Evolution of ARDS biomarkers: Will metabolomics be the answer?

To explore pharmacodynamic substances and mechanism of Xuanfei Baidu Decoction on LPS-induced ALI / ARDS by pharmacochemistry and metabolomics

ETHNOPHARMACOLOGICAL RELEVANCE

Xuanfei Baidu Decoction (XFBD) is made up of five classic prescriptions, which is composed of 13 traditional Chinese medicines, which have the effects of dispersing lung and resolving dampness, clearing heat and evil, purging lung and detoxification. It is used for epidemic diseases caused by damp toxin obstructing lung. In this paper, the endogenous and exogenous metabolites of ALI/ARDS rats after oral administration of XFBD were studied and the material basis and metabolic pathway of XFBD in relieving ALI/ARDS were explained.

MATERIALS AND METHODS

In this study, UPLC-Q-TOF/MS qualitative analysis method was established, and plasma-urine-feces pharmacochemistry was used to identify metabolites in plasma, urine and feces after oral administration of XFBD in rats. RT-PCR and immunohistochemistry were used to study the expression of CYP protein in XFBD and monomeric compounds. In addition, the functional mechanism of XFBD in ALI/ARDS rats was elucidated by non-targeted metabolomics.

RESULTS

A total of 77 prototype components and 389 metabolites in plasma, urine and feces were identified by exogenous components, mainly including oxidation, reduction, hydrolysis, glucuronidation, sulfation and other reactions. The results of RT-PCR and immunohistochemistry showed that the activity of CYP was inhibited under the pathological state of ALI/ARDS. At the same time, XFBD and its monomeric compounds can change the metabolic process of drugs in vivo by inducing or inhibiting the activity of CYPs. The metabolic process of drugs in vivo is the result of the combined action of different CYPs. In addition, a total of 33 differential metabolites were identified in plasma, 45 in urine and 14 in feces, which were mainly related to the synthesis and degradation of ketone bodies, phenylalanine metabolism, tyrosine metabolism, histidine metabolism, butyric acid metabolism and other metabolic pathways.

CONCLUSIONS

This study conducted a relatively scientific and systematic analysis of XFBD. A UPLC-Q-TOF/MS qualitative analysis method was established to identify 77 prototype components and 389 metabolites in plasma, urine and feces of rats after oral administration of XFBD.An ARDS rat model was established to analyze the pharmacokinetic differences of XFBD in normal and ARDS model rats and its regulation effect on CYPs.Non-targeted metabolomics was used to identify the pattern recognition of ARDS pathological model, the diagnosis of disease and the intervention effect of XFBD on ARDS. Preliminary discussion was conducted to provide a theoretical basis for clinical rational drug use.

Platelet count as a prognostic marker for acute respiratory distress syndrome

BACKGROUND

This study aimed to evaluate the role of platelet count (PLT) in the prognosis of patients with acute respiratory distress syndrome (ARDS).

METHODS

The data were extracted from the Medical Information Mart for Intensive Care database (version 2.2). Patients diagnosed with ARDS according to criteria from Berlin Definition and had the platelet count (PLT) measured within the first day after intensive care unit admission were analyzed. Based on PLT, ARDS patients were divided into four groups: PLT ≤ 100 × 109/L, PLT 101-200 × 109/L, PLT 201-300 × 109/L, and PLT > 300 × 109/L. The primary outcome was 28-day mortality. Survival probabilities were analyzed using Kaplan-Meier. Furthermore, the association between PLT and mortality in ARDS patients was assessed using a univariate and multivariable Cox proportional hazards model.

RESULTS

Overall, the final analysis included 3,207 eligible participants with ARDS. According to the Kaplan-Meier curves for 28-day mortality of PLT, PLT ≤ 100 × 109/L was associated with a higher incidence of mortality (P = 0.001), the same trends were observed in the 60-day (P = 0.001) and 90-day mortality (P = 0.001). In the multivariate model adjusted for the potential factors, the adjusted hazard ratio at PLT 101-200 × 109/L group, PLT 201-300 × 109/L, and PLT > 300 × 109/L was 0.681 [95% confidence interval (CI): 0.576-0.805, P < 0.001], 0.733 (95% CI: 0.604-0.889, P = 0.002), and 0.787 (95% CI: 0.624-0.994, P = 0.044) compared to the reference group (PLT ≤ 100 × 109/L), respectively. Similar relationships between the PLT ≤ 100 × 109/L group and 28-day mortality were obtained in most subgroups.

CONCLUSION

PLT appeared to be an independent predictor of mortality in critically ill patients with ARDS.

The Synthetic Surfactant CHF5633 Restores Lung Function and Lung Architecture in Severe Acute Respiratory Distress Syndrome in Adult Rabbits

PURPOSE

Acute respiratory distress syndrome (ARDS) is a major cause of hypoxemic respiratory failure in adults. In ARDS extensive inflammation and leakage of fluid into the alveoli lead to dysregulation of pulmonary surfactant metabolism and function. Altered surfactant synthesis, secretion, and breakdown contribute to the clinical features of decreased lung compliance and alveolar collapse. Lung function in ARDS could potentially be restored with surfactant replacement therapy, and synthetic surfactants with modified peptide analogues may better withstand inactivation in ARDS alveoli than natural surfactants.

