Single cell RNA sequencing identifies an early monocyte gene signature in acute respiratory distress syndrome

Single-cell RNA sequencing and immune repertoire analysis revealed dynamic immune characteristics associated with peripheral blood during sepsis

Sepsis is a potentially fatal condition arising from an abnormal immune response to an infection, which can result in organ failure and even death. To explore the mechanism underlying the dysregulated immune response during sepsis and identify potential therapeutic targets, single-cell RNA sequencing (scRNA-seq) and immune repertoire analysis were conducted to depict the cellular landscape of peripheral blood cells in septic mice. We observed significant alterations in the number and proportion of peripheral blood cell populations driven by sepsis. By combining single-cell gene expression profiles and B cell receptor (BCR) repertoire analysis, we discerned that infection inflicted serious damage on the antigen presentation ability of B cells and the diversity of BCR in a short time. In addition, we found that the cecal ligation and puncture procedure in mice inhibited the communication signals of CD4+ and CD8+ T cells and decreased the interactions between B cells and other cells. Our study provides detailed insights into the dynamic changes in the biological characteristics of peripheral blood cells driven by sepsis and provides important advances in our understanding of immune disorders during sepsis.

Cryo-PRO facilitates whole blood cryopreservation for single-cell RNA sequencing of immune cells from clinical samples

Single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) has enhanced our understanding of host immune mechanisms in small cohorts, particularly in diseases with complex and heterogeneous immune responses such as sepsis. However, PBMC isolation from blood requires technical expertise, training, and approximately two hours of onsite processing using Ficoll density gradient separation ('Ficoll') for scRNA-seq compatibility, precluding large-scale sample collection at most clinical sites. To minimize onsite processing, we developed Cryo-PRO (Cryopreservation with PBMC Recovery Offsite), a method of PBMC isolation from cryopreserved whole blood that allows immediate onsite sample cryopreservation and subsequent PBMC isolation in a central laboratory prior to sequencing. We compared scRNA-seq results from samples processed using Cryo-PRO versus standard onsite Ficoll separation in 23 patients with sepsis. Critical scRNA-seq outputs including cell substate fractions and marker genes were similar for each method across multiple cell types and substates, including an important monocyte substate enriched in patients with sepsis (Pearson correlation 0.78, p<0.001; 70% of top marker genes shared). Cryo-PRO reduced onsite sample processing time from >2 hours to <15 minutes and was reproducible across two enrollment sites, thus demonstrating potential for expanding scRNA-seq in multicenter studies of sepsis and other diseases.

Clinical significance of TLR7/IL-23/IL-17 signaling pathway in patients with acute respiratory distress syndrome

OBJECTIVES

To analyze the clinical significance of Toll-Like Receptor 7/Interleukin-23/Interleukin-17 (TLR7/IL-23/IL-17) signaling pathway in patients with Acute Respiratory Distress Syndrome (ARDS).

METHOD

The clinical data of 85 patients with ARDS were retrospectively analyzed and set as the ARDS group, and the clinical data of 85 healthy participants during the same period were set as the healthy control group. Univariate and multivariate logistic regression were used to analyze risk the factors affecting the prognosis of ARDS patients.

RESULTS

TheTLR7 mRNA expression and IL-23 and IL-17 levels in peripheral blood mononuclear cells were higher in the ARDS group than in the control group (p < 0.05). TLR7 mRNA expression, IL-23, IL-17, Surfactant Protein-D (SP-D), and Clara Cell protein-16 (CC-16) levels were the highest in the severe group, followed by the moderate group, and the lowest in the mild group, while Oxygenation Index (OI) was the lowest in the severe group, followed by the moderate group, and the highest in the mild group (p < 0.05). Multivariate logistic regression analysis found that the disease grade (severe), TLR7 mRNA expression, IL-23 level, and IL-17 level were the risk factors affecting the 28-d survival status of ARDS patients (OR > 1, p < 0.05).

CONCLUSIONS

In ARDS patients, the TLR7/IL-23/IL-17 signaling pathway is activated. The expression of this pathway is closely related to the severity of the disease and the levels of lung injury markers, and it is a risk factor that may have a direct impact on the prognosis of ARDS patients.

Establishment of an ovarian cancer exhausted CD8+T cells-related genes model by integrated analysis of scRNA-seq and bulk RNA-seq

Ovarian cancer (OC) was the fifth leading cause of cancer death and the deadliest gynecological cancer in women. This was largely attributed to its late diagnosis, high therapeutic resistance, and a dearth of effective treatments. Clinical and preclinical studies have revealed that tumor-infiltrating CD8+T cells often lost their effector function, the dysfunctional state of CD8+T cells was known as exhaustion. Our objective was to identify genes associated with exhausted CD8+T cells (CD8TEXGs) and their prognostic significance in OC. We downloaded the RNA-seq and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD8TEXGs were initially identified from single-cell RNA-seq (scRNA-seq) datasets, then univariate Cox regression, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were utilized to calculate risk score and to develop the CD8TEXGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), nomogram, and calibration were conducted to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in the risk groups were used to figure out the closely correlated pathways with the risk group. The role of risk score has been further explored in the homologous recombination repair deficiency (HRD), BRAC1/2 gene mutations and tumor mutation burden (TMB). A risk signature with 4 CD8TEXGs in OC was finally built in the TCGA database and further validated in large GEO cohorts. The signature also demonstrated broad applicability across various types of cancer in the pan-cancer analysis. The high-risk score was significantly associated with a worse prognosis and the risk score was proven to be an independent prognostic biomarker. The 1-, 3-, and 5-years ROC values, nomogram, calibration, and comparison with the previously published models confirmed the excellent prediction power of this model. The low-risk group patients tended to exhibit a higher HRD score, BRCA1/2 gene mutation ratio and TMB. The low-risk group patients were more sensitive to Poly-ADP-ribose polymerase inhibitors (PARPi). Our findings of the prognostic value of CD8TEXGs in prognosis and drug response provided valuable insights into the molecular mechanisms and clinical management of OC.

Dynamic immune status analysis of peripheral blood mononuclear cells in patients with Klebsiella pneumoniae bloodstream infection sepsis using single-cell RNA sequencing

Background

Klebsiella pneumoniae is a common Gram-negative bacterium. Blood infection caused by K. pneumoniae is one of the most common causes of human sepsis, which seriously threatens the life of patients. The immune status of peripheral blood mononuclear cells (PBMCs) based on single-cell RNA sequencing (scRNA-seq) in acute stage and recovery stage of sepsis caused by K. pneumoniae bloodstream infection has not been studied.

Methods

A total of 13 subjects were included in this study, 3 healthy controls, 7 patients with K. pneumoniae bloodstream infection in the acute stage (4 patients died), and 3 patients in the recovery stage. Peripheral blood of all patients was collected and PBMCs were isolated for scRNA-seq analysis. We studied the changes of PBMCs components, signaling pathways, differential genes, and cytokines in acute and recovery stages.

