Mass cytometry reveals a conserved immune trajectory of recovery in hospitalized COVID-19 patients.

While studies have elucidated many pathophysiological elements of COVID-19, little is known about immunological changes during COVID-19 resolution. We analyzed immune cells and phosphorylated signaling states at single-cell resolution from longitudinal blood samples of patients hospitalized with COVID-19, pneumonia and/or sepsis, and healthy individuals by mass cytometry. COVID-19 patients showed distinct immune compositions and an early, coordinated, and elevated immune cell signaling profile associated with early hospital discharge. Intra-patient longitudinal analysis revealed changes in myeloid and T cell frequencies and a reduction in immune cell signaling across cell types that accompanied disease resolution and discharge. These changes, together with increases in regulatory T cells and reduced signaling in basophils, also accompanied recovery from respiratory failure and were associated with better outcomes at time of admission. Therefore, although patients have heterogeneous immunological baselines and highly variable disease courses, a core immunological trajectory exists that defines recovery from severe SARS-CoV-2 infection.

Global absence and targeting of protective immune states in severe COVID-19.

Although infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has pleiotropic and systemic effects in some individuals1-3, many others experience milder symptoms. Here, to gain a more comprehensive understanding of the distinction between severe and mild phenotypes in the pathology of coronavirus disease 2019 (COVID-19) and its origins, we performed a whole-blood-preserving single-cell analysis protocol to integrate contributions from all major immune cell types of the blood-including neutrophils, monocytes, platelets, lymphocytes and the contents of the serum. Patients with mild COVID-19 exhibit a coordinated pattern of expression of interferon-stimulated genes (ISGs)3 across every cell population, whereas these ISG-expressing cells are systemically absent in patients with severe disease. Paradoxically, individuals with severe COVID-19 produce very high titres of anti-SARS-CoV-2 antibodies and have a lower viral load compared to individuals with mild disease. Examination of the serum from patients with severe COVID-19 shows that these patients uniquely produce antibodies that functionally block the production of the ISG-expressing cells associated with mild disease, by activating conserved signalling circuits that dampen cellular responses to interferons. Overzealous antibody responses pit the immune system against itself in many patients with COVID-19, and perhaps also in individuals with other viral infections. Our findings reveal potential targets for immunotherapies in patients with severe COVID-19 to re-engage viral defence.

Host and Microbe Blood Metagenomics Reveals Key Pathways Characterizing Critical Illness Phenotypes.

Rationale: Two molecular phenotypes of sepsis and acute respiratory distress syndrome, termed hyperinflammatory and hypoinflammatory, have been consistently identified by latent class analysis in numerous cohorts, with widely divergent clinical outcomes and differential responses to some treatments; however, the key biological differences between these phenotypes remain poorly understood.Objectives: We used host and microbe metagenomic sequencing data from blood to deepen our understanding of biological differences between latent class analysis-derived phenotypes and to assess concordance between the latent class analysis-derived phenotypes and phenotypes reported by other investigative groups (e.g., Sepsis Response Signature [SRS1-2], molecular diagnosis and risk stratification of sepsis [MARS1-4], reactive and uninflamed).Methods: We analyzed data from 113 patients with hypoinflammatory sepsis and 76 patients with hyperinflammatory sepsis enrolled in a two-hospital prospective cohort study. Molecular phenotypes had been previously assigned using latent class analysis.Measurements and Main Results: The hyperinflammatory and hypoinflammatory phenotypes of sepsis had distinct gene expression signatures, with 5,755 genes (31%) differentially expressed. The hyperinflammatory phenotype was associated with elevated expression of innate immune response genes, whereas the hypoinflammatory phenotype was associated with elevated expression of adaptive immune response genes and, notably, T cell response genes. Plasma metagenomic analysis identified differences in prevalence of bacteremia, bacterial DNA abundance, and composition between the phenotypes, with an increased presence and abundance of Enterobacteriaceae in the hyperinflammatory phenotype. Significant overlap was observed between these phenotypes and previously identified transcriptional subtypes of acute respiratory distress syndrome (reactive and uninflamed) and sepsis (SRS1-2). Analysis of data from the VANISH trial indicated that corticosteroids might have a detrimental effect in patients with the hypoinflammatory phenotype.Conclusions: The hyperinflammatory and hypoinflammatory phenotypes have distinct transcriptional and metagenomic features that could be leveraged for precision treatment strategies.