METHODS

This study aimed to investigate the activity in vitro and the bolus effect (200 mg phospholipids/kg) of synthetic surfactant CHF5633 with analogues of SP-B and SP-C, or natural surfactant Poractant alfa (Curosurf®, both preparations Chiesi Farmaceutici S.p.A.) in a severe ARDS model (the ratio of partial pressure arterial oxygen and fraction of inspired oxygen, P/F ratio ≤ 13.3 kPa) induced by hydrochloric acid instillation followed by injurious ventilation in adult New Zealand rabbits. The animals were ventilated for 4 h after surfactant treatment and the respiratory parameters, histological appearance of lung parenchyma and levels of inflammation, oxidative stress, surfactant dysfunction, and endothelial damage were evaluated.

RESULTS

Both surfactant preparations yielded comparable improvements in lung function parameters, reductions in lung injury score, pro-inflammatory cytokines levels, and lung edema formation compared to untreated controls.

CONCLUSIONS

This study indicates that surfactant replacement therapy with CHF5633 improves lung function and lung architecture, and attenuates inflammation in severe ARDS in adult rabbits similarly to Poractant alfa. Clinical trials have so far not yielded conclusive results, but exogenous surfactant may be a valid supportive treatment for patients with ARDS given its anti-inflammatory and lung-protective effects.

Biomarkers in Sepsis: A Current Review of New Technologies

Sepsis syndromes have been recognized since antiquity yet still pose significant challenges to modern medicine. One of the biggest challenges lies in the heterogeneity of triggers and its protean clinical manifestations, as well as its rapidly progressive and lethal nature. Thus, there is a critical need for biomarkers that can quickly and accurately detect sepsis onset and predict treatment response. In this review, we will briefly describe the current consensus definitions of sepsis and the ideal features of a biomarker. We will then delve into currently available and in-development markers of pathogens, hosts, and their interactions that together comprise the sepsis syndrome.

Metabolic signatures of acute respiratory distress syndrome: COVID versus non-COVID

Acute respiratory distress syndrome (ARDS) is a fatal pulmonary disorder characterized by severe hypoxia and inflammation. ARDS is commonly triggered by systemic and pulmonary infections, with bacteria and viruses. Notable pathogens include Pseudomonas aeruginosa, Streptococcus aureus, Enterobacter species, coronaviruses, influenza viruses, and herpesviruses. COVID-19 ARDS represents the latest etiological phenotype of the disease. The pathogenesis of ARDS caused by bacteria and viruses exhibits variations in host immune responses and lung mesenchymal injury. We postulate that the systemic and pulmonary metabolomics profiles of ARDS induced by COVID-19 pathogens may exhibit distinctions compared with those induced by other infectious agents. This review aims to compare metabolic signatures in blood and lung specimens specifically within the context of ARDS. Both prevalent and phenotype-specific metabolomic signatures, including but not limited to glycolysis, ketone body production, lipid oxidation, and dysregulation of the kynurenine pathways, were thoroughly examined in this review. The distinctions in metabolic signatures between COVID-19 and non-COVID ARDS have the potential to reveal new biomarkers, elucidate pathogenic mechanisms, identify druggable targets, and facilitate differential diagnosis in the future.

Expression and significance of serum KL-6 in patients with acute respiratory distress syndrome

Background

Acute respiratory distress syndrome (ARDS) is a common and serious complication that occurs in the ICU. the determination of early ARDS indicators, along with timely treatment, can potentially diminish medical costs and reduce ARDS-related mortality. In this report, we evaluated the clinical significance of circulating Krebs von den Lungen-6 (KL-6) content among patients with intra- and extrapulmonary ARDS to investigate the clinical significance of serum KL-6.

Methods

Patients who met the ARDS Berlin criteria and were hospitalized in the intensive care unit of the China-Japan Union Hospital of Jilin University between September 2021 and September 2022 were recruited for analysis. ARDS patients were divided into an intrapulmonary ARDS group (n=23) and an extrapulmonary ARDS group (n=27) based on their primary diagnosis. Baseline demographic data, including age and sex, and clinical data, including underlying diseases and mortality, of the two groups were collected and analyzed. Peripheral venous blood was collected on Day 0 (baseline), Day 1, Day 3, and Day 7. The kinetic levels of serum KL-6 were compared between patients who survived and those who died within one week of ARDS diagnosis. The prognosis, survival times, and status of patients within 28 days after diagnosis were evaluated.

Results

In the intrapulmonary ARDS group, patients who died had significantly higher serum KL-6 levels in the seven days following diagnosis than those who survived. In contrast, in the extrapulmonary group, the difference in KL-6 values between patients who survived and died was only significant on the first day after diagnosis. The peak levels of serum KL-6 in the death group were significantly higher than those in the survival group for both intra- and extrapulmonary ARDS (P=0.0253). The optimal cutoff value of the serum KL-6 level was 1,452.3 U/mL in intrapulmonary ARDS patients and 828.2 U/mL in extrapulmonary patients. Serum KL-6 levels higher than the cutoff levels were confirmed to be a significant prognostic predictor of poor survival within 28 days of diagnosis in patients with intra- and extrapulmonary ARDS.

Conclusions

The serum KL-6 level is potentially a good indicator for predicting the prognosis of patients with ARDS.

