BACKGROUND:To enhance biological understanding of ARDS, pneumonia, and sepsis and to accelerate therapeutic development in these areas, the National Institutes of Health developed the ARDS, Pneumonia, and Sepsis (APS) Consortium. RESEARCH QUESTION:Is the APS Consortium study rapidly generating data and biospecimens from a large cohort of critically ill adults with ARDS, pneumonia, and sepsis that will facilitate phenotyping of these syndromes? STUDY DESIGN AND METHODS:The APS Consortium Phenotyping Study is a multicenter, longitudinal, prospective, observational cohort study aimed at enrolling 4,000 critically ill adults with ARDS, pneumonia, sepsis, or a combination thereof over 4 years. Data and biospecimens are collected to characterize many aspects of each participant's chronic health, acute illness, and long-term recovery to facilitate phenotyping, that is, subclassifying ARDS, pneumonia, and sepsis into precise biologically based subsets with shared pathophysiologic characteristics. Feasibility of the study was assessed by evaluating the first 1,000 participants in terms of recruitment pace, participant characteristics, biospecimen collection, and proportion with confirmed ARDS, pneumonia, and sepsis based on expert adjudication. RESULTS:The first 1,000 participants were recruited ahead of schedule in < 13 months. Median age was 64 years, 75% received vasopressors, 50% received invasive mechanical ventilation, and 25% died in the hospital within 4 weeks of enrollment. Biospecimen collection rates were high, with 99% of participants with blood samples, 98% with upper respiratory swabs, 37% with lower respiratory samples, 80% with urine samples, and 65% with gastrointestinal samples. Expert adjudication resulted in 40% classified with ARDS, 52% classified with pneumonia, and 89% classified with sepsis. INTERPRETATION:The APS Consortium Phenotyping Study is producing a cohort of critically ill adults with ARDS, pneumonia, and sepsis with high severity of disease and a rich set of data and biospecimens. The study will continue to full enrollment of 4,000 participants. CLINICAL TRIAL REGISTRATION:ClinicalTrials.gov; No.: NCT06521502; URL: www. CLINICALTRIALS:gov.

Due to its nonspecific clinical criteria, sepsis is clinically, microbiologically, pathophysiologically and immunologically highly heterogeneous. Consequently, despite hundreds of clinical trials, no host-targeted therapy has been shown to be ubiquitously efficacious, leading investigators to pursue more precision-based approaches for enriching sepsis populations through the identification of subgroups or phenotypes. Here, we review the myriad domains in which heterogeneity is observed in sepsis and the challenges and opportunities they offer to improve outcomes. We review current strategies used by investigators leveraging novel biological measurements and/or computational algorithms to identify more homogeneous subgroups either based on pathogen or host characteristics or both. Finally, we review some of the most promising recent advances that seek to bring these complex and innovative discoveries to the bedside to facilitate precision medicine in sepsis.

Transcriptomic analysis of blood cells can reveal key elements of the dysregulated host response in sepsis and spur biomarker and mechanism identification. We hypothesized that sepsis nonsurvivors exhibit a distinct transcriptional signature in whole blood that reflects insights into sepsis mortality. We conducted a prospective observational cohort study of 161 critically ill sepsis patients. Whole blood RNA was collected within 24 hours of intensive care unit admission. Gene expression levels were measured using microarrays, and changes in gene levels were compared between 30-day nonsurvivors and survivors, adjusting for age, sex, and neutrophil count. Pathway overrepresentation analysis and weighted gene co-expression analysis were performed to identify biological pathways and gene co-expression groups, respectively, associated with sepsis mortality. Gene- and pathway-based results were compared to findings in an independent cohort of 479 sepsis patients with 28-day mortality data. Thirty-day mortality in the enrolled sepsis cohort was 37% (60 of 161 patients). We identified 1106 differentially expressed genes in nonsurvivors (Benjamini-Hochberg-adjusted P-value <.05), including several neutrophil-related genes (CEACAM8, ELANE, PRTN3, MPO, CEACAM6, DEFA4, MS4A3) with expression levels over 1.8 times higher in nonsurvivors despite adjusting for neutrophil counts. The neutrophil degranulation pathway was prominent based on its overrepresentation in (1) differentially expressed genes in both cohorts, (2) overrepresentation by gene set enrichment analysis, and (3) 4 of the 6 gene co-expression groups correlated with sepsis mortality. Our findings highlight the involvement of neutrophil degranulation genes in sepsis mortality, prompting further study to better understand whether they constitute a modifiable target.

