Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia

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.

CircRNAs in BALF exosomes and plasma as diagnostic biomarkers in patients with acute respiratory distress syndrome caused by severe pneumonia

Background

The transcriptomic studies targeting circular RNAs (circRNAs) in bronchoalveolar lavage fluid (BALF) exosomes of acute respiratory distress syndrome (ARDS) patients caused by severe pneumonia have rarely been reported. This study aimed to screen and validate abnormally expressed circRNAs in exosomes from BALF of patients with ARDS caused by severe pneumonia and then evaluate the diagnostic values of these circRNAs for ARDS.

Method

BALF was collected from four patients with ARDS caused by severe pneumonia and four healthy subjects. CircRNA expression profile was obtained by microarray analysis in BALF exosomes of the discovery cohort. The differentially expressed circRNAs in BALF exosomes were verified by real-time quantitative PCR (RT-qPCR) and underwent competitive endogenous RNA (ceRNA) network construction and functional enrichment analysis.

Results

A total of 629 circRNAs were differentially expressed in BALF exosomes between ARDS patients and healthy subjects. Nine differentially expressed circRNAs were validated by RT-qPCR, and seven were consistent with the results of microarray analysis. CeRNA network analysis was performed for hsa_circRNA_002809, hsa_circRNA_042882, and hsa_circRNA_104034. Functional enrichment analysis showed that the target genes were mainly associated with hypoxia-induced damage, inflammatory response, and the HIF-1 signaling pathway. Hsa_circRNA_042882 and hsa_circRNA_104034 can be regarded as promising diagnostic biomarkers for patients with ARDS caused by severe pneumonia, with remarkable sensitivity and specificity of the area under the curve of 0.8050 and 1 or 0.835 and 0.799, respectively.

Conclusion

This study obtained circRNA expression profiles of ARDS patients, and hsa_circRNA_042882 and hsa_circRNA_104034 were regarded as promising diagnostic biomarkers for patients with ARDS caused by severe pneumonia.

Metabolomic characterization benefits the identification of acute lung injury in patients with type A acute aortic dissection

Introduction: Acute aortic dissection (AAD) often leads to the development of acute lung injury (ALI). However, the early detection and diagnosis of AAD in patients with ALI pose significant challenges. The objective of this study is to investigate distinct metabolic alterations in the plasma samples of AAD patients with ALI, AAD patients without ALI, and healthy individuals. Method: Between September 2019 and September 2022, we retrospectively collected data from 228 AAD patients who were diagnosed with ALI through post-surgery chest X-ray and PaO2/FiO2 assessments. Univariate analysis was employed to identify pre-surgery risk factors for ALI. Additionally, we conducted high-throughput target metabolic analysis on 90 plasma samples, comprising 30 samples from AAD patients with ALI, 30 from patients with AAD only, and 30 from healthy controls. After LC-MS spectral processing and metabolite quantification, the recursive feature elimination with cross-validation (RFECV) analysis based on the random forest was used to select the optimal metabolites as a diagnostic panel for the detection of AAD patients with ALI. The support vector machines (SVM) machine learning model was further applied to validate the diagnostic accuracy of the established biomarker panel. Results: In the univariate analysis, preoperative β-HB and TNF-α exhibited a significant association with lung injury (OR = 0.906, 95% CI 0.852-0.965, p = 0.002; OR = 1.007, 95% CI 1.003-1.011, p < 0.0001). The multiple-reaction monitoring analysis of 417 common metabolites identified significant changes in 145 metabolites (fold change >1.2 or <0.833, p < 0.05) across the three groups. Multivariate statistical analysis revealed notable differences between AAD patients and healthy controls. When compared with the non-ALI group, AAD patients with ALI displayed remarkable upregulation in 19 metabolites and downregulation in 4 metabolites. Particularly, combining citric acid and glucuronic acid as a biomarker panel improved the classification performance for distinguishing between the ALI and non-ALI groups. Discussion: Differentially expressed metabolites in the ALI group were primarily involved in amino acids biosynthesis, carbohydrate metabolism (TCA cycle), arginine and proline metabolism, and glucagon signaling pathway. These findings demonstrate a great potential of the targeted metabolomic approach for screening, routine surveillance, and diagnosis of pulmonary injury in patients with AAD.

