Machine learning links unresolving secondary pneumonia to mortality in patients with severe pneumonia, including COVID-19.

BACKGROUNDDespite guidelines promoting the prevention and aggressive treatment of ventilator-associated pneumonia (VAP), the importance of VAP as a driver of outcomes in mechanically ventilated patients, including patients with severe COVID-19, remains unclear. We aimed to determine the contribution of unsuccessful treatment of VAP to mortality for patients with severe pneumonia.METHODSWe performed a single-center, prospective cohort study of 585 mechanically ventilated patients with severe pneumonia and respiratory failure, 190 of whom had COVID-19, who underwent at least 1 bronchoalveolar lavage. A panel of intensive care unit (ICU) physicians adjudicated the pneumonia episodes and endpoints on the basis of clinical and microbiological data. Given the relatively long ICU length of stay (LOS) among patients with COVID-19, we developed a machine-learning approach called CarpeDiem, which grouped similar ICU patient-days into clinical states based on electronic health record data.RESULTSCarpeDiem revealed that the long ICU LOS among patients with COVID-19 was attributable to long stays in clinical states characterized primarily by respiratory failure. While VAP was not associated with mortality overall, the mortality rate was higher for patients with 1 episode of unsuccessfully treated VAP compared with those with successfully treated VAP (76.4% versus 17.6%, P < 0.001). For all patients, including those with COVID-19, CarpeDiem demonstrated that unresolving VAP was associated with a transitions to clinical states associated with higher mortality.CONCLUSIONSUnsuccessful treatment of VAP is associated with higher mortality. The relatively long LOS for patients with COVID-19 was primarily due to prolonged respiratory failure, placing them at higher risk of VAP.FUNDINGNational Institute of Allergy and Infectious Diseases (NIAID), NIH grant U19AI135964; National Heart, Lung, and Blood Institute (NHLBI), NIH grants R01HL147575, R01HL149883, R01HL153122, R01HL153312, R01HL154686, R01HL158139, P01HL071643, and P01HL154998; National Heart, Lung, and Blood Institute (NHLBI), NIH training grants T32HL076139 and F32HL162377; National Institute on Aging (NIA), NIH grants K99AG068544, R21AG075423, and P01AG049665; National Library of Medicine (NLM), NIH grant R01LM013337; National Center for Advancing Translational Sciences (NCATS), NIH grant U01TR003528; Veterans Affairs grant I01CX001777; Chicago Biomedical Consortium grant; Northwestern University Dixon Translational Science Award; Simpson Querrey Lung Institute for Translational Science (SQLIFTS); Canning Thoracic Institute of Northwestern Medicine.

Hypercapnia alters stroma-derived Wnt production to limit ß-catenin signaling and proliferation in AT2 cells.

Persistent symptoms and radiographic abnormalities suggestive of failed lung repair are among the most common symptoms in patients with COVID-19 after hospital discharge. In mechanically ventilated patients with acute respiratory distress syndrome (ARDS) secondary to SARS-CoV-2 pneumonia, low tidal volumes to reduce ventilator-induced lung injury necessarily elevate blood CO2 levels, often leading to hypercapnia. The role of hypercapnia on lung repair after injury is not completely understood. Here - using a mouse model of hypercapnia exposure, cell lineage tracing, spatial transcriptomics, and 3D cultures - we show that hypercapnia limits ß-catenin signaling in alveolar type II (AT2) cells, leading to their reduced proliferative capacity. Hypercapnia alters expression of major Wnts in PDGFRα+ fibroblasts from those maintaining AT2 progenitor activity toward those that antagonize ß-catenin signaling, thereby limiting progenitor function. Constitutive activation of ß-catenin signaling in AT2 cells or treatment of organoid cultures with recombinant WNT3A protein bypasses the inhibitory effects of hypercapnia. Inhibition of AT2 proliferation in patients with hypercapnia may contribute to impaired lung repair after injury, preventing sealing of the epithelial barrier and increasing lung flooding, ventilator dependency, and mortality.

Obesity Is Associated with Attenuated Tissue Immunity in COVID-19.

RATIONALE: Obesity affects 40% of US adults, is associated with a pro-inflammatory state, and presents a significant risk factor for the development of severe COVID-19. To date, there is limited information on how obesity might affect immune cell responses in SARS-CoV-2 infection. OBJECTIVES: To determine the impact of obesity on respiratory tract immunity in COVID-19 across human lifespan. METHODS: We analysed single cell transcriptomes from bronchiolar lavage in three ventilated adult cohorts with (n=24) or without COVID-19 (n=9), from nasal immune cells in children with (n=14) or without COVID-19 (n=19), and from peripheral blood mononuclear cells in an independent adult COVID-19 cohort (n=42), comparing obese (Ob) and non-obese subjects (N-Ob). MEASUREMENTS AND MAIN RESULTS: Surprisingly, we found that adult Ob subjects had attenuated lung immune/inflammatory responses in SARS-CoV-2 infection, with decreased expression of interferon (IFN)α, IFNγ and tumour necrosis factor (TNF) alpha response gene signatures in almost all lung epithelial and immune cell subsets, and lower expression of IFNG and TNF in specific lung immune cells. Peripheral blood immune cells in an independent adult cohort showed a similar, but less marked, reduction in type I IFN and IFNγ response genes, as well as decreased serum IFNα in Ob patients with SARS-CoV-2. Nasal immune cells from Ob children with COVID-19 also showed reduced enrichment of IFNα and IFNγ response genes. CONCLUSIONS: These findings show blunted tissue immune responses in Ob COVID-19 patients, with implications for treatment stratification, supporting the specific application of inhaled recombinant type I IFNs in this vulnerable subset. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Biologically informed deep learning to query gene programs in single-cell atlases.