Rapidly improving ARDS differs clinically and biologically from persistent ARDS.

BACKGROUND: Rapidly improving acute respiratory distress syndrome (RIARDS) is an increasingly appreciated subgroup of ARDS in which hypoxemia improves within 24 h after initiation of mechanical ventilation. Detailed clinical and biological features of RIARDS have not been clearly defined, and it is unknown whether RIARDS is associated with the hypoinflammatory or hyperinflammatory phenotype of ARDS. The purpose of this study was to define the clinical and biological features of RIARDS and its association with inflammatory subphenotypes. METHODS: We analyzed data from 215 patients who met Berlin criteria for ARDS (endotracheally intubated) and were enrolled in a prospective observational cohort conducted at two sites, one tertiary care center and one urban safety net hospital. RIARDS was defined according to previous studies as improvement of hypoxemia defined as (i) PaO2:FiO2 > 300 or (ii) SpO2: FiO2 > 315 on the day following diagnosis of ARDS (day 2) or (iii) unassisted breathing by day 2 and for the next 48 h (defined as absence of endotracheal intubation on day 2 through day 4). Plasma biomarkers were measured on samples collected on the day of study enrollment, and ARDS phenotypes were allocated as previously described. RESULTS: RIARDS accounted for 21% of all ARDS participants. Patients with RIARDS had better clinical outcomes compared to those with persistent ARDS, with lower hospital mortality (13% vs. 57%; p value < 0.001) and more ICU-free days (median 24 vs. 0; p value < 0.001). Plasma levels of interleukin-6, interleukin-8, and plasminogen activator inhibitor-1 were significantly lower among patients with RIARDS. The hypoinflammatory phenotype of ARDS was more common among patients with RIARDS (78% vs. 51% in persistent ARDS; p value = 0.001). CONCLUSIONS: This study identifies a high prevalence of RIARDS in a multicenter observational cohort and confirms the more benign clinical course of these patients. We report the novel finding that RIARDS is characterized by lower concentrations of plasma biomarkers of inflammation compared to persistent ARDS, and that hypoinflammatory ARDS is more prevalent among patients with RIARDS. Identification and exclusion of RIARDS could potentially improve prognostic and predictive enrichment in clinical trials.

Causes and attributable fraction of death from ARDS in inflammatory phenotypes of sepsis.

BACKGROUND: Hypoinflammatory and hyperinflammatory phenotypes have been identified in both Acute Respiratory Distress Syndrome (ARDS) and sepsis. Attributable mortality of ARDS in each phenotype of sepsis is yet to be determined. We aimed to estimate the population attributable fraction of death from ARDS (PAFARDS) in hypoinflammatory and hyperinflammatory sepsis, and to determine the primary cause of death within each phenotype. METHODS: We studied 1737 patients with sepsis from two prospective cohorts. Patients were previously assigned to the hyperinflammatory or hypoinflammatory phenotype using latent class analysis. The PAFARDS in patients with sepsis was estimated separately in the hypo and hyperinflammatory phenotypes. Organ dysfunction, severe comorbidities, and withdrawal of life support were abstracted from the medical record in a subset of patients from the EARLI cohort who died (n = 130/179). Primary cause of death was defined as the organ system that most directly contributed to death or withdrawal of life support. RESULTS: The PAFARDS was 19% (95%CI 10,28%) in hypoinflammatory sepsis and, 14% (95%CI 6,20%) in hyperinflammatory sepsis. Cause of death differed between the two phenotypes (p < 0.001). Respiratory failure was the most common cause of death in hypoinflammatory sepsis, whereas circulatory shock was the most common cause in hyperinflammatory sepsis. Death with severe underlying comorbidities was more frequent in hypoinflammatory sepsis (81% vs. 67%, p = 0.004). CONCLUSIONS: The PAFARDS is modest in both phenotypes whereas primary cause of death among patients with sepsis differed substantially by phenotype. This study identifies challenges in powering future clinical trials to detect changes in mortality outcomes among patients with sepsis and ARDS.

