Novel biomarkers for acute respiratory distress syndrome: genetics, epigenetics and transcriptomics

Definition and Epidemiology of Sepsis

Here we review the epidemiology of sepsis, focusing on its definition, incidence, and mortality, as well as the demographic insights and risk factors that influence its occurrence and outcomes. We address how age, sex, and racial/ethnic disparities impact upon incidence and mortality rates. Sepsis is more frequent and severe among the elderly, males, and certain racial and ethnic groups. Poor socioeconomic status, geographic location, and pre-existing comorbidities also elevate the risk of developing and dying from sepsis. Seasonal variations, with an increased incidence during winter months, is also apparent. We delve into the predictive value of disease severity scores such as the Sequential Organ Failure Assessment score. We also highlight issues relating to coding and administrative data that can generate erroneous and misleading information, and the need for greater consistency. The Sepsis-3 definitions, offering more precise clinical criteria, are a step in the right direction. This overview will, we hope, facilitate understanding of the multi-faceted epidemiological characteristics of sepsis and current challenges.

Enhanced diabetic wound healing with injectable hydrogel containing self-assembling nanozymes

To build a smart system in response to the variable microenvironment in infected diabetic wounds, a multifunctional wound dressing was constructed by co-incorporating glucose oxidase (GOx) and a pH-responsive self-assembly Cu2-xSe-BSA nanozyme into a dual-dynamic bond cross-linked hydrogel (OBG). This composite hydrogel (OBG@CG) can adhere to the wound site and respond to the acidic inflammatory environment, initiating the GOx-catalyzed generation of H2O2 and the self-assembly activated peroxidase-like property of Cu2-xSe-BSA nanozymes, resulting in significant hydroxyl radical production to attack the biofilm during the acute infection period and alleviate the high-glucose microenvironment for better wound healing. During the wound recovery phase, Cu2-xSe-BSA aggregates disassembled owing to the elevated pH, terminating catalytic reactive oxygen species generation. Simultaneously, Cu2+ released from the Cu2-xSe-BSA not only promotes the production of mature collagen but also enhances the migration and proliferation of endothelial cells. RNA-seq analysis demonstrated that OBG@CG exerted its antibacterial property by damaging the integrity of the biofilm by inducing radicals and interfering with the energy supply, along with destroying the defense system by disturbing thiol metabolism and reducing transporter activities. This work proposes an innovative glucose consumption strategy for infected diabetic wound management, which may inspire new ideas in the exploration of smart wound dressing.

A pretrain-finetune approach for improving model generalizability in outcome prediction of acute respiratory distress syndrome patients

BACKGROUND

Early prediction of acute respiratory distress syndrome (ARDS) of critically ill patients in intensive care units (ICUs) has been intensively studied in the past years. Yet a prediction model trained on data from one hospital might not be well generalized to other hospitals. It is therefore essential to develop an accurate and generalizable ARDS prediction model adaptive to different hospital or medical centers.

METHODS

We analyzed electronic medical records of 200,859 and 50,920 hospitalized patients within 24 h after being diagnosed with ARDS from the Philips eICU Institute (eICU-CRD) and the Medical Information Mart for Intensive Care (MIMIC-IV) dataset, respectively. Patients were sorted into three groups, including rapid death, long stay, and recovery, based on their condition or outcome between 24 and 72 h after ARDS diagnosis. To improve prediction performance and generalizability, a "pretrain-finetune" approach was applied, where we pretrained models on the eICU-CRD dataset and performed model finetuning using only a part (35%) of the MIMIC-IV dataset, and then tested the finetuned models on the remaining data from the MIMIC-IV dataset. Well-known machine-learning algorithms, including logistic regression, random forest, extreme gradient boosting, and multilayer perceptron neural networks, were employed to predict ARDS outcomes. Prediction performance was evaluated using the area under the receiver-operating characteristic curve (AUC).

RESULTS

Results show that, in general, multilayer perceptron neural networks outperformed the other models. The use of pretrain-finetune yielded improved performance in predicting ARDS outcomes achieving a micro-AUC of 0.870 for the MIMIC-IV dataset, an improvement of 0.046 over the pretrain model.

CONCLUSIONS

The proposed pretrain-finetune approach can effectively improve model generalizability from one to another dataset in ARDS prediction.

