Dysregulated STAT3 signaling and T cell immunometabolic dysfunction define a targetable, high mortality subphenotype of critically ill children.

Sepsis is the leading cause of death of hospitalized children worldwide. Despite the established link between immune dysregulation and mortality in pediatric sepsis, it remains unclear which host immune factors contribute causally to adverse sepsis outcomes. Identifying modifiable pathobiology is an essential first step to successful translation of biologic insights into precision therapeutics. We designed a prospective, longitudinal cohort study of 88 critically ill pediatric patients with multiple organ dysfunction syndrome (MODS), including patients with and without sepsis, to define subphenotypes associated with targetable mechanisms of immune dysregulation. We first assessed plasma proteomic profiles and identified shared features of immune dysregulation in MODS patients with and without sepsis. We then employed consensus clustering to define three subphenotypes based on protein expression at disease onset and identified a strong association between subphenotype and clinical outcome. We next identified differences in immune cell frequency and activation state by MODS subphenotype and determined the association between hyperinflammatory pathway activation and cellular immunophenotype. Using single cell transcriptomics, we demonstrated STAT3 hyperactivation in lymphocytes from the sickest MODS subgroup and then identified an association between STAT3 hyperactivation and T cell immunometabolic dysregulation. Finally, we compared proteomics findings between patients with MODS and patients with inborn errors of immunity that amplify cytokine signaling pathways to further assess the impact of STAT3 hyperactivation in the most severe patients with MODS. Overall, these results identify a potentially pathologic and targetable role for STAT3 hyperactivation in a subset of pediatric patients with MODS who have high severity of illness and poor prognosis.

Vascular endothelial-derived SPARCL1 exacerbates viral pneumonia through pro-inflammatory macrophage activation.

Inflammation induced by lung infection is a double-edged sword, moderating both anti-viral and immune pathogenesis effects; the mechanism of the latter is not fully understood. Previous studies suggest the vasculature is involved in tissue injury. Here, we report that expression of Sparcl1, a secreted matricellular protein, is upregulated in pulmonary capillary endothelial cells (EC) during influenza-induced lung injury. Endothelial overexpression of SPARCL1 promotes detrimental lung inflammation, with SPARCL1 inducing 'M1-like' macrophages and related pro-inflammatory cytokines, while SPARCL1 deletion alleviates these effects. Mechanistically, SPARCL1 functions through TLR4 on macrophages in vitro, while TLR4 inhibition in vivo ameliorates excessive inflammation caused by endothelial Sparcl1 overexpression. Finally, SPARCL1 expression is increased in lung ECs from COVID-19 patients when compared with healthy donors, while fatal COVID-19 correlates with higher circulating SPARCL1 protein levels in the plasma. Our results thus implicate SPARCL1 as a potential prognosis biomarker for deadly COVID-19 pneumonia and as a therapeutic target for taming hyperinflammation in pneumonia.

Automated Cytometric Gating with Human-Level Performance Using Bivariate Segmentation.

Recent advances in cytometry technology have enabled high-throughput data collection with multiple single-cell protein expression measurements. The significant biological and technical variance between samples in cytometry has long posed a formidable challenge during the gating process, especially for the initial gates which deal with unpredictable events, such as debris and technical artifacts. Even with the same experimental machine and protocol, the target population, as well as the cell population that needs to be excluded, may vary across different measurements. To address this challenge and mitigate the labor-intensive manual gating process, we propose a deep learning framework UNITO to rigorously identify the hierarchical cytometric subpopulations. The UNITO framework transformed a cell-level classification task into an image-based semantic segmentation problem. For reproducibility purposes, the framework was applied to three independent cohorts and successfully detected initial gates that were required to identify single cellular events as well as subsequent cell gates. We validated the UNITO framework by comparing its results with previous automated methods and the consensus of at least four experienced immunologists. UNITO outperformed existing automated methods and differed from human consensus by no more than each individual human. Most critically, UNITO framework functions as a fully automated pipeline after training and does not require human hints or prior knowledge. Unlike existing multi-channel classification or clustering pipelines, UNITO can reproduce a similar contour compared to manual gating for each intermediate gating to achieve better interpretability and provide post hoc visual inspection. Beyond acting as a pioneering framework that uses image segmentation to do auto-gating, UNITO gives a fast and interpretable way to assign the cell subtype membership, and the speed of UNITO will not be impacted by the number of cells from each sample. The pre-gating and gating inference takes approximately 2 minutes for each sample using our pre-defined 9 gates system, and it can also adapt to any sequential prediction with different configurations.