Low Perfusion and Missed Diagnosis of Hypoxemia by Pulse Oximetry in Darkly Pigmented Skin: A Prospective Study.

BACKGROUND: Retrospective clinical trials of pulse oximeter accuracy report more frequent missed diagnoses of hypoxemia in hospitalized Black patients than White patients, differences that may contribute to racial disparities in health and health care. Retrospective studies have limitations including mistiming of blood samples and oximeter readings, inconsistent use of functional versus fractional saturation, and self-reported race used as a surrogate for skin color. Our objective was to prospectively measure the contributions of skin pigmentation, perfusion index (PI), sex, and age on pulse oximeter errors in a laboratory setting. METHODS: We enrolled 146 healthy subjects, including 25 with light skin (Fitzpatrick class I and II), 78 with medium (class III and IV), and 43 with dark (class V and VI) skin. We studied 2 pulse oximeters (Nellcor N-595 and Masimo Radical 7) in prevalent clinical use. We analyzed 9763 matched pulse oximeter readings (pulse oximeter measured functional saturation [Sp o2 ]) and arterial oxygen saturation (hemoximetry arterial functional oxygen saturation [Sa o2 ]) during stable hypoxemia (Sa o2 68%-100%). PI was measured as percent infrared light modulation by the pulse detected by the pulse oximeter probe, with low perfusion categorized as PI < 1%. The primary analysis was to assess the relationship between pulse oximeter bias (difference between Sa o2 and Sp o2 ) by skin pigment category in a multivariable mixed-effects model incorporating repeated-measures and different levels of Sa o2 and perfusion. RESULTS: Skin pigment, PI, and degree of hypoxemia significantly contributed to errors (bias) in both pulse oximeters. For PI values of 1.0% to 1.5%, 0.5% to 1.0%, and <0.5%, the P value of the relationship to mean bias or median absolute bias was <.00001. In lightly pigmented subjects, only PI was associated with positive bias, whereas in medium and dark subjects bias increased with both low perfusion and degree of hypoxemia. Sex and age was not related to pulse oximeter bias. The combined frequency of missed diagnosis of hypoxemia (pulse oximeter readings 92%-96% when arterial oxygen saturation was <88%) in low perfusion conditions was 1.1% for light, 8.2% for medium, and 21.1% for dark skin. CONCLUSIONS: Low peripheral perfusion combined with darker skin pigmentation leads to clinically significant high-reading pulse oximeter errors and missed diagnoses of hypoxemia. Darkly pigmented skin and low perfusion states are likely the cause of racial differences in pulse oximeter performance in retrospective studies.

Plasma metabolic profiling implicates dysregulated lipid metabolism and glycolytic shift in hyperinflammatory ARDS.

Using latent class analysis (LCA) of clinical and protein biomarkers, researchers have identified two phenotypes of the acute respiratory distress syndrome (ARDS) with divergent clinical trajectories and treatment responses. We investigated whether plasma metabolites differed among patients with LCA-derived hyperinflammatory and hypoinflammatory ARDS, and we tested the prognostic utility of adding metabolic clusters to LCA phenotypes. We analyzed data from 93 patients with ARDS and sepsis enrolled in a multicenter prospective cohort of critically ill patients, comparing 970 metabolites between the two LCA-derived phenotypes. In all, 188 metabolites were differentially abundant between the two LCA-derived phenotypes. After adjusting for age, sex, confounding medications, and comorbid liver and kidney disease, 82 metabolites remained significantly different. Patients with hyperinflammatory ARDS had reduced circulating lipids but high levels of pyruvate, lactate, and malate. Metabolic cluster and LCA-derived phenotypes were each significantly and independently associated with survival. Patients with hyperinflammatory ARDS may be experiencing a glycolytic shift leading to dysregulated lipid metabolism. Metabolic profiling offers prognostic information beyond what is captured by LCA phenotypes alone. Deeper biological profiling may identify key differences in pathogenesis among patients with ARDS and may lead to novel targeted therapies.