BACKGROUNDSepsis is a leading cause of morbidity and mortality in critically ill children, yet heterogeneous immune responses complicate the development of targeted therapies and the host immune factors driving sepsis pathobiology remain unclear.METHODSWe integrated deep immune phenotyping, plasma proteomics, single-cell transcriptomics, and phosphoflow cytometry in a prospective cohort of 88 critically ill children to elucidate the mechanisms underlying immune heterogeneity.RESULTSUnsupervised clustering of plasma cytokines identified 3 immunologic subgroups, including a high-severity group ("Group C") characterized by hypercytokinemia driven by IL-6 and IFN-γ. Group C exhibited distinct alterations in immune cell frequency and activation, with a strong association between hyperinflammatory cytokine signaling and lymphocyte dysfunction. Single-cell RNA-seq revealed transcriptional signatures of T cell activation and metabolic stress, with suppression of a lymphoid protective gene program across CD8+ T cell subsets. Despite increased expression of activation markers, T cell receptor repertoire analysis revealed no dominant clonotypes, consistent with bystander activation. Phosphoflow cytometry demonstrated baseline STAT1/STAT3 hyperactivation in Group C CD8+ T cells, which failed to respond to αCD3/αCD28/αCD49d stimulation.CONCLUSIONSThese findings define an IL-6/IFN-γ-driven endotype of T cell dysfunction in pediatric sepsis and highlight the JAK/STAT axis as a rational target for immunomodulatory therapy.FUNDINGK12HD047349, K23GM159013, K08AI135091, R01HD095976, Thrasher Research Fund, Burroughs Wellcome Fund, Immune Deficiency Foundation, Primary Immune Deficiency Treatment Consortium, Barbara Brodsky Foundation, CHOP Research Institute.

BACKGROUND:Two biological subphenotypes in acute respiratory distress syndrome (ARDS) have been identified in retrospective analyses, with differential clinical outcomes and post-hoc responses to investigational treatments. The ability to identify biological subphenotypes in real-time is unknown. We aimed to evaluate the feasibility of using the multisite ISPY COVID Network to prospectively evaluate biological subphenotypes in real-time. METHODS:This prospective, observational, cohort study enrolled patients with ARDS and severe acute hypoxaemic respiratory failure (AHRF) and assessed the feasibility of real-time stratification into biological subphenotypes using plasma concentrations of IL-6, soluble tumour necrosis factor-1 (TNFR1), and clinical variables. Participants were eligible if they were receiving mechanical ventilation, non-invasive positive pressure ventilation, or heated high flow nasal oxygen (at flow rates ≥30 L/min); had severe AHRF (defined by an SpO2 to FiO2 ratio ≤315, calculated with SpO2 ≤97%, or PaO2 to FiO2 ratio <300 if arterial blood gas was available); and the presence of these criteria for less than 48 h. Key exclusion criteria were being younger than 18 years, known pregnancy, being incarcerated, ARDS secondary to trauma, and rapidly improving hypoxaemia. Enrolled patients had to meet inclusion and exclusion criteria at the time of consent and blood draw. Enrolled patients were stratified into either a severe AHRF group (unilateral infiltrate) or an ARDS group (bilateral infiltrates) based on chest imaging at enrolment, determined by the study team. After enrolment, a blood sample (up to 6 mL) was collected and immediately taken to the local laboratory for plasma analysis. Following biomarker quantification participants were allocated to the hypoinflammatory or hyperinflammatory groups. Feasibility was defined a priori as successful real-time biological subphenotyping in greater than 75% of the final 100 enrolled participants. FINDINGS:From June 15, 2023, to Oct 31, 2024, 844 patients at 17 hospitals in the ISPY COVID Network across the USA were screened for the study. After 504 exclusions and two withdrawals of consent, 338 patients were enrolled. 124 (37%) of the enrolled cohort were classified as AHRF, and 214 (63%) were classified as ARDS. 199 (59%) of patients were male and 138 (41%) were female, and the median age at enrolment was 64 years (IQR 54-74). The majority of patients were white (239 [71%]). 250 (74%) of the enrolled cohort completed subphenotype assignment using fresh plasma and were defined as successfully subphenotyped. Successful real-time subphenotyping increased from 59 for the first 100 enrolled participants (59% [95% CI 49-69]) to 82 for the last 100 enrolled participants (82% [73-89]), meeting the predefined feasibility threshold. Median time to subphenotype assignment from blood collection in the overall cohort and the successfully subphenotyped subgroup was 2·2 h (IQR 1·5-19·8) and 1·9 h (1·3-2·3) from the time of blood collection, respectively. The hyperinflammatory subphenotype was identified in 61 (29%) of 214 participants with ARDS and 29 (23%) of the 124 participants with severe AHRF. Clinical outcomes including mortality, organ support-free days and ventilator-free days were worse in patients with hyperinflammatory ARDS compared with those with hypoinflammatory ARDS. INTERPRETATION:Rapid real-time biological subphenotyping for ARDS and severe AHRF in a multisite US hospital network is feasible; and successful real-time subphenotyping both improved over the study time-course and was completed within 2·2 h from study blood collection. These results support the feasibility of real-time precision trials of therapies targeting biological subphenotypes in ARDS. FUNDING:COVID R&D Consortium, Allergan, Amgen, Takeda Pharmaceutical Company, Ingenus Pharmaceuticals, Implicit Bioscience, Johnson & Johnson, Pfizer, Roche-Genentech, Apotex, FAST Grant from Emergent Venture George Mason University, and The Grove Foundation. This work was supported by the US Defense Threat Reduction Agency (MCDC-2013-001). This project has been funded in whole or in part with Federal funds from the US Department of Health and Human Services; Administration for Strategic Preparedness and Response; and Biomedical Advanced Research and Development Authority (MCDC-2014-001).