The increasing availability of large-scale single-cell atlases has enabled the detailed description of cell states. In parallel, advances in deep learning allow rapid analysis of newly generated query datasets by mapping them into reference atlases. However, existing data transformations learned to map query data are not easily explainable using biologically known concepts such as genes or pathways. Here we propose expiMap, a biologically informed deep-learning architecture that enables single-cell reference mapping. ExpiMap learns to map cells into biologically understandable components representing known 'gene programs'. The activity of each cell for a gene program is learned while simultaneously refining them and learning de novo programs. We show that expiMap compares favourably to existing methods while bringing an additional layer of interpretability to integrative single-cell analysis. Furthermore, we demonstrate its applicability to analyse single-cell perturbation responses in different tissues and species and resolve responses of patients who have coronavirus disease 2019 to different treatments across cell types.

Age-related Differences in the Nasal Mucosal Immune Response to SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 180 million people since the onset of the pandemic. Despite similar viral load and infectivity rates between children and adults, children rarely develop severe illness. Differences in the host response to the virus at the primary infection site are among the mechanisms proposed to account for this disparity. Our objective was to investigate the host response to SARS-CoV-2 in the nasal mucosa in children and adults and compare it with the host response to respiratory syncytial virus (RSV) and influenza virus. We analyzed clinical outcomes and gene expression in the nasal mucosa of 36 children with SARS-CoV-2, 24 children with RSV, 9 children with influenza virus, 16 adults with SARS-CoV-2, and 7 healthy pediatric and 13 healthy adult controls. In both children and adults, infection with SARS-CoV-2 led to an IFN response in the nasal mucosa. The magnitude of the IFN response correlated with the abundance of viral reads, not the severity of illness, and was comparable between children and adults infected with SARS-CoV-2 and children with severe RSV infection. Expression of ACE2 and TMPRSS2 did not correlate with age or presence of viral infection. SARS-CoV-2-infected adults had increased expression of genes involved in neutrophil activation and T-cell receptor signaling pathways compared with SARS-CoV-2-infected children, despite similar severity of illness and viral reads. Age-related differences in the immune response to SARS-CoV-2 may place adults at increased risk of developing severe illness.

Mapping single-cell data to reference atlases by transfer learning.

Large single-cell atlases are now routinely generated to serve as references for analysis of smaller-scale studies. Yet learning from reference data is complicated by batch effects between datasets, limited availability of computational resources and sharing restrictions on raw data. Here we introduce a deep learning strategy for mapping query datasets on top of a reference called single-cell architectural surgery (scArches). scArches uses transfer learning and parameter optimization to enable efficient, decentralized, iterative reference building and contextualization of new datasets with existing references without sharing raw data. Using examples from mouse brain, pancreas, immune and whole-organism atlases, we show that scArches preserves biological state information while removing batch effects, despite using four orders of magnitude fewer parameters than de novo integration. scArches generalizes to multimodal reference mapping, allowing imputation of missing modalities. Finally, scArches retains coronavirus disease 2019 (COVID-19) disease variation when mapping to a healthy reference, enabling the discovery of disease-specific cell states. scArches will facilitate collaborative projects by enabling iterative construction, updating, sharing and efficient use of reference atlases.

Distinctive features of severe SARS-CoV-2 pneumonia.

The coronavirus disease 2019 (COVID-19) pandemic is among the most important public health crises of our generation. Despite the promise of prevention offered by effective vaccines, patients with severe COVID-19 will continue to populate hospitals and intensive care units for the foreseeable future. The most common clinical presentation of severe COVID-19 is hypoxemia and respiratory failure, typical of the acute respiratory distress syndrome (ARDS). Whether the clinical features and pathobiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia differ from those of pneumonia secondary to other pathogens is unclear. This uncertainty has created variability in the application of historically proven therapies for ARDS to patients with COVID-19. We review the available literature and find many similarities between patients with ARDS from pneumonia attributable to SARS-CoV-2 versus other respiratory pathogens. A notable exception is the long duration of illness among patients with COVID-19, which could result from its unique pathobiology. Available data support the use of care pathways and therapies proven effective for patients with ARDS, while pointing to unique features that might be therapeutically targeted for patients with severe SARS-CoV-2 pneumonia.