Results

During K. pneumoniae acute infection we observed a decrease in the proportion of T cells, most probably due to apoptosis and the function of T cell subtypes was disorder. The proportion of monocytes increased in acute stage. Although genes related to their phagocytosis function were upregulated, their antigen presentation capacity-associated genes were downregulated. The expression of IL-1β, IL-18, IFNGR1 and IFNGR2 genes was also increased in monocytes. The proportion of DCs was depleted during the acute stage and did not recover during sepsis recovery. DCs antigen presentation was weakened during the acute stage but recovered fast during the recovery stage. pDCs response to MCP-1 chemokine was weakened, they recovered it quickly during the recovery stage. B cells showed apoptosis both in the acute stage and recovery stage. Their response to complement was weakened, but their antigen presentation function was enhanced. The proportion of NK cells stable during all disease's stages, and the expression of IFN-γ gene was upregulated.

Conclusion

The proportion of PBMCs and their immune functions undergo variations throughout the course of the disease, spanning from the acute stage to recovery. These findings provide new insights into the mechanism of PBMCs immune function during K. pneumoniae bloodstream infection sepsis and recovery and sets the basis for further understanding and treatment.

Deciphering Abnormal Platelet Subpopulations in COVID-19, Sepsis and Systemic Lupus Erythematosus through Machine Learning and Single-Cell Transcriptomics

This study focuses on understanding the transcriptional heterogeneity of activated platelets and its impact on diseases such as sepsis, COVID-19, and systemic lupus erythematosus (SLE). Recognizing the limited knowledge in this area, our research aims to dissect the complex transcriptional profiles of activated platelets to aid in developing targeted therapies for abnormal and pathogenic platelet subtypes. We analyzed single-cell transcriptional profiles from 47,977 platelets derived from 413 samples of patients with these diseases, utilizing Deep Neural Network (DNN) and eXtreme Gradient Boosting (XGB) to distinguish transcriptomic signatures predictive of fatal or survival outcomes. Our approach included source data annotations and platelet markers, along with SingleR and Seurat for comprehensive profiling. Additionally, we employed Uniform Manifold Approximation and Projection (UMAP) for effective dimensionality reduction and visualization, aiding in the identification of various platelet subtypes and their relation to disease severity and patient outcomes. Our results highlighted distinct platelet subpopulations that correlate with disease severity, revealing that changes in platelet transcription patterns can intensify endotheliopathy, increasing the risk of coagulation in fatal cases. Moreover, these changes may impact lymphocyte function, indicating a more extensive role for platelets in inflammatory and immune responses. This study identifies crucial biomarkers of platelet heterogeneity in serious health conditions, paving the way for innovative therapeutic approaches targeting platelet activation, which could improve patient outcomes in diseases characterized by altered platelet function.

Overactivated MX1 Positive Natural Killer Cells Promote the Progression of Sepsis-Induced Acute Respiratory Distress Syndrome

Background

Natural killer (NK) cells are key regulators of immune defense in sepsis-induced acute respiratory distress syndrome (ARDS), yet the characteristics of NK cell clusters in ARDS remain poorly understood.

Methods

A prospective and observational study enrolled septic patients with ARDS or not was conducted to determine the percentage of NK cells via flow cytometry. The transcriptomes of peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with sepsis only, and patients with sepsis-induced ARDS were profiled. Vitro experiments were performed to confirm the mechanism mediating MX1+NK cell infiltration.

Results

A total of 115 septic patients were analyzed, among whom 63 patients developed ARDS and 52 patients did not. Decreased NK percentages were found in sepsis with ARDS patients (%, 7.46±4.40 vs 11.65±6.88, P=0.0001) compared with sepsis-only patients. A lower percentage of NK cells showed a significant increase in 28-day mortality. Single-cell sequencing analysis revealed distinct characteristics of NK cells in sepsis-induced ARDS, notably the identification of a unique cluster defined as MX1+NK cells. Flow cytometry analysis showed an elevated percentage of MX1+NK cells specifically in individuals with sepsis-induced ARDS, compared with patients with sepsis only. Pseudo-time analysis showed that MX1+NK cells were characterized by upregulation of type I interferon-induced genes and other pro-inflammatory genes. MX1+NK cells can respond to type I interferons and secrete type I interferons themselves. Ligand-receptor interaction analysis also revealed extensive interaction between MX1+NK cells and T/B cells, leading to an uncontrolled inflammatory response in ARDS.

Conclusion

MX1+NK cells can respond to type I interferons and secrete type I interferons themselves, promoting the development of sepsis-induced ARDS. Interfering with the infiltration of MX1+NK cells could be a therapeutic approach for this disease. Due to the limited sample size, a larger sample size was needed for further exploration.

Profiling the dysregulated immune response in sepsis: overcoming challenges to achieve the goal of precision medicine

Sepsis is characterised by a dysregulated host immune response to infection. Despite recognition of its significance, immune status monitoring is not implemented in clinical practice due in part to the current absence of direct therapeutic implications. Technological advances in immunological profiling could enhance our understanding of immune dysregulation and facilitate integration into clinical practice. In this Review, we provide an overview of the current state of immune profiling in sepsis, including its use, current challenges, and opportunities for progress. We highlight the important role of immunological biomarkers in facilitating predictive enrichment in current and future treatment scenarios. We propose that multiple immune and non-immune-related parameters, including clinical and microbiological data, be integrated into diagnostic and predictive combitypes, with the aid of machine learning and artificial intelligence techniques. These combitypes could form the basis of workable algorithms to guide clinical decisions that make precision medicine in sepsis a reality and improve patient outcomes.

ARDS and aging: TYMS emerges as a promising biomarker and therapeutic target

Background

Acute Respiratory Distress Syndrome (ARDS) is a common condition in the intensive care unit (ICU) with a high mortality rate, yet the diagnosis rate remains low. Recent studies have increasingly highlighted the role of aging in the occurrence and progression of ARDS. This study is committed to investigating the pathogenic mechanisms of cellular and genetic changes in elderly ARDS patients, providing theoretical support for the precise treatment of ARDS.

Methods

Gene expression profiles for control and ARDS samples were obtained from the Gene Expression Omnibus (GEO) database, while aging-related genes (ARGs) were sourced from the Human Aging Genomic Resources (HAGR) database. Differentially expressed genes (DEGs) were subjected to functional enrichment analysis to understand their roles in ARDS and aging. The Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning pinpointed key modules and marker genes, with ROC curves illustrating their significance. The expression of four ARDS-ARDEGs was validated in lung samples from aged mice with ARDS using qRT-PCR. Gene set enrichment analysis (GSEA) investigated the signaling pathways and immune cell infiltration associated with TYMS expression. Single-nucleus RNA sequencing (snRNA-Seq) explored gene-level differences among cells to investigate intercellular communication during ARDS onset and progression.

Results

ARDEGs are involved in cellular responses to DNA damage stimuli, inflammatory reactions, and cellular senescence pathways. The MEmagenta module exhibited a significant correlation with elderly ARDS patients. The LASSO, RRF, and XGBoost algorithms were employed to screen for signature genes, including CKAP2, P2RY14, RBP2, and TYMS. Further validation emphasized the potential role of TYMS in the onset and progression of ARDS. Immune cell infiltration indicated differential proportion and correlations with TYMS expression. SnRNA-Seq and cell-cell communication analysis revealed that TYMS is highly expressed in endothelial cells, and the SEMA3 signaling pathway primarily mediates cell communication between endothelial cells and other cells.

Conclusion

Endothelial cell damage associated with aging could contribute to ARDS progression by triggering inflammation. TYMS emerges as a promising diagnostic biomarker and potential therapeutic target for ARDS.

