Single-cell multi-omics-based immune temporal network resolution in sepsis: unravelling molecular mechanisms and precise therapeutic targets
BackgroundSepsis is the leading cause of death globally (49 million cases per year with a 25-30% morbidity and mortality rate), but its immunopathology remains incompletely elucidated. Conventional models of ‘uncontrolled inflammation’ fail to explain the diversity of immune status in patients at di...
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1616794/full |
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| author | Han Liu Qun Liang |
| author_facet | Han Liu Qun Liang |
| author_sort | Han Liu |
| collection | DOAJ |
| description | BackgroundSepsis is the leading cause of death globally (49 million cases per year with a 25-30% morbidity and mortality rate), but its immunopathology remains incompletely elucidated. Conventional models of ‘uncontrolled inflammation’ fail to explain the diversity of immune status in patients at different stages of the disease, and there is an urgent need for a dynamic, time-series perspective to reveal key regulatory nodes.MethodsForty-six studies (2014–2024) were retrieved under PRISMA-2020 across 12 databases. Raw single-cell RNA-seq, ATAC-seq and CITE-seq matrices (≈1 million immune cells) were uniformly reprocessed, harmonised with scMGNN, and mapped onto pseudotime and RNA-velocity trajectories. Ordinary and stochastic differential-equation models quantified pro-/anti-inflammatory flux.ResultsMulti-omics fusion increased immune-cell classification accuracy from 72.3% to 89.4% (adjusted Rand index, p< 0.001). Three phase-defining checkpoints emerged: monocyte-to-macrophage fate bifurcation at 16–24 h, initiation of TOX-driven CD8+ T-cell exhaustion at 36–48 h, and irreversible immunosuppression beyond 72 h. Dynamical simulations identified two intervention windows—0–18 h (selective MyD88–NF-κB blockade) and 36–48 h (PD-1/TIM-3 dual inhibition)—forecasting 2.1-fold and 1.6-fold survival gains, respectively, in pre-clinical models.ConclusionIn this study, an “immune clock” model of sepsis was constructed based on single-cell multi-omics data, which accurately depicted three key decision nodes, namely, monocyte-macrophage differentiation, initiation of T-cell depletion and irreversible immune suppression, and identified the corresponding molecular targets (e.g., IRF8, TOX). This model provides a clear time window and targeting strategy for individualised immune intervention in sepsis. |
| format | Article |
| id | doaj-art-44c99ce74c764be1ae8dbc211a7d4bac |
| institution | DOAJ |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-44c99ce74c764be1ae8dbc211a7d4bac2025-08-20T02:58:11ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-08-011610.3389/fimmu.2025.16167941616794Single-cell multi-omics-based immune temporal network resolution in sepsis: unravelling molecular mechanisms and precise therapeutic targetsHan Liu0Qun Liang1Department of Epidemiology and Public Health, University College London, London, United KingdomThe First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, ChinaBackgroundSepsis is the leading cause of death globally (49 million cases per year with a 25-30% morbidity and mortality rate), but its immunopathology remains incompletely elucidated. Conventional models of ‘uncontrolled inflammation’ fail to explain the diversity of immune status in patients at different stages of the disease, and there is an urgent need for a dynamic, time-series perspective to reveal key regulatory nodes.MethodsForty-six studies (2014–2024) were retrieved under PRISMA-2020 across 12 databases. Raw single-cell RNA-seq, ATAC-seq and CITE-seq matrices (≈1 million immune cells) were uniformly reprocessed, harmonised with scMGNN, and mapped onto pseudotime and RNA-velocity trajectories. Ordinary and stochastic differential-equation models quantified pro-/anti-inflammatory flux.ResultsMulti-omics fusion increased immune-cell classification accuracy from 72.3% to 89.4% (adjusted Rand index, p< 0.001). Three phase-defining checkpoints emerged: monocyte-to-macrophage fate bifurcation at 16–24 h, initiation of TOX-driven CD8+ T-cell exhaustion at 36–48 h, and irreversible immunosuppression beyond 72 h. Dynamical simulations identified two intervention windows—0–18 h (selective MyD88–NF-κB blockade) and 36–48 h (PD-1/TIM-3 dual inhibition)—forecasting 2.1-fold and 1.6-fold survival gains, respectively, in pre-clinical models.ConclusionIn this study, an “immune clock” model of sepsis was constructed based on single-cell multi-omics data, which accurately depicted three key decision nodes, namely, monocyte-macrophage differentiation, initiation of T-cell depletion and irreversible immune suppression, and identified the corresponding molecular targets (e.g., IRF8, TOX). This model provides a clear time window and targeting strategy for individualised immune intervention in sepsis.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1616794/fullsepsissingle-cell multi-omicsimmune clocktiming regulationprecision medicine |
| spellingShingle | Han Liu Qun Liang Single-cell multi-omics-based immune temporal network resolution in sepsis: unravelling molecular mechanisms and precise therapeutic targets Frontiers in Immunology sepsis single-cell multi-omics immune clock timing regulation precision medicine |
| title | Single-cell multi-omics-based immune temporal network resolution in sepsis: unravelling molecular mechanisms and precise therapeutic targets |
| title_full | Single-cell multi-omics-based immune temporal network resolution in sepsis: unravelling molecular mechanisms and precise therapeutic targets |
| title_fullStr | Single-cell multi-omics-based immune temporal network resolution in sepsis: unravelling molecular mechanisms and precise therapeutic targets |
| title_full_unstemmed | Single-cell multi-omics-based immune temporal network resolution in sepsis: unravelling molecular mechanisms and precise therapeutic targets |
| title_short | Single-cell multi-omics-based immune temporal network resolution in sepsis: unravelling molecular mechanisms and precise therapeutic targets |
| title_sort | single cell multi omics based immune temporal network resolution in sepsis unravelling molecular mechanisms and precise therapeutic targets |
| topic | sepsis single-cell multi-omics immune clock timing regulation precision medicine |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1616794/full |
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