Stability and structure-activity relationship of the SPA4 peptide under ambient and stressed conditions of lung injury

Lung inflammation and injuries are major health problems. The SPA4 peptide (amino acid sequence GDFRYSDGTPVNYTNWYRGE) binds to Toll-like receptor-4 and exerts anti-inflammatory activity. In this study, we have determined the stability of the structure and structure-activity relationship of the SPA4 peptide under ambient and stressed conditions of lung injury. The SPA4 peptide was maintained at different pH and temperatures, in solutions of different ionic strengths, and simulated lung fluids. The primary and secondary structure of the SPA4 peptide was determined by ultraviolet-visible (UV-VIS) and circular dichroism (CD) spectroscopy. The activity of the SPA4 peptide was determined by measurement of secreted levels of chemokine C-X-C motif ligand 1/keratinocyte-derived chemokine (CXCL1/KC) and lactate by primary mouse lung epithelial cells against lipopolysaccharide (LPS) stimuli. Our results demonstrate the stability of the structure of the SPA4 peptide at room temperature and 4 °C over 10 days. The original UV-VIS spectra of the SPA4 peptide followed a typical pattern when incubated in solutions of pH 5.7, 7.0, and 8.0 at different temperatures, simulated lung fluids, and most of the chemical components. Slight shifts in the absorbance peaks, derivative values, and vibrational fine structures were noted in the fourth-derivative spectra of the SPA4 peptide under some conditions. An increased level of lactate is the hallmark of lung injury. The SPA4 peptide on its own and in the presence of lactate exerts anti-inflammatory activity. The primary and secondary structure and the activity of the SPA4 peptide remain intact when pre-incubated in 2 mM sodium lactate solution. The results provide important insights about the stability and structure-activity relationship of the SPA4 peptide.

Serum metabolomic signatures of fatty acid oxidation defects differentiate host-response subphenotypes of acute respiratory distress syndrome

BACKGROUND

Fatty acid oxidation (FAO) defects have been implicated in experimental models of acute lung injury and associated with poor outcomes in critical illness. In this study, we examined acylcarnitine profiles and 3-methylhistidine as markers of FAO defects and skeletal muscle catabolism, respectively, in patients with acute respiratory failure. We determined whether these metabolites were associated with host-response ARDS subphenotypes, inflammatory biomarkers, and clinical outcomes in acute respiratory failure.

METHODS

In a nested case-control cohort study, we performed targeted analysis of serum metabolites of patients intubated for airway protection (airway controls), Class 1 (hypoinflammatory), and Class 2 (hyperinflammatory) ARDS patients (N = 50 per group) during early initiation of mechanical ventilation. Relative amounts were quantified by liquid chromatography high resolution mass spectrometry using isotope-labeled standards and analyzed with plasma biomarkers and clinical data.

RESULTS

Of the acylcarnitines analyzed, octanoylcarnitine levels were twofold increased in Class 2 ARDS relative to Class 1 ARDS or airway controls (P = 0.0004 and < 0.0001, respectively) and was positively associated with Class 2 by quantile g-computation analysis (P = 0.004). In addition, acetylcarnitine and 3-methylhistidine were increased in Class 2 relative to Class 1 and positively correlated with inflammatory biomarkers. In all patients within the study with acute respiratory failure, increased 3-methylhistidine was observed in non-survivors at 30 days (P = 0.0018), while octanoylcarnitine was increased in patients requiring vasopressor support but not in non-survivors (P = 0.0001 and P = 0.28, respectively).

CONCLUSIONS

This study demonstrates that increased levels of acetylcarnitine, octanoylcarnitine, and 3-methylhistidine distinguish Class 2 from Class 1 ARDS patients and airway controls. Octanoylcarnitine and 3-methylhistidine were associated with poor outcomes in patients with acute respiratory failure across the cohort independent of etiology or host-response subphenotype. These findings suggest a role for serum metabolites as biomarkers in ARDS and poor outcomes in critically ill patients early in the clinical course.

Research Progress on Phenotypic Classification of Acute Respiratory Distress Syndrome: A Narrative Review

Acute respiratory distress syndrome (ARDS) is a clinical syndrome that is characterized by an acute onset and refractory hypoxemia. It remains an important contributor to high mortality in critically ill patients, and the majority of clinical randomized controlled trials on ARDS provide underwhelming findings, which is attributed in large part to its pathophysiological and clinical heterogeneity, among other aspects. It is now widely accepted that ARDS is highly heterogeneous, growing evidences support this. ARDS phenotypic and subphenotypic studies aim to further differentiate and identify ARDS heterogeneity in the hope that clinicians can benefit from it, then can diagnose ARDS faster and more accurately and provide targeted treatments. This review collates and evaluates the major phenotype-related research advances of recent years, with a specific focus on ARDS biomarkers and clinical factors.

Personalized medicine using omics approaches in acute respiratory distress syndrome to identify biological phenotypes

In the last decade, research on acute respiratory distress syndrome (ARDS) has made considerable progress. However, ARDS remains a leading cause of mortality in the intensive care unit. ARDS presents distinct subphenotypes with different clinical and biological features. The pathophysiologic mechanisms of ARDS may contribute to the biological variability and partially explain why some pharmacologic therapies for ARDS have failed to improve patient outcomes. Therefore, identifying ARDS variability and heterogeneity might be a key strategy for finding effective treatments. Research involving studies on biomarkers and genomic, metabolomic, and proteomic technologies is increasing. These new approaches, which are dedicated to the identification and quantitative analysis of components from biological matrixes, may help differentiate between different types of damage and predict clinical outcome and risk. Omics technologies offer a new opportunity for the development of diagnostic tools and personalized therapy in ARDS. This narrative review assesses recent evidence regarding genomics, proteomics, and metabolomics in ARDS research.