Rationale: Our group recently identified a novel pediatric sepsis endotype associated with dysregulated STAT3 signaling, CD8+ T cell hyperactivation, increased mortality, and higher cumulative organ dysfunction scores. T cell activation can occur via bystander activation, which is associated with off-target tissue injury, or antigen-specific activation, which is associated with pathogen control. We hypothesized that CD8+ T cell hyperactivation within the dysregulated STAT3 signaling endotype would be driven by bystander activation, which could influence treatment strategies. Methods: To analyze T cell activation and T cell receptor (TCR) repertoire within this sepsis endotype, we performed 5’ single-cell RNA sequencing (scRNAseq) and TCR sequencing (TCRseq) on CD45+ lymphocytes from 9 patients with dysregulated STAT3 signaling and 3 age-matched healthy controls. We annotated cell subsets using ScType and performed differential expression analysis using FindMarkers. We assessed CD8+ T cell activation using gene set enrichment analysis (GSEA) and cell-specific ligand-receptor interactions using CellChat. We measured TCR diversity and clonal abundance using scRepertoire. Results: Compared to healthy controls, patients with sepsis have reduced effector CD8+ T cell and increased naïve CD8+ T cell populations (p<0.0001). Perforin and granzyme expression are increased in naïve and effector CD8+ T cells from patients with the dysregulated STAT3 signaling endotype (“STAT3 endotype” patients) compared to healthy controls (all p<0.0001), suggesting increased cytotoxic activity. GSEA of CD8+ T cell subsets revealed increased IFNγ production (NES +2.27 [naïve], +2.46 [effector], both p<0.0001) and cytokine signaling (NES +1.68 [naïve], NES +1.73 [effector], both p<0.01) in STAT3 endotype patients compared to healthy controls, consistent with increased T cell activation. Ligand-receptor interaction analysis demonstrated significant interactions between HLA class I molecules and CD8A in CD8+ T cells from STAT3 endotype patients compared to healthy controls (p<0.01, Figure 1A), suggesting increased TCR signaling. TCR repertoire analysis identified increased clonal diversity in STAT3 endotype patients compared to healthy controls (p<0.0001, Figure 1B) without evidence of clonal expansion (Figure 1C). Within T cell subsets, STAT3 endotype patients demonstrated increased TCR diversity in naïve CD8+ T cells and reduced TCR diversity in effector CD8+ T cells (Figure 1D). Conclusions: Through paired scRNAseq and TCRseq analysis, we identified CD8+ T cell hyperactivation and increased TCR clonal diversity in patients with the dysregulated STAT3 signaling endotype of pediatric sepsis. Polyclonal bystander activation of CD8+ T cells may be a reversible cause of organ failure within this sepsis endotype. Dysregulated STAT3 signaling is a candidate target for precision immunomodulation in pediatric sepsis.

