Integrated longitudinal multiomics study identifies immune programs associated with acute COVID-19 severity and mortality.

BACKGROUNDPatients hospitalized for COVID-19 exhibit diverse clinical outcomes, with outcomes for some individuals diverging over time even though their initial disease severity appears similar to that of other patients. A systematic evaluation of molecular and cellular profiles over the full disease course can link immune programs and their coordination with progression heterogeneity.METHODSWe performed deep immunophenotyping and conducted longitudinal multiomics modeling, integrating 10 assays for 1,152 Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) study participants and identifying several immune cascades that were significant drivers of differential clinical outcomes.RESULTSIncreasing disease severity was driven by a temporal pattern that began with the early upregulation of immunosuppressive metabolites and then elevated levels of inflammatory cytokines, signatures of coagulation, formation of neutrophil extracellular traps, and T cell functional dysregulation. A second immune cascade, predictive of 28-day mortality among critically ill patients, was characterized by reduced total plasma Igs and B cells and dysregulated IFN responsiveness. We demonstrated that the balance disruption between IFN-stimulated genes and IFN inhibitors is a crucial biomarker of COVID-19 mortality, potentially contributing to failure of viral clearance in patients with fatal illness.CONCLUSIONOur longitudinal multiomics profiling study revealed temporal coordination across diverse omics that potentially explain the disease progression, providing insights that can inform the targeted development of therapies for patients hospitalized with COVID-19, especially those who are critically ill.TRIAL REGISTRATIONClinicalTrials.gov NCT04378777.FUNDINGNIH (5R01AI135803-03, 5U19AI118608-04, 5U19AI128910-04, 4U19AI090023-11, 4U19AI118610-06, R01AI145835-01A1S1, 5U19AI062629-17, 5U19AI057229-17, 5U19AI125357-05, 5U19AI128913-03, 3U19AI077439-13, 5U54AI142766-03, 5R01AI104870-07, 3U19AI089992-09, 3U19AI128913-03, and 5T32DA018926-18); NIAID, NIH (3U19AI1289130, U19AI128913-04S1, and R01AI122220); and National Science Foundation (DMS2310836).

Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID pipeline.

Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. To address this need, we developed the CZ ID AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and WGS data. Its development represents a critical step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.

Doxycycline post-exposure prophylaxis for sexually transmitted infections impacts the gut antimicrobial resistome.

Doxycycline post-exposure prophylaxis (doxy-PEP) reduces bacterial sexually transmitted infections (STIs) among men who have sex with men and transgender women. While poised for widespread clinical implementation, the impact of doxy-PEP on antimicrobial resistance remains a primary concern as its effects on the gut microbiome and resistome, or the antimicrobial resistance genes (ARGs) present in the gut microbiome, are unknown. To investigate these effects, we studied participants from a randomized clinical trial who either received doxy-PEP as a one-time doxycycline 200 mg taken after condomless sex (DP arm, n = 100) or standard of care treatment (SOC arm, n = 50). From self-collected rectal swabs at enrollment (day-0) and after 6 months (month-6), we performed metagenomic DNA sequencing (DNA-seq) or metatranscriptomic RNA sequencing (RNA-seq). DNA-seq data was analyzable from 127 samples derived from 89 participants, and RNA-seq data from 86 samples derived from 70 participants. We compared the bacterial microbiome and resistome between the two study arms and over time. Tetracycline ARGs were detected in all day-0 DNA-seq samples and 85% of day-0 RNA-seq samples. The proportional mass of tetracycline ARGs in the resistome increased between day-0 and month-6 in DP participants from 46-51% in the metagenome (p = 0.02) and 4-15% in the metatranscriptome (p < 0.01), but no changes in other ARG classes were observed. Exposure to a higher number of doxycycline doses correlated with proportional enrichment of tetracycline ARGs in the metagenome (Spearman's ρ = 0.23, p < 0.01) and metatranscriptome (Spearman's ρ = 0.55, p < 0.01). Bacterial microbiome alpha diversity, beta diversity, and total bacterial mass did not differ between day-0 and month-6 samples from DP participants when assessed by either DNA-seq or RNA-seq. In an abundance-based correlation analysis, we observed an increase over time in the strength of the correlation between tetracycline ARGs and specific bacterial taxa, including some common human pathogens. In sum, doxy-PEP use over a 6-month period was associated with an increase in the proportion of tetracycline ARGs comprising the gut resistome, and an increase in the expression of tetracycline ARGs. Notably, doxy-PEP did not significantly alter alpha diversity or taxonomic composition of the gut microbiome, and did not demonstrate significant increases in non-tetracycline ARG classes. Further studies and population level surveillance are needed to understand the implications of these findings as doxy-PEP is implemented as a public health strategy.