Potential of in vitro nuclear magnetic resonance of biofluids and tissues in clinical research

Body fluids, cells, and tissues contain a wide variety of metabolites that consist of a mixture of various low-molecular-weight compounds, including amino acids, peptides, lipids, nucleic acids, and organic acids, which makes comprehensive analysis more difficult. Quantitative nuclear magnetic resonance (NMR) spectroscopy is a well-established analytical technique for analyzing the metabolic profiles of body fluids, cells, and tissues. It enables fast and comprehensive detection, characterization, a high level of experimental reproducibility, minimal sample preparation, and quantification of various endogenous metabolites. In recent times, NMR-based metabolomics has been appreciably utilized in diverse branches of medicine, including microbiology, toxicology, pathophysiology, pharmacology, nutritional intervention, and disease diagnosis/prognosis. In this review, the utility of NMR-based metabolomics in clinical studies is discussed. The significance of in vitro NMR-based metabolomics as an effective tool for detecting metabolites and their variations in different diseases are discussed, together with the possibility of identifying specific biomarkers that can contribute to early detection and diagnosis of disease.

The Oxygen Cascade from Atmosphere to Mitochondria as a Tool to Understand the (Mal)adaptation to Hypoxia

Hypoxia is a life-threatening challenge for about 1% of the world population, as well as a contributor to high morbidity and mortality scores in patients affected by various cardiopulmonary, hematological, and circulatory diseases. However, the adaptation to hypoxia represents a failure for a relevant portion of the cases as the pathways of potential adaptation often conflict with well-being and generate diseases that in certain areas of the world still afflict up to one-third of the populations living at altitude. To help understand the mechanisms of adaptation and maladaptation, this review examines the various steps of the oxygen cascade from the atmosphere to the mitochondria distinguishing the patterns related to physiological (i.e., due to altitude) and pathological (i.e., due to a pre-existing disease) hypoxia. The aim is to assess the ability of humans to adapt to hypoxia in a multidisciplinary approach that correlates the function of genes, molecules, and cells with the physiologic and pathological outcomes. We conclude that, in most cases, it is not hypoxia by itself that generates diseases, but rather the attempts to adapt to the hypoxia condition. This underlies the paradigm shift that when adaptation to hypoxia becomes excessive, it translates into maladaptation.

Personalizing Care for Critically Ill Adults Using Omics: A Concise Review of Potential Clinical Applications

Current guidelines for critically ill patients use broad recommendations to promote uniform protocols for the management of conditions such as acute kidney injury, acute respiratory distress syndrome, and sepsis. Although these guidelines have enabled the substantial improvement of care, mortality for critical illness remains high. Further outcome improvement may require personalizing care for critically ill patients, which involves tailoring management strategies for different patients. However, the current understanding of disease heterogeneity is limited. For critically ill patients, genomics, transcriptomics, proteomics, and metabolomics have illuminated such heterogeneity and unveiled novel biomarkers, giving clinicians new means of diagnosis, prognosis, and monitoring. With further engineering and economic development, omics would then be more accessible and affordable for frontline clinicians. As the knowledge of pathophysiological pathways mature, targeted treatments can then be developed, validated, replicated, and translated into clinical practice.

