ARDS metabolic fingerprints: characterization, benchmarking, and potential mechanistic interpretation

In this study, we aimed to identify acute respiratory distress syndrome (ARDS) metabolic fingerprints in selected patient cohorts and compare the metabolic profiles of direct versus indirect ARDS and hypoinflammatory versus hyperinflammatory ARDS. We hypothesized that the biological and inflammatory processes in ARDS would manifest as unique metabolomic fingerprints that set ARDS apart from other intensive care unit (ICU) conditions and could help examine ARDS subphenotypes and clinical subgroups. Patients with ARDS (n = 108) and ICU ventilated controls (n = 27) were included. Samples were randomly divided into 2/3 training and 1/3 test sets. Samples were analyzed using ¹H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry. Twelve proteins/cytokines were also measured. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to select the most differentiating ARDS metabolites and protein/cytokines. Predictive performance of OPLS-DA models was measured in the test set. Temporal changes of metabolites were examined as patients progressed through ARDS until clinical recovery. Metabolic profiles of direct versus indirect ARDS subgroups and hypoinflammatory versus hyperinflammatory ARDS subgroups were compared. Serum metabolomics and proteins/cytokines had similar area under receiver operator curves when distinguishing ARDS from ICU controls. Pathway analysis of ARDS differentiating metabolites identified a dominant involvement of serine-glycine metabolism. In longitudinal tracking, the identified pathway metabolites generally exhibited correction by 7-14 days, coinciding with clinical improvement. ARDS subphenotypes and clinical subgroups were metabolically distinct. However, our identified metabolic fingerprints are not ARDS diagnostic biomarkers, and further research is required to ascertain generalizability. In conclusion, patients with ARDS are metabolically different from ICU controls. ARDS subphenotypes and clinical subgroups are metabolically distinct.

Identification of a Circulating miRNA Signature to Stratify Acute Respiratory Distress Syndrome Patients

There is a need to improve acute respiratory distress syndrome (ARDS) diagnosis and management, particularly with extracorporeal membrane oxygenation (ECMO), and different biomarkers have been tested to implement a precision-focused approach. We included ARDS patients on veno-venous (V-V) ECMO in a prospective observational pilot study. Blood samples were obtained before cannulation, and screened for the expression of 754 circulating microRNA (miRNAs) using high-throughput qPCR and hierarchical cluster analysis. The miRNet database was used to predict target genes of deregulated miRNAs, and the DIANA tool was used to identify significant enrichment pathways. A hierarchical cluster of 229 miRNAs (identified after quality control screening) produced a clear separation of 11 patients into two groups: considering the baseline SAPS II, SOFA, and RESP score cluster A (n = 6) showed higher severity compared to cluster B (n = 5); p values < 0.05. After analysis of differentially expressed miRNAs between the two clusters, 95 deregulated miRNAs were identified, and reduced to 13 by in silico analysis. These miRNAs target genes implicated in tissue remodeling, immune system, and blood coagulation pathways. The blood levels of 13 miRNAs are altered in severe ARDS. Further investigations will have to match miRNA results with inflammatory biomarkers and clinical data.