Whole Transcriptomic Analysis of Key Genes and Signaling Pathways in Endogenous ARDS

Objective

To analyze the differentially expressed genes (DEGs) in rats with endogenous acute respiratory distress syndrome (ARDS) lung injury and explore the pathogenesis and early diagnostic molecular markers using whole transcriptomic data.

Methods

Twelve 8-week-old male Sprague Dawley rats were selected and randomly and equally divided into ARDS lung injury group and normal control group. RNA was extracted from the left lung tissues of both the groups and sequenced using the paired-end sequencing mode of the Illumina Hiseq sequencing platform. The DEGs of miRNA, cirRNA, lncRNA, and mRNA were screened using DESeq2 software, and the ceRNA regulatory network was constructed using Cytoscape. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using the mRNA DEGs. STRING and Cytoscape software were used to construct the protein interaction network and identify the 15 key genes, which were verified using quantitative real-time polymerase chain reaction (qRT-PCR).

Results

Based on different screening conditions, and compared with the control group, the ARDS lung injury group showed 836 mRNA DEGs (386 upregulated and 450 downregulated), 110 lncRNA DEGs (53 upregulated and 57 downregulated), 19 circRNA DEGs (3 upregulated and 16 downregulated), and 6 miRNA DEGs (5 upregulated and 1 downregulated gene). GO showed that the DEGs of mRNA were mainly involved in biological processes, such as defense response to lipopolysaccharide and other organisms, leukocyte chemotaxis, neutrophil chemotaxis, and cytokine-mediated signaling. KEGG enrichment analysis showed that the DEGs played their biological roles mainly by participating in IL-17, TNF, and chemokine signaling pathways. The PPI analysis showed a total of 281 node proteins and 634 interaction edges. The top 15 key genes, which were screened, included Cxcl10, Mx1, Irf7, Isg15, Ifit3, Ifit2, Rsad2, Ifi47, Oasl, Dhx58, Usp18, Cmpk2, Herc6, Ifit1, and Gbp4. The ceRNA network analysis showed 69 nodes and 73 correlation pairs, where the key gene nodes were miR-21-3p, Camk2g, and Stx2.

Conclusions

The chemotaxis, migration, and degranulation of inflammatory cells, cytokine immune response, autophagy, and apoptosis have significant biological functions in the occurrence and development of endogenous acute lung injury during ARDS. Thus, the camk2g/miR-21-3p/lncRNA/circRNA network, CXCL10/CXCR3, and IL-17 signaling pathways might provide novel insights and targets for further studying the lung injury mechanism and clinical treatment.

Kynurenine Pathway of Tryptophan Metabolism Is Associated with Hospital Mortality in Patients with Acute Respiratory Distress Syndrome: A Prospective Cohort Study

Acute respiratory distress syndrome (ARDS) involves dysregulated immune-inflammatory responses, characterized by severe oxidative stress and high mortality. Metabolites modulating the inflammatory and immune responses may play a central role in the pathogenesis of ARDS. Most biogenic amines may induce the production of reactive oxygen species, oxidative stress, mitochondrial dysfunction, and programmed cell death. We conducted a prospective study on metabolic profiling specific to the amino acids and biogenic amines of 69 patients with ARDS. Overall, hospital mortality was 52.2%. Between day 1 and day 7 after ARDS onset, plasma kynurenine levels and the kynurenine/tryptophan ratio were significantly higher among non-survivors than in survivors (all p < 0.05). Urine metabolic profiling revealed a significantly higher prevalence of tryptophan degradation and higher concentrations of metabolites downstream of the kynurenine pathway among non-survivors than among survivors upon ARDS onset. Cox regression models revealed that plasma kynurenine levels and the plasma kynurenine/tryptophan ratio on day 1 were independently associated with hospital mortality. The activation of the kynurenine pathway was associated with mortality in patients with ARDS. Metabolic phenotypes and modulating metabolic perturbations of the kynurenine pathway could perhaps serve as prognostic markers or as a target for therapeutic interventions aimed at reducing oxidative stress and mortality in ARDS.

Plasma microRNA and metabolic changes associated with pediatric acute respiratory distress syndrome: a prospective cohort study

Acute respiratory distress syndrome is a heterogeneous pathophysiological process responsible for significant morbidity and mortality in pediatric intensive care patients. Diagnosis is defined by clinical characteristics that identify the syndrome after development. Subphenotyping patients at risk of progression to ARDS could provide the opportunity for therapeutic intervention. microRNAs, non-coding RNAs stable in circulation, are a promising biomarker candidate. We conducted a single-center prospective cohort study to evaluate random forest classification of microarray-quantified circulating microRNAs in critically ill pediatric patients. We additionally selected a sub-cohort for parallel metabolomics profiling as a pilot study for concurrent use of miRNAs and metabolites as circulating biomarkers. In 35 patients (n = 21 acute respiratory distress, n = 14 control) 15 microRNAs were differentially expressed. Unsupervised random forest classification accurately grouped ARDS and control patients with an area under the curve of 0.762, which was improved to 0.839 when subset to only patients with bacterial infection. Nine metabolites were differentially abundant between acute respiratory distress and control patients (n = 4, both groups) and abundance was highly correlated with miRNA expression. Random forest classification of microRNAs differentiated critically ill pediatric patients who developed acute respiratory distress relative to those who do not. The differential expression of microRNAs and metabolites provides a strong foundation for further work to validate their use as a prognostic biomarker.