Lung transplantation for patients with severe COVID-19.

Lung transplantation can potentially be a life-saving treatment for patients with nonresolving COVID-19-associated respiratory failure. Concerns limiting lung transplantation include recurrence of SARS-CoV-2 infection in the allograft, technical challenges imposed by viral-mediated injury to the native lung, and the potential risk for allograft infection by pathogens causing ventilator-associated pneumonia in the native lung. Additionally, the native lung might recover, resulting in long-term outcomes preferable to those of transplant. Here, we report the results of lung transplantation in three patients with nonresolving COVID-19-associated respiratory failure. We performed single-molecule fluorescence in situ hybridization (smFISH) to detect both positive and negative strands of SARS-CoV-2 RNA in explanted lung tissue from the three patients and in additional control lung tissue samples. We conducted extracellular matrix imaging and single-cell RNA sequencing on explanted lung tissue from the three patients who underwent transplantation and on warm postmortem lung biopsies from two patients who had died from COVID-19-associated pneumonia. Lungs from these five patients with prolonged COVID-19 disease were free of SARS-CoV-2 as detected by smFISH, but pathology showed extensive evidence of injury and fibrosis that resembled end-stage pulmonary fibrosis. Using machine learning, we compared single-cell RNA sequencing data from the lungs of patients with late-stage COVID-19 to that from the lungs of patients with pulmonary fibrosis and identified similarities in gene expression across cell lineages. Our findings suggest that some patients with severe COVID-19 develop fibrotic lung disease for which lung transplantation is their only option for survival.

The lung microenvironment shapes a dysfunctional response of alveolar macrophages in aging.

Alveolar macrophages orchestrate the response to viral infections. Age-related changes in these cells may underlie the differential severity of pneumonia in older patients. We performed an integrated analysis of single-cell RNA-Seq data that revealed homogenous age-related changes in the alveolar macrophage transcriptome in humans and mice. Using genetic lineage tracing with sequential injury, heterochronic adoptive transfer, and parabiosis, we found that the lung microenvironment drove an age-related resistance of alveolar macrophages to proliferation that persisted during influenza A viral infection. Ligand-receptor pair analysis localized these changes to the extracellular matrix, where hyaluronan was increased in aged animals and altered the proliferative response of bone marrow-derived macrophages to granulocyte macrophage colony-stimulating factor (GM-CSF). Our findings suggest that strategies targeting the aging lung microenvironment will be necessary to restore alveolar macrophage function in aging.

Circuits between infected macrophages and T cells in SARS-CoV-2 pneumonia.

Some patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop severe pneumonia and acute respiratory distress syndrome1 (ARDS). Distinct clinical features in these patients have led to speculation that the immune response to virus in the SARS-CoV-2-infected alveolus differs from that in other types of pneumonia2. Here we investigate SARS-CoV-2 pathobiology by characterizing the immune response in the alveoli of patients infected with the virus. We collected bronchoalveolar lavage fluid samples from 88 patients with SARS-CoV-2-induced respiratory failure and 211 patients with known or suspected pneumonia from other pathogens, and analysed them using flow cytometry and bulk transcriptomic profiling. We performed single-cell RNA sequencing on 10 bronchoalveolar lavage fluid samples collected from patients with severe coronavirus disease 2019 (COVID-19) within 48 h of intubation. In the majority of patients with SARS-CoV-2 infection, the alveolar space was persistently enriched in T cells and monocytes. Bulk and single-cell transcriptomic profiling suggested that SARS-CoV-2 infects alveolar macrophages, which in turn respond by producing T cell chemoattractants. These T cells produce interferon-γ to induce inflammatory cytokine release from alveolar macrophages and further promote T cell activation. Collectively, our results suggest that SARS-CoV-2 causes a slowly unfolding, spatially limited alveolitis in which alveolar macrophages containing SARS-CoV-2 and T cells form a positive feedback loop that drives persistent alveolar inflammation.

Epithelial cell-specific loss of function of Miz1 causes a spontaneous COPD-like phenotype and up-regulates Ace2 expression in mice.

Cigarette smoking, the leading cause of chronic obstructive pulmonary disease (COPD), has been implicated as a risk factor for severe disease in patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here we show that mice with lung epithelial cell-specific loss of function of Miz1, which we identified as a negative regulator of nuclear factor κB (NF-κB) signaling, spontaneously develop progressive age-related changes resembling COPD. Furthermore, loss of Miz1 up-regulates the expression of Ace2, the receptor for SARS-CoV-2. Concomitant partial loss of NF-κB/RelA prevented the development of COPD-like phenotype in Miz1-deficient mice. Miz1 protein levels are reduced in the lungs from patients with COPD, and in the lungs of mice exposed to chronic cigarette smoke. Our data suggest that Miz1 down-regulation-induced sustained activation of NF-κB-dependent inflammation in the lung epithelium is sufficient to induce progressive lung and airway destruction that recapitulates features of COPD, with implications for COVID-19.