Integrated analysis of multimodal single-cell data.

The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce "weighted-nearest neighbor" analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.

Molecular Endotypes of Idiopathic Pulmonary Fibrosis: A Latent Class Analysis of Two Multicenter Observational Cohorts.

Rationale: Idiopathic pulmonary fibrosis (IPF) causes irreversible fibrosis of the lung parenchyma. Although antifibrotic therapy can slow IPF progression, treatment response is variable. There exists a critical need to develop a precision medicine approach to IPF. Objectives: To identify and validate biologically driven molecular endotypes of IPF. Methods: Latent class analysis (LCA) was independently performed in prospectively recruited discovery (n = 875) and validation (n = 347) cohorts. Twenty-five plasma biomarkers associated with fibrogenesis served as class-defining variables. The association between molecular endotype and 4-year transplant-free survival was tested using multivariable Cox regression adjusted for baseline confounders. Endotype-dependent differential treatment response to future antifibrotic exposure was then assessed in a pooled cohort of patients naive to antifibrotic therapy at the time of biomarker measurement (n = 555). Measurements and Main Results: LCA independently identified two latent classes in both cohorts (P < 0.0001). WFDC2 (WAP four-disulfide core domain protein 2) was the most important determinant of class membership across cohorts. Membership in class 2 was characterized by higher biomarker concentrations and a higher risk of death or transplant (discovery, hazard ratio [HR], 2.02; 95% confidence interval [CI], 1.64-2.48; P < 0.001; validation, HR, 1.95; 95% CI, 1.34-2.82; P < 0.001). In pooled analysis, significant heterogeneity in treatment effect was observed between endotypes (P = 0.030 for interaction), with a favorable antifibrotic response in class 2 (HR, 0.64; 95% CI, 0.45-0.93; P = 0.018) but not in class 1 (HR, 1.19; 95% CI, 0.77-1.84; P = 0.422). Conclusions: In this multicohort study, we identified two novel molecular endotypes of IPF with divergent clinical outcomes and responses to antifibrotic therapy. Pending further validation, these endotypes could enable a precision medicine approach for future IPF clinical trials.

Viral and Host Factors Are Associated With Mortality in Hospitalized Patients With COVID-19.

BACKGROUND: Persistent mortality in adults hospitalized due to acute COVID-19 justifies pursuit of disease mechanisms and potential therapies. The aim was to evaluate which virus and host response factors were associated with mortality risk among participants in Therapeutics for Inpatients with COVID-19 (TICO/ACTIV-3) trials. METHODS: A secondary analysis of 2625 adults hospitalized for acute SARS-CoV-2 infection randomized to 1 of 5 antiviral products or matched placebo in 114 centers on 4 continents. Uniform, site-level collection of participant baseline clinical variables was performed. Research laboratories assayed baseline upper respiratory swabs for SARS-CoV-2 viral RNA and plasma for anti-SARS-CoV-2 antibodies, SARS-CoV-2 nucleocapsid antigen (viral Ag), and interleukin-6 (IL-6). Associations between factors and time to mortality by 90 days were assessed using univariate and multivariable Cox proportional hazards models. RESULTS: Viral Ag ≥4500 ng/L (vs <200 ng/L; adjusted hazard ratio [aHR], 2.07; 1.29-3.34), viral RNA (<35 000 copies/mL [aHR, 2.42; 1.09-5.34], ≥35 000 copies/mL [aHR, 2.84; 1.29-6.28], vs below detection), respiratory support (<4 L O2 [aHR, 1.84; 1.06-3.22]; ≥4 L O2 [aHR, 4.41; 2.63-7.39], or noninvasive ventilation/high-flow nasal cannula [aHR, 11.30; 6.46-19.75] vs no oxygen), renal impairment (aHR, 1.77; 1.29-2.42), and IL-6 >5.8 ng/L (aHR, 2.54 [1.74-3.70] vs ≤5.8 ng/L) were significantly associated with mortality risk in final adjusted analyses. Viral Ag, viral RNA, and IL-6 were not measured in real-time. CONCLUSIONS: Baseline virus-specific, clinical, and biological variables are strongly associated with mortality risk within 90 days, revealing potential pathogen and host-response therapeutic targets for acute COVID-19 disease.

Evaluation of Acebilustat, a Selective Inhibitor of Leukotriene B4 Biosynthesis, for Treatment of Outpatients With Mild-Moderate Coronavirus Disease 2019: A Randomized, Double-Blind, Placebo-Controlled Phase 2 Trial.