Early plasma angiopoietin-2 is prognostic for ARDS and mortality among critically ill patients with sepsis.

Angiopoietin-2 (Ang-2) is associated with vascular endothelial injury and permeability in the acute respiratory distress syndrome (ARDS) and sepsis. Elevated circulating Ang-2 levels may identify critically ill patients with distinct pathobiology amenable to targeted therapy. We hypothesized that plasma Ang-2 measured shortly after hospitalization among patients with sepsis would be associated with the development of ARDS and poor clinical outcomes. To test this hypothesis, we measured plasma Ang-2 in a cohort of 757 patients with sepsis, including 267 with ARDS, enrolled in the emergency department or early in their ICU course before the COVID-19 pandemic. Multivariable models were used to test the association of Ang-2 with the development of ARDS and 30-day morality. We found that early plasma Ang-2 in sepsis was associated with higher baseline severity of illness, the development of ARDS, and mortality risk. The association between Ang-2 and mortality was strongest among patients with ARDS and sepsis as compared to those with sepsis alone (OR 1.81 vs. 1.52 per log Ang-2 increase). These findings might inform models testing patient risk prediction and strengthen the evidence for Ang-2 as an appealing biomarker for patient selection for novel therapeutic agents to target vascular injury in sepsis and ARDS.

COVID-19-associated Lung Microvascular Endotheliopathy: A "From the Bench" Perspective.

Rationale: Autopsy and biomarker studies suggest that endotheliopathy contributes to coronavirus disease (COVID-19)-associated acute respiratory distress syndrome. However, the effects of COVID-19 on the lung endothelium are not well defined. We hypothesized that the lung endotheliopathy of COVID-19 is caused by circulating host factors and direct endothelial infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Objectives: We aimed to determine the effects of SARS-CoV-2 or sera from patients with COVID-19 on the permeability and inflammatory activation of lung microvascular endothelial cells. Methods: Human lung microvascular endothelial cells were treated with live SARS-CoV-2; inactivated viral particles; or sera from patients with COVID-19, patients without COVID-19, and healthy volunteers. Permeability was determined by measuring transendothelial resistance to electrical current flow, where decreased resistance signifies increased permeability. Inflammatory mediators were quantified in culture supernatants. Endothelial biomarkers were quantified in patient sera. Measurements and Main Results: Viral PCR confirmed that SARS-CoV-2 enters and replicates in endothelial cells. Live SARS-CoV-2, but not dead virus or spike protein, induces endothelial permeability and secretion of plasminogen activator inhibitor 1 and vascular endothelial growth factor. There was substantial variability in the effects of SARS-CoV-2 on endothelial cells from different donors. Sera from patients with COVID-19 induced endothelial permeability, which correlated with disease severity. Serum levels of endothelial activation and injury biomarkers were increased in patients with COVID-19 and correlated with severity of illness. Conclusions: SARS-CoV-2 infects and dysregulates endothelial cell functions. Circulating factors in patients with COVID-19 also induce endothelial cell dysfunction. Our data point to roles for both systemic factors acting on lung endothelial cells and viral infection of endothelial cells in COVID-19-associated endotheliopathy.

Cigarette Smoke Exposure and Acute Respiratory Distress Syndrome in Sepsis: Epidemiology, Clinical Features, and Biologic Markers.