Acute respiratory distress syndrome heterogeneity and the septic ARDS subgroup

Acute respiratory distress syndrome (ARDS) is an acute diffuse inflammatory lung injury characterized by the damage of alveolar epithelial cells and pulmonary capillary endothelial cells. It is mainly manifested by non-cardiogenic pulmonary edema, resulting from intrapulmonary and extrapulmonary risk factors. ARDS is often accompanied by immune system disturbance, both locally in the lungs and systemically. As a common heterogeneous disease in critical care medicine, researchers are often faced with the failure of clinical trials. Latent class analysis had been used to compensate for poor outcomes and found that targeted treatment after subgrouping contribute to ARDS therapy. The subphenotype of ARDS caused by sepsis has garnered attention due to its refractory nature and detrimental consequences. Sepsis stands as the most predominant extrapulmonary cause of ARDS, accounting for approximately 32% of ARDS cases. Studies indicate that sepsis-induced ARDS tends to be more severe than ARDS caused by other factors, leading to poorer prognosis and higher mortality rate. This comprehensive review delves into the immunological mechanisms of sepsis-ARDS, the heterogeneity of ARDS and existing research on targeted treatments, aiming to providing mechanism understanding and exploring ideas for accurate treatment of ARDS or sepsis-ARDS.

Deciphering the molecular and cellular atlas of immune cells in septic patients with different bacterial infections

BACKGROUND

Sepsis is a life-threatening organ dysfunction caused by abnormal immune responses to various, predominantly bacterial, infections. Different bacterial infections lead to substantial variation in disease manifestation and therapeutic strategies. However, the underlying cellular heterogeneity and mechanisms involved remain poorly understood.

METHODS

Multiple bulk transcriptome datasets from septic patients with 12 types of bacterial infections were integrated to identify signature genes for each infection. Signature genes were mapped onto an integrated large single-cell RNA (scRNA) dataset from septic patients, to identify subsets of cells associated with different sepsis types, and multiple omics datasets were combined to reveal the underlying molecular mechanisms. In addition, an scRNA dataset and spatial transcriptome data were used to identify signaling pathways in sepsis-related cells. Finally, molecular screening, optimization, and de novo design were conducted to identify potential targeted drugs and compounds.

RESULTS

We elucidated the cellular heterogeneity among septic patients with different bacterial infections. In Escherichia coli (E. coli) sepsis, 19 signature genes involved in epigenetic regulation and metabolism were identified, of which DRAM1 was demonstrated to promote autophagy and glycolysis in response to E. coli infection. DRAM1 upregulation was confirmed in an independent sepsis cohort. Further, we showed that DRAM1 could maintain survival of a pro-inflammatory monocyte subset, C10_ULK1, which induces systemic inflammation by interacting with other cell subsets via resistin and integrin signaling pathways in blood and kidney tissue, respectively. Finally, retapamulin was identified and optimized as a potential drug for treatment of E. coli sepsis targeting the signature gene, DRAM1, and inhibiting E. coli protein synthesis. Several other targeted drugs were also identified in other types of sepsis, including nystatin targeting C1QA in Neisseria sepsis and dalfopristin targeting CTSD in Streptococcus viridans sepsis.

CONCLUSION

Our study provides a comprehensive overview of the cellular heterogeneity and underlying mechanisms in septic patients with various bacterial infections, providing insights to inform development of stratified targeted therapies for sepsis.

Comprehensive single-cell analysis reveals novel anergic antigen-presenting cell subtypes in human sepsis

Background

Sepsis is a life-threatening condition with high mortality. A few studies have emerged utilizing single-cell RNA sequencing (scRNA-seq) to analyze gene expression at the single-cell resolution in sepsis, but a comprehensive high-resolution analysis of blood antigen-presenting cells has not been conducted.

Methods

All published human scRNA-seq data were downloaded from the single cell portal database. After manually curating the dataset, we extracted all antigen-presenting cells, including dendritic cells (DCs) and monocytes, for identification of cell subpopulations and their gene profiling and intercellular interactions between septic patients and healthy controls. Finally, we further validated the findings by performing deconvolution analysis on bulk RNA sequencing (RNA-seq) data and flow cytometry.

Results

Within the traditional DC populations, we discovered novel anergic DC subtypes characterized by low major histocompatibility complex class II expression. Notably, these anergic DC subtypes showed a significant increase in septic patients. Additionally, we found that a previously reported immunosuppressive monocyte subtype, Mono1, exhibited a similar gene expression profile to these anergic DCs. The consistency of our findings was confirmed through validation using bulk RNA-seq and flow cytometry, ensuring accurate identification of cell subtypes and gene expression patterns.

Conclusions

This study represents the first comprehensive single-cell analysis of antigen-presenting cells in human sepsis, revealing novel disease-associated anergic DC subtypes. These findings provide new insights into the cellular mechanisms of immune dysregulation in bacterial sepsis.

A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications

BACKGROUND

A significant proportion of septic patients with acute lung injury (ALI) are recognized late due to the absence of an efficient diagnostic test, leading to the postponed treatments and consequently higher mortality. Identifying diagnostic biomarkers may improve screening to identify septic patients at high risk of ALI earlier and provide the potential effective therapeutic drugs. Machine learning represents a powerful approach for making sense of complex gene expression data to find robust ALI diagnostic biomarkers.

METHODS

The datasets were obtained from GEO and ArrayExpress databases. Following quality control and normalization, the datasets (GSE66890, GSE10474 and GSE32707) were merged as the training set, and four machine learning feature selection methods (Elastic net, SVM, random forest and XGBoost) were applied to construct the diagnostic model. The other datasets were considered as the validation sets. To further evaluate the performance and predictive value of diagnostic model, nomogram, Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) were constructed. Finally, the potential small molecular compounds interacting with selected features were explored from the CTD database.

RESULTS

The results of GSEA showed that immune response and metabolism might play an important role in the pathogenesis of sepsis-induced ALI. Then, 52 genes were identified as putative biomarkers by consensus feature selection from all four methods. Among them, 5 genes (ARHGDIB, ALDH1A1, TACR3, TREM1 and PI3) were selected by all methods and used to predict ALI diagnosis with high accuracy. The external datasets (E-MTAB-5273 and E-MTAB-5274) demonstrated that the diagnostic model had great accuracy with AUC value of 0.725 and 0.833, respectively. In addition, the nomogram, DCA and CIC showed that the diagnostic model had great performance and predictive value. Finally, the small molecular compounds (Curcumin, Tretinoin, Acetaminophen, Estradiol and Dexamethasone) were screened as the potential therapeutic agents for sepsis-induced ALI.

CONCLUSION

This consensus of multiple machine learning algorithms identified 5 genes that were able to distinguish ALI from septic patients. The diagnostic model could identify septic patients at high risk of ALI, and provide potential therapeutic targets for sepsis-induced ALI.

Single-Cell RNA Sequencing and Transcriptome Analysis Revealed the Immune Microenvironment and Gene Markers of Acute Respiratory Distress Syndrome

Background

Acute respiratory distress syndrome (ARDS) is caused by severe pulmonary inflammation and the leading cause of death in the intensive care unit.