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.

Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID pipeline.

Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. To address this need, we developed the Chan Zuckerberg ID (CZ ID) AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and WGS data. Its development represents a critical step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.

Host-microbe multiomic profiling reveals age-dependent immune dysregulation associated with COVID-19 immunopathology.

Age is a major risk factor for severe coronavirus disease 2019 (COVID-19), yet the mechanisms behind this relationship have remained incompletely understood. To address this, we evaluated the impact of aging on host immune response in the blood and the upper airway, as well as the nasal microbiome in a prospective, multicenter cohort of 1031 vaccine-naïve patients hospitalized for COVID-19 between 18 and 96 years old. We performed mass cytometry, serum protein profiling, anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody assays, and blood and nasal transcriptomics. We found that older age correlated with increased SARS-CoV-2 viral abundance upon hospital admission, delayed viral clearance, and increased type I interferon gene expression in both the blood and upper airway. We also observed age-dependent up-regulation of innate immune signaling pathways and down-regulation of adaptive immune signaling pathways. Older adults had lower naïve T and B cell populations and higher monocyte populations. Over time, older adults demonstrated a sustained induction of pro-inflammatory genes and serum chemokines compared with younger individuals, suggesting an age-dependent impairment in inflammation resolution. Transcriptional and protein biomarkers of disease severity differed with age, with the oldest adults exhibiting greater expression of pro-inflammatory genes and proteins in severe disease. Together, our study finds that aging is associated with impaired viral clearance, dysregulated immune signaling, and persistent and potentially pathologic activation of pro-inflammatory genes and proteins.

Biological Effects of Corticosteroids on Pneumococcal Pneumonia in Mice and Humans.

Background: Streptococcus pneumoniae is the most common bacterial cause of community acquired pneumonia and the acute respiratory distress syndrome (ARDS). Some clinical trials have demonstrated a beneficial effect of corticosteroid therapy in community acquired pneumonia, COVID-19, and ARDS, but the mechanisms of this benefit remain unclear. The objective of this study was to investigate the effects of corticosteroids on the pulmonary biology of pneumococcal pneumonia in an observational cohort of mechanically ventilated patients and in a mouse model of bacterial pneumonia with Streptococcus pneumoniae. Methods: We studied gene expression with lower respiratory tract transcriptomes from a cohort of mechanically ventilated patients and in mice. We also carried out comprehensive physiologic, biochemical, and histological analyses in mice to identify the mechanisms of lung injury in Streptococcus pneumoniae with and without adjunctive steroid therapy. Results: Transcriptomic analysis identified pleiotropic effects of steroid therapy on the lower respiratory tract in critically ill patients with pneumococcal pneumonia, findings that were reproducible in mice. In mice with pneumonia, dexamethasone in combination with ceftriaxone reduced (1) pulmonary edema formation, (2) alveolar protein permeability, (3) proinflammatory cytokine release, (4) histopathologic lung injury score, and (5) hypoxemia but did not increase bacterial burden. Conclusions: The gene expression studies in patients and in the mice support the clinical relevance of the mouse studies, which replicate several features of pneumococcal pneumonia and steroid therapy in humans. In combination with appropriate antibiotic therapy in mice, treatment of pneumococcal pneumonia with steroid therapy reduced hypoxemia, pulmonary edema, lung permeability, and histologic criteria of lung injury, and also altered inflammatory responses at the protein and gene expression level. The results from these studies provide evidence for the mechanisms that may explain the beneficial effects of glucocorticoid therapy in patients with community acquired pneumonia from Streptococcus Pneumoniae.

Molecular Phenotypes of Acute Respiratory Distress Syndrome in the ROSE Trial Have Differential Outcomes and Gene Expression Patterns That Differ at Baseline and Longitudinally over Time.