Rationale: Cigarette smoke exposure is associated with an increased risk of developing acute respiratory distress syndrome (ARDS) in trauma, transfusion, and nonpulmonary sepsis. It is unknown whether this relationship exists in the general sepsis population. Furthermore, it is unknown if patients with ARDS have differences in underlying biology based on smoking status. Objectives: To assess the relationship between cigarette smoke exposure and ARDS in sepsis and identify tobacco-related biomarkers of lung injury. Methods: We studied a prospective cohort of 592 patients with sepsis from 2009 to 2017. Plasma cotinine and urine NNAL [urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol] were measured to categorize smoking status. Plasma biomarkers of inflammation and lung injury were measured, including in a smaller cohort of trauma patients with ARDS to increase generalizability. Measurements and Main Results: Passive and active smoking were associated with increased odds of developing ARDS in patients with sepsis. Among patients with sepsis and ARDS, active cigarette smokers were younger and had lower severity of illness than nonsmokers. Patients with ARDS with cigarette smoke exposure had lower plasma levels of IL-8 (P = 0.01) and sTNFR-1 (soluble tumor necrosis factor 1; P = 0.01) compared with those without exposure. Similar biomarker patterns were observed in blunt trauma patients with ARDS. Conclusions: Passive and active smoking are associated with an increased risk of developing ARDS in patients with pulmonary and nonpulmonary sepsis. Among patients with ARDS, those with cigarette smoke exposure have less systemic inflammation, while active smokers also have lower severity of illness compared with nonsmokers, suggesting that smoking contributes to biological heterogeneity in ARDS.

Internal and External Validation of an Alcohol Biomarker for Screening in Trauma.

OBJECTIVE: We aimed to examine biomarkers for screening unhealthy alcohol use in the trauma setting. SUMMARY AND BACKGROUND DATA: Self-report tools are the practice standard for screening unhealthy alcohol use; however, their collection suffers from recall bias and incomplete collection by staff. METHODS: We performed a multi-center prospective clinical study of 251 adult patients who arrived within 24 hours of injury with external validation in another 60 patients. The Alcohol Use Disorders Identification Test served as the reference standard. The following biomarkers were measured: (1) PEth; (2) ethyl glucuronide; (3) ethyl sulfate; (4) gamma-glutamyl-transpeptidase; (5) carbohydrate deficient transferrin; and (6) blood alcohol concentration (BAC). Candidate single biomarkers and multivariable models were compared by considering discrimination (AUROC). The optimal cutpoint for the final model was identified using a criterion for setting the minimum value for specificity at 80% and maximizing sensitivity. Decision curve analysis was applied to compare to existing screening with BAC. RESULTS: PEth alone had an AUROC of 0.93 [95% confidence interval (CI): 0.92-0.93] in internal validation with an optimal cutpoint of 25 ng/mL. A 4- variable biomarker model and the addition of any single biomarker to PEth did not improve AUROC over PEth alone ( P > 0.05). Decision curve analysis showed better performance of PEth over BAC across most predicted probability thresholds. In external validation, sensitivity and specificity were 76.0% (95% CI: 53.0%-92.0%) and 73.0% (95% CI: 56.0%-86.0%), respectively.Conclusion and Relevance: PEth alone proved to be the single best biomarker for screening of unhealthy alcohol use and performed better than existing screening systems with BAC. PEth may overcome existing screening barriers.

Latent class analysis-derived subphenotypes are generalisable to observational cohorts of acute respiratory distress syndrome: a prospective study.