BACKGROUND: The vast majority of coronavirus disease 2019 (COVID-19) disease occurs in outpatients where treatment is limited to antivirals for high-risk subgroups. Acebilustat, a leukotriene B4 inhibitor, has potential to reduce inflammation and symptom duration. METHODS: In a single-center trial spanning Delta and Omicron variants, outpatients were randomized to 100 mg/d of oral acebilustat or placebo for 28 days. Patients reported daily symptoms via electronic query through day 28 with phone follow-up on day 120 and collected nasal swab samples on days 1-10. The primary outcome was sustained symptom resolution to day 28. Secondary 28-day outcomes included time to first symptom resolution, area under the curve (AUC) for longitudinal daily symptom scores, duration of viral shedding through day 10, and symptoms on day 120. RESULTS: Sixty participants were randomized to each study arm. At enrollment, the median duration was 4 days (interquartile range, 3-5 days), and the median number of symptoms was 9 (7-11). Most patients (90%) were vaccinated, with 73% having neutralizing antibodies. A minority of participants (44%; 35% in the acebilustat arm and 53% in placebo) had sustained symptom resolution at day 28 (hazard ratio, 0.6 [95% confidence interval, .34-1.04]; P = .07 favoring placebo). There was no difference in the mean AUC for symptom scores over 28 days (difference in mean AUC, 9.4 [95% confidence interval, -42.1 to 60.9]; P = .72). Acebilustat did not affect viral shedding or symptoms at day 120. CONCLUSIONS: Sustained symptoms through day 28 were common in this low-risk population. Despite this, leukotriene B4 antagonism with acebilustat did not shorten symptom duration in outpatients with COVID-19. Clinical Trials Registration. NCT04662060.

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.

Elevated Plasma Interleukin-18 Identifies High-Risk Acute Respiratory Distress Syndrome Patients not Distinguished by Prior Latent Class Analyses Using Traditional Inflammatory Cytokines: A Retrospective Analysis of Two Randomized Clinical Trials.

OBJECTIVES: Interleukin-18 (IL-18) plasma level and latent class analysis (LCA) have separately been shown to predict prognosis and treatment response in acute respiratory distress syndrome (ARDS). IL-18 is a measure of inflammasome activation, a pathway potentially distinct from inflammation captured by biomarkers defining previously published LCA classes. We hypothesized that elevated IL-18 would identify distinct "high-risk" patients not captured by prior LCA classifications. DESIGN: Statins for acutely injured lungs from sepsis (SAILS) and hydroxymethylglutaryl-CoA reductase inhibition with simvastatin in acute lung injury to reduce pulmonary dysfunction trial (HARP-2) are two large randomized, controlled trials in ARDS in which both LCA assignments and IL-18 levels were shown to predict mortality. We first evaluated the overlap between high IL-18 levels (≥ 800 pg/mL) with prior LCA class assignments using McNemar's test and then tested the correlation between IL-18 and LCA biomarkers using Pearson's exact test on log-2 transformed values. Our primary analysis was the association of IL-18 level with 60-day mortality in the hypoinflammatory LCA class, which was assessed using the Fisher exact test and Cox proportional hazards modeling adjusting for age, Acute Physiology and Chronic Health Evaluation score, and gender. Secondary analyses included the association of IL-18 and LCA with mortality within each IL-18/LCA subgroup. SETTING: Secondary analysis of two multicenter, randomized controlled clinical trials of ARDS patients. SUBJECTS: Six hundred eighty-three patients in SAILS and 511 patients in HARP-2. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We found that 33% of patients in SAILS and HARP-2 were discordant by IL-18 level and LCA class. We further found that IL-18 level was only modestly correlated (0.17-0.47) with cytokines used in the LCA assignment. A substantial subset of individuals classified as hypoinflammatory by LCA (14% of SAILS and 43% of HARP-2) were classified as high risk by elevated IL-18. These individuals were at high risk for mortality in both SAILS (42% 60-d mortality, odds ratio [OR] 3.3; 95% CI, 1.8-6.1; p < 0.001) and HARP-2 (27% 60-d mortality, OR 2.1; 95% CI, 1.2-3.8; p = 0.009). CONCLUSIONS: Plasma IL-18 level provides important additional prognostic information to LCA subphenotypes defined largely by traditional inflammatory biomarkers in two large ARDS cohorts.

Effect of total cholesterol and statin therapy on mortality in ARDS patients: a secondary analysis of the SAILS and HARP-2 trials.