Prone position in the mechanical ventilation of acute respiratory distress syndrome children: a systematic review and meta-analysis

Background

Prone position has been well recognized for the treatment of adult acute respiratory distress syndrome (ARDS). We aimed to evaluate the role of prone position in the mechanical ventilation in children with ARDS, to provide evidence to the treatment and care of children with ARDS.

Methods

We searched the Pubmed et al. databases by computer until January 23, 2024 for randomized controlled trials (RCTs) on the role of prone position in the mechanical ventilation in children with ARDS. We evaluated the quality of included studies according to the quality evaluation criteria recommended by the Cochrane library. RevMan 5.3 software was used for meta-analysis.

Results

7 RCTs involving 433 children with ARDS were included. Meta-analysis indicated that prone position is beneficial to improve the arterial oxygenation pressure [MD = 4.27 mmHg, 95% CI (3.49, 5.06)], PaO2/FiO2 [MD = 26.97, 95% CI (19.17, 34.77)], reduced the oxygenation index [MD = -3.52, 95% CI (-5.41, -1.64)], mean airway pressure [MD = -1.91 cmH2O, 95% CI (-2.27, -1.55)] and mortality [OR = 0.33, 95% CI (0.15, 0.73), all P < 0.05]. There were no statistical differences in the duration of mechanical ventilation between the prone position group and control group [MD = -17.01, 97.27, 95% CI (-38.28, 4.26), P = 0.12]. Egger test results showed that no significant publication bias was found (all P > 0.05).

Conclusions

Prone position ventilation has obvious advantages in improving oxygenation, but there is no significant improvement in the time of mechanical ventilation in the treatment of children with ARDS. In the future, more large-sample, high-quality RCTs are still needed to further analyze the role of prone position in the mechanical ventilation in children with ARDS.

Translational medicine for acute lung injury

Acute lung injury (ALI) is a complex disease with numerous causes. This review begins with a discussion of disease development from direct or indirect pulmonary insults, as well as varied pathogenesis. The heterogeneous nature of ALI is then elaborated upon, including its epidemiology, clinical manifestations, potential biomarkers, and genetic contributions. Although no medication is currently approved for this devastating illness, supportive care and pharmacological intervention for ALI treatment are summarized, followed by an assessment of the pathophysiological gap between human ALI and animal models. Lastly, current research progress on advanced nanomedicines for ALI therapeutics in preclinical and clinical settings is reviewed, demonstrating new opportunities towards developing an effective treatment for ALI.

Predictive value of combination of lung injury prediction score and receptor for advanced glycation end‑products for the occurrence of acute respiratory distress syndrome

The present study evaluated the predictive value of the combination of the lung injury prediction score (LIPS) and receptor for advanced glycation end-products (RAGE) for the occurrence of acute respiratory distress syndrome (ARDS) in critically ill patients with ARDS risk factors. A total of 551 patients with risk factors of ARDS were divided into an ARDS group and a non-ARDS group. LIPS was computed within 6 h of admission into the ICU, and the plasma concentration of RAGE was detected within 24 h of admission. Multivariate analysis was performed to identify independent associations, and the predictive values for ARDS occurrence were assessed with receiver operating characteristic (ROC) curve. Within 7 days after admission into the ICU, ARDS occurred in 176 patients (31.9%). Multivariate analysis demonstrated that LIPS [odds ratio (OR), 1.282; 95% confidence interval (CI), 1.108-1.604], RAGE levels (OR, 2.359; 95% CI, 1.351-4.813) and Acute Physiology and Chronic Health Evaluation II score (OR, 1.167; 95% CI, 1.074-1.485) were independently associated with ARDS occurrence. ROC curves demonstrated that the area under curve (AUC) of LIPS, RAGE levels and their combination was 0.714 [standard error (SE), 0.023; 95% CI, 0.670-0.759], 0.709 (SE, 0.025; 95% CI, 0.660-0.758) and 0.889 (SE, 0.014; 95% CI, 0.861-0.917), respectively. The AUC of LIPS combined with RAGE levels was significantly higher compared with those of LIPS (0.889 vs. 0.714; Z=6.499; P<0.001) and RAGE (0.889 vs. 0.709; Z=6.282; P<0.001) levels alone. In conclusion, both LIPS and RAGE levels were independently associated with ARDS occurrence in critically ill patients with ARDS risk factors, and had medium predictive values for ARDS occurrence. Combination of LIPS with RAGE levels increased the predictive value for ARDS occurrence.

miRNA transcriptomics analysis shows miR-483-5p and miR-503-5p targeted miRNA in extracellular vesicles from severe acute pancreatitis-associated lung injury patients

AIM

This study sought to identify potential biomarkers and miRNA-mRNA networks within extracellular vesicles (EVs) for detecting severe acute pancreatitis-associated lung injury (SAPALI).