Rationale: Two molecular phenotypes have been identified in acute respiratory distress syndrome (ARDS). In the ROSE (Reevaluation of Systemic Early Neuromuscular Blockade) trial of cisatracurium in moderate to severe ARDS, we addressed three unanswered questions: 1) Do the same phenotypes emerge in a more severe ARDS cohort with earlier recruitment; 2) Do phenotypes respond differently to neuromuscular blockade? and 3) What biological pathways most differentiate inflammatory phenotypes?Methods: We performed latent class analysis in ROSE using preenrollment clinical and protein biomarkers. In a subset of patients (n = 134), we sequenced whole-blood RNA using enrollment and Day 2 samples and performed differential gene expression and pathway analyses. Informed by the differential gene expression analysis, we measured additional plasma proteins and evaluated their abundance relative to gene expression amounts.Measurements and Main Results: In ROSE, we identified the hypoinflammatory (60.4%) and hyperinflammatory (39.6%) phenotypes with similar biological and clinical characteristics as prior studies, including higher mortality at Day 90 for the hyperinflammatory phenotype (30.3% vs. 61.6%; P < 0.0001). We observed no treatment interaction between the phenotypes and randomized groups for mortality. The hyperinflammatory phenotype was enriched for genes associated with innate immune response, tissue remodeling, and zinc metabolism at Day 0 and collagen synthesis and neutrophil degranulation at Day 2. Longitudinal changes in gene expression patterns differed dependent on survivorship. For most highly expressed genes, we observed correlations with their corresponding plasma proteins' abundance. However, for the class-defining plasma proteins in the latent class analysis, no correlation was observed with their corresponding genes' expression.Conclusions: The hyperinflammatory and hypoinflammatory phenotypes have different clinical, protein, and dynamic transcriptional characteristics. These findings support the clinical and biological potential of molecular phenotypes to advance precision care in ARDS.

Host-Microbe Multiomic Profiling Reveals Age-Dependent COVID-19 Immunopathology.

Age is a major risk factor for severe coronavirus disease-2019 (COVID-19), yet the mechanisms responsible for this relationship have remained incompletely understood. To address this, we evaluated the impact of aging on host and viral dynamics in a prospective, multicenter cohort of 1,031 patients hospitalized for COVID-19, ranging from 18 to 96 years of age. We performed blood transcriptomics and nasal metatranscriptomics, and measured peripheral blood immune cell populations, inflammatory protein expression, anti-SARS-CoV-2 antibodies, and anti-interferon (IFN) autoantibodies. We found that older age correlated with an increased SARS-CoV-2 viral load at the time of admission, and with delayed viral clearance over 28 days. This contributed to an age-dependent increase in type I IFN gene expression in both the respiratory tract and blood. We also observed age-dependent transcriptional increases in peripheral blood IFN-γ, neutrophil degranulation, and Toll like receptor (TLR) signaling pathways, and decreases in T cell receptor (TCR) and B cell receptor signaling pathways. Over time, older adults exhibited a remarkably sustained induction of proinflammatory genes (e.g., CXCL6) and serum chemokines (e.g., CXCL9) compared to younger individuals, highlighting a striking age-dependent impairment in inflammation resolution. Augmented inflammatory signaling also involved the upper airway, where aging was associated with upregulation of TLR, IL17, type I IFN and IL1 pathways, and downregulation TCR and PD-1 signaling pathways. Metatranscriptomics revealed that the oldest adults exhibited disproportionate reactivation of herpes simplex virus and cytomegalovirus in the upper airway following hospitalization. Mass cytometry demonstrated that aging correlated with reduced naïve T and B cell populations, and increased monocytes and exhausted natural killer cells. Transcriptional and protein biomarkers of disease severity markedly differed with age, with the oldest adults exhibiting greater expression of TLR and inflammasome signaling genes, as well as proinflammatory proteins (e.g., IL6, CXCL8), in severe COVID-19 compared to mild/moderate disease. Anti-IFN autoantibody prevalence correlated with both age and disease severity. Taken together, this work profiles both host and microbe in the blood and airway to provide fresh insights into aging-related immune changes in a large cohort of vaccine-naïve COVID-19 patients. We observed age-dependent immune dysregulation at the transcriptional, protein and cellular levels, manifesting in an imbalance of inflammatory responses over the course of hospitalization, and suggesting potential new therapeutic targets.

