Background Multiple organ dysfunction syndrome (MODS) is a severe, life-threatening condition characterized by progressive dysfunction of multiple organ systems, commonly observed in critically ill patients within intensive care units (ICUs). Despite intensive medical interventions, MODS continues to be a major cause of mortality due to its multifactorial pathophysiology and the absence of effective targeted therapies. The significant burden on patients, families, and healthcare systems underscores the critical need for a deeper molecular understanding of MODS pathophysiology to inform the development of targeted therapeutic interventions. Aim This study aims to elucidate the molecular mechanisms of MODS through a comprehensive integration of transcriptomic profiling and network-based approaches. Methods Differential expression analysis (DEA) was followed by the identification of hub modules via weighted gene co-expression network (WGCN), establishment of protein interaction network (PPIN), gene ontology (GO) term & pathway enrichment analysis of PPIN hub module, and feed-forward loop (FFL) analysis. Results Using the GSE13205 dataset, we identified <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43042_2025_697_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="33" /> </InlineMediaObject> <EquationSource Format="TEX">$2365$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>2365</mn> </mrow> </math></EquationSource> </InlineEquation> differentially expressed genes (DEGs) followed by obtaining a total of 179 hub DEGs from the WGCN hub modules. The PPIN highlighted key regulatory nodes such as BMS1, FBL, and NOP14, emphasizing the disruption of ribosomal function and cellular stress responses in MODS. Furthermore, a MODS-specific 3-node FFL comprising <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43042_2025_697_Article_IEq2.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="25" /> </InlineMediaObject> <EquationSource Format="TEX">$325$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>325</mn> </mrow> </math></EquationSource> </InlineEquation> nodes and 784 edges revealed a tightly interconnected regulatory motif involving ZNF749 (transcription factor), miR-6726-5p (miRNA), and BMS1 (mRNA). Discussion This motif underscores the central role of transcriptional and post-transcriptional regulation in MODS pathophysiology. Functional enrichment analyses linked these hub genes to significant pathways, including rRNA processing and ribonucleoprotein complex biogenesis. Through advanced multiomics approaches, this study unveils groundbreaking insights into the molecular landscape of MODS, identifying critical biomarkers and therapeutic targets. Conclusion This study lays the groundwork for precision medicine solutions by revealing important facets of MODS's molecular landscape using sophisticated multiomics techniques. One important step in improving critical care for patients with MODS is identifying important regulatory networks and molecular targets. Future research should concentrate on confirming these results using clinical trials and experimental models, opening the door for focused therapies that could raise survival rates and lessen the toll that MODS takes on patients, families, and healthcare systems around the globe.

Unraveling the roles of BMS1, ZNF749 and miR-6726-5p in MODS progression via integrated multiomics and ML-based approach

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2025年4月14日

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Dhairya Mathur,
Anam Beg,
Sajani K.,
Syed Asif Husain,
Prithvi Singh

摘要

Background

Multiple organ dysfunction syndrome (MODS) is a severe, life-threatening condition characterized by progressive dysfunction of multiple organ systems, commonly observed in critically ill patients within intensive care units (ICUs). Despite intensive medical interventions, MODS continues to be a major cause of mortality due to its multifactorial pathophysiology and the absence of effective targeted therapies. The significant burden on patients, families, and healthcare systems underscores the critical need for a deeper molecular understanding of MODS pathophysiology to inform the development of targeted therapeutic interventions.

Aim

This study aims to elucidate the molecular mechanisms of MODS through a comprehensive integration of transcriptomic profiling and network-based approaches.

Methods

Differential expression analysis (DEA) was followed by the identification of hub modules via weighted gene co-expression network (WGCN), establishment of protein interaction network (PPIN), gene ontology (GO) term & pathway enrichment analysis of PPIN hub module, and feed-forward loop (FFL) analysis.

Results

Using the GSE13205 dataset, we identified $2365$ $2365$ differentially expressed genes (DEGs) followed by obtaining a total of 179 hub DEGs from the WGCN hub modules. The PPIN highlighted key regulatory nodes such as BMS1, FBL, and NOP14, emphasizing the disruption of ribosomal function and cellular stress responses in MODS. Furthermore, a MODS-specific 3-node FFL comprising $325$ $325$ nodes and 784 edges revealed a tightly interconnected regulatory motif involving ZNF749 (transcription factor), miR-6726-5p (miRNA), and BMS1 (mRNA).

Discussion

This motif underscores the central role of transcriptional and post-transcriptional regulation in MODS pathophysiology. Functional enrichment analyses linked these hub genes to significant pathways, including rRNA processing and ribonucleoprotein complex biogenesis. Through advanced multiomics approaches, this study unveils groundbreaking insights into the molecular landscape of MODS, identifying critical biomarkers and therapeutic targets.

Conclusion

This study lays the groundwork for precision medicine solutions by revealing important facets of MODS's molecular landscape using sophisticated multiomics techniques. One important step in improving critical care for patients with MODS is identifying important regulatory networks and molecular targets. Future research should concentrate on confirming these results using clinical trials and experimental models, opening the door for focused therapies that could raise survival rates and lessen the toll that MODS takes on patients, families, and healthcare systems around the globe.