METHODS

Blood-derived EVs were isolated, and their miRNA transcriptomic profiles were comprehensively analyzed using miRBase v.21 database along with miRDeep2 tool to predict novel miRNAs. DEGseq R package was deployed for the identification of differentially expressed miRNAs (DEMs). Protein-protein interaction (PPI) networks were assembled using STRING and Cytoscape. A lung injury model was established using Lipopolysaccharide (LPS)-induced BEAS-2B cells, chosen for their respiratory epithelial origin and pertinent association with lung injury. The expression levels of targeted miRNA and associated proteins, TLR4, NF-κB mRNA were quantified via RT-PCR and Western Blot. Levels of IL-6, IL-1β, TNF-α, and ROS were measured using designated kits. Dual-luciferase reporter assay was conducted to examine the interaction between miRNA and proteins.

RESULTS

The comparisons between the SAPALI and the control group revealed 10 DEM, including miR-503-5p and miR-483-5p. The cytoHubba plugin in Cytoscape identified three principal miRNA-mRNA interactions: miR-483-5p with PTK2 and HDAC2; miR-28-5p with MAPK1, TP53BP1, SEMA3A; and miR-503-5p with PPP1CB, SEMA6D, EPHB2, UNC5B. The SAPALI model exhibited elevated miR-503-5p, HDAC2 and inflammatory markers, with a decline UNC5B, miR-483-5p and miR-28-5p. Transfection with miR-503-5p and miR-483-5p inhibitors increased the levels of their supposed binding proteins but not miR-28-5p inhibitor. The Dual-luciferase reporter gene assay identified the interaction of miR-503-5p with UNC5B, and miR-483-5p with HDAC2, but not miR-28-5p with TP53BP1.

CONCLUSIONS

Our study maps miRNA-mRNA interactions in SAPALI, identifying miR-503-5p and miR-483-5p as critical regulatory miRNAs.

Network analysis identifies a gene biomarker panel for sepsis-induced acute respiratory distress syndrome

BACKGROUND

Acute respiratory distress syndrome (ARDS) is characterized by non-cardiogenic pulmonary edema caused by inflammation, which can lead to serious respiratory complications. Due to the high mortality of ARDS caused by sepsis, biological markers that enable early diagnosis are urgently needed for clinical treatment.

METHODS

In the present study, we used the public microarray data of whole blood from patients with sepsis-induced ARDS, patients with sepsis-alone and healthy controls to perform an integrated analysis based on differential expressed genes (DEGs) and co-expression network to identify the key genes and pathways related to the development of sepsis into ARDS that may be key targets for diagnosis and treatment.

RESULTS

Compared with controls, we identified 180 DEGs in the sepsis-alone group and 152 DEGs in the sepsis-induced ARDS group. About 70% of these genes were unique to the two groups. Functional analysis of DEGs showed that neutrophil-mediated inflammation and mitochondrial dysfunction are the main features of ARDS induced by sepsis. Gene network analysis identified key modules and screened out key regulatory genes related to ARDS. The key genes and their upstream regulators comprised a gene panel, including EOMES, LTF, CSF1R, HLA-DRA, IRF8 and MPEG1. Compared with the healthy controls, the panel had an area under the curve (AUC) of 0.900 and 0.914 for sepsis-alone group and sepsis-induced ARDS group, respectively. The AUC was 0.746 between the sepsis-alone group and sepsis-induced ARDS group. Moreover, the panel of another independent blood transcriptional expression profile dataset showed the AUC was 0.769 in diagnosing sepsis-alone group and sepsis-induced ARDS group.

CONCLUSIONS

Taken together, our method contributes to the diagnosis of sepsis and sepsis-induced ARDS. The biological pathway involved in this gene biomarker panel may also be a critical target in combating ARDS caused by sepsis.