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.

Features of acute COVID-19 associated with post-acute sequelae of SARS-CoV-2 phenotypes: results from the IMPACC study.

Post-acute sequelae of SARS-CoV-2 (PASC) is a significant public health concern. We describe Patient Reported Outcomes (PROs) on 590 participants prospectively assessed from hospital admission for COVID-19 through one year after discharge. Modeling identified 4 PRO clusters based on reported deficits (minimal, physical, mental/cognitive, and multidomain), supporting heterogenous clinical presentations in PASC, with sub-phenotypes associated with female sex and distinctive comorbidities. During the acute phase of disease, a higher respiratory SARS-CoV-2 viral burden and lower Receptor Binding Domain and Spike antibody titers were associated with both the physical predominant and the multidomain deficit clusters. A lower frequency of circulating B lymphocytes by mass cytometry (CyTOF) was observed in the multidomain deficit cluster. Circulating fibroblast growth factor 21 (FGF21) was significantly elevated in the mental/cognitive predominant and the multidomain clusters. Future efforts to link PASC to acute anti-viral host responses may help to better target treatment and prevention of PASC.

The antibiotic resistance reservoir of the lung microbiome expands with age in a population of critically ill patients.

Antimicrobial resistant lower respiratory tract infections are an increasing public health threat and an important cause of global mortality. The lung microbiome can influence susceptibility of respiratory tract infections and represents an important reservoir for exchange of antimicrobial resistance genes. Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene burden, however, corollary studies in the lung microbiome remain absent. We performed an observational study of children and adults with acute respiratory failure admitted to the intensive care unit. From tracheal aspirate RNA sequencing data, we evaluated age-related differences in detectable antimicrobial resistance gene expression in the lung microbiome. Using a multivariable logistic regression model, we find that detection of antimicrobial resistance gene expression was significantly higher in adults compared with children after adjusting for demographic and clinical characteristics. This association remained significant after additionally adjusting for lung bacterial microbiome characteristics, and when modeling age as a continuous variable. The proportion of adults expressing beta-lactam, aminoglycoside, and tetracycline antimicrobial resistance genes was higher compared to children. Together, these findings shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

Viral Detection by Reverse Transcriptase Polymerase Chain Reaction in Upper Respiratory Tract and Metagenomic RNA Sequencing in Lower Respiratory Tract in Critically Ill Children With Suspected Lower Respiratory Tract Infection.

OBJECTIVES: Viral lower respiratory tract infection (vLRTI) contributes to substantial morbidity and mortality in children. Diagnosis is typically confirmed by reverse transcriptase polymerase chain reaction (RT-PCR) of nasopharyngeal specimens in hospitalized patients; however, it is unknown whether nasopharyngeal detection accurately reflects presence of virus in the lower respiratory tract (LRT). This study evaluates agreement between viral detection from nasopharyngeal specimens by RT-PCR compared with metagenomic next-generation RNA sequencing (RNA-Seq) from tracheal aspirates (TAs). DESIGN: This is an analysis of of a seven-center prospective cohort study. SETTING: Seven PICUs within academic children's hospitals in the United States. PATIENTS: Critically ill children (from 1 mo to 18 yr) who required mechanical ventilation via endotracheal tube for greater than or equal to 72 hours. INTERVENTIONS: We evaluated agreement in viral detection between paired upper and LRT samples. Results of clinical nasopharyngeal RT-PCR were compared with TA RNA-Seq. Positive and negative predictive agreement and Cohen's Kappa were used to assess agreement. MEASUREMENTS AND MAIN RESULTS: Of 295 subjects with paired testing available, 200 (68%) and 210 (71%) had positive viral testing by RT-PCR from nasopharyngeal and RNA-Seq from TA samples, respectively; 184 (62%) were positive by both nasopharyngeal RT-PCR and TA RNA-Seq for a virus, and 69 (23%) were negative by both methods. Nasopharyngeal RT-PCR detected the most abundant virus identified by RNA-Seq in 92.4% of subjects. Among the most frequent viruses detected, respiratory syncytial virus demonstrated the highest degree of concordance (κ = 0.89; 95% CI, 0.83-0.94), whereas rhinovirus/enterovirus demonstrated lower concordance (κ = 0.55; 95% CI, 0.44-0.66). Nasopharyngeal PCR was more likely to detect multiple viruses than TA RNA-Seq (54 [18.3%] vs 24 [8.1%], p ≤ 0.001). CONCLUSIONS: Viral nucleic acid detection in the upper versus LRT reveals good overall agreement, but concordance depends on the virus. Further studies are indicated to determine the utility of LRT sampling or the use of RNA-Seq to determine LRTI etiology.

