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Updated: Feb 10, 2026
Use of an Influenza Antigen Microarray to Measure the Breadth of Serum Antibodies Across Virus Subtypes
Published on: July 26, 2019
Molecular subtyping and immune microenvironment heterogeneity in pediatric influenza-associated prolonged multiple
Ming Chi1, Lei Wang2, Wenliang Bi3
1Department of Pediatrics, The 960th Hospital of the Joint Logistics Support Force of the People's Liberation Army of China, Jinan, China.
Background:
Pediatric influenza infections that progress to prolonged multiple organ dysfunction syndrome (PMODS) carry a high mortality rate. The underlying molecular heterogeneity, particularly involving dysregulated autophagy pathways and the immune microenvironment, remains poorly characterized, hindering the development of targeted interventions. This study aimed to integrate transcriptomic profiling and machine learning to dissect autophagy-related gene (ARG) dysregulation, characterize the immune microenvironment, and identify clinical biomarkers associated with PMODS severity.
Methods:
We analyzed the publicly available transcriptomic dataset GSE236877, comprising 191 pediatric samples from influenza patients: 38 with PMODS or who died, 27 who recovered from MODS (RM), and 126 who never developed MODS (NM). Differential expression analysis of ARGs was performed. Unsupervised consensus clustering was used to identify molecular subtypes within the PMODS group. Immune cell infiltration was quantified using CIBERSORT. A Random Forest (RF) machine learning algorithm was employed to prioritize key discriminatory genes, whose correlations with clinical parameters were subsequently assessed.
Results:
Compared to NM samples, PMODS cases exhibited significant upregulation of CCL2, CTSB, HIF1A, and NFKB1, alongside downregulation of CASP1, CASP8, TNFSF10, and EIF2AK2. Consensus clustering stratified PMODS patients into two distinct molecular subtypes (C1 and C2). Subtype C1 was characterized by a hyperinflammatory signature, marked by elevated expression of CCL2 and increased infiltration of Macrophages M0. In contrast, subtype C2 displayed a profile of apoptotic activation, with upregulated TNFSF10 and significantly reduced Macrophages M0 infiltration. RF analysis identified CCL2, TNFSF10, and HIF1A as the top three genes for discriminating disease states. Their expression levels showed significant correlations with leukocyte counts and clinical disease severity scores.
Conclusions:
This study reveals significant molecular heterogeneity within pediatric influenza-associated PMODS, delineating two distinct subtype-specific mechanisms: C1 hyperinflammation vs. C2 apoptotic activation. It identifies CCL2, TNFSF10, and HIF1A as key biomarkers linked to immune dysregulation and clinical severity. These findings provide a foundational framework for the development of subtype-stratified, precision management strategies for this critical condition.
Insights
Pediatric influenza can cause prolonged multiple organ dysfunction syndrome (PMODS). This study identified two molecular subtypes of PMODS, revealing key biomarkers like CCL2 and TNFSF10 for targeted interventions.
Area of Science:
- Pediatric critical care medicine
- Molecular biology
- Immunology
Background:
- Prolonged multiple organ dysfunction syndrome (PMODS) in pediatric influenza patients has a high mortality rate.
- The molecular mechanisms and immune microenvironment of PMODS are poorly understood, hindering effective treatment.
- Autophagy pathway dysregulation is implicated but requires further characterization.
Purpose of the Study:
- To integrate transcriptomic data and machine learning to analyze autophagy-related gene (ARG) dysregulation in pediatric PMODS.
- To characterize the immune microenvironment associated with PMODS.
- To identify clinical biomarkers correlating with PMODS severity.
Main Methods:
- Analysis of the GSE236877 transcriptomic dataset (191 pediatric influenza samples).
- Differential expression analysis of ARGs and unsupervised consensus clustering to identify PMODS subtypes.
- Immune cell infiltration quantification (CIBERSORT) and Random Forest (RF) machine learning for biomarker identification.
Main Results:
- PMODS cases showed differential ARG expression (e.g., upregulated CCL2, HIF1A; downregulated CASP1, TNFSF10) compared to non-MODS cases.
- Two PMODS subtypes were identified: C1 (hyperinflammatory, high CCL2, Macrophages M0 infiltration) and C2 (apoptotic, high TNFSF10, low Macrophages M0 infiltration).
- RF analysis highlighted CCL2, TNFSF10, and HIF1A as key discriminatory genes, correlating with leukocyte counts and clinical severity.
Conclusions:
- Pediatric influenza-associated PMODS exhibits significant molecular heterogeneity with distinct hyperinflammatory (C1) and apoptotic (C2) subtypes.
- CCL2, TNFSF10, and HIF1A are identified as critical biomarkers associated with immune dysregulation and clinical severity.
- These findings support the development of subtype-specific precision management strategies for pediatric PMODS.
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