RATIONALE: Using latent class analysis (LCA), two subphenotypes of acute respiratory distress syndrome (ARDS) have consistently been identified in five randomised controlled trials (RCTs), with distinct biological characteristics, divergent outcomes and differential treatment responses to randomised interventions. Their existence in unselected populations of ARDS remains unknown. We sought to identify subphenotypes in observational cohorts of ARDS using LCA. METHODS: LCA was independently applied to patients with ARDS from two prospective observational cohorts of patients admitted to the intensive care unit, derived from the Validating Acute Lung Injury markers for Diagnosis (VALID) (n=624) and Early Assessment of Renal and Lung Injury (EARLI) (n=335) studies. Clinical and biological data were used as class-defining variables. To test for concordance with prior ARDS subphenotypes, the performance metrics of parsimonious classifier models (interleukin 8, bicarbonate, protein C and vasopressor-use), previously developed in RCTs, were evaluated in EARLI and VALID with LCA-derived subphenotypes as the gold-standard. RESULTS: A 2-class model best fit the population in VALID (p=0.0010) and in EARLI (p<0.0001). Class 2 comprised 27% and 37% of the populations in VALID and EARLI, respectively. Consistent with the previously described 'hyperinflammatory' subphenotype, Class 2 was characterised by higher proinflammatory biomarkers, acidosis and increased shock and worse clinical outcomes. The similarities between these and prior RCT-derived subphenotypes were further substantiated by the performance of the parsimonious classifier models in both cohorts (area under the curves 0.92-0.94). The hyperinflammatory subphenotype was associated with increased prevalence of chronic liver disease and neutropenia and reduced incidence of chronic obstructive pulmonary disease. Measurement of novel biomarkers showed significantly higher levels of matrix metalloproteinase-8 and markers of endothelial injury in the hyperinflammatory subphenotype, whereas, matrix metalloproteinase-9 was significantly lower. CONCLUSION: Previously described subphenotypes are generalisable to unselected populations of non-trauma ARDS.

Plasma SARS-CoV-2 nucleocapsid antigen levels are associated with progression to severe disease in hospitalized COVID-19.

BACKGROUND: Studies quantifying SARS-CoV-2 have focused on upper respiratory tract or plasma viral RNA with inconsistent association with clinical outcomes. The association between plasma viral antigen levels and clinical outcomes has not been previously studied. Our aim was to investigate the relationship between plasma SARS-CoV-2 nucleocapsid antigen (N-antigen) concentration and both markers of host response and clinical outcomes. METHODS: SARS-CoV-2 N-antigen concentrations were measured in the first study plasma sample (D0), collected within 72 h of hospital admission, from 256 subjects admitted between March 2020 and August 2021 in a prospective observational cohort of hospitalized patients with COVID-19. The rank correlations between plasma N-antigen and plasma biomarkers of tissue damage, coagulation, and inflammation were assessed. Multiple ordinal regression was used to test the association between enrollment N-antigen plasma concentration and the primary outcome of clinical deterioration at one week as measured by a modified World Health Organization (WHO) ordinal scale. Multiple logistic regression was used to test the association between enrollment plasma N-antigen concentration and the secondary outcomes of ICU admission, mechanical ventilation at 28 days, and death at 28 days. The prognostic discrimination of an externally derived "high antigen" cutoff of N-antigen ≥ 1000 pg/mL was also tested. RESULTS: N-antigen on D0 was detectable in 84% of study participants. Plasma N-antigen levels significantly correlated with RAGE (r = 0.61), IL-10 (r = 0.59), and IP-10 (r = 0.59, adjusted p = 0.01 for all correlations). For the primary outcome of clinical status at one week, each 500 pg/mL increase in plasma N-antigen level was associated with an adjusted OR of 1.05 (95% CI 1.03-1.08) for worse WHO ordinal status. D0 plasma N-antigen ≥ 1000 pg/mL was 77% sensitive and 59% specific (AUROC 0.68) with a positive predictive value of 23% and a negative predictive value of 93% for a worse WHO ordinal scale at day 7 compared to baseline. D0 N-antigen concentration was independently associated with ICU admission and 28-day mechanical ventilation, but not with death at 28 days. CONCLUSIONS: Plasma N-antigen levels are readily measured and provide important insight into the pathogenesis and prognosis of COVID-19. The measurement of N-antigen levels early in-hospital course may improve risk stratification, especially for identifying patients who are unlikely to progress to severe disease.

Using best subset regression to identify clinical characteristics and biomarkers associated with sepsis-associated acute kidney injury.

