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.
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•“Weighted nearest neighbor” analysis integrates multimodal single-cell data•A multimodal reference “atlas” of the circulating human immune system•Identification and validation of novel sources of lymphoid heterogeneity•“Reference-based” mapping of query datasets onto a multimodal atlas
A framework that allows for the integration of multiple data types using single cells is applied to understand distinct immune cell states, previously unidentified immune populations, and to interpret immune responses to vaccinations.
There is an urgent need to better understand the pathophysiology of Coronavirus disease 2019 (COVID-19), the global pandemic caused by SARS-CoV-2, which has infected more than three million people ...worldwide
. Approximately 20% of patients with COVID-19 develop severe disease and 5% of patients require intensive care
. Severe disease has been associated with changes in peripheral immune activity, including increased levels of pro-inflammatory cytokines
that may be produced by a subset of inflammatory monocytes
, lymphopenia
and T cell exhaustion
. To elucidate pathways in peripheral immune cells that might lead to immunopathology or protective immunity in severe COVID-19, we applied single-cell RNA sequencing (scRNA-seq) to profile peripheral blood mononuclear cells (PBMCs) from seven patients hospitalized for COVID-19, four of whom had acute respiratory distress syndrome, and six healthy controls. We identify reconfiguration of peripheral immune cell phenotype in COVID-19, including a heterogeneous interferon-stimulated gene signature, HLA class II downregulation and a developing neutrophil population that appears closely related to plasmablasts appearing in patients with acute respiratory failure requiring mechanical ventilation. Importantly, we found that peripheral monocytes and lymphocytes do not express substantial amounts of pro-inflammatory cytokines. Collectively, we provide a cell atlas of the peripheral immune response to severe COVID-19.
...because GWASs typically incorporate nearly 1 million tests, the threshold for significance of these studies is the Bonferroni a of 0.05/ 1,000,000, or 5 X 10~8. There was no evidence of ...replication of any of the three SNPs in the African American cohort of MESSI, and only marginal evidence (P = 0.14) of replication in rs2228315 among European Americans. ...the genetic evidence for SELPLG as an ARDS gene is not compelling, but the functional follow-up using animal models of ARDS is provocative. The SELPLG variant rs2228315 that identified this locus has a minor allele frequency of 31% in African Americans versus 7% in whites. ...incorporating nonwhite populations into GWASs is not just the right thing to do to ensure that all populations benefit from personalized medicine, but also good science (14). ...this study again shows the likely value of animal models in ARDS research (15)-although SELPLG was identified by genetic screening, it is the highly convincing functional data that make this a priority locus for follow-up study.
BACKGROUNDElevated levels of inflammatory cytokines have been associated with poor outcomes among COVID-19 patients. It is unknown, however, how these levels compare with those observed in critically ...ill patients with acute respiratory distress syndrome (ARDS) or sepsis due to other causes.METHODSWe used a Luminex assay to determine expression of 76 cytokines from plasma of hospitalized COVID-19 patients and banked plasma samples from ARDS and sepsis patients. Our analysis focused on detecting statistical differences in levels of 6 cytokines associated with cytokine storm (IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α) between patients with moderate COVID-19, severe COVID-19, and ARDS or sepsis.RESULTSFifteen hospitalized COVID-19 patients, 9 of whom were critically ill, were compared with critically ill patients with ARDS (n = 12) or sepsis (n = 16). There were no statistically significant differences in baseline levels of IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α between patients with COVID-19 and critically ill controls with ARDS or sepsis.CONCLUSIONLevels of inflammatory cytokines were not higher in severe COVID-19 patients than in moderate COVID-19 or critically ill patients with ARDS or sepsis in this small cohort. Broad use of immunosuppressive therapies in ARDS has failed in numerous Phase 3 studies; use of these therapies in unselected patients with COVID-19 may be unwarranted.FUNDINGFunding was received from NHLBI K23 HL125663 (AJR); The Bill and Melinda Gates Foundation OPP1113682 (AJR and CAB); Burroughs Wellcome Fund Investigators in the Pathogenesis of Infectious Diseases #1016687 NIH/NIAID U19AI057229-16; Stanford Maternal Child Health Research Institute; and Chan Zuckerberg Biohub (CAB).
Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable ...host-gene-expression-based classifier for acute bacterial and viral infections. We use training data (N = 1069) from 18 retrospective transcriptomic studies. Using only 29 preselected host mRNAs, we train a neural-network classifier with a bacterial-vs-other area under the receiver-operating characteristic curve (AUROC) 0.92 (95% CI 0.90-0.93) and a viral-vs-other AUROC 0.92 (95% CI 0.90-0.93). We then apply this classifier, inflammatix-bacterial-viral-noninfected-version 1 (IMX-BVN-1), without retraining, to an independent cohort (N = 163). In this cohort, IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.86 (95% CI 0.77-0.93), and viral-vs.-other 0.85 (95% CI 0.76-0.93). In patients enrolled within 36 h of hospital admission (N = 70), IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.92 (95% CI 0.83-0.99), and viral-vs.-other 0.91 (95% CI 0.82-0.98). With further study, IMX-BVN-1 could provide a tool for assessing patients with suspected infection and sepsis at hospital admission.