COVID-19 progression towards ARDS: a genome wide study reveals host factors underlying critical COVID-19

Coronavirus disease 2019 (COVID-19) is a viral infection produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus epidemic, which was declared a global pandemic in March 2020. The World Health Organization has recorded around 43.3 billion cases and 59.4 million casualties to date, posing a severe threat to global health. Severe COVID-19 indicates viral pneumonia caused by the SARS-CoV-2 infections, which can induce fatal consequences, including acute respiratory distress syndrome (ARDS). The purpose of this research is to better understand the COVID-19 and ARDS pathways, as well as to find targeted single nucleotide polymorphism. To accomplish this, we retrieved over 100 patients' samples from the Sequence Read Archive, National Center for Biotechnology Information. These sequences were processed through the Galaxy server next generation sequencing pipeline for variant analysis and then visualized in the Integrative Genomics Viewer, and performed statistical analysis using t-tests and Bonferroni correction, where six major genes were identified as DNAH7, CLUAP1, PPA2, PAPSS1, TLR4, and IFITM3. Furthermore, a complete understanding of the genomes of COVID-19-related ARDS will aid in the early identification and treatment of target proteins. Finally, the discovery of novel therapeutics based on discovered proteins can assist to slow the progression of ARDS and lower fatality rates.

Genetic Determinants of the Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is a life-threatening lung condition that arises from multiple causes, including sepsis, pneumonia, trauma, and severe coronavirus disease 2019 (COVID-19). Given the heterogeneity of causes and the lack of specific therapeutic options, it is crucial to understand the genetic and molecular mechanisms that underlie this condition. The identification of genetic risks and pharmacogenetic loci, which are involved in determining drug responses, could help enhance early patient diagnosis, assist in risk stratification of patients, and reveal novel targets for pharmacological interventions, including possibilities for drug repositioning. Here, we highlight the basis and importance of the most common genetic approaches to understanding the pathogenesis of ARDS and its critical triggers. We summarize the findings of screening common genetic variation via genome-wide association studies and analyses based on other approaches, such as polygenic risk scores, multi-trait analyses, or Mendelian randomization studies. We also provide an overview of results from rare genetic variation studies using Next-Generation Sequencing techniques and their links with inborn errors of immunity. Lastly, we discuss the genetic overlap between severe COVID-19 and ARDS by other causes.

A Systematic Review and Meta-Analysis of Independent Predictors for Acute Respiratory Distress Syndrome in Patients Presenting With Sepsis

The current meta-analysis was conducted to determine the predictors of acute respiratory distress syndrome (ARDS) in patients with sepsis. The present meta-analysis was conducted in accordance with the MOOSE (Meta-analysis of Observational Studies in Epidemiology) guidelines. We conducted a systematic search using the PubMed, Cochrane Library, and EMBASE databases for studies published between 1 January 2000 and 28 February 2023 that assessed the predictors of ARDS in patients with sepsis. We used key terms such as "predictors," "acute respiratory distress syndrome," and "sepsis" to search for relevant articles. Our search was limited to human studies published in English. A total of six studies were included in this meta-analysis. Of the six studies, four were retrospective and two were prospective. The pooled incidence of ARDS was 11.27%. We identified six factors with a consistent and statistically significant association with ARDS, including sequential organ failure assessment (SOFA) score, Acute Physiology and Chronic Health Evaluation (APACHE) II score, pulmonary sepsis, smoking, pancreatitis, and C-reactive protein. Age, diabetes, and chronic obstructive pulmonary disease (COPD) were not found to be significantly associated with ARDS in this patient population. It is important for healthcare providers to consider these predictors when assessing patients with sepsis and septic shock to identify those at high risk for developing ARDS and implement appropriate preventive measures.

Advanced development and mechanism of sepsis-related acute respiratory distress syndrome

The introduction of the Sepsis 3.0 guidelines in 2016 improved our understanding of sepsis diagnosis and therapy. Personalized treatment strategies and nursing methods for sepsis patients are recommended in the "Save Sepsis Campaign" in 2021. However, mortality in sepsis patients remains high. Patients with sepsis-related acute respiratory distress syndrome account for around 30% of them, with fatality rates ranging from 30 to 40%. Pathological specimens from individuals with sepsis-related ARDS frequently demonstrate widespread alveolar damage, and investigations have revealed that pulmonary epithelial and pulmonary endothelial injury is the underlying cause. As a result, the purpose of this work is to evaluate the mechanism and research progress of pulmonary epithelial and pulmonary endothelial damage in sepsis-related ARDS, which may provide new directions for future research, diagnosis, and therapy.