Methods

We used single-cell RNA sequencing to compare peripheral blood mononuclear cells from sepsis-induced ARDS (SEP-ARDS) and pneumonic ARDS (PNE-ARDS) patient. Then, we used the GSE152978 and GSE152979 datasets to identify molecular dysregulation mechanisms at the transcriptional level in ARDS.

Results

Markedly increased CD14 cells were the predominant immune cell type observed in SEP-ARDS and PNE-ARDS patients. Cytotoxic cells and natural killer (NK) T cells were exclusively identified in patients with PNE-ARDS. An enrichment analysis of differentially expressed genes (DEGs) suggested that Th1 cell differentiation and Th2 cell differentiation were enriched in cytotoxic cells, and that the IL-17 signaling pathway, NOD receptor signaling pathway, and complement and coagulation cascades were enriched in CD14 cells. Furthermore, according to GSE152978 and GSE152979, 1939 DEGs were identified in patients with ARDS and controls; they were mainly enriched in the Kyoto Encyclopedia of Genes and Genomes pathways. RBP7 had the highest area under the curve values among the 12 hub genes and was mainly expressed in CD14 cells. Additionally, hub genes were negatively correlated with NK cells and positively correlated with neutrophils, cytotoxic cells, B cells, and macrophages.

Conclusion

A severe imbalance in the proportion of immune cells and immune dysfunction were observed in SEP-ARDS and PNE-ARDS patients. RBP7 may be immunologically associated with CD14 cells and serve as a potential marker of ARDS.

Single-cell transcriptome profiling of sepsis identifies HLA-DRlowS100Ahigh monocytes with immunosuppressive function

BACKGROUND

Sustained yet intractable immunosuppression is commonly observed in septic patients, resulting in aggravated clinical outcomes. However, due to the substantial heterogeneity within septic patients, precise indicators in deciphering clinical trajectories and immunological alterations for septic patients remain largely lacking.

METHODS

We adopted cross-species, single-cell RNA sequencing (scRNA-seq) analysis based on two published datasets containing circulating immune cell profile of septic patients as well as immune cell atlas of murine model of sepsis. Flow cytometry, laser scanning confocal microscopy (LSCM) imaging and Western blotting were applied to identify the presence of S100A9⁺ monocytes at protein level. To interrogate the immunosuppressive function of this subset, splenic monocytes isolated from septic wild-type or S100a9^-/- mice were co-cultured with naïve CD4⁺ T cells, followed by proliferative assay. Pharmacological inhibition of S100A9 was implemented using Paquinimod via oral gavage.

RESULTS

ScRNA-seq analysis of human sepsis revealed substantial heterogeneity in monocyte compartments following the onset of sepsis, for which distinct monocyte subsets were enriched in disparate subclusters of septic patients. We identified a unique monocyte subset characterized by high expression of S100A family genes and low expression of human leukocyte antigen DR (HLA-DR), which were prominently enriched in septic patients and might exert immunosuppressive function. By combining single-cell transcriptomics of murine model of sepsis with in vivo experiments, we uncovered a similar subtype of monocyte significantly associated with late sepsis and immunocompromised status of septic mice, corresponding to HLA-DR^lowS100A^high monocytes in human sepsis. Moreover, we found that S100A9⁺ monocytes exhibited profound immunosuppressive function on CD4⁺ T cell immune response and blockade of S100A9 using Paquinimod could partially reverse sepsis-induced immunosuppression.

CONCLUSIONS

This study identifies HLA-DR^lowS100A^high monocytes correlated with immunosuppressive state upon septic challenge, inhibition of which can markedly mitigate sepsis-induced immune depression, thereby providing a novel therapeutic strategy for the management of sepsis.

Single-cell analysis reveals dysregulated inflammatory response in peripheral blood immunity in patients with acute respiratory distress syndrome

Introduction: Acute respiratory distress syndrome (ARDS) remains a major clinical challenge for patients in intensive care units. Determining the differential mechanisms underlying ARDS with different etiologies is a key goal to improve the effectiveness of ARDS therapy. Despite growing evidence that different immune cell types are involved in ARDS, the role of altered immune cell subpopulations in disease progression is unelucidated. Methods: In this study, we combined scRNA-seq and bulk-level sequencing to analyze the transcriptomes of peripheral blood mononuclear cells from healthy volunteers and patients with septic ARDS (sep-ARDS) and pneumonic ARDS (PNE-ARDS). Results: Our data revealed differential alterations at the cellular and molecular levels and within biological signaling pathways in ARDS with different etiologies. The dynamics of neutrophils, macrophages (Macs), classical dendritic cells (cDCs), myeloid-derived suppressive cells (MDSCs), and CD8⁺ T cells varied significantly among groups of different samples, with neutrophils and cDCs at higher, and Macs at significantly lower, amounts in the patients with sep-ARDS. Furthermore, MDSCs were highly enriched only in the sep-ARDS patients, whereas a higher abundance of CD8⁺ T cells was observed in patients with PNE-ARDS. In addition, these cell subpopulations were found to be significantly involved in apoptosis, inflammatory, and immune-related pathways. In particular, a significant enhancement of the oxidative stress response was observed in the neutrophil subpopulation. Conclusion: Our study shows that the composition of cells involved in the main peripheral circulation differs in patients with ARDS with different etiologies. Studying the role and mechanism of action of these cells during ARDS will provide new opportunities for the treatment of this condition.

Pediatric Critical Care in the Twenty-first Century and Beyond

Pediatric critical care addresses prevention, diagnosis, and treatment of organ dysfunction in the setting of increasingly complex patients, therapies, and environments. Soon burgeoning data science will enable all aspects of intensive care: driving facilitated diagnostics, empowering a learning health-care environment, promoting continuous advancement of care, and informing the continuum of critical care outside the intensive care unit preceding and following critical illness/injury. Although novel technology will progressively objectify personalized critical care, humanism, practiced at the bedside, defines the essence of pediatric critical care now and in the future.

Innate immune responses in pneumonia

The lungs are an immunologically unique environment; they are exposed to innumerable pathogens and particulate matter daily. Appropriate clearance of pathogens and response to pollutants is required to prevent overwhelming infection, while preventing tissue damage and maintaining efficient gas exchange. Broadly, the innate immune system is the collection of immediate, intrinsic immune responses to pathogen or tissue injury. In this review, we will examine the innate immune responses of the lung, with a particular focus on their role in pneumonia. We will discuss the anatomic barriers and antimicrobial proteins of the lung, pathogen and injury recognition, and the role of leukocytes (macrophages, neutrophils, and innate lymphocytes) and lung stromal cells in innate immunity. Throughout the review, we will focus on new findings in innate immunity as well as features that are unique to the lung.

COVID-19 immunopathology: From acute diseases to chronic sequelae

The clinical manifestation of coronavirus disease 2019 (COVID-19) mainly targets the lung as a primary affected organ, which is also a critical site of immune cell activation by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, recent reports also suggest the involvement of extrapulmonary tissues in COVID-19 pathology. The interplay of both innate and adaptive immune responses is key to COVID-19 management. As a result, a robust innate immune response provides the first line of defense, concomitantly, adaptive immunity neutralizes the infection and builds memory for long-term protection. However, dysregulated immunity, both innate and adaptive, can skew towards immunopathology both in acute and chronic cases. Here we have summarized some of the recent findings that provide critical insight into the immunopathology caused by SARS-CoV-2, in acute and post-acute cases. Finally, we further discuss some of the immunomodulatory drugs in preclinical and clinical trials for dampening the immunopathology caused by COVID-19.

