Traumatic brain injury (TBI) is one of the leading causes of disability and mortality worldwide. The TBI pathogenesis can induce broad pathophysiological consequences and clinical outcomes attributed to the complexity of the brain. Thus, the diagnosis and prognosis are important issues for the management of mild, moderate, and severe forms of TBI. Metabolomics of readily accessible biofluids is a promising tool for establishing more useful and reliable biomarkers of TBI than using clinical findings alone. Metabolites are an integral part of all biochemical and pathophysiological pathways. Metabolomic processes respond to the internal and external stimuli resulting in an alteration of metabolite concentrations. Current high-throughput and highly sensitive analytical tools are capable of detecting and quantifying small concentrations of metabolites, allowing one to measure metabolite alterations after a pathological event when compared to a normal state or a different pathological process. Further, these metabolic biomarkers could be used for the assessment of injury severity, discovery of mechanisms of injury, and defining structural damage in the brain in TBI. Metabolic biomarkers can also be used for the prediction of outcome, monitoring treatment response, in the assessment of or prognosis of post-injury recovery, and potentially in the use of neuroplasticity procedures. Metabolomics can also enhance our understanding of the pathophysiological mechanisms of TBI, both in primary and secondary injury. Thus, this review presents the promising application of metabolomics for the assessment of TBI as a stand-alone platform or in association with proteomics in the clinical setting.

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.

Aims: In this study we aimed to identify ARDS metabolic fingerprints in selected patient cohorts, compare the metabolic profiles of direct vs indirect ARDS and hypoinflammatory vs hyperinflammatory ARDS. Hypothesis: We hypothesize that the biological and inflammatory processes in ARDS would manifest as unique metabolomic fingerprints which set ARDS apart from other ICU conditions, help examine ARDS subphenotypes and clinical subgroups.Subjects: 108 ARDS patients and 27 ICU ventilated controls were analyzed. Samples were randomly divided into 2/3 training and 1/3 test sets. Methods: Samples were analyzed using proton nuclear magnetic resonance spectroscopy (1H-NMR) and gas chromatography mass spectrometry (GC-MS). 12 proteins/cytokines were also measured. Orthogonal partial least squares discriminant analysis (OPLS-DA) was utilized 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 vs indirect ARDS subgroups and hypoinflammatory vs hyperinflammatory ARDS subgroups were compared.Results: Serum metabolomics and proteins/cytokines have similar AUROC 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 exhibit correction by 7-14 days, coinciding with clinical improvement. ARDS subphenotypes and clinical subgroups are metabolically distinct.Limitations: Our identified metabolic fingerprints are not ARDS diagnostic biomarkers. Further research is required to ascertain generalizability.Conclusions: ARDS patients are metabolically different from ICU controls. ARDS subphenotypes and clinical subgroups are metabolically distinct.

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.

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Background Hepatocellular carcinoma (HCC) is an increasingly common disease and is classified as one of the most common cancers leading to mortality worldwide. Only a small percentage of patients with this disease are eligible to curative treatment. Quite often the main reason is the late diagnosis of the disease. In the last decade, a Nobel prize awarded discovery of the volatile organic compounds in the breath opened the frontiers for new diagnostic tools and methods for several diseases. Cancer is one of the target diseases that appears to have unique biomarkers in the breath of the affected individuals. This have been found true in colorectal, breast, lung cancers. This systematic review aims to answer the question if markers specific to hepatocellular carcinoma exist in exhaled breath and what is the current knowledge regarding its detection. Methods A systematic search was conducted by two reviewers and the Royal College of Surgeons of Edinburgh librarian using the Embase, Medline, PubMed and Web od Science databases. Search strategy included all studied published until the 24th of March 2021 containing combination of keywords (Hepatocellular carcinoma, hepatocellular neoplasm, hepatocellular cancer, hepatocellular tumor, hepatocellular tumour, HCC, liver cancer, liver carcinoma, liver neoplasm, liver tumor, liver tumour AND volatile organic compound, VOC, volatilome, volatilomics, metabolome, metabolomics, breath analysis). Results The search yielded 6 publications using PRISMA pathway. Two of the studies described in vitro experiments and four were conducted on a small number of groups of patients. Overall, in the in vitro studies 42 headspace gases were analysed. Clinical studies included 164 patients with HCC and as control groups - 110 patients with cirrhosis and 130 healthy individuals. Multiple VOCs were found in the studies. Following their identification in PubChem library, a pathway analysis was performed using the Kyoto Encyclopaedia of Genes and Genomes (KEGG). Only three VOCs were annotated in the KEGG maps and out of those, two could be traced back to their biological pathways. These are acetaldehyde and ethanol which participate in glycolysis and gluconeogenesis (Figure 1). Conclusions At present time there are no specific volatile biomarker in exhaled breath characterising hepatocellular carcinoma. Data on extracted studies emphasised lack of unified methodology. This review, however, highlighted metabolic pathway which might be the source of VOCs produced by cancerous hepatocytes. Large population studies are required to verify this finding.

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