BACKGROUND: Two acute respiratory distress syndrome (ARDS) trials showed no benefit for statin therapy, though secondary analyses suggest inflammatory subphenotypes may have a differential response to simvastatin. Statin medications decrease cholesterol levels, and low cholesterol has been associated with increased mortality in critical illness. We hypothesized that patients with ARDS and sepsis with low cholesterol could be harmed by statins. METHODS: Secondary analysis of patients with ARDS and sepsis from two multicenter trials. We measured total cholesterol from frozen plasma samples obtained at enrollment in Statins for Acutely Injured Lungs from Sepsis (SAILS) and Simvastatin in the Acute Respiratory Distress Syndrome (HARP-2) trials, which randomized subjects with ARDS to rosuvastatin versus placebo and simvastatin versus placebo, respectively, for up to 28 days. We compared the lowest cholesterol quartile (< 69 mg/dL in SAILS, < 44 mg/dL in HARP-2) versus all other quartiles for association with 60-day mortality and medication effect. Fisher's exact test, logistic regression, and Cox Proportional Hazards were used to assess mortality. RESULTS: There were 678 subjects with cholesterol measured in SAILS and 509 subjects in HARP-2, of whom 384 had sepsis. Median cholesterol at enrollment was 97 mg/dL in both SAILS and HARP-2. Low cholesterol was associated with higher APACHE III and shock prevalence in SAILS, and higher Sequential Organ Failure Assessment score and vasopressor use in HARP-2. Importantly, the effect of statins differed in these trials. In SAILS, patients with low cholesterol who received rosuvastatin were more likely to die (odds ratio (OR) 2.23, 95% confidence interval (95% CI) 1.06-4.77, p = 0.02; interaction p = 0.02). In contrast, in HARP-2, low cholesterol patients had lower mortality if randomized to simvastatin, though this did not reach statistical significance in the smaller cohort (OR 0.44, 95% CI 0.17-1.07, p = 0.06; interaction p = 0.22). CONCLUSIONS: Cholesterol levels are low in two cohorts with sepsis-related ARDS, and those in the lowest cholesterol quartile are sicker. Despite the very low levels of cholesterol, simvastatin therapy seems safe and may reduce mortality in this group, though rosuvastatin was associated with harm.

The Metabolomics of Critical Illness.

Critical illness is associated with dramatic changes in metabolism driven by immune, endocrine, and adrenergic mediators. These changes involve early activation of catabolic processes leading to increased energetic substrate availability; later on, they are followed by a hypometabolic phase characterized by deranged mitochondrial function. In sepsis and ARDS, these rapid clinical changes are reflected in metabolomic profiles of plasma and other fluids, suggesting that metabolomics could one day be used to assist in the diagnosis and prognostication of these syndromes. Some metabolites, such as lactate, are already in clinical use and define patients with septic shock, a high-mortality subtype of sepsis. Larger-scale metabolomic profiling may ultimately offer a tool to identify subgroups of critically ill patients who may respond to therapy, but further work is needed before this type of precision medicine is readily employed in the clinical setting.

The Association of Baseline Plasma SARS-CoV-2 Nucleocapsid Antigen Level and Outcomes in Patients Hospitalized With COVID-19.