Sepsis is characterized by profound changes in systemic and cellular metabolism that disrupt normal metabolic homeostasis. These metabolic changes can serve as biomarkers for disease severity. ...Lactate, a metabolite of anaerobic metabolism, is the most widely used ICU biomarker and it is incorporated into multiple management algorithms. Technological advances now make broader metabolic profiling possible, with early studies identifying metabolic changes associated with sepsis mortality. Finally, given the marked changes in metabolism in sepsis and the association of worse prognosis in patients with severe metabolic derangements, we summarize the seminal trials conducted to optimize nutrition in the ICU.
Treatment with bone-marrow-derived mesenchymal stromal cells (MSCs) has shown benefits in preclinical models of acute respiratory distress syndrome (ARDS). Safety has not been established for ...administration of MSCs in critically ill patients with ARDS. We did a phase 2a trial to assess safety after administration of MSCs to patients with moderate to severe ARDS.
We did a prospective, double-blind, multicentre, randomised trial to assess treatment with one intravenous dose of MSCs compared with placebo. We recruited ventilated patients with moderate to severe ARDS (ratio of partial pressure of oxygen to fractional inspired oxygen <27 kPa and positive end-expiratory pressure PEEP ≥8 cm H
O) in five university medical centres in the USA. Patients were randomly assigned 2:1 to receive either 10 × 10
/kg predicted bodyweight MSCs or placebo, according to a computer-generated schedule with a variable block design and stratified by site. We excluded patients younger than 18 years, those with trauma or moderate to severe liver disease, and those who had received cancer treatment in the previous 2 years. The primary endpoint was safety and all analyses were done by intention to treat. We also measured biomarkers in plasma. MSC viability was tested in a post-hoc analysis. This trial is registered with ClinicalTrials.gov, number NCT02097641.
From March 24, 2014, to Feb 9, 2017 we screened 1038 patients, of whom 60 were eligible for and received treatment. No patient experienced any of the predefined MSC-related haemodynamic or respiratory adverse events. One patient in the MSC group died within 24 h of MSC infusion, but death was judged to be probably unrelated. 28-day mortality did not differ between the groups (30% in the MSC group vs 15% in the placebo group, odds ratio 2·4, 95% CI 0·5-15·1). At baseline, the MSC group had numerically higher mean scores than the placebo group for Acute Physiology and Chronic Health Evaluation III (APACHE III; 104 SD 31 vs 89 33), minute ventilation (11·1 3·2 vs 9·6 2·4 L/min), and PEEP (12·4 3·7 vs 10·8 2·6 cm H
O). After adjustment for APACHE III score, the hazard ratio for mortality at 28 days was 1·43 (95% CI 0·40-5·12, p=0·58). Viability of MSCs ranged from 36% to 85%.
One dose of intravenous MSCs was safe in patients with moderate to severe ARDS. Larger trials are needed to assess efficacy, and the viability of MSCs must be improved.
National Heart, Lung, and Blood Institute.
Nasal transcriptomics can provide an accessible window into asthma pathobiology.
Our goal was to move beyond gene signatures of asthma to identify master regulator genes that causally regulate genes ...associated with asthma phenotypes.
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.
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.
The identified master regulator genes of asthma provide a novel path forward to further uncovering asthma mechanisms and therapy.
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To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults.
Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with ...mortality has recently become feasible.
We performed metabolomic profiling of plasma from 90 ICU subjects enrolled in the BWH Registry of Critical Illness (RoCI). We tested individual metabolites and a Bayesian Network of metabolites for association with 28-day mortality, using logistic regression in R, and the CGBayesNets Package in MATLAB. Both individual metabolites and the network were tested for replication in an independent cohort of 149 adults enrolled in the Community Acquired Pneumonia and Sepsis Outcome Diagnostics (CAPSOD) study.
We tested variable metabolites for association with 28-day mortality. In RoCI, nearly one third of metabolites differed among ICU survivors versus those who died by day 28 (N = 57 metabolites, p<.05). Associations with 28-day mortality replicated for 31 of these metabolites (with p<.05) in the CAPSOD population. Replicating metabolites included lipids (N = 14), amino acids or amino acid breakdown products (N = 12), carbohydrates (N = 1), nucleotides (N = 3), and 1 peptide. Among 31 replicated metabolites, 25 were higher in subjects who progressed to die; all 6 metabolites that are lower in those who die are lipids. We used Bayesian modeling to form a metabolomic network of 7 metabolites associated with death (gamma-glutamylphenylalanine, gamma-glutamyltyrosine, 1-arachidonoylGPC(20:4), taurochenodeoxycholate, 3-(4-hydroxyphenyl) lactate, sucrose, kynurenine). This network achieved a 91% AUC predicting 28-day mortality in RoCI, and 74% of the AUC in CAPSOD (p<.001 in both populations).
Both individual metabolites and a metabolomic network were associated with 28-day mortality in two independent cohorts. Metabolomic profiling represents a valuable new approach for identifying novel biomarkers in critically ill patients.
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.
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-1β compared.
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-1β.
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.
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