The importance of a sepsis layered early warning system for critical patients

Critical illness, particularly sepsis, is associated with high mortality, so prevention is more important than effective therapy. Advances in medical science have provided more opportunities for early warning and early intervention to avoid the development of critical illness. Existing early warning systems (EWS) have the advantages of high efficiency and convenience. However, with the development of medical technology, they do not completely meet clinical needs. EWS should contain elements that meet many dimensions of clinical requirements, including risk warning, response warning, injury warning, critical warning, and death warning. By summarizing previous studies, we outlined a layered EWS that follows RISK bundles. RISK represents different warning sign categories: R: host response, I: organ injury, S: changes in vital signs, and K: gradual appearance of "killed" organs. We plan to construct a complete layered EWS to guide clinical activities and subsequent clinical studies in the near future.

Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival

Background

Metabolic predictors and potential mediators of survival in sepsis have been incompletely characterized. We examined whether machine learning (ML) tools applied to the human plasma metabolome could consistently identify and prioritize metabolites implicated in sepsis survivorship, and whether these methods improved upon conventional statistical approaches.

Methods

Plasma gas chromatography–liquid chromatography mass spectrometry quantified 411 metabolites measured ≤ 72 h of ICU admission in 60 patients with sepsis at a single center (Brigham and Women’s Hospital, Boston, USA). Seven ML approaches were trained to differentiate survivors from non-survivors. Model performance predicting 28 day mortality was assessed through internal cross-validation, and innate top-feature (metabolite) selection and rankings were compared across the 7 ML approaches and with conventional statistical methods (logistic regression). Metabolites were consensus ranked by a summary, ensemble ML ranking procedure weighing their contribution to mortality risk prediction across multiple ML models.

Results

Median (IQR) patient age was 58 (47, 62) years, 45% were women, and median (IQR) SOFA score was 9 (6, 12). Mortality at 28 days was 42%. The models’ specificity ranged from 0.619 to 0.821. Partial least squares regression-discriminant analysis and nearest shrunken centroids prioritized the greatest number of metabolites identified by at least one other method. Penalized logistic regression demonstrated top-feature results that were consistent with many ML methods. Across the plasma metabolome, the 13 metabolites with the strongest linkage to mortality defined through an ensemble ML importance score included lactate, bilirubin, kynurenine, glycochenodeoxycholate, phenylalanine, and others. Four of these top 13 metabolites (3-hydroxyisobutyrate, indoleacetate, fucose, and glycolithocholate sulfate) have not been previously associated with sepsis survival. Many of the prioritized metabolites are constituents of the tryptophan, pyruvate, phenylalanine, pentose phosphate, and bile acid pathways.

Conclusions

We identified metabolites linked with sepsis survival, some confirming prior observations, and others representing new associations. The application of ensemble ML feature-ranking tools to metabolomic data may represent a promising statistical platform to support biologic target discovery.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-022-00445-8.

The effect of N6-methyladenosine (m6A) factors on the development of acute respiratory distress syndrome in the mouse model

Acute respiratory distress syndrome (ARDS) can cause loss of alveolar-capillary membrane integrity and life-threatening immune responses. The underlying molecular mechanisms of ARDS remain unclear. N6-methyladenosine (m6A)-RNA modification plays an important part in many biological processes. However, it is not clear whether ARDS alters RNA methylation in lung tissue. We tried to investigate the changes of m6A-RNA methylation in lung tissues of lipopolysaccharide (LPS)-induced ARDS mice. Lung tissue samples were collected to detect the expression of m6A factors through hematoxylin and eosin (HE) staining, quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR), immunohistochemical analysis and western blot. The overall m6A levels in lung tissue of ARDS in mouse were detected by UPLC-UV-MS. HE staining showed that the degree of the inflammatory response was more severe in the LPS-3 h group. The mRNA expression of YTHDF1, YTHDC1 and IGFBP3 was remarkably up-regulated at, respectively, 6, 6 and 12 h after LPS treatment. The mRNA expression of METTL16, FTO, METTL3, KIAA1429, RBM15, ALKBH5, YTHDF2, YTHDF3, YTHDC2 and IGFBP2 was significantly down-regulated at 24 h after LPS treatment. The protein expression of METTL16 and FTO increased, YTHDC1, IGFBP3 YTHDF1 and YTHDF3 showed a down-regulation trend after LPS induction. Overall m6A-RNA methylation levels were significantly increased at 6 h after LPS induction. In ARDS mice, LPS-induced m6A methylation may be involved in the expression regulation of inflammatory factors and may play important roles in the occurrence and development of lung tissue. It is suggested that m6A modification may be a promising therapeutic target for ARDS.

Impact of Plasma 5 Hydroxyindoleacetic Acid, a Serotonin Metabolite, on Clinical Severity in Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is characterized by dysregulated vascular permeability. The clinical outcomes remain poor, and the disease burden is widespread. We demonstrated that plasma 5-hydroxyindoleacetic acid (5-HIAA), a serotonin metabolite, is a pivotal severity indicator of ARDS. Serotonin is an effector of cellular contraction and a modulator of vascular permeability. Plasma 5-HIAA levels were significantly elevated in severe ARDS cases with shock status (p = 0.047) and positively correlated with SOFA (p < 0.0001) and APACHE-II score (p < 0.0001). In the longitudinal analysis, plasma 5-HIAA levels were also a strong independent predictor of mortality rate (p = 0.005). This study indicates that plasma 5-HIAA is a biomarker of ARDS severity and highlights the importance of evaluating vascular leakage levels for ARDS treatment.

An analysis of the 28-day mortality risk factors in acute respiratory distress syndrome patients and the establishment of prediction models

OBJECTIVE

To explore the risk factors and prediction models of 28-day mortality in acute respiratory distress syndrome (ARDS) patients.

METHODS

A total of 215 ARDS patients treated in our hospital were enrolled in this prospective observational study, including 70 patients who died within 28 days and were placed in the death group, and the remaining 145 patients who survived and were placed in the survival group. The laboratory examination indexes and critical scoring system scores were compared between the two groups. A Cox regression analysis was used to analyze the factors associated with 28-day mortality, and a receiver operating characteristic (ROC) curve was used to analyze the performance of the prediction models.

RESULTS

The ROC curve analysis showed that the erythrocyte distribution width (RDW), the neutrophil to lymphocyte ratio (NLR), the procalcitonin to albumin ratio (PAR), and the Murray lung injury score (MLIS) were effective at diagnosing the 28-day mortality, each with an area under the curve (AUC) of >0.5 (P<0.001). A multivariate Cox analysis showed that the RDW, NLR, PAR, and MLIS were independent predictors of 28-day mortality. The results of the multi-index joint prediction showed that the AUC of RDW+NLR+PAR+MLIS was 0.945 (95% CI: 0.910-0.979), and the sensitivity was as high as 94.25%.

CONCLUSION

NLR, PAR, RDW, and MLIS are independent predictors of 28-day mortality, and their combined prediction can significantly improve the predictive ability of the 28-day mortality in ARDS patients.

A metabolomic endotype of bioenergetic dysfunction predicts mortality in critically ill patients with acute respiratory failure

Acute respiratory failure (ARF) requiring mechanical ventilation, a complicating factor in sepsis and other disorders, is associated with high morbidity and mortality. Despite its severity and prevalence, treatment options are limited. In light of accumulating evidence that mitochondrial abnormalities are common in ARF, here we applied broad spectrum quantitative and semiquantitative metabolomic analyses of serum from ARF patients to detect bioenergetic dysfunction and determine its association with survival. Plasma samples from surviving and non-surviving patients (N = 15/group) were taken at day 1 and day 3 after admission to the medical intensive care unit and, in survivors, at hospital discharge. Significant differences between survivors and non-survivors (ANOVA, 5% FDR) include bioenergetically relevant intermediates of redox cofactors nicotinamide adenine dinucleotide (NAD) and NAD phosphate (NADP), increased acyl-carnitines, bile acids, and decreased acyl-glycerophosphocholines. Many metabolites associated with poor outcomes are substrates of NAD(P)-dependent enzymatic processes, while alterations in NAD cofactors rely on bioavailability of dietary B-vitamins thiamine, riboflavin and pyridoxine. Changes in the efficiency of the nicotinamide-derived cofactors' biosynthetic pathways also associate with alterations in glutathione-dependent drug metabolism characterized by substantial differences observed in the acetaminophen metabolome. Based on these findings, a four-feature model developed with semi-quantitative and quantitative metabolomic results predicted patient outcomes with high accuracy (AUROC = 0.91). Collectively, this metabolomic endotype points to a close association between mitochondrial and bioenergetic dysfunction and mortality in human ARF, thus pointing to new pharmacologic targets to reduce mortality in this condition.

Biomarkers in acute respiratory distress syndrome

PURPOSE OF REVIEW

This article provides an overview of protein biomarkers for acute respiratory distress syndrome (ARDS) and their potential use in future clinical trials.

RECENT FINDINGS

The protein biomarkers studied as indices of biological processes involved in the pathogenesis of ARDS may have diagnostic and/or prognostic value. Recently, they also proved useful for identifying ARDS phenotypes and assessing heterogeneity of treatment effect in retrospective analyses of completed clinical trials.

SUMMARY

This article summarizes the current research on ARDS biomarkers and provides insights into how they should be integrated as prognostic and predictive enrichment tools in future clinical trials.

Identification of Genes with Altered Methylation and Its Role in Early Diagnosis of Sepsis-Induced Acute Respiratory Distress Syndrome

Purpose

Early diagnosis of sepsis-induced acute respiratory distress syndrome (ARDS) is critical for effective treatment. We aimed to identify early stage biomarkers.