Cell-Specific Transposable Element Gene Expression Analysis Identifies Associations with Systemic Lupus Erythematosus Phenotypes.

There is an established yet unexplained link between interferon (IFN) and systemic lupus erythematosus (SLE). The expression of sequences derived from transposable elements (TEs) may contribute to production of type I IFNs and generation of autoantibodies. We profiled cell-sorted RNA-seq data (CD4+ T cells, CD14+ monocytes, CD19+ B cells, and NK cells) from PBMCs of 120 SLE patients and quantified TE expression identifying 27,135 TEs. We tested for differential TE expression across 10 SLE phenotypes including autoantibody production and disease activity and discovered 731 differentially expressed (DE) TEs whose effects were mostly cell-specific and phenotype-specific. DE TEs were enriched for specific families and viral genes encoded in TE sequences. Increased expression of DE TEs was associated with genes involved in antiviral activity such as LY6E, ISG15, TRIM22 and pathways such as interferon signaling. These findings suggest that expression of TEs contributes to activation of SLE-related mechanisms in a cell-specific manner, which can impact disease diagnostics and therapeutics.

Integrated longitudinal multi-omics study identifies immune programs associated with COVID-19 severity and mortality in 1152 hospitalized participants.

Hospitalized COVID-19 patients exhibit diverse clinical outcomes, with some individuals diverging over time even though their initial disease severity appears similar. A systematic evaluation of molecular and cellular profiles over the full disease course can link immune programs and their coordination with progression heterogeneity. In this study, we carried out deep immunophenotyping and conducted longitudinal multi-omics modeling integrating ten distinct assays on a total of 1,152 IMPACC participants and identified several immune cascades that were significant drivers of differential clinical outcomes. Increasing disease severity was driven by a temporal pattern that began with the early upregulation of immunosuppressive metabolites and then elevated levels of inflammatory cytokines, signatures of coagulation, NETosis, and T-cell functional dysregulation. A second immune cascade, predictive of 28-day mortality among critically ill patients, was characterized by reduced total plasma immunoglobulins and B cells, as well as dysregulated IFN responsiveness. We demonstrated that the balance disruption between IFN-stimulated genes and IFN inhibitors is a crucial biomarker of COVID-19 mortality, potentially contributing to the failure of viral clearance in patients with fatal illness. Our longitudinal multi-omics profiling study revealed novel temporal coordination across diverse omics that potentially explain disease progression, providing insights that inform the targeted development of therapies for hospitalized COVID-19 patients, especially those critically ill.

The antibiotic resistance reservoir of the lung microbiome expands with age.