The role of lung macrophages in acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) is an acute and diffuse inflammatory lung injury in a short time, one of the common severe manifestations of the respiratory system that endangers human life and health. As an innate immune cell, macrophages play a key role in the inflammatory response. For a long time, the role of pulmonary macrophages in ARDS has tended to revolve around the polarization of M1/M2. However, with the development of single-cell RNA sequencing, fate mapping, metabolomics, and other new technologies, a deeper understanding of the development process, classification, and function of macrophages in the lung are acquired. Here, we discuss the function of pulmonary macrophages in ARDS from the two dimensions of anatomical location and cell origin and describe the effects of cell metabolism and intercellular interaction on the function of macrophages. Besides, we explore the treatments for targeting macrophages, such as enhancing macrophage phagocytosis, regulating macrophage recruitment, and macrophage death. Considering the differences in responsiveness of different research groups to these treatments and the tremendous dynamic changes in the gene expression of monocyte/macrophage, we discussed the possibility of characterizing the gene expression of monocyte/macrophage as the biomarkers. We hope that this review will provide new insight into pulmonary macrophage function and therapeutic targets of ARDS.

Identification of two robust subclasses of sepsis with both prognostic and therapeutic values based on machine learning analysis

Background

Sepsis is a heterogeneous syndrome with high morbidity and mortality. Optimal and effective classifications are in urgent need and to be developed.

Methods and results

A total of 1,936 patients (sepsis samples, n=1,692; normal samples, n=244) in 7 discovery datasets were included to conduct weighted gene co-expression network analysis (WGCNA) to filter out candidate genes related to sepsis. Then, two subtypes of sepsis were classified in the training sepsis set (n=1,692), the Adaptive and Inflammatory, using K-means clustering analysis on 90 sepsis-related features. We validated these subtypes using 617 samples in 5 independent datasets and the merged 5 sets. Cibersort method revealed the Adaptive subtype was related to high infiltration levels of T cells and natural killer (NK) cells and a better clinical outcome. Immune features were validated by single-cell RNA sequencing (scRNA-seq) analysis. The Inflammatory subtype was associated with high infiltration of macrophages and a disadvantageous prognosis. Based on functional analysis, upregulation of the Toll-like receptor signaling pathway was obtained in Inflammatory subtype and NK cell-mediated cytotoxicity and T cell receptor signaling pathway were upregulated in Adaptive group. To quantify the cluster findings, a scoring system, called, risk score, was established using four datasets (n=980) in the discovery cohorts based on least absolute shrinkage and selection operator (LASSO) and logistic regression and validated in external sets (n=760). Multivariate logistic regression analysis revealed the risk score was an independent predictor of outcomes of sepsis patients (OR [odds ratio], 2.752, 95% confidence interval [CI], 2.234-3.389, P<0.001), when adjusted by age and gender. In addition, the validation sets confirmed the performance (OR, 1.638, 95% CI, 1.309-2.048, P<0.001). Finally, nomograms demonstrated great discriminatory potential than that of risk score, age and gender (training set: AUC=0.682, 95% CI, 0.643-0.719; validation set: AUC=0.624, 95% CI, 0.576-0.664). Decision curve analysis (DCA) demonstrated that the nomograms were clinically useful and had better discriminative performance to recognize patients at high risk than the age, gender and risk score, respectively.

Conclusions

In-depth analysis of a comprehensive landscape of the transcriptome characteristics of sepsis might contribute to personalized treatments and prediction of clinical outcomes.

Evolution of multiple omics approaches to define pathophysiology of pediatric acute respiratory distress syndrome

Pediatric acute respiratory distress syndrome (PARDS), though both common and deadly in critically ill children, lacks targeted therapies. The development of effective pharmacotherapies has been limited, in part, by lack of clarity about the pathobiology of pediatric ARDS. Epithelial lung injury, vascular endothelial activation, and systemic immune activation are putative drivers of this complex disease process. Prior studies have used either hypothesis-driven (e.g., candidate genes and proteins, in vitro investigations) or unbiased (e.g., genome-wide association, transcriptomic, metabolomic) approaches to predict clinical outcomes and to define subphenotypes. Advances in multiple omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have permitted more comprehensive investigation of PARDS pathobiology. However, omics studies have been limited in children compared to adults, and analyses across multiple tissue types are lacking. Here, we synthesized existing literature on the molecular mechanism of PARDS, summarized our interrogation of publicly available genomic databases to determine the association of candidate genes with PARDS phenotypes across multiple tissues and cell types, and integrated recent studies that used single-cell RNA sequencing (scRNA-seq). We conclude that novel profiling methods such as scRNA-seq, which permits more comprehensive, unbiased evaluation of pathophysiological mechanisms across tissue and cell types, should be employed to investigate the molecular mechanisms of PRDS toward the goal of identifying targeted therapies.

Low expression and Hypermethylation of ATP2B1 in Intrahepatic Cholangiocarcinoma Correlated With Cold Tumor Microenvironment

Background

The efficacy of current therapeutic schedule is limited owing to fibroproliferative tumor microenvironment (TME) of cholangiocarcinoma, compelling a search for new therapeutic targets.

Methods

Gene expression profiles and methylation profiles were obtained from UCSC Xena. Consensus clustering was performed on the transcriptome data of cholangiocarcinoma to determine the different immune subtypes. The differentially expressed genes (DEGs) between hot tumor and cold tumors were identified. ESTIMATE was used to assess immune score, and the cases were separated into relatively superior and inferior immune score groups. Single-sample gene set enrichment analysis was applied to assess 28 immune cells in the cholangiocarcinoma microenvironment. Unsupervised consensus was applied for methylation profiling to distribute the high and low methylation groups. The correlation between DNA methylation and mRNA expression was investigated, and the relationship between the ATP2B1 gene and the immune microenvironment was explored. Finally, 77 cases of intrahepatic cholangiocarcinoma (ICC) were collected for verification.

Results

Seven subtypes were related to patient outcomes (P=0.005). The proportions of CD8⁺ T cells in the “hot” immune type was significantly greater than that in the “cold” immune type (P<0.05). Next, DEGs and DNA methylation-governed genes were intersected, and ATP2B1 was identified as a prognosis factor in ICC (P=0.035). ATP2B1 expression was positively correlated with immune scores (P=0.005, r=0.458), the levels of infiltrating CD8⁺ T cells (P=0.004, r=0.47), and CD4⁺ T cells (P=0.027, r=0.37). Immunohistochemistry confirmed that the amounts of CD8⁺ and CD4⁺ T cells were significantly higher in ICC tissue samples than in tissues with ATP2B1 overexpression (P<0.05).

Conclusions

ATP2B1 overexpression can activate immune signals and prompt cold tumor response.