The Role of Macrophages and Alveolar Epithelial Cells in the Development of ARDS

Acute lung injury (ALI) usually causes acute respiratory distress syndrome (ARDS), or even death in critical ill patients. Immune cell infiltration in inflamed lungs is an important hallmark of ARDS. Macrophages are a type of immune cell that participate in the entire pathogenic trajectory of ARDS and most prominently via their interactions with lung alveolar epithelial cells (AECs). In the early stage of ARDS, classically activated macrophages secrete pro-inflammatory cytokines to clearance of the pathogens which may damage alveolar AECs cell structure and result in cell death. Paradoxically, in late stage of ARDS, anti-inflammatory cytokines secreted by alternatively activated macrophages dampen the inflammation response and promote epithelial regeneration and alveolar structure remodeling. In this review, we discuss the important role of macrophages and AECs in the progression of 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.

Inside the Alterations of Circulating Metabolome in Antarctica: The Adaptation to Chronic Hypoxia

Although the human body may dynamically adapt to mild and brief oxygen shortages, there is a growing interest in understanding how the metabolic pathways are modified during sustained exposure to chronic hypoxia. Located at an equivalent altitude of approximately 3,800 m asl, the Concordia Station in Antarctica represents an opportunity to study the course of human adaption to mild hypoxia with reduced impact of potentially disturbing variables else than oxygen deprivation. We recruited seven healthy subjects who spent 10 months in the Concordia Station, and collected plasma samples at sea level before departure, and 90 days, 6 months, and 10 months during hypoxia. Samples were analyzed by untargeted liquid chromatography high resolution mass spectrometry to unravel how the non-polar and polar metabolomes are affected. Statistical analyses were performed by clustering the subjects into four groups according to the duration of hypoxia exposure. The non-polar metabolome revealed a modest decrease in the concentration of all the major lipid classes. By contrast, the polar metabolome showed marked alterations in several metabolic pathways, especially those related to amino acids metabolism, with a particular concern of arginine, glutamine, phenylalanine, tryptophan, and tyrosine. Remarkably, all the changes were evident since the first time point and remained unaffected by hypoxia duration (with the exception of a slight return of the non-polar metabolome after 6 months), highlighting a relative inability of the body to compensate them. Finally, we identified a few metabolic pathways that emerged as the main targets of chronic hypoxia.

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.

Experimental Technologies in the Diagnosis and Treatment of COVID-19 in Patients with Comorbidities

The COVID-19 pandemic has impacted the whole world and raised concerns about its effects on different human organ systems. Early detection of COVID-19 may significantly increase the rate of survival; thus, it is critical that the disease is detected early. Emerging technologies have been used to prevent, diagnose, and manage COVID-19 among the populace in the USA and globally. Numerous studies have revealed the growing implementation of novel engineered systems during the intervention at various points of the disease’s pathogenesis, especially as it relates to comorbidities and complications related to cardiovascular and respiratory organ systems. In this review, we provide a succinct, but extensive, review of the pathogenesis of COVID-19, particularly as it relates to angiotensin-converting enzyme 2 (ACE2) as a viral entry point. This is followed by a comprehensive analysis of cardiovascular and respiratory comorbidities of COVID-19 and novel technologies that are used to diagnose and manage hospitalized patients. Continuous cardiorespiratory monitoring systems, novel machine learning algorithms for rapidly triaging patients, various imaging modalities, wearable immunosensors, hotspot tracking systems, and other emerging technologies are reviewed. COVID-19 effects on the immune system, associated inflammatory biomarkers, and innovative therapies are also assessed. Finally, with emphasis on the impact of wearable and non-wearable systems, this review highlights future technologies that could help diagnose, monitor, and mitigate disease progression. Technologies that account for an individual’s health conditions, comorbidities, and even socioeconomic factors can drastically reduce the high mortality seen among many COVID-19 patients, primarily via disease prevention, early detection, and pertinent management.

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.

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.