BACKGROUND: Levels of plasma SARS-CoV-2 nucleocapsid (N) antigen may be an important biomarker in patients with COVID-19 and enhance our understanding of the pathogenesis of COVID-19. OBJECTIVE: To evaluate whether levels of plasma antigen can predict short-term clinical outcomes and identify clinical and viral factors associated with plasma antigen levels in hospitalized patients with SARS-CoV-2. DESIGN: Cross-sectional study of baseline plasma antigen level from 2540 participants enrolled in the TICO (Therapeutics for Inpatients With COVID-19) platform trial from August 2020 to November 2021, with additional data on day 5 outcome and time to discharge. SETTING: 114 centers in 10 countries. PARTICIPANTS: Adults hospitalized for acute SARS-CoV-2 infection with 12 days or less of symptoms. MEASUREMENTS: Baseline plasma viral N antigen level was measured at a central laboratory. Delta variant status was determined from baseline nasal swabs using reverse transcriptase polymerase chain reaction. Associations between baseline patient characteristics and viral factors and baseline plasma antigen levels were assessed using both unadjusted and multivariable modeling. Association between elevated baseline antigen level of 1000 ng/L or greater and outcomes, including worsening of ordinal pulmonary scale at day 5 and time to hospital discharge, were evaluated using logistic regression and Fine-Gray regression models, respectively. RESULTS: Plasma antigen was below the level of quantification in 5% of participants at enrollment, and 1000 ng/L or greater in 57%. Baseline pulmonary severity of illness was strongly associated with plasma antigen level, with mean plasma antigen level 3.10-fold higher among those requiring noninvasive ventilation or high-flow nasal cannula compared with room air (95% CI, 2.22 to 4.34). Plasma antigen level was higher in those who lacked antispike antibodies (6.42 fold; CI, 5.37 to 7.66) and in those with the Delta variant (1.73 fold; CI, 1.41 to 2.13). Additional factors associated with higher baseline antigen level included male sex, shorter time since hospital admission, decreased days of remdesivir, and renal impairment. In contrast, race, ethnicity, body mass index, and immunocompromising conditions were not associated with plasma antigen levels. Plasma antigen level of 1000 ng/L or greater was associated with a markedly higher odds of worsened pulmonary status at day 5 (odds ratio, 5.06 [CI, 3.41 to 7.50]) and longer time to hospital discharge (median, 7 vs. 4 days; subhazard ratio, 0.51 [CI, 0.45 to 0.57]), with subhazard ratios similar across all levels of baseline pulmonary severity. LIMITATIONS: Plasma samples were drawn at enrollment, not hospital presentation. No point-of-care test to measure plasma antigen is currently available. CONCLUSION: Elevated plasma antigen is highly associated with both severity of pulmonary illness and clinically important patient outcomes. Multiple clinical and viral factors are associated with plasma antigen level at presentation. These data support a potential role of ongoing viral replication in the pathogenesis of SARS-CoV-2 in hospitalized patients. PRIMARY FUNDING SOURCE: U.S. government Operation Warp Speed and National Institute of Allergy and Infectious Diseases.

SARS-CoV-2 RNAemia Predicts Clinical Deterioration and Extrapulmonary Complications from COVID-19.

BACKGROUND: The determinants of coronavirus disease 2019 (COVID-19) disease severity and extrapulmonary complications (EPCs) are poorly understood. We characterized relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNAemia and disease severity, clinical deterioration, and specific EPCs. METHODS: We used quantitative and digital polymerase chain reaction (qPCR and dPCR) to quantify SARS-CoV-2 RNA from plasma in 191 patients presenting to the emergency department with COVID-19. We recorded patient symptoms, laboratory markers, and clinical outcomes, with a focus on oxygen requirements over time. We collected longitudinal plasma samples from a subset of patients. We characterized the role of RNAemia in predicting clinical severity and EPCs using elastic net regression. RESULTS: Of SARS-CoV-2-positive patients, 23.0% (44 of 191) had viral RNA detected in plasma by dPCR, compared with 1.4% (2 of 147) by qPCR. Most patients with serial measurements had undetectable RNAemia within 10 days of symptom onset, reached maximum clinical severity within 16 days, and symptom resolution within 33 days. Initially RNAemic patients were more likely to manifest severe disease (odds ratio, 6.72 [95% confidence interval, 2.45-19.79]), worsening of disease severity (2.43 [1.07-5.38]), and EPCs (2.81 [1.26-6.36]). RNA loads were correlated with maximum severity (r = 0.47 [95% confidence interval, .20-.67]). CONCLUSIONS: dPCR is more sensitive than qPCR for the detection of SARS-CoV-2 RNAemia, which is a robust predictor of eventual COVID-19 severity and oxygen requirements, as well as EPCs. Because many COVID-19 therapies are initiated on the basis of oxygen requirements, RNAemia on presentation might serve to direct early initiation of appropriate therapies for the patients most likely to deteriorate.

A Retrospective Analysis of Medical Student Performance Evaluations, 2014-2020: Recommend with Reservations.