Mechanistic Understanding of Lung Inflammation: Recent Advances and Emerging Techniques

Acute respiratory distress syndrome (ARDS) is a life-threatening lung injury characterized by an acute inflammatory response in the lung parenchyma. Hence, it is considered as the most appropriate clinical syndrome to study pathogenic mechanisms of lung inflammation. ARDS is associated with increased morbidity and mortality in the intensive care unit (ICU), while no effective pharmacological treatment exists. It is very important therefore to fully characterize the underlying pathobiology and the related mechanisms, in order to develop novel therapeutic approaches. In vivo and in vitro models are important pre-clinical tools in biological and medical research in the mechanistic and pathological understanding of the majority of diseases. In this review, we will present data from selected experimental models of lung injury/acute lung inflammation, which have been based on clinical disorders that can lead to the development of ARDS and related inflammatory lung processes in humans, including ventilation-induced lung injury (VILI), sepsis, ischemia/reperfusion, smoke, acid aspiration, radiation, transfusion-related acute lung injury (TRALI), influenza, Streptococcus (S.) pneumoniae and coronaviruses infection. Data from the corresponding clinical conditions will also be presented. The mechanisms related to lung inflammation that will be covered are oxidative stress, neutrophil extracellular traps, mitogen-activated protein kinase (MAPK) pathways, surfactant, and water and ion channels. Finally, we will present a brief overview of emerging techniques in the field of omics research that have been applied to ARDS research, encompassing genomics, transcriptomics, proteomics, and metabolomics, which may recognize factors to help stratify ICU patients at risk, predict their prognosis, and possibly, serve as more specific therapeutic targets.

Advances in Immune Monitoring Approaches for Sepsis-Induced Immunosuppression

Sepsis represents a life-threatening organ dysfunction due to an aberrant host response. Of note is that majority of patients have experienced a severe immune depression during and after sepsis, which is significantly correlated with the occurrence of nosocomial infection and higher risk of in-hospital death. Nevertheless, the clinical sign of sepsis-induced immune paralysis remains highly indetectable and ambiguous. Given that, specific yet robust biomarkers for monitoring the immune functional status of septic patients are of prominent significance in clinical practice. In turn, the stratification of a subgroup of septic patients with an immunosuppressive state will greatly contribute to the implementation of personalized adjuvant immunotherapy. In this review, we comprehensively summarize the mechanism of sepsis-associated immunosuppression at the cellular level and highlight the recent advances in immune monitoring approaches targeting the functional status of both innate and adaptive immune responses.

Therapeutic hypothermia attenuates physiologic, histologic, and metabolomic markers of injury in a porcine model of acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) is a lung injury characterized by noncardiogenic pulmonary edema and hypoxic respiratory failure. The purpose of this study was to investigate the effects of therapeutic hypothermia on short-term experimental ARDS. Twenty adult female Yorkshire pigs were divided into four groups (n = 5 each): normothermic control (C), normothermic injured (I), hypothermic control (HC), and hypothermic injured (HI). Acute respiratory distress syndrome was induced experimentally via intrapulmonary injection of oleic acid. Target core temperature was achieved in the HI group within 1 h of injury induction. Cardiorespiratory, histologic, cytokine, and metabolomic data were collected on all animals prior to and following injury/sham. All data were collected for approximately 12 h from the beginning of the study until euthanasia. Therapeutic hypothermia reduced injury in the HI compared to the I group (histological injury score = 0.51 ± 0.18 vs. 0.76 ± 0.06; p = 0.02) with no change in gas exchange. All groups expressed distinct phenotypes, with a reduction in pro-inflammatory metabolites, an increase in anti-inflammatory metabolites, and a reduction in inflammatory cytokines observed in the HI group compared to the I group. Changes to respiratory system mechanics in the injured groups were due to increases in lung elastance (E) and resistance (R) (ΔE from pre-injury = 46 ± 14 cmH₂ O L^-1 , p < 0.0001; ΔR from pre-injury: 3 ± 2 cmH₂ O L^-1  s^- , p = 0.30) rather than changes to the chest wall (ΔE from pre-injury: 0.7 ± 1.6 cmH₂ O L^-1 , p = 0.99; ΔR from pre-injury: 0.6 ± 0.1 cmH₂ O L^-1  s^- , p = 0.01). Both control groups had no change in respiratory mechanics. In conclusion, therapeutic hypothermia can reduce markers of injury and inflammation associated with experimentally induced short-term ARDS.

Longitudinal Plasma Proteomics Analysis Reveals Novel Candidate Biomarkers in Acute COVID-19

The host response to COVID-19 pathophysiology over the first few days of infection remains largely unclear, especially the mechanisms in the blood compartment. We report on a longitudinal proteomic analysis of acute-phase COVID-19 patients, for which we used blood plasma, multiple reaction monitoring with internal standards, and data-independent acquisition. We measured samples on admission for 49 patients, of which 21 had additional samples on days 2, 4, 7, and 14 after admission. We also measured 30 externally obtained samples from healthy individuals for comparison at baseline. The 31 proteins differentiated in abundance between acute COVID-19 patients and healthy controls belonged to acute inflammatory response, complement activation, regulation of inflammatory response, and regulation of protein activation cascade. The longitudinal analysis showed distinct profiles revealing increased levels of multiple lipid-associated functions, a rapid decrease followed by recovery for complement activation, humoral immune response, and acute inflammatory response-related proteins, and level fluctuation in the regulation of smooth muscle cell proliferation, secretory mechanisms, and platelet degranulation. Three proteins were differentiated between survivors and nonsurvivors. Finally, increased levels of fructose-bisphosphate aldolase B were determined in patients with exposure to angiotensin receptor blockers versus decreased levels in those exposed to angiotensin-converting enzyme inhibitors. Data are available via ProteomeXchange PXD029437.

Investigating the Intercellular Communication Network of Immune Cell in Acute Respiratory Distress Syndrome with Sepsis

Acute respiratory distress syndrome (ARDS) is recognized as a serious public health issue that results in respiratory failure and high mortality rates. The syndrome is characterized by immune cell aggregation, communication, activation, and alveolar epithelial damage. To elucidate the complex dynamic process of the immune system's response in ARDS, we construct the intercellular communication network of immune cells in ARDS based on a single-cell RNA sequencing dataset (including three sepsis-induced ARDS patients and four sepsis-only patients). The results show that macrophages relayed most of the intercellular signals (ligand–receptor pairs) in both groups. Many genes related to immune response (IFI44L, ISG, and HLA-DQB1) and biological functions (response to virus, negative regulation of viral life cycle, and response to interferon-beta) were detected via differentially expressed gene analysis of macrophages between the two groups. Deep analysis of the intercellular signals related to the macrophage found that sepsis-induced ARDS harbored distinctive intercellular signals related to chemokine–chemokine receptors (CCL3/4/5−CCR1), which mainly are involved in the disturbance of the STAT family transcription factors (TFs), such as STAT2 and STAT3. These signals and downstream TFs might play key roles in macrophage M1/M2 polarization in the process of sepsis-induced ARDS. This study provides a comprehensive view of the intercellular communication landscape between sepsis and sepsis-induced ARDS and identifies key intercellular communications and TFs involved in sepsis-induced ARDS. We believe that our study provides valuable clues for understanding the immune response mechanisms of ARDS.

Single-cell transcriptomics highlights immunological dysregulations of monocytes in the pathobiology of COPD

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a common respiratory disease, whose pathogenetic complexity was strongly associated with aging/smoking and poorly understood.