Acute lung injury - from pathophysiology to treatment

Acute lung injury is characterized by acute respiratory insufficiency with tachypnea, cyanosis refractory to oxygen, decreased lung compliance, and diffuse alveolar infiltrates on chest X-ray. The 1994 American-European Consensus Conference defined "acute respiratory distress syndrome, ARDS" by acute onset after a known trigger, severe hypoxemia defined by PaO2/FiO2</=200 mm Hg, bilateral infiltrates on chest X-ray, and absence of cardiogenic edema. Milder form of the syndrome with PaO2/FiO2 between 200-300 mm Hg was named "acute lung injury, ALI". Berlin Classification in 2012 defined three categories of ARDS according to hypoxemia (mild, moderate, and severe), and the term "acute lung injury" was assigned for general description or for animal models. ALI/ARDS can originate from direct lung triggers such as pneumonia or aspiration, or from extrapulmonary reasons such as sepsis or trauma. Despite growing understanding the ARDS pathophysiology, efficacy of standard treatments, such as lung protective ventilation, prone positioning, and neuromuscular blockers, is often limited. However, there is an increasing evidence that direct and indirect forms of ARDS may differ not only in the manifestations of alterations, but also in the response to treatment. Thus, individualized treatment according to ARDS subtypes may enhance the efficacy of given treatment and improve the survival of patients.

Metabolomics in Radiation Biodosimetry: Current Approaches and Advances

Triage and medical intervention strategies for unanticipated exposure during a radiation incident benefit from the early, rapid and accurate assessment of dose level. Radiation exposure results in complex and persistent molecular and cellular responses that ultimately alter the levels of many biological markers, including the metabolomic phenotype. Metabolomics is an emerging field that promises the determination of radiation exposure by the qualitative and quantitative measurements of small molecules in a biological sample. This review highlights the current role of metabolomics in assessing radiation injury, as well as considerations for the diverse range of bioanalytical and sampling technologies that are being used to detect these changes. The authors also address the influence of the physiological status of an individual, the animal models studied, the technology and analysis employed in interrogating response to the radiation insult, and variables that factor into discovery and development of robust biomarker signatures. Furthermore, available databases for these studies have been reviewed, and existing regulatory guidance for metabolomics are discussed, with the ultimate goal of providing both context for this area of radiation research and the consideration of pathways for continued development.

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.

1H-NMR based metabolomic profiling of cord blood in gestational hypothyroidism

Background

Gestational hypothyroidism (GHT) is a common pregnancy-related thyroid disfunction. The adverse outcomes by GHT has been increasingly recognized, leading to more public awareness of the disease. However, comprehensive understanding of the prognosis of GHT has not yet achieved. Metabolomics is a powerful tool in evaluation of disease outcomes, and cord blood represents an excellent candidate for the investigation of gestational outcomes.

Methods

In the present study, we performed 1H-NMR based metabolomics on cord blood of 18 pregnant women with GHT and 18 non hypothyroidism (NHT) control.

Results

The metabolomic profile of GHT was separated with the NHT control. A total of 8 metabolites with altered abundances were observed, among which Creatinine and O-Phosphocholine were elevated and the others were downregulated in GHT. Spearman rank correlation suggested that the eight differential metabolites were correlated with the GHT related thyroid hormones. Pathway analysis of the differential metabolites indicated that two metabolic pathways were significantly altered in GHT (adjusted P<0.05), including tyrosine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis. Enrichment analysis of the differential metabolites against disease-associated metabolite sets suggested that GHT was associated with disease risks of non-insulin dependent diabetes mellitus, isovaleric acidemia, and methylmalonic aciduria.

Conclusions

The results of this study revealed GHT associated metabolic changes in cord blood, providing insights into the metabolic intermediates between GHT and its related disease risks.