BACKGROUND: The Medical Student Performance Evaluations (MSPE) is a cornerstone of residency applications. Little is known regarding adherence to Association of American Medical Colleges (AAMC) MSPE recommendations and longitudinal changes in MSPE content. OBJECTIVES: Evaluate current MSPE quality and longitudinal changes in MSPE and grading practices. DESIGN: Retrospective analysis. PARTICIPANTS: Students from all Liaison Committee on Medical Education (LCME)-accredited medical schools from which the Stanford University Internal Medicine residency program received applications between 2014-2015 and 2019-2020. MAIN MEASURES: Inclusion of key words to describe applicant performance and metrics thereof, including distribution among students and key word assignment explanation; inclusion of clerkship grades, grade distributions, and grade composition; and evidence of grade inflation over time. KEY RESULTS: MSPE comprehensiveness varied substantially among the 149 schools analyzed. In total, 25% of schools provided complete information consistent with AAMC recommendations regarding key word/categorization of medical students and clerkship grades in 2019-2020. Seventy-seven distinct key word terms appeared across the 139 schools examined in 2019-2020. Grading practices markedly varied, with 2-83% of students receiving the top internal medicine clerkship grade depending on the year and school. Individual schools frequently changed key word and grading practices, with 33% and 18% of schools starting and/or stopping use of key words and grades, respectively. Significant grade inflation occurred over the 6-year study period, with an average 14% relative increase in the proportion of students receiving top clerkship grades. CONCLUSIONS: A minority of schools complies with AAMC MSPE guidelines, and MSPEs are inconsistent across time and schools. These practices may impair evaluation of students within and between schools.

Baseline plasma IL-18 may predict simvastatin treatment response in patients with ARDS: a secondary analysis of the HARP-2 randomised clinical trial.

BACKGROUND: Interleukin (IL)-18 is a marker of inflammasome activation, and high baseline plasma IL-18 is associated with increased mortality in patients with sepsis-induced ARDS. The aim of this analysis was to determine if simvastatin was associated with benefit in patients with ARDS and high plasma IL-18. METHODS: In this secondary analysis of the HARP-2 study, we compared 28-day mortality and response to simvastatin according to baseline plasma IL-18 using cox proportional hazards analysis. Separately, monocyte-derived macrophages from healthy volunteers were pre-incubated with simvastatin or rosuvastatin before stimulation with ATP and LPS, and the effect on secreted IL-18 and IL-1ß compared. RESULTS: 511 patients from HARP-2 had available data. High baseline plasma IL-18 (≥ 800 pg/ml) was associated with increased 28-day mortality (high IL-18 30.6% vs. low IL-18 17.5%; HR 1.89 [95% CI 1.30-2.73]; p = 0.001). Allocation to simvastatin in patients with high baseline plasma IL-18 was associated with a lower probability of 28-day mortality compared with placebo (24.0% vs 36.8%; p = 0.01). Finally, simvastatin, but not rosuvastatin, reduced stimulated macrophage secretion of IL-18 and IL-1ß. CONCLUSION: In patients with high baseline plasma IL-18, simvastatin is associated with a higher probability of survival, and this effect may be due to reduced inflammasome activation. These data suggest that baseline plasma IL-18 may allow a personalised treatment approach by identifying patients with ARDS who could benefit from simvastatin therapy.

Circulating N-formylmethionine and metabolic shift in critical illness: a multicohort metabolomics study.

BACKGROUND: Cell stress promotes degradation of mitochondria which release danger-associated molecular patterns that are catabolized to N-formylmethionine. We hypothesized that in critically ill adults, the response to N-formylmethionine is associated with increases in metabolomic shift-related metabolites and increases in 28-day mortality. METHODS: We performed metabolomics analyses on plasma from the 428-subject Correction of Vitamin D Deficiency in Critically Ill Patients trial (VITdAL-ICU) cohort and the 90-subject Brigham and Women's Hospital Registry of Critical Illness (RoCI) cohort. In the VITdAL-ICU cohort, we analyzed 983 metabolites at Intensive Care Unit (ICU) admission, day 3, and 7. In the RoCI cohort, we analyzed 411 metabolites at ICU admission. The association between N-formylmethionine and mortality was determined by adjusted logistic regression. The relationship between individual metabolites and N-formylmethionine abundance was assessed with false discovery rate correction via linear regression, linear mixed-effects, and Gaussian graphical models. RESULTS: Patients with the top quartile of N-formylmethionine abundance at ICU admission had a significantly higher adjusted odds of 28-day mortality in the VITdAL-ICU (OR, 2.4; 95%CI 1.5-4.0; P = 0.001) and RoCI cohorts (OR, 5.1; 95%CI 1.4-18.7; P = 0.015). Adjusted linear regression shows that with increases in N-formylmethionine abundance at ICU admission, 55 metabolites have significant differences common to both the VITdAL-ICU and RoCI cohorts. With increased N-formylmethionine abundance, both cohorts had elevations in individual short-chain acylcarnitine, branched chain amino acid, kynurenine pathway, and pentose phosphate pathway metabolites. CONCLUSIONS: The results indicate that circulating N-formylmethionine promotes a metabolic shift with heightened mortality that involves incomplete mitochondrial fatty acid oxidation, increased branched chain amino acid metabolism, and activation of the pentose phosphate pathway.