Sepsis-associated acute kidney injury (AKI) is a complex clinical disorder associated with inflammation, endothelial dysfunction, and dysregulated coagulation. With standard regression methods, collinearity among biomarkers may lead to the exclusion of important biological pathways in a single final model. Best subset regression is an analytic technique that identifies statistically equivalent models, allowing for more robust evaluation of correlated variables. Our objective was to identify common clinical characteristics and biomarkers associated with sepsis-associated AKI. We enrolled 453 septic adults within 24 h of intensive care unit admission. Using best subset regression, we evaluated for associations using a range of models consisting of 1-38 predictors (composed of clinical risk factors and plasma and urine biomarkers) with AKI as the outcome [defined as a serum creatinine (SCr) increase of ≥0.3 mg/dL within 48 h or ≥1.5× baseline SCr within 7 days]. Two hundred ninety-seven patients had AKI. Five-variable models were found to be of optimal complexity, as the best subset of five- and six-variable models were statistically equivalent. Within the subset of five-variable models, 46 permutations of predictors were noted to be statistically equivalent. The most common predictors in this subset included diabetes, baseline SCr, angiopoetin-2, IL-8, soluble tumor necrosis factor receptor-1, and urine neutrophil gelatinase-associated lipocalin. The models had a c-statistic of ∼0.70 (95% confidence interval: 0.65-0.75). In conclusion, using best subset regression, we identified common clinical characteristics and biomarkers associated with sepsis-associated AKI. These variables may be especially relevant in the pathogenesis of sepsis-associated AKI.

Peripheral blood leukocyte telomere length is associated with survival of sepsis patients.

Shorter peripheral blood leukocyte (PBL) telomere length (TL) has been associated with poor outcomes in various chronic lung diseases. Whether PBL-TL is associated with survival from critical illness was tested in this study.We analysed data from a prospective observational cohort study of 937 critically ill patients at Vanderbilt University Medical Center (VUMC). PBL-TL was measured using quantitative PCR of DNA isolated from PBLs. Findings were validated in an independent cohort of 394 critically ill patients with sepsis admitted to the University of California San Francisco (UCSF).In the VUMC cohort, shorter PBL-TL was associated with worse 90-day survival (adjusted hazard ratio (aHR) 1.3, 95% CI 1.1-1.6 per 1 kb TL decrease; p=0.004); in subgroup analyses, shorter PBL-TL was associated with worse 90-day survival for patients with sepsis (aHR 1.5, 95% CI 1.2-2.0 per 1 kb TL decrease; p=0.001), but not trauma. Although not associated with development of acute respiratory distress syndrome (ARDS), among ARDS subjects, shorter PBL-TL was associated with more severe ARDS (OR 1.7, 95% CI 1.2-2.5 per 1 kb TL decrease; p=0.006). The associations of PBL-TL with survival (adjusted HR 1.6, 95% CI 1.2-2.1 per 1 kb TL decrease; p=0.003) and risk for developing severe ARDS (OR 2.5, 95% CI 1.1-6.3 per 1 kb TL decrease; p=0.044) were validated in the UCSF cohort.Short PBL-TL is strongly associated with worse survival and more severe ARDS in critically ill patients, especially patients with sepsis. These findings suggest that telomere dysfunction may contribute to outcomes from critical illness.

Higher plasma cystatin C is associated with mortality after acute respiratory distress syndrome: findings from a Fluid and Catheter Treatment Trial (FACTT) substudy.