Background Almost all large-scale trials of disease-modifying therapeutic agents in critical care have failed to show benefit for patients, which may be explained in part by the clinical and biological heterogeneity inherent in virtually all critical illness syndromes. Enrichment strategies have been developed to separate responders from non-responders and better target treatments. In patients with the acute respiratory distress syndrome, a critical illness syndrome involving severe lung inflammation, latent class analysis and other clustering approaches have led to the discovery of subgroups (phenotypes) that appear to respond differently to treatment based on retrospective analyses of published clinical trials and observational cohorts. The next step is to test these phenotypes in a prospective trial. Rapid, point-of-care analytical methods have now made such a trial possible. There is a need to advance treatment for patients with acute respiratory distress syndrome and other critical illness syndromes by incorporating a phenotype-based approach into prospective trial design. The hyperinflammatory and hypoinflammatory phenotypes, that have been identified in acute respiratory distress syndrome, will be the first to be included in such a trial, with scope for further phenotypes to be studied over time. Future work This Efficacy and Mechanism Evaluation report, through expert consensus, describes a new Phase II, multiarm, adaptive platform randomised controlled trial design that tests multiple pharmacological therapies in a population of patients with acute respiratory distress syndrome stratified by baseline inflammatory phenotype. This report also reviews issues to be considered in developing precision medicine trials in critical care, which are designed with newly developed clinical phenotypes in mind. This work has been used to develop the Precision medicine Adaptive Network platform Trial in Hypoxaemic acutE respiratory failuRe precision medicine trial in acute respiratory distress syndrome, which has been funded and will begin recruitment in June 2025. Limitations This report is the result of expert consensus review, rather than utilising strict review methodologies (e.g. Delphi consensus process). However, expert consensus has been found to generate similar results to consensus processes when a high degree of agreement is reached and > 70% agreement was reached for all included recommendations. Funding This article presents independent research funded by the (NIHR) Efficacy and Mechanism Evaluation programme as award number NIHR154493.

Recent advances in cytometry have enabled high-throughput data collection with multiple single-cell protein expression measurements. The significant biological and technical variance in cytometry has posed a formidable challenge during the gating process, especially for the initial pre-gates which deal with unpredictable events, such as debris and technical artifacts. To mitigate the labor-intensive manual gating process, we propose UNITO, a framework to rigorously identify the hierarchical cytometric subpopulations. UNITO transforms a cell-level classification task into an image-based segmentation problem. The framework is validated on three independent cohorts (two mass cytometry and one flow cytometry datasets). We compare its results with previous automated methods using the consensus of at least four experienced immunologists. UNITO outperforms existing methods and deviates from human consensus by no more than any individual does. UNITO can reproduce a similar contour compared to manual gating for post-hoc inspection, and it also allows parallelization of samples for faster processing.

Red blood cells (RBCs), traditionally recognized for their role in transporting oxygen, play a pivotal role in the body's immune response by expressing TLR9 and scavenging excess host cell-free DNA. DNA capture by RBCs leads to accelerated RBC clearance and triggers inflammation. Whether RBCs can also acquire microbial DNA during infections is unknown. Murine RBCs acquire microbial DNA in vitro, and bacterial DNA-induced (bDNA-induced) macrophage activation was augmented by WT, but not Tlr9-deleted, RBCs. In a mouse model of polymicrobial sepsis, RBC-bound bDNA was elevated in WT mice but not in erythroid Tlr9-deleted mice. Plasma cytokine analysis in these mice revealed distinct sepsis clusters characterized by persistent hypothermia and hyperinflammation in the most severely affected mice. RBC Tlr9 deletion attenuated plasma and tissue IL-6 production in the most severely affected group. Parallel findings in humans confirmed that RBCs from patients with sepsis harbored more bDNA than did RBCs from healthy individuals. Further analysis through 16S sequencing of RBCbound DNA illustrated distinct microbial communities, with RBC-bound DNA composition correlating with plasma IL-6 in patients with sepsis. Collectively, these findings unveil RBCs as overlooked reservoirs and couriers of microbial DNA, capable of influencing host inflammatory responses in sepsis.