Network study of nasal transcriptome profiles reveals master regulator genes of asthma.

BACKGROUND: Nasal transcriptomics can provide an accessible window into asthma pathobiology. OBJECTIVE: Our goal was to move beyond gene signatures of asthma to identify master regulator genes that causally regulate genes associated with asthma phenotypes. METHODS: We recruited 156 children with severe persistent asthma and controls for nasal transcriptome profiling and applied network-based and probabilistic causal methods to identify severe asthma genes and their master regulators. We then took the same approach in an independent cohort of 190 adults with mild/moderate asthma and controls to identify mild/moderate asthma genes and their master regulators. Comparative analysis of the master regulator genes followed by validation testing in independent children with severe asthma (n = 21) and mild/moderate asthma (n = 154) was then performed. RESULTS: Nasal gene signatures for severe persistent asthma and for mild/moderate persistent asthma were identified; both were found to be enriched in coexpression network modules for ciliary function and inflammatory response. By applying probabilistic causal methods to these gene signatures and validation testing in independent cohorts, we identified (1) a master regulator gene common to asthma across severity and ages (FOXJ1); (2) master regulator genes of severe persistent asthma in children (LRRC23, TMEM231, CAPS, PTPRC, and FYB); and (3) master regulator genes of mild/moderate persistent asthma in children and adults (C1orf38 and FMNL1). The identified master regulators were statistically inferred to causally regulate the expression of downstream genes that modulate ciliary function and inflammatory response to influence asthma. CONCLUSION: The identified master regulator genes of asthma provide a novel path forward to further uncovering asthma mechanisms and therapy.

Gender Differences in Authorship of Critical Care Literature.

Rationale: Gender gaps exist in academic leadership positions in critical care. Peer-reviewed publications are crucial to career advancement, and yet little is known regarding gender differences in authorship of critical care research.Objectives: To evaluate gender differences in authorship of critical care literature.Methods: We used a validated database of author gender to analyze authorship of critical care articles indexed in PubMed between 2008 and 2018 in 40 frequently cited journals. High-impact journals were defined as those in the top 5% of all journals. We used mixed-effects logistic regression to evaluate the association of senior author gender with first and middle author gender, as well as association of first author gender with journal impact factor.Measurements and Main Results: Among 18,483 studies, 30.8% had female first authors, and 19.5% had female senior authors. Female authorship rose slightly over the last decade (average annual increases of 0.44% [P < 0.01] and 0.51% [P < 0.01] for female first and senior authors, respectively). When the senior author was female, the odds of female coauthorship rose substantially (first author adjusted odds ratio [aOR], 1.93; 95% confidence interval [CI], 1.71-2.17; middle author aOR, 1.48; 95% CI, 1.29-1.69). Female first authors had higher odds than men of publishing in lower-impact journals (aOR, 1.30; 95% CI, 1.16-1.45).Conclusions: Women comprise less than one-third of first authors and one-fourth of senior authors of critical care research, with minimal increase over the past decade. When the senior author was female, the odds of female coauthorship rose substantially. However, female first authors tend to publish in lower-impact journals. These findings may help explain the underrepresentation of women in critical care academic leadership positions and identify targets for improvement.

Association of Elevated Plasma Interleukin-18 Level With Increased Mortality in a Clinical Trial of Statin Treatment for Acute Respiratory Distress Syndrome.