From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations For Developing Precision Medicine in ICU.

Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. In order to impact clinical care, identified subpopulations must do more than differentiate prognosis. They must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Association between Age and Mortality in Pediatric and Adult Acute Respiratory Distress Syndrome.

Rationale: The epidemiology, management, and outcomes of acute respiratory distress syndrome (ARDS) differ between children and adults, with lower mortality rates in children despite comparable severity of hypoxemia. However, the relationship between age and mortality is unclear.Objective: We aimed to define the association between age and mortality in ARDS, hypothesizing that it would be nonlinear.Methods: We performed a retrospective cohort study using data from two pediatric ARDS observational cohorts (n = 1,236), multiple adult ARDS trials (n = 5,547), and an adult observational ARDS cohort (n = 1,079). We aligned all datasets to meet Berlin criteria. We performed unadjusted and adjusted logistic regression using fractional polynomials to assess the potentially nonlinear relationship between age and 90-day mortality, adjusting for sex, PaO2/FiO2, immunosuppressed status, year of study, and observational versus randomized controlled trial, treating each individual study as a fixed effect.Measurements and Main Results: There were 7,862 subjects with median ages of 4 years in the pediatric cohorts, 52 years in the adult trials, and 61 years in the adult observational cohort. Most subjects (43%) had moderate ARDS by Berlin criteria. Ninety-day mortality was 19% in the pediatric cohorts, 33% in the adult trials, and 67% in the adult observational cohort. We found a nonlinear relationship between age and mortality, with mortality risk increasing at an accelerating rate between 11 and 65 years of age, after which mortality risk increased more slowly.Conclusions: There was a nonlinear relationship between age and mortality in pediatric and adult ARDS.

Deep phenotyping of the lipidomic response in COVID-19 and non-COVID-19 sepsis.

BACKGROUND: Lipids may influence cellular penetrance by viral pathogens and the immune response that they evoke. We deeply phenotyped the lipidomic response to SARs-CoV-2 and compared that with infection with other pathogens in patients admitted with acute respiratory distress syndrome to an intensive care unit (ICU). METHODS: Mass spectrometry was used to characterise lipids and relate them to proteins, peripheral cell immunotypes and disease severity. RESULTS: Circulating phospholipases (sPLA2, cPLA2 (PLA2G4A) and PLA2G2D) were elevated on admission in all ICU groups. Cyclooxygenase, lipoxygenase and epoxygenase products of arachidonic acid (AA) were elevated in all ICU groups compared with controls. sPLA2 predicted severity in COVID-19 and correlated with TxA2, LTE4 and the isoprostane, iPF2α-III, while PLA2G2D correlated with LTE4. The elevation in PGD2, like PGI2 and 12-HETE, exhibited relative specificity for COVID-19 and correlated with sPLA2 and the interleukin-13 receptor to drive lymphopenia, a marker of disease severity. Pro-inflammatory eicosanoids remained correlated with severity in COVID-19 28 days after admission. Amongst non-COVID ICU patients, elevations in 5- and 15-HETE and 9- and 13-HODE reflected viral rather than bacterial disease. Linoleic acid (LA) binds directly to SARS-CoV-2 and both LA and its di-HOME products reflected disease severity in COVID-19. In healthy marines, these lipids rose with seroconversion. Eicosanoids linked variably to the peripheral cellular immune response. PGE2, TxA2 and LTE4 correlated with T cell activation, as did PGD2 with non-B non-T cell activation. In COVID-19, LPS stimulated peripheral blood mononuclear cell PGF2α correlated with memory T cells, dendritic and NK cells while LA and DiHOMEs correlated with exhausted T cells. Three high abundance lipids - ChoE 18:3, LPC-O-16:0 and PC-O-30:0 - were altered specifically in COVID. LPC-O-16:0 was strongly correlated with T helper follicular cell activation and all three negatively correlated with multi-omic inflammatory pathways and disease severity. CONCLUSIONS: A broad based lipidomic storm is a predictor of poor prognosis in ARDS. Alterations in sPLA2, PGD2 and 12-HETE and the high abundance lipids, ChoE 18:3, LPC-O-16:0 and PC-O-30:0 exhibit relative specificity for COVID-19 amongst such patients and correlate with the inflammatory response to link to disease severity.