Materials and Methods

Differentially expressed genes were identified in whole blood samples from patients with sepsis or ARDS based on the Gene Expression Omnibus (GEO) datasets GSE32707, GSE54514 and GSE10361. Functional enrichment analysis explored the biological characteristics of differentially expressed genes. Genes with high functional connectivity based on a protein-protein interaction network were marked as hub genes, which were validated using the GEO dataset GSE76293, and a gene set variation analysis index (GSVA) was assigned. Diagnostic and predictive ability of the hub genes were assessed by receiver operating characteristic (ROC) curve analysis. DNA methylation levels of hub genes were quantified using the GEO dataset GSE67530.

Results

Forty-one differentially expressed genes were shared between sepsis-specific and ARDS-specific datasets. MAP2K2 and IRF7 functional activity was highly connected in sepsis-induced ARDS. Hub genes included RETN, MVP, DEFA4, CTSG, AZU1, FMNL1, RBBP7, POLD4, RIN3, IRF7. ROC curve analysis of the hub gene GSVA index showed good diagnostic ability in sepsis or ARDS. Among genes related to sepsis-induced ARDS, 17 were differentially methylated. Principal component analysis and heatmaps indicated that gene methylation patterns differed significantly between ARDS patients and controls.

Conclusion

We identified a genetic profile specific to early-stage sepsis-induced ARDS. The abnormal expression of these genes may be caused by hypomethylation, which may serve as a biomarker for early diagnosis of ARDS.

Association of Serum Mannose With Acute Respiratory Distress Syndrome Risk and Survival

IMPORTANCE

Acute respiratory distress syndrome (ARDS) confers high mortality risk among critically ill patients. Identification of biomarkers associated with ARDS risk may guide clinical diagnosis and prognosis.

OBJECTIVE

To systematically evaluate the association of blood metabolites with ARDS risk and survival.

DESIGN, SETTING, AND PARTICIPANTS

In this cohort study, data from the Molecular Epidemiology of ARDS (MEARDS) study, a prospective cohort of 403 patients with ARDS and 1227 non-ARDS controls, were analyzed. Patients were recruited in intensive care units (ICUs) at Massachusetts General Hospital and Beth Israel Deaconess Medical Center, both in Boston, Massachusetts, from January 1, 1998, to December 31, 2014. Data analysis was performed from December 9, 2018, to January 4, 2019.

MAIN OUTCOMES AND MEASURES

Participants were followed up daily for ARDS development defined by Berlin criteria, requiring fulfillment of chest radiograph and oxygenation criteria on the same calendar day during invasive ventilatory assistance. A 2-stage study design was used to explore novel metabolites associated with ARDS risk and survival.

RESULTS

Of the 1630 participants from MEARDS who were admitted to the ICU , 403 (24.7%) were diagnosed with ARDS (mean [SD] age, 63.0 [17.0] years; 251 [62.3%] male) and 1227 (75.3%) were at-risk but did not have ARDS (mean [SD] age, 62.3 [16.9] years; 753 [61.4%] male). Mendelian randomization suggested that genetically regulated serum mannose was associated with ARDS risk (odds ratio [OR], 0.64; 95% CI, 0.53-0.78; P = 7.46 × 10-6) in the discovery stage. In the functional validation stage incorporating 83 participants with ARDS and matched at-risk participants in the control group from the ICU, the protective association of mannose with ARDS risk was validated (OR, 0.67; 95% CI, 0.46-0.97; P = .03). Furthermore, serum mannose was associated with 28-day (OR, 0.25; 95% CI, 0.11-0.56; P = 6.95 × 10-4) and 60-day (OR, 0.36; 95% CI, 0.19-0.71; P = 3.12 × 10-3) mortality and 28-day (hazard ratio, 0.49; 95% CI, 0.32-0.74; P = 6.41 × 10-4) and 60-day (hazard ratio, 0.55; 95% CI, 0.37-0.80; P = 2.11 × 10-3) survival.

CONCLUSIONS AND RELEVANCE

In this study, genetically regulated serum mannose appeared to be associated with ARDS risk and outcome, and increased serum mannose at admission was associated with reduced ARDS risk and better survival. These findings could inform prevention and clinical intervention in ARDS cases, which have increased with the expansion of the coronavirus disease 2019 pandemic.

Therapeutic targeting of metabolic alterations in acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) remains a significant source of mortality in critically ill patients. Characterised by acute, widespread alveolar inflammation and pulmonary oedema, its pathophysiological heterogeneity has meant that targeted treatments have remained elusive. Metabolomic analysis has made initial steps in characterising the underlying metabolic derangements of ARDS as an indicator of phenotypical class and has identified mitochondrial dysfunction as a potential therapeutic target. Mesenchymal stem cells and their derived extracellular vesicles have shown significant promise as potential therapies in delivering mitochondria in order to redivert metabolism onto physiological pathways.

Systems Biology ARDS Research with a Focus on Metabolomics

Acute respiratory distress syndrome (ARDS) is a clinical syndrome that inflicts a considerably heavy toll in terms of morbidity and mortality. While there are multitudes of conditions that can lead to ARDS, the vast majority of ARDS cases are caused by a relatively small number of diseases, especially sepsis and pneumonia. Currently, there is no clinically agreed upon reliable diagnostic test for ARDS, and the detection or diagnosis of ARDS is based on a constellation of laboratory and radiological tests in the absence of evidence of left ventricular dysfunction, as specified by the Berlin definition of ARDS. Virtually all the ARDS biomarkers to date have been proven to be of very limited clinical utility. Given the heterogeneity of ARDS due to the wide variation in etiology, clinical and molecular manifestations, there is a current scientific consensus agreement that ARDS is not just a single entity but rather a spectrum of conditions that need further study for proper classification, the identification of reliable biomarkers and the adequate institution of therapeutic targets. This scoping review aims to elucidate ARDS omics research, focusing on metabolomics and how metabolomics can boost the study of ARDS biomarkers and help to facilitate the identification of ARDS subpopulations.