OBJECTIVE: A high plasma level of inflammasome mediator interleukin-18 was associated with mortality in observational acute respiratory distress syndrome cohorts. Statin exposure increases both inflammasome activation and lung injury in mouse models. We tested whether randomization to statin therapy correlated with increased interleukin-18 in the ARDS Network Statins for Acutely Injured Lungs from Sepsis trial. DESIGN: Retrospective analysis of randomized controlled clinical trial. SETTING: Multicenter North American clinical trial, the ARDS Network Statins for Acutely Injured Lungs from Sepsis. PATIENTS: Six hundred eighty-three subjects with infection-related acute respiratory distress syndrome, representing 92% of the original trial population. INTERVENTIONS: Random assignment of rosuvastatin or placebo for up to 28 days or 3 days after ICU discharge. MEASUREMENTS AND MAIN RESULTS: We measured plasma interleukin-18 levels in all Statins for Acutely Injured Lungs from Sepsis patients with sample available at day 0 (baseline, n = 683) and day 3 (after randomization, n = 588). We tested the association among interleukin-18 level at baseline, rising interleukin-18, and the impact of statin therapy on 60-day mortality, adjusting for severity of illness. Baseline plasma interleukin-18 level greater than or equal to 800 pg/mL was highly associated with 60-day mortality, with a hazard of death of 2.3 (95% CI, 1.7-3.1). Rising plasma interleukin-18 was also associated with increased mortality. For each unit increase in log2 (interleukin-18) at day 3 compared with baseline, the hazard of death increased by 2.3 (95% CI, 1.5-3.5). Subjects randomized to statin were significantly more likely to experience a rise in plasma interleukin-18 levels. Subjects with acute kidney injury, shock, low baseline interleukin-18, and those not receiving systemic corticosteroids were more likely to experience rising interleukin-18. Randomization to statin therapy was associated with rising in interleukin-18 in all of those subsets, however. CONCLUSIONS: Elevated baseline plasma interleukin-18 was associated with higher mortality in sepsis-induced acute respiratory distress syndrome. A rise in plasma interleukin-18 was also associated with increased mortality and was more common in subjects randomized to statin therapy in this clinical trial.

Current Status and Future Opportunities in Lung Precision Medicine Research with a Focus on Biomarkers. An American Thoracic Society/National Heart, Lung, and Blood Institute Research Statement.

BACKGROUND: Thousands of biomarker tests are either available or under development for lung diseases. In many cases, adoption of these tests into clinical practice is outpacing the generation and evaluation of sufficient data to determine clinical utility and ability to improve health outcomes. There is a need for a systematically organized report that provides guidance on how to understand and evaluate use of biomarker tests for lung diseases. METHODS: We assembled a diverse group of clinicians and researchers from the American Thoracic Society and leaders from the National Heart, Lung, and Blood Institute with expertise in various aspects of precision medicine to review the current status of biomarker tests in lung diseases. Experts summarized existing biomarker tests that are available for lung cancer, pulmonary arterial hypertension, idiopathic pulmonary fibrosis, asthma, chronic obstructive pulmonary disease, sepsis, acute respiratory distress syndrome, cystic fibrosis, and other rare lung diseases. The group identified knowledge gaps that future research studies can address to efficiently translate biomarker tests into clinical practice, assess their cost-effectiveness, and ensure they apply to diverse, real-life populations. RESULTS: We found that the status of biomarker tests in lung diseases is highly variable depending on the disease. Nevertheless, biomarker tests in lung diseases show great promise in improving clinical care. To efficiently translate biomarkers into tests used widely in clinical practice, researchers need to address specific clinical unmet needs, secure support for biomarker discovery efforts, conduct analytical and clinical validation studies, ensure tests have clinical utility, and facilitate appropriate adoption into routine clinical practice. CONCLUSIONS: Although progress has been made toward implementation of precision medicine for lung diseases in clinical practice in certain settings, additional studies focused on addressing specific unmet clinical needs are required to evaluate the clinical utility of biomarkers; ensure their generalizability to diverse, real-life populations; and determine their cost-effectiveness.

Multicohort Analysis of Whole-Blood Gene Expression Data Does Not Form a Robust Diagnostic for Acute Respiratory Distress Syndrome.