Tracking gut microbiome and bloodstream infection in critically ill adults.

BACKGROUND: The gut microbiome is believed to contribute to bloodstream infection (BSI) via translocation of dominant gut bacteria in vulnerable patient populations. However, conclusively linking gut and blood organisms requires stringent approaches to establish strain-level identity. METHODS: We enrolled a convenience cohort of critically ill patients and investigated 86 bloodstream infection episodes that occurred in 57 patients. Shotgun metagenomic sequencing was used to define constituents of their gut microbiomes, and whole genome sequencing and assembly was done on 23 unique bloodstream isolates that were available from 21 patients. Whole genome sequences were downloaded from public databases and used to establish sequence-identity distribution and define thresholds for unrelated genomes of BSI species. Gut microbiome reads were then aligned to whole genome sequences of the cognate bloodstream isolate and unrelated database isolates to assess identity. RESULTS: Gut microbiome constituents matching the bloodstream infection species were present in half of BSI episodes, and represented >30% relative abundance of gut sequences in 10% of episodes. Among the 23 unique bloodstream organisms that were available for whole genome sequencing, 14 were present in gut at the species level. Sequence alignment applying defined thresholds for identity revealed that 6 met criteria for identical strains in blood and gut, but 8 did not. Sequence identity between BSI isolates and gut microbiome reads was more likely when the species was present at higher relative abundance in gut. CONCLUSION: In assessing potential gut source for BSI, stringent sequence-based approaches are essential to determine if organisms responsible for BSI are identical to those in gut: of 14 evaluable patients in which the same species was present in both sites, they were identical in 6/14, but were non-identical in 8/14 and thus inconsistent with gut source. This report demonstrates application of sequencing as a key tool to investigate infection tracking within patients.

The Penn Medicine COVID-19 Therapeutics Committee-Reflections on a Model for Rapid Evidence Review and Dynamic Practice Recommendations During a Public Health Emergency.

The Penn Medicine COVID-19 Therapeutics Committee-an interspecialty, clinician-pharmacist, and specialist-front line primary care collaboration-has served as a forum for rapid evidence review and the production of dynamic practice recommendations during the 3-year coronavirus disease 2019 public health emergency. We describe the process by which the committee went about its work and how it navigated specific challenging scenarios. Our target audiences are clinicians, hospital leaders, public health officials, and researchers invested in preparedness for inevitable future threats. Our objectives are to discuss the logistics and challenges of forming an effective committee, undertaking a rapid evidence review process, aligning evidence-based guidelines with operational realities, and iteratively revising recommendations in response to changing pandemic data. We specifically discuss the arc of evidence for corticosteroids; the noble beginnings and dangerous misinformation end of hydroxychloroquine and ivermectin; monoclonal antibodies and emerging viral variants; and patient screening and safety processes for tocilizumab, baricitinib, and nirmatrelvir-ritonavir.

Exposure to ambient air pollutants and acute respiratory distress syndrome risk in sepsis.

