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Article
Peer-Review Record

Exploring the Shared Diagnostic Biomarkers and Molecular Mechanisms Related to Mitochondrial Dysfunction in Inflammatory Bowel Disease and Rheumatoid Arthritis

Curr. Issues Mol. Biol. 2026, 48(1), 89; https://doi.org/10.3390/cimb48010089
by Lijiao Cui 1,†, Shicai Ye 1,2,†, Zhiwei Gu 2, Guixia Zhang 2, Tingen Chen 2, Yu Zhou 2,* and Caiyuan Yu 2,*
Reviewer 2: Anonymous
Curr. Issues Mol. Biol. 2026, 48(1), 89; https://doi.org/10.3390/cimb48010089
Submission received: 19 December 2025 / Revised: 12 January 2026 / Accepted: 14 January 2026 / Published: 16 January 2026

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The work by Cui and colleagues, “Exploring the shared diagnostic biomarkers and molecular mechanisms related to mitochondrial dysfunction in inflammatory bowel disease and rheumatoid arthritis,” allows us to understand the comorbidity between inflammatory bowel disease and rheumatoid arthritis by identifying shared molecular biomarkers related to mitochondrial dysfunction. This suggests that diseases, particularly chronic inflammatory diseases, should be studied as interconnected pathological networks.

The following comments are made: In the introduction, it is necessary to include a sentence indicating the existing knowledge gap that necessitates the development of this project. It is also necessary to explain the advantage or impact of using networks as part of a complementary must connect or integrate mitochondrial dysfunction followed by the activation of inflammatory pathways that cause the immunological changes in IBD/RA. Improve the conclusion, avoiding redundancies and repetitions (e.g., “may serve as”, lines 544 and 545, etc.). Ensure that gene names are in italics. Include a projection on the methodological and technical perspectives of the work.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Review on the manuscript titled “Exploring the shared diagnostic biomarkers and molecular mechanisms related to mitochondrial dysfunction in inflammatory bowel disease and rheumatoid arthritis” by Cui et al., 2026.

                In the abstract the authors report, they elucidated and assessed the commonalities of IBD and RA in the context of the mitochondrial dysfunction. Based on co-expression analysis they identified ‘cross-talk’ (CT) genes. They also ascertained the differentially expressed mitochondrial dysfunction-related genes (MDRGs) collected from the GeneCards database in the pathologies considered.

As a conclusion within abstract, they state “findings highlight the close association between IBD, RA, and mitochondrial dysfunction. PDIA4 and DUSP6 may serve as potential biomarkers of mitochondrial dysfunction in patients with IBD and RA”.

                After comprehensive introduction, the authors listed the stages of their analysis.

  1. Materials and Methods comprises several subchapters.

2.1 Data acquisition and preprocessing: The authors listed four datasets: IBD (GSE75214 and GSE179285) and RA (GSE89408 and GSE17755) they employed for analysis. Detailed dataset information is presented in Table 1 (haven’t found one).

2.2 Differential genes expression analysis: (R package limma (version 3.58.1)

2.3 WGCNA and identification of CGs (WGCNA)

2.4 Enrichment analysis of CGs

2.5 Screening of potential diagnostic biomarkers in CGs

2.6 Validation of diagnostic models for IBD and RA

2.7 Construction of PPI network and regulatory network

2.8 ROC curve analysis of hub genes

2.9 Immune infiltration analysis

2.10 Cell culture and construction of inflammation model

2.11 Real-time quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR)

2.12 Statistical analysis

2.13 Technology roadmap (Fig. 1, Block-scheme of the analysis).

 

  1. Results

3.1. DEGs in IBD/RA related to mitochondrial dysfunction (Figure 2. DEGs analysis in IBD and RA ; Supplementary Tables S1, S2)

3.2 WGCNA and the acquisition of CGs of IBD and RA (Fig. 3; Supplementary Figure S2; Tables S5, S6).

3.3 GO and KEGG enrichment analysis for CGs (GO and KEGG enrichment analyses were performed for the 87 CGs (Supplementary File S1; Fig. 4).

3.4 GSVA for IBD and RA (Fig. 5; Tables S2, S3)

3.5 Construction of diagnostic model for IBD and RA (Fig. 6: The LASSO regression model based on logistic regression models; Tables S2, S3)

3.6 Identification of hub genes and network analyses based on hub genes (Fig.7; Tables S4, S5)

3.7 Validation of diagnostic models for IBD and RA (Fig.8): the authors used regression analysis to provide risk scores for IBD and RA based on 2 target hub genes DUSP6 and PDA4 .

3.8 ROC analysis and validation of hub genes (Fig.9)

3.9 Differential expression analysis and validation of DUSP6 and PDIA4 (Fig.10)

3.10 Immune infiltration analysis (Fig.11)

                Thus, the authors provide 10 assessments for elucidating the mitochondrial dysfunction in IBD an RA leading to outlining two hub genes PDIA4 and DUSP6 as highly specific markers of MTD.

After the comprehensive Discussion section elaborating on the results obtained, the authors provide some conclusion statements:

  • The study identified a set of mitochondrial dysfunction-related Cross talk Genes (CGs) associated with IBD and RA.
  • PDIA4 and DUSP6 hub genes have been exposed as potential common predictive factors for IBD and RA

 

The manuscript is well composed, and rather long range of tasks have been accomplished, leading to exposing the hub genes DUSP5 and PDIA4 with subsequent regression models for IBD and RA risk prediction. The manuscript would be of interest to the researchers in the field. Some notes are presented below.

 

  • “Detailed dataset information is presented in Table 1”. It’s absent within the manuscript (along any other tables).
  • Supplementary Files1…5 should be renamed Supplementary Tables1…5 in Supplementary and listed in ascending order in a manuscript (currently Table S1 goes third and named as Supplementary File S1).
  • It’s still unclear to me what does specifically crosstalk genes (CG) term means within genes annotation routine. As I take it, the CG are built with WGCNA routine and can be associated with the particular GO term which authors have essentially done in (3.3) by GO analysis. So please, explain the necessity for introducing CG term.
  • Supplementary Fig.S1 plots are not quite informative in particular, a-d. Also, the comprehensive titles for the figures should be provided within each figure.
  • Supplementary Fig. S3: ordinate axis should be denoted explicitly,

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I have no more observations.

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