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Background <p>Interferons play a central role in antiviral defense, but their dysregulation contributes to inflammation and immune dysfunction in respiratory viral infections, including COVID-19. While interferon-stimulated genes (ISGs) are essential effectors of this response, their expression patterns in patients are heterogeneous and not always predictive of disease severity. The immunometabolic consequences of this heterogeneity remain poorly understood.</p> Methods <p>We analyzed hospitalized COVID-19 patients (<i>n</i> = 37) and uninfected controls (<i>n</i> = 31) using whole-blood transcriptomics, immune cell deconvolution, plasma proteomics, and standardized plasma metabolomics from a previously generated dataset within this cohort. Patients were stratified into low (LIS), moderate (MIS), and high (HIS) ISG score clusters. Plasma innate immune activation markers were measured by ELISA. Interferon-directed antibody reactivity was analyzed by multiplex bead-based assays measuring antigen reactivity. Functional immune responses were assessed via ex vivo stimulation of healthy donor immune cells with patient plasma, and correlations were performed between metabolites and immune activation markers.</p> Results <p>HIS patients exhibited increased inflammatory mediators and innate immune cell expansion compared with LIS and MIS groups. However, within the HIS group, severe cases displayed distinct metabolic and immune dysregulation. Specifically, severe HIS cases showed reductions in phospholipids, sphingolipids, and tricarboxylic acid cycle intermediates, suggestive of disrupted mitochondrial and lipid metabolism. Plasma from severe HIS patients tended to impair neutrophil and monocyte activation, indicating functional attenuation of innate immune activation within a shared high-ISG background. Correlation analysis revealed that branched-chain lipids, tryptophan-derived metabolites, and a branched-chain dicarboxylic acid were positively associated with immune activation markers. Although type-I interferon neutralization was detected in a subset of patients with IFN antigen reactivity, these samples did not fully account for the observed ISG heterogeneity or disease severity.</p> Conclusions <p>High ISG expression in COVID-19 defines a transcriptional endotype associated with systemic inflammation and innate immune activation. However, severe cases within this group exhibit metabolic constraints and reduced innate immune responsiveness, supporting an immune-metabolic axis in which inflammatory mediators and altered lipid/energy metabolism intersect with innate immune function. These findings motivate future studies to determine whether interferon-associated immune-metabolic states during acute infection relate to persistent inflammation or post-acute sequelae in selected patient subsets.</p>

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Systemic multi-omics analysis reveals interferon response heterogeneity and links lipid metabolism to immune alterations in severe COVID-19

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月29日

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  • Ronaldo Lira-Junior,
  • Anoop T. Ambikan,
  • Axel Cederholm,
  • Sefanit Rezene,
  • Flora Mikaeloff,
  • Sara Svensson Akusjärvi,
  • Ahmet Yalcinkaya,
  • Xi Chen,
  • Maike Sperk,
  • Maribel Aranda-Guillén,
  • Hampus Nordqvist,
  • Carl Johan Treutiger,
  • Nils Landegren,
  • Ujjwal Neogi,
  • Soham Gupta

摘要

Background

Interferons play a central role in antiviral defense, but their dysregulation contributes to inflammation and immune dysfunction in respiratory viral infections, including COVID-19. While interferon-stimulated genes (ISGs) are essential effectors of this response, their expression patterns in patients are heterogeneous and not always predictive of disease severity. The immunometabolic consequences of this heterogeneity remain poorly understood.

Methods

We analyzed hospitalized COVID-19 patients (n = 37) and uninfected controls (n = 31) using whole-blood transcriptomics, immune cell deconvolution, plasma proteomics, and standardized plasma metabolomics from a previously generated dataset within this cohort. Patients were stratified into low (LIS), moderate (MIS), and high (HIS) ISG score clusters. Plasma innate immune activation markers were measured by ELISA. Interferon-directed antibody reactivity was analyzed by multiplex bead-based assays measuring antigen reactivity. Functional immune responses were assessed via ex vivo stimulation of healthy donor immune cells with patient plasma, and correlations were performed between metabolites and immune activation markers.

Results

HIS patients exhibited increased inflammatory mediators and innate immune cell expansion compared with LIS and MIS groups. However, within the HIS group, severe cases displayed distinct metabolic and immune dysregulation. Specifically, severe HIS cases showed reductions in phospholipids, sphingolipids, and tricarboxylic acid cycle intermediates, suggestive of disrupted mitochondrial and lipid metabolism. Plasma from severe HIS patients tended to impair neutrophil and monocyte activation, indicating functional attenuation of innate immune activation within a shared high-ISG background. Correlation analysis revealed that branched-chain lipids, tryptophan-derived metabolites, and a branched-chain dicarboxylic acid were positively associated with immune activation markers. Although type-I interferon neutralization was detected in a subset of patients with IFN antigen reactivity, these samples did not fully account for the observed ISG heterogeneity or disease severity.

Conclusions

High ISG expression in COVID-19 defines a transcriptional endotype associated with systemic inflammation and innate immune activation. However, severe cases within this group exhibit metabolic constraints and reduced innate immune responsiveness, supporting an immune-metabolic axis in which inflammatory mediators and altered lipid/energy metabolism intersect with innate immune function. These findings motivate future studies to determine whether interferon-associated immune-metabolic states during acute infection relate to persistent inflammation or post-acute sequelae in selected patient subsets.