PURPOSE: Exposures to ambient air pollutants may prime the lung enhancing risk of acute respiratory distress syndrome (ARDS) in sepsis. Our objective was to determine the association of short-, medium-, and long-term pollutant exposures and ARDS risk in critically ill sepsis patients. METHODS: We analyzed a prospective cohort of 1858 critically ill patients with sepsis, and estimated short- (3 days), medium- (6 weeks), and long- (5 years) term exposures to ozone, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 µm (PM2.5), and PM < 10 µm (PM10) using weighted averages of daily levels from monitors within 50 km of subjects' residences. Subjects were followed for 6 days for ARDS by the Berlin Criteria. The association between each pollutant and ARDS was determined using multivariable logistic regression adjusting for preselected confounders. In 764 subjects, we measured plasma concentrations of inflammatory proteins at presentation and tested for an association between pollutant exposure and protein concentration via linear regression. RESULTS: ARDS developed in 754 (41%) subjects. Short- and long-term exposures to SO2, NO2, and PM2.5 were associated with ARDS risk (SO2: odds ratio (OR) for the comparison of the 75-25th long-term exposure percentile 1.43 (95% confidence interval (CI) 1.16, 1.77); p < 0.01; NO2: 1.36 (1.06, 1.74); p = 0.04, PM2.5: 1.21 (1.04, 1.41); p = 0.03). Long-term exposures to these three pollutants were also associated with plasma interleukin-1 receptor antagonist and soluble tumor necrosis factor receptor-1 concentrations. CONCLUSION: Short and long-term exposures to ambient SO2, PM2.5, and NO2 are associated with increased ARDS risk in sepsis, representing potentially modifiable environmental risk factors for sepsis-associated ARDS.

Patients' Perspectives on Life and Recovery 1 Year After COVID-19 Hospitalization.

BACKGROUND: Many patients hospitalized for COVID-19 experience prolonged symptoms months after discharge. Little is known abou t patients' personal experiences recovering from COVID-19 in the United States (US), where medically underserved populations are at particular risk of adverse outcomes. OBJECTIVE: To explore patients' perspectives on the impact of COVID-19 hospitalization and barriers to and facilitators of recovery 1 year after hospital discharge in a predominantly Black American study population with high neighborhood-level socioeconomic disadvantage. DESIGN: Qualitative study utilizing individual, semi-structured interviews. PARTICIPANTS: Adult patients hospitalized for COVID-19 approximately 1 year after discharge home who were engaged in a COVID-19 longitudinal cohort study. APPROACH: The interview guide was developed and piloted by a multidisciplinary team. Interviews were audio-recorded and transcribed. Data were coded and organized into discrete themes using qualitative content analysis with constant comparison techniques. KEY RESULTS: Of 24 participants, 17 (71%) self-identified as Black, and 13 (54%) resided in neighborhoods with the most severe neighborhood-level socioeconomic disadvantage. One year after discharge, participants described persistent deficits in physical, cognitive, or psychological health that impacted their current lives. Repercussions included financial suffering and a loss of identity. Participants reported that clinicians often focused on physical health over cognitive and psychological health, an emphasis that posed a barrier to recovering holistically. Facilitators of recovery included robust financial or social support systems and personal agency in health maintenance. Spirituality and gratitude were common coping mechanisms. CONCLUSIONS: Persistent health deficits after COVID-19 resulted in downstream consequences in participants' lives. Though participants received adequate care to address physical needs, many described persistent unmet cognitive and psychological needs. A more comprehensive understanding of barriers and facilitators for COVID-19 recovery, contextualized by specific healthcare and socioeconomic needs related to socioeconomic disadvantage, is needed to better inform intervention delivery to patients that experience long-term sequelae of COVID-19 hospitalization.

ESICM guidelines on acute respiratory distress syndrome: definition, phenotyping and respiratory support strategies.

The aim of these guidelines is to update the 2017 clinical practice guideline (CPG) of the European Society of Intensive Care Medicine (ESICM). The scope of this CPG is limited to adult patients and to non-pharmacological respiratory support strategies across different aspects of acute respiratory distress syndrome (ARDS), including ARDS due to coronavirus disease 2019 (COVID-19). These guidelines were formulated by an international panel of clinical experts, one methodologist and patients' representatives on behalf of the ESICM. The review was conducted in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement recommendations. We followed the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of evidence and grade recommendations and the quality of reporting of each study based on the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) network guidelines. The CPG addressed 21 questions and formulates 21 recommendations on the following domains: (1) definition; (2) phenotyping, and respiratory support strategies including (3) high-flow nasal cannula oxygen (HFNO); (4) non-invasive ventilation (NIV); (5) tidal volume setting; (6) positive end-expiratory pressure (PEEP) and recruitment maneuvers (RM); (7) prone positioning; (8) neuromuscular blockade, and (9) extracorporeal life support (ECLS). In addition, the CPG includes expert opinion on clinical practice and identifies the areas of future research.