Recent advances in our understanding of the mechanisms of lung alveolarization and bronchopulmonary dysplasia

Bronchopulmonary dysplasia (BPD) is the most common cause of morbidity and mortality in preterm infants. A key histopathological feature of BPD is stunted late lung development, where the process of alveolarization-the generation of alveolar gas exchange units-is impeded, through mechanisms that remain largely unclear. As such, there is interest in the clarification both of the pathomechanisms at play in affected lungs, and the mechanisms of de novo alveoli generation in healthy, developing lungs. A better understanding of normal and pathological alveolarization might reveal opportunities for improved medical management of affected infants. Furthermore, disturbances to the alveolar architecture are a key histopathological feature of several adult chronic lung diseases, including emphysema and fibrosis, and it is envisaged that knowledge about the mechanisms of alveologenesis might facilitate regeneration of healthy lung parenchyma in affected patients. To this end, recent efforts have interrogated clinical data, developed new-and refined existing-in vivo and in vitro models of BPD, have applied new microscopic and radiographic approaches, and have developed advanced cell-culture approaches, including organoid generation. Advances have also been made in the development of other methodologies, including single-cell analysis, metabolomics, lipidomics, and proteomics, as well as the generation and use of complex mouse genetics tools. The objective of this review is to present advances made in our understanding of the mechanisms of lung alveolarization and BPD over the period 1 January 2017-30 June 2019, a period that spans the 50th anniversary of the original clinical description of BPD in preterm infants.

Exhaled breath metabolomics reveals a pathogen-specific response in a rat pneumonia model for two human pathogenic bacteria: a proof-of-concept study

Volatile organic compounds in breath can reflect host and pathogen metabolism and might be used to diagnose pneumonia. We hypothesized that rats with Streptococcus pneumoniae ( SP) or Pseudomonas aeruginosa ( PA) pneumonia can be discriminated from uninfected controls by thermal desorption-gas chromatography-mass-spectrometry (TD-GC-MS) and selected ion flow tube-mass spectrometry (SIFT-MS) of exhaled breath. Male adult rats ( n = 50) received an intratracheal inoculation of 1) 200 µl saline, or 2) 1 × 107 colony-forming units of SP or 3) 1 × 107 CFU of PA. Twenty-four hours later the rats were anaesthetized, tracheotomized, and mechanically ventilated. Exhaled breath was analyzed via TD-GC-MS and SIFT-MS. Area under the receiver operating characteristic curves (AUROCCs) and correct classification rate (CCRs) were calculated after leave-one-out cross-validation of sparse partial least squares-discriminant analysis. Analysis of GC-MS data showed an AUROCC (95% confidence interval) of 0.85 (0.73–0.96) and CCR of 94.6% for infected versus noninfected animals, AUROCC of 0.98 (0.94–1) and CCR of 99.9% for SP versus PA, 0.92 (0.83–1.00), CCR of 98.1% for SP versus controls and 0.97 (0.92–1.00), and CCR of 99.9% for PA versus controls. For these comparisons the SIFT-MS data showed AUROCCs of 0.54, 0.89, 0.63, and 0.79, respectively. Exhaled breath analysis discriminated between respiratory infection and no infection but with even better accuracy between specific pathogens. Future clinical studies should not only focus on the presence of respiratory infection but also on the discrimination between specific pathogens.

Distinct Metabolic Endotype Mirroring Acute Respiratory Distress Syndrome (ARDS) Subphenotype and its Heterogeneous Biology

Predisposing aetiologies in Acute Respiratory Distress Syndrome (ARDS), perpetuates to heterogeneous clinical course hampering therapeutic response. Therefore, physiological variables need to be identified by stratifying ARDS subphenotypes and endotype, to target ARDS heterogeneity. The present study is stimulated by the fact that the ARDS heterogeneity arises from diverse pathophysiological changes leading to distinct ARDS endotypes characterized by perturbed biological mechanism which can be exploited in terms of metabolic profile by metabolomics. Biological endotypes using (n = 464 patients and controls), mBALF and serum samples were identified by high - resolution NMR spectroscopy from two clinically diagnosed ARDS subtypes grouped under mild, moderate and severe ARDS as subphenotype1and pulmonary and extra - pulmonary ARDS as subphenotype2. The identified mBALF endotypes (isoleucine, leucine, valine, lysine/arginine, tyrosine, threonine) and serum endotypes (proline, glutamate, phenylalanine, valine) in both subphenotypes by statistical analysis were tested for their reproducibility and robustness. By combining metabolic endotypes with clinical based mortality score (APACHE and SOFA) added to their predictive performance as ARDS mortality predictors. Thus, a comprehensive set of mBALF endotypes representing compartmentalized lung milieu and serological endotypes representing systemic markers of ARDS subtypes were validated. The interlinked biological pathway of these disease specific endotype further elucidated their role as candidate biomarker in governing ARDS heterogeneous biology.