OBJECTIVES: To identify a novel, generalizable diagnostic for acute respiratory distress syndrome using whole-blood gene expression arrays from multiple acute respiratory distress syndrome cohorts of varying etiologies. DATA SOURCES: We performed a systematic search for human whole-blood gene expression arrays of acute respiratory distress syndrome in National Institutes of Health Gene Expression Omnibus and ArrayExpress. We also included the Glue Grant gene expression cohorts. STUDY SELECTION: We included investigator-defined acute respiratory distress syndrome within 48 hours of diagnosis and compared these with relevant critically ill controls. DATA EXTRACTION: We used multicohort analysis of gene expression to identify genes significantly associated with acute respiratory distress syndrome, both with and without adjustment for clinical severity score. We performed gene ontology enrichment using Database for Annotation, Visualization and Integrated Discovery and cell type enrichment tests for both immune cells and pneumocyte gene expression. Finally, we selected a gene set optimized for diagnostic power across the datasets and used leave-one-dataset-out cross validation to assess robustness of the model. DATA SYNTHESIS: We identified datasets from three adult cohorts with sepsis, one pediatric cohort with acute respiratory failure, and two datasets of adult patients with trauma and burns, for a total of 148 acute respiratory distress syndrome cases and 268 critically ill controls. We identified 30 genes that were significantly associated with acute respiratory distress syndrome (false discovery rate < 20% and effect size >1.3), many of which had been previously associated with sepsis. When metaregression was used to adjust for clinical severity scores, none of these genes remained significant. Cell type enrichment was notable for bands and neutrophils, suggesting that the gene expression signature is one of acute inflammation rather than lung injury per se. Finally, an attempt to develop a generalizable diagnostic gene set for acute respiratory distress syndrome showed a mean area under the receiver-operating characteristic curve of only 0.63 on leave-one-dataset-out cross validation. CONCLUSIONS: The whole-blood gene expression signature across a wide clinical spectrum of acute respiratory distress syndrome is likely confounded by systemic inflammation, limiting the utility of whole-blood gene expression studies for uncovering a generalizable diagnostic gene signature.

Plasma mitochondrial DNA and metabolomic alterations in severe critical illness.

BACKGROUND: Cell-free plasma mitochondrial DNA (mtDNA) levels are associated with endothelial dysfunction and differential outcomes in critical illness. A substantial alteration in metabolic homeostasis is commonly observed in severe critical illness. We hypothesized that metabolic profiles significantly differ between critically ill patients relative to their level of plasma mtDNA. METHODS: We performed a metabolomic study with biorepository plasma samples collected from 73 adults with systemic inflammatory response syndrome or sepsis at a single academic medical center. Patients were treated in a 20-bed medical ICU between 2008 and 2010. To identify key metabolites and metabolic pathways related to plasma NADH dehydrogenase 1 (ND1) mtDNA levels in critical illness, we first generated metabolomic data using gas and liquid chromatography-mass spectroscopy. We performed fold change analysis and volcano plot visualization based on false discovery rate-adjusted p values to evaluate the distribution of individual metabolite concentrations relative to ND1 mtDNA levels. We followed this by performing orthogonal partial least squares discriminant analysis to identify individual metabolites that discriminated ND1 mtDNA groups. We then interrogated the entire metabolomic profile using pathway overrepresentation analysis to identify groups of metabolite pathways that were different relative to ND1 mtDNA levels. RESULTS: Metabolomic profiles significantly differed in critically ill patients with ND1 mtDNA levels ≥ 3200 copies/µl plasma relative to those with an ND1 mtDNA level < 3200 copies/µl plasma. Several analytical strategies showed that patients with ND1 mtDNA levels ≥ 3200 copies/µl plasma had significant decreases in glycerophosphocholines and increases in short-chain acylcarnitines. CONCLUSIONS: Differential metabolic profiles during critical illness are associated with cell-free plasma ND1 mtDNA levels that are indicative of cell damage. Elevated plasma ND1 mtDNA levels are associated with decreases in glycerophosphocholines and increases in short-chain acylcarnitines that reflect phospholipid metabolism dysregulation and decreased mitochondrial function, respectively.

Gene Expression Analysis to Assess the Relevance of Rodent Models to Human Lung Injury.

The relevance of animal models to human diseases is an area of intense scientific debate. The degree to which mouse models of lung injury recapitulate human lung injury has never been assessed. Integrating data from both human and animal expression studies allows for increased statistical power and identification of conserved differential gene expression across organisms and conditions. We sought comprehensive integration of gene expression data in experimental acute lung injury (ALI) in rodents compared with humans. We performed two separate gene expression multicohort analyses to determine differential gene expression in experimental animal and human lung injury. We used correlational and pathway analyses combined with external in vitro gene expression data to identify both potential drivers of underlying inflammation and therapeutic drug candidates. We identified 21 animal lung tissue datasets and three human lung injury bronchoalveolar lavage datasets. We show that the metasignatures of animal and human experimental ALI are significantly correlated despite these widely varying experimental conditions. The gene expression changes among mice and rats across diverse injury models (ozone, ventilator-induced lung injury, LPS) are significantly correlated with human models of lung injury (Pearson r = 0.33-0.45, P < 1E-16). Neutrophil signatures are enriched in both animal and human lung injury. Predicted therapeutic targets, peptide ligand signatures, and pathway analyses are also all highly overlapping. Gene expression changes are similar in animal and human experimental ALI, and provide several physiologic and therapeutic insights to the disease.