Vascular Endothelial-derived SPARCL1 Exacerbates Viral Pneumonia Through Pro-Inflammatory Macrophage Activation.

Inflammation upon infectious lung injury is a double-edged sword: while tissue-infiltrating immune cells and cytokines are necessary to control infection, these same factors often aggravate injury. Full appreciation of both the sources and targets of inflammatory mediators is required to facilitate strategies to maintain antimicrobial effects while minimizing off-target epithelial and endothelial damage. Recognizing that the vasculature is centrally involved in tissue responses to injury and infection, we observed that pulmonary capillary endothelial cells (ECs) exhibit dramatic transcriptomic changes upon influenza injury punctuated by profound upregulation of Sparcl1 . Endothelial deletion and overexpression of SPARCL1 implicated this secreted matricellular protein in driving key pathophysiologic symptoms of pneumonia, which we demonstrate result from its effects on macrophage polarization. SPARCL1 induces a shift to a pro-inflammatory "M1-like" phenotype (CD86 + CD206 - ), thereby increasing associated cytokine levels. Mechanistically, SPARCL1 acts directly on macrophages in vitro to induce the pro-inflammatory phenotype via activation of TLR4, and TLR4 inhibition in vivo ameliorates inflammatory exacerbations caused by endothelial Sparcl1 overexpression. Finally, we confirmed significant elevation of SPARCL1 in COVID-19 lung ECs in comparison with those from healthy donors. Survival analysis demonstrated that patients with fatal COVID-19 had higher levels of circulating SPARCL1 protein compared to those who recovered, indicating the potential of SPARCL1 as a biomarker for prognosis of pneumonia and suggesting that personalized medicine approaches might be harnessed to block SPARCL1 and improve outcomes in high-expressing patients.

WNT9A Affects Late-Onset Acute Respiratory Distress Syndrome and 28-Day Survival: Evidence from a Three-Step Multiomics Study.

Late-onset (more than 48 h after ICU admission) acute respiratory distress syndrome (ARDS) is associated with shorter survival time and higher mortality; however, the underlying molecular targets remain unclear. As the WNT gene family is known to drive inflammation, immunity, and tissue fibrosis, all of which are closely related to the pathogenesis and prognosis of ARDS, we aim to investigate the associations of the WNT family with late-onset ARDS and 28-day survival. Genetic (n = 380), epigenetic (n = 185), transcriptional (n = 160), and protein (n = 300) data of patients with ARDS were extracted from the MEARDS (Molecular Epidemiology of ARDS) cohort. We used sure independence screening to identify late onset-related genetic biomarkers and constructed a genetic score on the basis of eight SNPs, which was associated with risk for late-onset ARDS (odds ratio [OR], 2.72; P = 3.81 × 10-14) and survival (hazard ratio [HR], 1.28; P = 0.008). The associations were further externally validated in the iSPAAR (Identification of SNPs Predisposing to Altered Acute Lung Injury Risk) (ORlate onset, 2.49 [P = 0.006]; HRsurvival, 1.87 [P = 0.045]) and MESSI (Molecular Epidemiology of Severe Sepsis in the ICU) (ORlate onset, 4.12 [P = 0.026]; HRsurvival, 1.45 [P = 0.036]) cohorts. Furthermore, we functionally interrogated the six mapped genes of eight SNPs in the multiomics data and noted associations of WNT9A (WNT family member 9A) in epigenetic (ORlate onset, 2.95 [P = 9.91 × 10-4]; HRsurvival, 1.53 [P = 0.011]) and protein (ORlate onset, 1.42 [P = 0.035]; HRsurvival, 1.38 [P = 0.011]) data. The mediation analysis indicated that the effects of WNT9A on ARDS survival were mediated by late onset (HRindirect, 1.12 [P = 0.014] for genetic data; HRindirect, 1.05 [P = 0.030] for protein data). The essential roles of WNT9A in immunity and fibrosis may explain the different trajectories of recovery and dysfunction between early- and late-onset ARDS, providing clues for ARDS treatment.

Interrogating the sepsis host immune response using cytomics.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .