i.e. normal, steatosis, early fibrosis, bridging fibrosis and cirrhosis. Machine learning widgets, shown in workflow, are executed to load, process, classify, cluster, and visualize the imaging data.'; in 2.2 'DGE analysis for NASH and zonation expression is performed over four independ-110 ent studies GSE89632, GSE126848, GSE83990, GSE105127 using NCBI GEO2R analysis 111 tool.'; in 2.3 'Single-cell transcriptomic analysis is performed over liver cells (n=9 i.e. three patients 125 in each group) in control, DILI(intrinsic) and NASH datasets available at NCBI GEO 126 GSE166178[13] and analyzed for the heterogeneity of inter- and intra-group endothelial 127 cells in healthy and diseased mouse livers', etc. These sentences should be moved in materials and methods, since they don't represent results but methodology
4. In discussion section, the lines 265-277 seem out of place. If the authors wish to talk about new ways of identificating biomarkers for fibrosis that should be placed in another part of discussion and not between the talk regarding gene expression profiles.
5. In conclusions section, a possible clinical relevance of the various gene profiles should be placed
Comments on the Quality of English LanguageEnglish language fine
Author Response
Point-by-point response
Dear Reviewer, I would like to convey my sincere thanks for reviewing my manuscript. All the points raised by you are valuable and important for making this manuscript a quality research document for the readers. The following are the point-by-point responses, and all these recommendations are accepted and included in the revised updated draft.
Reviewer`s comments:
The authors present a very interesting manuscript with novel findings. However, it should be substantially improved to reach publication status.
- In introduction section, NAFLD should be substituted for MASLD (ref: Rinella ME, J Hepatol 2023)
Response: Thanks for bringing this important point here. NAFLD is replaced with MASLD in the revised draft (highlighted in yellow).
- Also in introduction section, the following reviews regarding LSECs should be added: Gao J, Mol Med Rep 2024; Velliou RI, Cell Mol Life Sci 2023; Nasiri-Ansari N, Cells 2022
Response: Thanks for sharing these important missing references. Added in the revised manuscript.
- In results section, in the beggining of each paragraph, a small sentence explains what the authors did and reach each result. T.ex. in 2.1 'Image analytics and experimental workflow, illustrated in Fig.1 D, is designed to classify Hematoxylin and Eosin (H&E) histopathology images under five categories i.e. normal, steatosis, early fibrosis, bridging fibrosis and cirrhosis. Machine learning widgets, shown in workflow, are executed to load, process, classify, cluster, and visualize the imaging data.'; in 2.2 'DGE analysis for NASH and zonation expression is performed over four independ-110 ent studies GSE89632, GSE126848, GSE83990, GSE105127 using NCBI GEO2R analysis 111 tool.'; in 2.3 'Single-cell transcriptomic analysis is performed over liver cells (n=9 i.e. three patients 125 in each group) in control, DILI(intrinsic) and NASH datasets available at NCBI GEO 126 GSE166178[13] and analyzed for the heterogeneity of inter- and intra-group endothelial 127 cells in healthy and diseased mouse livers', etc. These sentences should be moved in materials and methods, since they don't represent results but methodology
Response: Thanks for bringing this important point. These sentences moved to methodology section.
- In discussion section, the lines 265-277 seem out of place. If the authors wish to talk about new ways of identificating biomarkers for fibrosis that should be placed in another part of discussion and not between the talk regarding gene expression profiles.
Response: Thanks for bringing this important point here. These lines now moved to other part of discussion section in the revised draft.
- In conclusions section, a possible clinical relevance of the various gene profiles should be placed
Response: Thanks for the comments. Clinical relevance is added.
Reviewer 3 Report
Comments and Suggestions for AuthorsMunish Puri in this manuscript identified zonation marker genes using scRNA-seq and spatial transcriptomics molecular profiling technologies in normal, DILI, and NASH liver injury
It is recommended that the author carefully review the wording and check the abbreviations for the first time in the text.
Line 47and 48 DGE homogenize
Increase image resolution
Línea 175 Single-cell scRNA-seq data used here was acquired from separate five independent studies reported elsewhere in (16). Add the reference of the other 4 independent studies.
References line 265 to 268
line 277and 278
Recommend adding references in the discussion.
Add the study limitations in the discussion section and not in the conclusions.
2.2. DGE analysis for NASH and zonation expression.
What were the selection criteria and the steps taken to include these 4 studies?
The conclusions are confusing since the author puts references, improve.
You could add more specific data in the methodology so that it can be reproduced.
Author Response
Point-by-point response
Dear Reviewer, I would like to convey my sincere thanks for reviewing my manuscript. All the points raised by you are valuable and important for making this manuscript a quality research document for the readers. The following are the point-by-point responses, and all these recommendations are accepted and included in the revised updated draft.
Reviewer`s comments:
Munish Puri in this manuscript identified zonation marker genes using scRNA-seq and spatial transcriptomics molecular profiling technologies in normal, DILI, and NASH liver injury
It is recommended that the author carefully review the wording and check the abbreviations for the first time in the text.
Line 47and 48 DGE homogenize
Response: Thanks for the correction. It’s fixed in the updated revised draft.
Increase image resolution. Línea 175 Single-cell scRNA-seq data used here was acquired from separate five independent studies reported elsewhere in (16). Add the reference of the other 4 independent studies.
Response: Thanks for the comments. Four other references are added.
References line 265 to 268
Response: Thanks for the comments. References are added.
line 277and 278
Recommend adding references in the discussion.
Response: Thanks for the comments. References are added.
Add the study limitations in the discussion section and not in the conclusions.
Response: Thanks for bringing this important point here. Study limitations moved to the discussion section in the revised draft.
2.2. DGE analysis for NASH and zonation expression.
What were the selection criteria and the steps taken to include these 4 studies?
Response: Thanks for bringing this important point here. The selection criteria were to select studies in NASH & Control and DILI groups representing DGE and zonation specific expression in liver. Two studies selected in each group i.e. GSE89632, GSE126848, in NASH & control group, GSE83990, GSE105127 in liver zonation group ( zone1.zone2, zone3) from NCBI GEO (Gene expression omnibus) database to understand DGE expression for NASH and zonation-specific genes. In the first steps, patients in respective studies were grouped as in NASH and controls groups (in studies GSE89632, GSE126848) and zone1, zone2, zone 3 as in zone-specific DGE studies ( in GSE83990, GSE105127). The second step was to run GEO2R tool (available at NCBI GEO website) to run DGE analysis and then volcano plots were generated for respective studies shown in Figure 2.
The conclusions are confusing since the author puts references, improve.
Response: Thanks for the comments. References are removed from the conclusion section.
You could add more specific data in the methodology so that it can be reproduced.
Response: Thanks for the comments. Data provided in the methodology section added from NCBI GEO NIH database which is fully reproducible.
Reviewer 4 Report
Comments and Suggestions for AuthorsThe aim of this study was to analyze zone-specific effect of liver steatosis/fibrosis on differential gene expression in liver cells using informatics tools and publically available sets of data. In particular, they focused on the interplay of liver sinusoid endothelial cells (LSECs) in mid-lobular zone 2 and their contributions in initiation of early fibrosis.
The topic and the results are of interest. After reading the manuscript, I have few comments how it could be improved.
1) Line 8, the abbreviation “LSECs” should be clarified.
2) Line 30 and elsewhere: the text and parenthesis should be separated, e.g. “…deaths [1]”, not “…deaths[1]”.
3) Line 320: were slides categorized according to the fibrosis stage already in the database or were categorized by the authors?
4) Lines 3200321: was etiology of steatosis/fibrosis taken into consideration? Do you have data about etiology (the underlying disease) in a given patient?
5) Conclusion section should be focused on the results of this study.
Author Response
Point-by-point response
Dear Reviewer, I would like to convey my sincere thanks for reviewing my manuscript. All the points raised by you are valuable and important for making this manuscript a quality research document for the readers. The following are the point-by-point responses, and all these recommendations are accepted and included in the revised updated draft.
Reviewer`s comments:
The aim of this study was to analyze zone-specific effect of liver steatosis/fibrosis on differential gene expression in liver cells using informatics tools and publically available sets of data. In particular, they focused on the interplay of liver sinusoid endothelial cells (LSECs) in mid-lobular zone 2 and their contributions in initiation of early fibrosis.
The topic and the results are of interest. After reading the manuscript, I have few comments how it could be improved.
- Line 8, the abbreviation “LSECs” should be clarified.
Response: Thanks for the comments. Abbreviation of “LSECs” is added.
2) Line 30 and elsewhere: the text and parenthesis should be separated, e.g. “…deaths [1]”, not “…deaths[1]”.
Response: Thanks for the comments. Fixed.
3) Line 320: were slides categorized according to the fibrosis stage already in the database or were categorized by the authors?
Response: Slides already categorized according to the fibrosis stages in the NCI GTEX database.
4) Lines 3200321: was etiology of steatosis/fibrosis taken into consideration? Do you have data about etiology (the underlying disease) in a given patient?
Response: Yes, steatosis/fibrosis taken into consideration for image classification in ML model shown in Figure 1.
5) Conclusion section should be focused on the results of this study.
Response: Thanks for the comments. Conclusion section made more focused on results and findings of the study in the revised updated draft.