BACKGROUND: Cystatin C is a well-validated marker of glomerular filtration rate in chronic kidney disease. Higher plasma concentrations of cystatin C are associated with worse clinical outcomes in heterogenous populations of critically ill patients and may be superior to creatinine in identifying kidney injury in critically ill patients. We hypothesized that elevated levels of plasma cystatin C in patients with acute respiratory distress syndrome (ARDS) would be associated with mortality risk. METHODS: In a retrospective study, cystatin C was measured by nephelometry on plasma obtained at enrollment from 919 patients in the Fluid and Catheter Treatment Trial. Multivariable logistic regression was performed testing the association between quartiles of cystatin C and 60-day mortality. Analyses were stratified by acute kidney injury (AKI) status identified in the first 7 days after enrollment by Kidney Disease: Improving Global Outcomes (KDIGO) criteria. RESULTS: Cystatin C was significantly higher among those patients who died compared to those who survived to 60 days [1.2 (0.9-1.9) mg/L vs. 0.8 (0.6-1.2) mg/L, p < 0.001]. Compared to the lower three quartiles, subjects in the highest quartile of cystatin C had a significantly higher odds of death at 60 days [OR 1.8 (1.2-2.6), p = 0.003 in adjusted analyses]; the odds of death incrementally rose in higher cystatin C quartiles compared to the lowest quartile (OR 1.1, 1.8, and 2.5). In adjusted analyses stratified by AKI status, compared to subjects in the lower three quartiles, subjects in the highest quartile of cystatin C with AKI had a significantly higher odds of death at 60 days both in participants with AKI [OR 1.6 (1.0-2.4), p = 0.048] and those without AKI [OR 2.4 (1.2-5.0), p = 0.017]. In adjusted analyses, there was no significant association between sex-stratified baseline creatinine quartiles and mortality. CONCLUSIONS: Higher plasma levels of cystatin C on enrollment were strongly associated with mortality at 60 days in patients with ARDS with and without AKI identified by creatinine-based definitions. Compared to creatinine, cystatin C may be a better biomarker of kidney function in patients with ARDS and therefore identify patients with multiple organ failure at higher risk of death.

Higher mini-BAL total protein concentration in early ARDS predicts faster resolution of lung injury measured by more ventilator-free days.

The protein concentration of alveolar edema fluid in acute respiratory distress syndrome (ARDS) is dynamic. It reflects alveolar flooding during acute injury, as well as fluid and protein clearance over time. We hypothesized that among ARDS patients treated with low tidal volume ventilation, higher concentrations of protein in mini-bronchoalveolar lavage (mBAL) samples would predict slower resolution of lung injury and worse clinical outcomes. Total protein and IgM concentrations in day 0 mBAL samples from 79 subjects enrolled in the aerosolized albuterol (ALTA) ARDS Network Albuterol Trial were measured by colorimetric assay and ELISA, respectively. Linear regression models were used to test the association of mBAL proteins with clinical outcomes and measures of length of illness, including ventilator-free days (VFDs). Median mBAL total protein concentration was 1,740 µg/ml [interquartile range (IQR): 890-3,170]. Each 500 µg/ml increase in day 0 mBAL total protein was associated with an additional 0.8 VFDs [95% confidence interval (CI): 0.05-1.6, P value = 0.038]. Median mBAL IgM concentration was 410 ng/ml (IQR: 340-500). Each 50 ng/ml increase in mBAL IgM was associated with an additional 1.1 VFDs (95% CI 0.2-2.1, P value = 0.022). These associations remained significant and were not attenuated in multivariate models adjusted for age, serum protein concentration, and vasopressor use in the 24 h before enrollment. Thus, higher mBAL total protein and IgM concentrations at day 0 are associated with more VFDs in patients with ARDS and may identify patients with preserved alveolar epithelial mechanisms for net alveolar fluid clearance.

Distinct pulmonary and systemic effects of dexamethasone in severe COVID-19.

Dexamethasone is the standard of care for critically ill patients with COVID-19, but the mechanisms by which it decreases mortality and its immunological effects in this setting are not understood. Here we perform bulk and single-cell RNA sequencing of samples from the lower respiratory tract and blood, and assess plasma cytokine profiling to study the effects of dexamethasone on both systemic and pulmonary immune cell compartments. In blood samples, dexamethasone is associated with decreased expression of genes associated with T cell activation, including TNFSFR4 and IL21R. We also identify decreased expression of several immune pathways, including major histocompatibility complex-II signaling, selectin P ligand signaling, and T cell recruitment by intercellular adhesion molecule and integrin activation, suggesting these are potential mechanisms of the therapeutic benefit of steroids in COVID-19. We identify additional compartment- and cell- specific differences in the effect of dexamethasone that are reproducible in publicly available datasets, including steroid-resistant interferon pathway expression in the respiratory tract, which may be additional therapeutic targets. In summary, we demonstrate compartment-specific effects of dexamethasone in critically ill COVID-19 patients, providing mechanistic insights with potential therapeutic relevance. Our results highlight the importance of studying compartmentalized inflammation in critically ill patients.