INTRODUCTION:Few artificial intelligence (AI) clinical decision support systems (CDSSs) are ever evaluated in practice. Although some signal of clinical effectiveness may be needed to justify AI deployment and testing, such data are typically unavailable in early-stage research. This conundrum is especially relevant in the intensive care unit (ICU), where conditions like sepsis and acute respiratory distress syndrome (ARDS) require high-stakes decisions. Our group developed the AI ventilator assistant (AVA), a novel AI CDSS for patients with sepsis ARDS receiving invasive mechanical ventilation. But the promising results of predictive performance estimates are not sufficient to assess AVA's clinical safety and appropriateness prior to future evaluation and deployment. Therefore, we propose a Clinician Turing Test as a novel validation approach to determine whether clinicians can distinguish AVA-generated treatment recommendations from those enacted by real human clinicians. If AVA's recommendations are consistently indistinguishable from those of real clinicians, thereby 'passing' this Turing test, this would provide a strong preclinical signal of safety and appropriateness. METHODS AND ANALYSIS:This multisite, randomised, electronic, vignette-based Phase 1b study will use a Clinician Turing Test design. We aim to recruit 350 critical care clinicians, including physicians and advanced practice providers from six US hospitals. Participants will review nine clinical vignettes of patients with sepsis and ARDS derived from the Molecular Epidemiology of Severe Sepsis in the ICU cohort and an associated profile of a suggested treatment plan. For each participant-vignette combination, the source of the treatment profile will be randomly assigned (AI-generated by AVA vs the actually enacted treatment from real human clinicians) in a 1:1 allocation. The primary endpoint is the participants' accuracy in identifying whether a treatment profile was AI-generated or human-generated, assessed using equivalence testing through a mixed-effects logistic regression model with random effects for participants and vignettes. Secondarily, a fitted binary classifier will assess discrimination ability using the C-statistic. Secondary endpoints include clinicians' perceptions of the safety and appropriateness of the treatment profiles, confidence in distinguishing AI-generated and human-generated recommendations, interest in AI CDSSs for sepsis and ventilator management and the time to complete the survey. This novel Phase 1b design provides preliminary but essential information about an AI CDSS's clinical appropriateness without the risk or cost of actual deployment, thereby informing decisions about future clinical implementation and evaluation in real clinical environments. ETHICS AND DISSEMINATION:This protocol was approved by the Institutional Review Board of the University of Pennsylvania (Protocol #858201). Results are expected in 2026 and will be submitted for publication in peer-reviewed journals and presented at scientific conferences. TRIAL REGISTRATION NUMBER:NCT07025096.