An NMR based panorama of the heterogeneous biology of acute respiratory distress syndrome (ARDS) from the standpoint of metabolic biomarkers

Acute respiratory distress syndrome (ARDS), manifested by intricate etiology and pathophysiology, demands careful clinical surveillance due to its high mortality and imminent life support measures. NMR based metabolomics provides an approach for ARDS which culminates from a wide spectrum of illness thereby confounding early manifestation and prognosis predictors. ¹ H NMR with its manifold applications in critical disease settings can unravel the biomarker of ARDS thus holding potent implications by providing surrogate endpoints of clinical utility. NMR metabolomics which is the current apogee platform of omics trilogy is contributing towards the possible panacea of ARDS by subsequent validation of biomarker credential on larger datasets. In the present review, the physiological derangements that jeopardize the whole metabolic functioning in ARDS are exploited and the biomarkers involved in progression are addressed and substantiated. The following sections of the review also outline the clinical spectrum of ARDS from the standpoint of NMR based metabolomics which is an emerging element of systems biology. ARDS is the main premise of intensivists textbook, which has been thoroughly reviewed along with its incidence, progressive stages of severity, new proposed diagnostic definition, and the preventive measures and the current pitfalls of clinical management. The advent of new therapies, the need for biomarkers, the methodology and the contemporary promising approaches needed to improve survival and address heterogeneity have also been evaluated. The review has been stepwise illustrated with potent biometrics employed to selectively pool out differential metabolites as diagnostic markers and outcome predictors. The following sections have been drafted with an objective to better understand ARDS mechanisms with predictive and precise biomarkers detected so far on the basis of underlying physiological parameters having close proximity to diseased phenotype. The aim of this review is to stimulate interest in conducting more studies to help resolve the complex heterogeneity of ARDS with biomarkers of clinical utility and relevance.

Towards early monitoring of chemotherapy-induced drug resistance based on single cell metabolomics: Combining single-probe mass spectrometry with machine learning

Despite the presence of methods evaluating drug resistance during chemotherapies, techniques, which allow for monitoring the degree of drug resistance in early chemotherapeutic stage from single cells in their native microenvironment, are still absent. Herein, we report an analytical approach that combines single cell mass spectrometry (SCMS) based metabolomics with machine learning (ML) models to address the existing challenges. Metabolomic profiles of live cancer cells (HCT-116) with different levels (i.e., no, low, and high) of chemotherapy-induced drug resistance were measured using the Single-probe SCMS technique. A series of ML models, including random forest (RF), artificial neural network (ANN), and penalized logistic regression (LR), were constructed to predict the degrees of drug resistance of individual cells. A systematic comparison of performance was conducted among multiple models, and the method validation was carried out experimentally. Our results indicate that these ML models, especially the RF model constructed on the obtained SCMS datasets, can rapidly and accurately predict different degrees of drug resistance of live single cells. With such rapid and reliable assessment of drug resistance demonstrated at the single cell level, our method can be potentially employed to evaluate chemotherapeutic efficacy in the clinic.

Precision Medicine in Critical Illness: Sepsis and Acute Respiratory Distress Syndrome

Sepsis and the acute respiratory distress syndrome (ARDS) each cause substantial morbidity and mortality. In contrast to other lung diseases, the entire course of disease in these syndromes is measured in days to weeks rather than months to years, which raises unique challenges in achieving precision medicine. We review advances in sepsis and ARDS resulting from omics studies, including those involving genome-wide association, gene expression, targeted proteomics, and metabolomics approaches. We focus on promising evidence of biological subtypes in both sepsis and ARDS that consistently display high risk for death. In sepsis, a gene expression signature with dysregulated adaptive immune signaling has evidence for a differential response to systemic steroid therapy, whereas in ARDS, a hyperinflammatory pattern identified in plasma using targeted proteomics responded more favorably to randomized interventions including high positive end-expiratory pressure, volume conservative fluid therapy, and simvastatin therapy. These early examples suggest heterogeneous biology that may be challenging to detect by clinical factors alone and speak to the promise of a precision approach that targets the right treatment at the right time to the right patient.