Antimicrobial resistant lower respiratory tract infections (LRTI) are an increasing public health threat, and an important cause of global mortality. The lung microbiome influences LRTI susceptibility and represents an important reservoir for exchange of antimicrobial resistance genes (ARGs). Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene (ARG) burden, however corollary studies in the lung microbiome remain absent, despite the respiratory tract representing one of the most clinically significant sites for drug resistant infections. We performed a prospective, multicenter observational study of 261 children and 88 adults with acute respiratory failure, ranging in age from 31 days to ≥ 89 years, admitted to intensive care units in the United States. We performed RNA sequencing on tracheal aspirates collected within 72 hours of intubation, and evaluated age-related differences in detectable ARG expression in the lung microbiome as a primary outcome. Secondary outcomes included number and classes of ARGs detected, proportion of patients with an ARG class, and composition of the lung microbiome. Multivariable logistic regression models (adults vs children) or continuous age (years) were adjusted for sex, race/ethnicity, LRTI status, and days from intubation to specimen collection. Detection of ARGs was significantly higher in adults compared with children after adjusting for sex, race/ethnicity, LRTI diagnosis, and days from intubation to specimen collection (adjusted odds ratio (aOR): 2.16, 95% confidence interval (CI): 1.10-4.22). A greater proportion of adults compared with children had beta-lactam ARGs (31% (CI: 21-41%) vs 13% (CI: 10-18%)), aminoglycoside ARGs (20% (CI: 13-30%) vs 2% (CI: 0.6-4%)), and tetracycline ARGs (14% (CI: 7-23%) vs 3% (CI: 1-5%)). Adults ≥70 years old had the highest proportion of these three ARG classes. The total bacterial abundance of the lung microbiome increased with age, and microbiome alpha diversity varied with age. Taxonomic composition of the lung microbiome, measured by Bray Curtis dissimilarity index, differed between adults and children (p = 0.003). The association between age and increased ARG detection remained significant after additionally including lung microbiome total bacterial abundance and alpha diversity in the multivariable logistic regression model (aOR: 2.38, (CI: 1.25-4.54)). Furthermore, this association remained robust when modeling age as a continuous variable (aOR: 1.02, (CI: 1.01-1.03) per year of age). Taken together, our results demonstrate that age is an independent risk factor for ARG detection in the lower respiratory tract microbiome. These data shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

A myeloid program associated with COVID-19 severity is decreased by therapeutic blockade of IL-6 signaling.

Altered myeloid inflammation and lymphopenia are hallmarks of severe infections. We identified the upregulated EN-RAGE gene program in airway and blood myeloid cells from patients with acute lung injury from SARS-CoV-2 or other causes across 7 cohorts. This program was associated with greater clinical severity and predicted future mechanical ventilation and death. EN-RAGEhi myeloid cells express features consistent with suppressor cell functionality, including low HLA-DR and high PD-L1. Sustained EN-RAGE program expression in airway and blood myeloid cells correlated with clinical severity and increasing expression of T cell dysfunction markers. IL-6 upregulated many EN-RAGE program genes in monocytes in vitro. IL-6 signaling blockade by tocilizumab in a placebo-controlled clinical trial led to rapid normalization of EN-RAGE and T cell gene expression. This identifies IL-6 as a key driver of myeloid dysregulation associated with worse clinical outcomes in COVID-19 patients and provides insights into shared pathophysiological mechanisms in non-COVID-19 ARDS.

In host evolution of beta lactam resistance during active treatment for Pseudomonas aeruginosa bacteremia.

Multidrug-resistant (MDR) Pseudomonas aeruginosa has been declared a serious threat by the United States Centers for Disease Control and Prevention. Here, we used whole genome sequencing (WGS) to investigate recurrent P. aeruginosa bloodstream infections in a severely immunocompromised patient. The infections demonstrated unusual, progressive increases in resistance to beta lactam antibiotics in the setting of active treatment with appropriate, guideline-directed agents. WGS followed by comparative genomic analysis of isolates collected over 44 days demonstrated in host evolution of a single P. aeruginosa isolate characterized by stepwise acquisition of two de-novo genetic resistance mechanisms over the course of treatment. We found a novel deletion affecting the ampC repressor ampD and neighboring gene ampE, which associated with initial cefepime treatment failure. This was followed by acquisition of a porin nonsense mutation, OprD, associated with resistance to carbapenems. This study highlights the potential for in-host evolution of P. aeruginosa during bloodstream infections in severely immunocompromised patients despite appropriate antimicrobial therapy. In addition, it demonstrates the utility of WGS for understanding unusual resistance patterns in the clinical context.

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. We performed bulk and single-cell RNA sequencing of the lower respiratory tract and blood, and plasma cytokine profiling to study the effect of dexamethasone on systemic and pulmonary immune cells. We find decreased signatures of antigen presentation, T cell recruitment, and viral injury in patients treated with dexamethasone. We identify compartment- and cell- specific differences in the effect of dexamethasone in patients with severe COVID-19 that are reproducible in publicly available datasets. Our results highlight the importance of studying compartmentalized inflammation in critically ill patients.