Sepsis is the leading cause of pediatric in-hospital mortality worldwide, driven in part by immune dysregulation. As sepsis biology is marked by immune heterogeneity, precision medicine approaches to identify actionable phenotypes are crucial to improving patient outcomes. Among three molecular subphenotypes we previously identified in children with sepsis, Group C patients have poor clinical outcomes and a unique immune profile involving dysregulated STAT3 signaling. In this analysis, we sought to evaluate cytokine production in CD8+ T cells from pediatric sepsis patients across molecular subphenotypes. We measured T cell cytokine production by flow cytometry in pediatric sepsis samples (n = 17) after 24-hour stimulation with αCD3/αCD28. We calculated absolute and relative change in geometric mean fluorescent intensity from baseline for both conditions for six cytokines: IL-2, IL-13, IL-17, IL-21, TNF-α, and IFN-γ. Samples were acquired via a Cytek Aurora spectral flow cytometer and analyzed in FlowJo and Rstudio. We compared cytokine expression across sepsis subphenotypes by ANOVA. Baseline, unstimulated cytokine production was minimal in all groups. In response to αCD3/αCD28 stimulation, CD8+ T cells from Group C patients demonstrated significantly increased IL-2 production (p = 0.012) compared with Groups A and B, and a trend toward sustained TNF-α production (p = 0.11). Conversely, Group C showed an exaggerated reduction in IL-17 production in response to stimulation (p = 0.03). CD4+ T cells from Group C patients similarly demonstrated significantly increased IL-2 production (p = 0.003) after stimulation compared with Groups A and B, and a similar trend toward sustained TNF-α production (p = 0.11). IFN-γ, IL-13, and IL-21 expression increased with stimulation in all groups but did not vary by subphenotype. Group C patients demonstrate increased pro-inflammatory cytokine production in CD8+ T cells following αCD3/αCD28 stimulation compared with Groups A and B. This dysregulated response to T cell stimulation in the most severe molecular sepsis subphenotype is a potentially reversible cause of organ dysfunction in pediatric patients with sepsis.

Sepsis is a leading cause of morbidity and mortality in critically ill children, yet heterogeneity in immune responses complicates the development of targeted therapies. Although immune dysregulation is associated with poor outcomes in sepsis, it remains unclear which host immune factors contribute causally to sepsis morbidity and mortality. To address this gap, we integrated deep immune phenotyping, plasma proteomics, single-cell transcriptomics, and phosphoflow cytometry in a prospective cohort of 88 critically ill children to elucidate the immunologic mechanisms which underly disease heterogeneity. Unsupervised clustering of plasma cytokines identified three immunologic subgroups, including a high-severity group ("Group C") characterized by marked hypercytokinemia, driven primarily by IL-6 and IFN-γ. Group C exhibited distinct alterations in immune cell frequency and activation status, along with a strong association between hyperinflammatory signaling and lymphocyte dysfunction. Single-cell RNA sequencing revealed transcriptional signatures of T cell activation and metabolic stress, and identified widespread suppression of a lymphoid protective gene program across CD8⁺ T cell subsets. In the setting of increased expression of activation markers, T cell receptor repertoire analysis revealed no dominant clonotypes, consistent with a bystander mechanism of T cell activation. Using phosphoflow cytometry, we demonstrated baseline hyperactivation of STAT1 and STAT3 in CD8⁺ T cells from patients in Group C, and these cells failed to respond to aCD3/aCD28 stimulation. Together, these findings define IL-6/IFN-γ-driven T-cell dysfunction as a distinct endotype of immune dysregulation in pediatric sepsis, highlighting the JAK/STAT axis as a potential future target for immunomodulatory therapy.

Rationale: Damage-associated molecular patterns (DAMPs), endogenous immunostimulatory molecules, are elevated and pathogenic in sepsis, the dysregulated host response to infection. Among DAMPs, extracellular nucleic acids play a key role in triggering innate immune responses, and extracellular RNA is increasingly recognized as a DAMP. We hypothesize that extracellular mitochondrial RNA (mtRNA) functions as a DAMP and that extracellular mtRNA is elevated in sepsis. Methods: We used in vitro assays, a murine model of sepsis and plasma from patients with sepsis to determine if mtRNA triggers inflammation and is abundant in sepsis. For in vitro studies, mtRNA was extracted from wild-type mouse livers and Raw 264.7 cells were treated with 0.5µg, 1µg or 1.5µg/mL of mtRNA for 24 hours. Cytokines were measured by ELISA. Plasma mtRNA was measured in mice subjected to the cecal slurry model of sepsis. Whole blood was collected at 24 hours and spun at 1500g for 10 minutes. RNA was extracted from plasma and RTqPCR for the mitochondrial ribosomal 12S subunit was performed (mtRNR1). For mtRNA measurements in humans, plasma was obtained from sepsis patients on the day of admission to the ICU and healthy controls. Whole blood was spun at 3000g on collection and the plasma was stored at -80°C. RNA was extracted from the plasma and RTqPCR for the mitochondrial ribosomal 12S (mtRNR1) and 16S (mtRNR2) subunits was performed. Results: In vitro, mtRNA induced an inflammatory response in macrophages as measured by TNF⍺ release at 24 hours (p=0.02, 0.0003 and <0.0001 for 0.5µg, 1µg or 1.5µg/mL mtRNA v control ). In vivo, plasma levels of mtRNA were increased in murine sepsis (n=19) compared to controls (n=14) at 24 hours (p = 0.02). We also found that levels of mtRNA were elevated in the plasma of sepsis patients (n=15) on the day of ICU admission compared to healthy donors (n=8) (p<0.0001). Conclusions: mtRNA alone is sufficient to induce an inflammatory response in vitro. In both a murine model of sepsis and human sepsis we found that levels of mtRNA are elevated in plasma. These data suggest that mtRNA may function as a novel DAMP in the pathogenesis of sepsis. Further studies are needed to elucidate the mechanism of release from cells and the downstream pathway that results in inflammatory activation. Future studies will also be needed to determine whether mtRNA is sufficient to cause a sepsis phenotype in vivo.