METHODS

Here we performed single-cell RNA sequencing (scRNA-seq) analysis of 66,610 cells from COPD and age-stratified control lung tissues of donors with different smoking histories to prioritize cell types most perturbed in COPD lungs in aging/smoking dependent or independent manner. By performing an array of advanced bioinformatic analyses, such as gene set enrichment analysis, trajectory analysis, cell-cell interactions analysis, regulatory potential analysis, weighted correlation network analysis, functional interaction analysis, and gene set variation analysis, we integrated cell-type-level alterations into a system-level malfunction and provided a more clarified COPD pathological model containing specific mechanisms by which aging and smoking facilitate COPD development. Finally, we integrated the publicly available scRNA-seq data of 9 individuals, resulting in a total of 110,931 cells, and replicated the analyses to enhance the credibility of our findings.

RESULTS

Our study pointed to enrichment of COPD molecular alteration in monocytes, which further induced a previously unrecognized pro-inflammatory effect on alveolar epithelial cells. In addition, aged monocytes and club cells facilitated COPD development via maintaining an autoimmune airway niche. Unexpectedly, macrophages, whose defect to resolve inflammation was long-recognized in COPD pathogenesis, primarily induced an imbalance of sphingolipids rheostat in a smoking-dependent way. These findings were validated in a meta-analysis including other public single-cell transcriptomic data.

CONCLUSIONS

In sum, our study provided a clarified view of COPD pathogenesis and demonstrated the potential of targeting monocytes in COPD diagnosis and treatment.

People critically ill with COVID-19 exhibit peripheral immune profiles predictive of mortality and reflective of SARS-CoV-2 lung viral burden

Despite extensive analyses, there remains an urgent need to delineate immune cell states that contribute to mortality in people critically ill with COVID-19. Here, we present high-dimensional profiling of blood and respiratory samples from people with severe COVID-19 to examine the association between cell-linked molecular features and mortality outcomes. Peripheral transcriptional profiles by single-cell RNA sequencing (RNA-seq)-based deconvolution of immune states are associated with COVID-19 mortality. Further, persistently high levels of an interferon signaling module in monocytes over time lead to subsequent concerted upregulation of inflammatory cytokines. SARS-CoV-2-infected myeloid cells in the lower respiratory tract upregulate CXCL10, leading to a higher risk of death. Our analysis suggests a pivotal role for viral-infected myeloid cells and protracted interferon signaling in severe COVID-19.

Predicting candidate therapeutic drugs for sepsis-induced acute respiratory distress syndrome based on transcriptome profiling

Sepsis-induced acute respiratory distress syndrome (ARDS) remains a major threat to human health without effective therapeutic drugs. Previous studies demonstrated the power of gene expression profiling to reveal pathological changes associated with sepsis-induced ARDS. However, there is still a lack of systematic data mining framework for identifying potential targets for treatment. In this study, we demonstrated the feasibility of druggable targets prediction based on gene expression data. Through the functional enrichment analysis of microarray-based expression profiles between sepsis-induced ARDS and non-sepsis ARDS samples, we revealed genes involved in anti-microbial infection immunity were significantly altered in sepsis-induced ARDS. Protein-protein interaction (PPI) network analysis highlighted TOP2A gene as the key regulator in the dysregulated gene network of sepsis-induced ARDS. We were also able to predict several therapeutic drug candidates for sepsis-induced ARDS using Connectivity Map (Cmap) database, among which doxorubicin was identified to interact with TOP2A with a high affinity similar to its endogenous ligand. Overall, our findings suggest that doxorubicin could be a potential therapeutic for sepsis-induced ARDS by targeting TOP2A, which requires further investigation and validation. The whole study relies on publicly available dataset and publicly accessible database or bioinformatic tools for data mining. Therefore, our study benchmarks a workflow for druggable target prediction which can be widely applicable in the search of targets in other pathological conditions.

Attenuated activation of pulmonary immune cells in mRNA-1273-vaccinated hamsters after SARS-CoV-2 infection

The mRNA-1273 vaccine is effective against SARS-CoV-2 and was granted emergency use authorization by the FDA. Clinical studies, however, cannot provide the controlled response to infection and complex immunological insight that are only possible with preclinical studies. Hamsters are the only model that reliably exhibits severe SARS-CoV-2 disease similar to that in hospitalized patients, making them pertinent for vaccine evaluation. We demonstrate that prime or prime-boost administration of mRNA-1273 in hamsters elicited robust neutralizing antibodies, ameliorated weight loss, suppressed SARS-CoV-2 replication in the airways, and better protected against disease at the highest prime-boost dose. Unlike in mice and nonhuman primates, low-level virus replication in mRNA-1273-vaccinated hamsters coincided with an anamnestic response. Single-cell RNA sequencing of lung tissue permitted high-resolution analysis that is not possible in vaccinated humans. mRNA-1273 prevented inflammatory cell infiltration and the reduction of lymphocyte proportions, but enabled antiviral responses conducive to lung homeostasis. Surprisingly, infection triggered transcriptome programs in some types of immune cells from vaccinated hamsters that were shared, albeit attenuated, with mock-vaccinated hamsters. Our results support the use of mRNA-1273 in a 2-dose schedule and provide insight into the potential responses within the lungs of vaccinated humans who are exposed to SARS-CoV-2.

Dynamic changes in human single-cell transcriptional signatures during fatal sepsis

Systemic infections, especially in patients with chronic diseases, may result in sepsis: an explosive, uncoordinated immune response that can lead to multisystem organ failure with a high mortality rate. Patients with similar clinical phenotypes or sepsis biomarker expression upon diagnosis may have different outcomes, suggesting that the dynamics of sepsis is critical in disease progression. A within-subject study of patients with Gram-negative bacterial sepsis with surviving and fatal outcomes was designed and single-cell transcriptomic analyses of peripheral blood mononuclear cells (PBMC) collected during the critical period between sepsis diagnosis and 6 h were performed. The single-cell observations in the study are consistent with trends from public datasets but also identify dynamic effects in individual cell subsets that change within hours. It is shown that platelet and erythroid precursor responses are drivers of fatal sepsis, with transcriptional signatures that are shared with severe COVID-19 disease. It is also shown that hypoxic stress is a driving factor in immune and metabolic dysfunction of monocytes and erythroid precursors. Last, the data support CD52 as a prognostic biomarker and therapeutic target for sepsis as its expression dynamically increases in lymphocytes and correlates with improved sepsis outcomes. In conclusion, this study describes the first single-cell study that analyzed short-term temporal changes in the immune cell populations and their characteristics in surviving or fatal sepsis. Tracking temporal expression changes in specific cell types could lead to more accurate predictions of sepsis outcomes and identify molecular biomarkers and pathways that could be therapeutically controlled to improve the sepsis trajectory toward better outcomes.

Genetics of Acute Respiratory Distress Syndrome: Pathways to Precision

Clinical risk factors alone fail to fully explain acute respiratory distress syndrome (ARDS) risk or ARDS death, suggesting that individual risk factors contribute. The goals of genomic ARDS studies include better mechanistic understanding, identifying dysregulated pathways that may be amenable to pharmacologic targeting, using genomic causal inference techniques to find measurable traits with meaning, and deconvoluting ARDS heterogeneity by proving reproducible subpopulations that may share a unique biology. This article discusses the latest advances in ARDS genomics, provides historical perspective, and highlights some of the ways that the coronavirus disease 2019 (COVID-19) pandemic is accelerating genomic ARDS research.