Hyperoxia affects the lung tissue: A porcine histopathological and metabolite study using five hours of apneic oxygenation

Background

Oxygen is a liberally dosed medicine; however, too much oxygen can be harmful. In certain situations, treatment with high oxygen concentration is necessary, e.g. after cardiopulmonary resuscitation. The amount of oxygen and duration of hyperoxia causing pulmonary damage is not fully elucidated. The aim of this study was to investigate pathophysiological and metabolite changes in lung tissue during hyperoxia while the lungs were kept open under constant low pressure.

Methods

Seven pigs were exposed to 100% oxygen for five hours, using an apneic oxygenation technique with one long uninterrupted inspiration, while carbon dioxide was removed with an interventional lung assist. Arterial blood samples were collected every 30 minutes. Lung biopsies were obtained before and after hyperoxia. Microscopy and high-resolution magic angle spinning nuclear magnetic resonance spectroscopy were used to detect possible pathological and metabolite changes, respectively. Unsupervised multivariate analysis of variance and paired sample tests were performed. A two-tailed p-value ≤ 0.05 was considered significant.

Results

No significant changes in arterial pH, and partial pressure of carbon dioxide, and no clear histopathological changes were observed after hyperoxia. While blood glucose and lactate levels changed to a minor degree, their levels dropped significantly in the lung after hyperoxia (p ≤ 0.04). Reduced levels of antioxidants (p ≤ 0.05), tricarboxylic acid cycle and energy (p ≤ 0.04) metabolites and increased levels of several amino acids (p ≤ 0.05) were also detected.

Conclusion

Despite no histological changes, tissue metabolites were altered, indicating that exposure to hyperoxia affects lung tissue matrix on a molecular basis.

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No significant histopathological changes in lung tissue after five hours hyperoxia.

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Five hours hyperoxia induces significant metabolite changes in lung tissue.

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Hyperoxia affects cellular energy, Krebs cycle, and oxidant-antioxidant defense.

Biomarkers of Acute Lung Injury The Individualized Approach: for Phenotyping, Risk Stratification and Treatment Surveillance

Do we need biomarkers of lung damage and infection: For what purpose and how should they be used properly? Biomarkers of lung damage can be used for diagnosis, risk stratification/prediction, treatment surveillance and adjustment of targeted therapy. Additionally, novel "omics" methods may offer a completely different and effective way of improving the understanding of pathogenesis of lung damage and a way to develop new candidate lung damage biomarkers. In the current review, we give an overview within the field of acute lung damage of (i) disease mechanism biomarkers, (ii) of "ready to use" evidence-based biomarker-guided lung infection management, (iii) of novel strategies of inflammatory phenotyping and how this can be used to tailor corticosteroid treatment, (iv) a future perspective of where "omics" technologies and mindsets may become increasingly important in developing new strategies for treatment and for understanding the development of acute lung damage.

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.

Evolution of ARDS biomarkers: Will metabolomics be the answer?

To date, there is no clinically agreed-upon diagnostic test for acute respiratory distress syndrome (ARDS): the condition is still diagnosed on the basis of a constellation of clinical findings, laboratory tests, and radiological images. Development of ARDS biomarkers has been in a state of continuous flux during the past four decades. To address ARDS heterogeneity, several studies have recently focused on subphenotyping the disease on the basis of observable clinical characteristics and associated blood biomarkers. However, the strong correlation between identified biomarkers and ARDS subphenotypes has yet to establish etiology; hence, there is a need for the adoption of other methodologies for studying ARDS. In this review, we will shed light on ARDS metabolomics research in the literature and discuss advances and major obstacles encountered in ARDS metabolomics research. Generally, the ARDS metabolomics studies focused on identification of differentiating metabolites for diagnosing ARDS, but they were performed to different standards in terms of sample size, selection of control cohort, type of specimens collected, and measuring technique utilized. Virtually none of these studies have been properly validated to identify true metabolomics biomarkers of ARDS. Though in their infancy, metabolomics studies exhibit promise to unfold the biological processes underlying ARDS and, in our opinion, have great potential for pushing forward our present understanding of ARDS.