Interferon-related genes are involved in antiviral responses, inflammation, and immunity, which are closely related to sepsis-associated acute respiratory distress syndrome (ARDS). We analyzed 1972 participants with genotype data and 681 participants with gene expression data from the Molecular Epidemiology of ARDS (MEARDS), the Molecular Epidemiology of Sepsis in the ICU (MESSI), and the Molecular Diagnosis and Risk Stratification of Sepsis (MARS) cohorts in a three-step study focusing on sepsis-associated ARDS and sepsis-only controls. First, we identified and validated interferon-related genes associated with sepsis-associated ARDS risk using genetically regulated gene expression (GReX). Second, we examined the association of the confirmed gene (interferon regulatory factor 1, IRF1) with ARDS risk and survival and conducted a mediation analysis. Through discovery and validation, we found that the GReX of IRF1 was associated with ARDS risk (odds ratio [OR MEARDS] = 0.84, P = 0.008; OR MESSI = 0.83, P = 0.034). Furthermore, individual-level measured IRF1 expression was associated with reduced ARDS risk (OR = 0.58, P = 8.67 × 10 -4), and improved overall survival in ARDS patients (hazard ratio [HR 28-day] = 0.49, P = 0.009) and sepsis patients (HR 28-day = 0.76, P = 0.008). Mediation analysis revealed that IRF1 may enhance immune function by regulating the major histocompatibility complex, including HLA-F, which mediated more than 70% of protective effects of IRF1 on ARDS. The findings were validated by in vitro biological experiments including time-series infection dynamics, overexpression, knockout, and chromatin immunoprecipitation sequencing. Early prophylactic interventions to activate IRF1 in sepsis patients, thereby regulating HLA-F, may reduce the risk of ARDS and mortality, especially in severely ill patients.

Critical care syndromes such as sepsis, acute respiratory distress syndrome (ARDS) and trauma continue to have unacceptably high morbidity and mortality, with progress limited by the inherent heterogeneity within syndromic illnesses. Although numerous immune endotypes have been proposed for sepsis and critical care, the similarities and differences between these endotypes remain unclear, hindering clinical translation. The SUBSPACE consortium is an international consortium that aims to advance precision medicine in critical care through the sharing of transcriptomic data. Here, evaluating the overlap of existing immune endotypes in sepsis across >7,074 samples from 37 independent cohorts, we developed cell-type-specific gene expression signatures to quantify dysregulation within immune compartments. Myeloid and lymphoid dysregulation were associated with disease severity and mortality across all cohorts. Importantly, this dysregulation was also observed in patients with ARDS, trauma and burns, suggesting a conserved mechanism across various critical illness syndromes. Moreover, analysis of randomized controlled trial data revealed that myeloid and lymphoid dysregulation are associated with differential mortality in patients treated with anakinra in the SAVE-MORE trial (n = 452) and corticosteroids in the VICTAS (n = 89) and VANISH (n = 117) trials, underscoring their prognostic and therapeutic implications. In conclusion, our proposed immunology-based framework for quantifying cellular compartment dysregulation offers a potentially valuable tool for understanding immune dysregulation in critical illness with prognostic and therapeutic significance.