Autotaxin levels in serum and bronchoalveolar lavage fluid are associated with inflammatory and fibrotic biomarkers and the clinical outcome in patients with acute respiratory distress syndrome

Background

Autotaxin (ATX) is a secreted glycoprotein that is widely present in extracellular biological fluids and has been implicated in many inflammatory and fibrotic diseases. However, the clinical impact of the release of ATX in patients with acute respiratory distress syndrome (ARDS) remains unclear.

Methods

Serum and bronchoalveolar lavage fluid (BALF) levels of ATX, interleukin (IL)-6, IL-8, tumor necrosis factor (TNF)-α, matrix metalloproteinase (MMP)-7, fibronectin, oncostatin M (OSM), and SPARC (secreted protein acidic and rich in cysteine) were collected from 52 patients with ARDS within 24 h of diagnosis. All cytokines were measured by Magnetic Luminex Assay. BALF albumin (BA) and serum albumin (SA) were measured by enzyme-linked immunosorbent assay.

Results

Serum ATX, MMP-7, and BALF IL-8 levels were significantly higher in patients who did not survive than in those who survived up to 28 days after diagnosis of ARDS (P < 0.05). BALF and serum ATX levels were correlated with IL-6, IL-8, and MMP-7 levels in BALF and serum, respectively. In addition, BALF ATX was positively correlated with BALF TNF-α, fibronectin, OSM, and SPARC as well as the BA/SA ratio, while serum ATX was correlated with severity of illness based on the SOFA score and PaO₂/FIO₂ ratio. Furthermore, serum ATX was better able to predict 28-day ARDS-related mortality (area under the curve 0.744, P < 0.01) than the SOFA score, APACHE II score, or PaO₂/FIO₂ ratio. Serum ATX independently predicted mortality in a univariate Cox regression model (P < 0.0001).

Conclusion

The serum ATX level is a potential prognostic biomarker in patients with ARDS. BALF ATX is associated with pulmonary biomarkers of inflammation and fibrosis, suggesting a role of ATX in the pathogenesis of ARDS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40560-021-00559-3.

MicroRNA-877-5p alleviates ARDS via enhancing PI3K/Akt path by targeting CDKN1B both in vivo and in vitro

Acute respiratory distress syndrome (ARDS) is a public health problem with high morbidity and mortality worldwide due to lacking known characteristic biomarkers and timely intervention. Pulmonary edema caused by inflammation and pulmonary microvascular endothelial cell disfunction is the main pathophysiological change of ARDS. Circulating microRNAs (miRNAs) are differentially expressed between subjects who did and did not develop ARDS. Many miRNAs have been exemplified to be involved in ARDS and could represent the novel therapeutic targets, but the role of microRNA-877-5p (miR-877-5p) in ARDS and its regulatory mechanisms are still unknown. Herein, we explore the underlying function of miR-877-5p toward anesis of ARDS and addressed that miRNA-877 can reduce the release of tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, and IL-6 thus attenuating the damage of pulmonary microvascular endothelial cells (HPMECs). Have further evaluated the protein expression, we detected that miR-877-5p contributed to the relief of ARDS by suppressing Cyclin-dependent kinase inhibitor 1B (CDKN1B), which serves as a regulator of endothelial cell polarization and migration through phosphatidylinositol-3-kinase and AKT (PI3K/Akt) signaling pathway. Besides, we noticed that CDKN1B restrains cell differentiation by inhibiting Cdk2 (cyclin-dependent kinase 2), instead of Cdk4 (cyclin-dependent kinase 4), during which the nuclear translocation of CDKN1B may participate. Together, our works testified that miR-877-5p might suppress inflammatory responses and promote HPMECs regeneration via targeting CDKN1B by modulation of Cdk2 and PI3K/Akt path. These molecules likely modulating ARDS progression may inform biomarkers and therapeutic development.

Sepsis: deriving biological meaning and clinical applications from high-dimensional data

The pathophysiology of sepsis is multi-facetted and highly complex. As sepsis is a leading cause of global mortality that still lacks targeted therapies, increased understanding of its pathogenesis is vital for improving clinical care and outcomes. An increasing number of investigations seeks to unravel the complexity of sepsis through high-dimensional data analysis, enabled by advances in -omics technologies. Here, we summarize progress in the following major -omics fields: genomics, epigenomics, transcriptomics, proteomics, lipidomics, and microbiomics. We describe what these fields can teach us about sepsis, and highlight current trends and future challenges. Finally, we focus on multi-omics integration, and discuss the challenges in deriving biological meaning and clinical applications from these types of data.

Single-cell RNA sequencing reveals the sustained immune cell dysfunction in the pathogenesis of sepsis secondary to bacterial pneumonia

Sepsis is a leading cause of mortality in intensive care unit worldwide, it's accompanied by immune cell dysfunction induced by multiple factors. However, little is known about the specific alterations in immune cells in the dynamic pathogenesis of sepsis secondary to bacterial pneumonia. Here, we used single cell RNA sequencing (scRNA-seq) to profile peripheral blood mononuclear cells (PBMCs) in a healthy control and two patients with sepsis secondary to bacterial pneumonia, including acute, stable and recovery stage. We analyzed the quantity and function of immune cells. During disease course, interferon gamma response was upregulated; T/NK cell subtypes presented activation and exhaustion properties, which might be driven by monocytes through IL-1β signaling pathways; The proportion of plasma cells was increased, which might be driven by NK cells through IFN signaling pathways; Additionally, interferon gamma response was upregulated to a greater degree in sepsis secondary to pneumonia induced by SARS-COV-2 compared with that induced by influenza virus and bacteria.

Bifurcated monocyte states are predictive of mortality in severe COVID-19

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection presents with varied clinical manifestations1, ranging from mild symptoms to acute respiratory distress syndrome (ARDS) with high mortality2,3. Despite extensive analyses, there remains an urgent need to delineate immune cell states that contribute to mortality in severe COVID-19. We performed high-dimensional cellular and molecular profiling of blood and respiratory samples from critically ill COVID-19 patients to define immune cell genomic states that are predictive of outcome in severe COVID-19 disease. Critically ill patients admitted to the intensive care unit (ICU) manifested increased frequencies of inflammatory monocytes and plasmablasts that were also associated with ARDS not due to COVID-19. Single-cell RNAseq (scRNAseq)-based deconvolution of genomic states of peripheral immune cells revealed distinct gene modules that were associated with COVID-19 outcome. Notably, monocytes exhibited bifurcated genomic states, with expression of a cytokine gene module exemplified by CCL4 (MIP-1β) associated with survival and an interferon signaling module associated with death. These gene modules were correlated with higher levels of MIP-1β and CXCL10 levels in plasma, respectively. Monocytes expressing genes reflective of these divergent modules were also detectable in endotracheal aspirates. Machine learning algorithms identified the distinctive monocyte modules as part of a multivariate peripheral immune system state that was predictive of COVID-19 mortality. Follow-up analysis of the monocyte modules on ICU day 5 was consistent with bifurcated states that correlated with distinct inflammatory cytokines. Our data suggests a pivotal role for monocytes and their specific inflammatory genomic states in contributing to mortality in life-threatening COVID-19 disease and may facilitate discovery of new diagnostics and therapeutics.