Transplanted hair follicle mesenchymal stem cells alleviated small intestinal ischemia–reperfusion injury via intrinsic and paracrine mechanisms in a rat model

Background: Small intestinal ischemia-reperfusion (IR) injury is a common intestinal disease with high morbidity and mortality. Mesenchymal stem cells (MSCs) have been increasingly used in various intestinal diseases. This study aimed to evaluate the therapeutic effect of hair follicle MSCs (HFMSCs) on small intestinal IR injury.

Methods: We divided Sprague–Dawley rats into three groups: the sham group, IR group and IR + HFMSCs group. A small intestinal IR injury rat model was established by clamping of the superior mesenteric artery (SMA) for 30 min and reperfusion for 2 h. HFMSCs were cultured in vitro and injected into the rats through the tail vein. Seven days after treatment, the intrinsic homing and differentiation characteristics of the HFMSCs were observed by immunofluorescence and immunohistochemical staining, and the paracrine mechanism of HFMSCs was assessed by Western blotting and enzyme-linked immunosorbent assay (ELISA).

Results: A small intestinal IR injury model was successfully established. HFMSCs could home to damaged sites, express proliferating cell nuclear antigen (PCNA) and intestinal stem cell (ISC) markers, and promote small intestinal ISC marker expression. The expression levels of angiopoietin-1 (ANG1), vascular endothelial growth factor (VEGF) and insulin growth factor-1 (IGF1) in the IR + HFMSCs group were higher than those in the IR group. HFMSCs could prevent IR-induced apoptosis by increasing B-cell lymphoma-2 (Bcl-2) expression and decreasing Bcl-2 homologous antagonist/killer (Bax) expression. Oxidative stress level detection showed that the malondialdehyde (MDA) content was decreased, while the superoxide dismutase (SOD) content was increased in the IR + HFMSCs group compared to the IR group. An elevated diamine oxidase (DAO) level reflected the potential protective effect of HFMSCs on the intestinal mucosal barrier.

Conclusion: HFMSCs are beneficial to alleviate small intestinal IR injury through intrinsic homing to the small intestine and by differentiating into ISCs, via a paracrine mechanism to promote angiogenesis, reduce apoptosis, regulate the oxidative stress response, and protect intestinal mucosal function potentially. Therefore, this study suggests that HFMSCs serve as a new option for the treatment of small intestinal IR injury.

Risk factors for acute respiratory distress syndrome in sepsis patients: a retrospective study from a tertiary hospital in China

Background

Less is known about the risk factors for acute respiratory distress syndrome (ARDS) in sepsis patients diagnosed according to sepsis 3.0 criteria. Moreover, the risk factors for ARDS severity remain unclear.

Methods

We retrospectively collected the characteristics of sepsis patients from the intensive care unit of the First Affiliated Hospital of China Medical University from January 2017 to September 2018. Logistic regression was used in determining the risk factors.

Results

529 patients with sepsis were enrolled and 179 developed ARDS. The most common infection sites were acute abdominal infection (n = 304) and pneumonia (n = 117). Multivariate analysis showed that patients with pancreatitis with local infection (odds ratio [OR], 3.601; 95% confidence interval [CI], 1.429–9.073, P = 0.007), pneumonia (OR 3.486; 95% CI 1.890–6.430, P < 0.001), septic shock (OR 2.163; 95% CI 1.429–3.275, P < 0.001), a higher sequential organ failure assessment (SOFA) score (OR 1.241; 95% CI 1.155–1.333, P < 0.001) and non-pulmonary SOFA score (OR 2.849; 95% CI 2.113–3.841, P < 0.001) were independent risk factors for ARDS. Moreover, pneumonia is associated with increased severity of ARDS (OR 2.512; 95% CI 1.039–6.067, P = 0.041).

Conclusions

We determined five risk factors for ARDS in sepsis patients. Moreover, pneumonia is significantly associated with an increased severity of ARDS.

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.