Metabolomics in psoriatic disease: pilot study reveals metabolite differences in psoriasis and psoriatic arthritis.

ImportanceWhile "omics" studies have advanced our understanding of inflammatory skin diseases, metabolomics is mostly an unexplored field in dermatology.ObjectiveWe sought to elucidate the pathogenesis of psoriatic diseases by determining the differences in metabolomic profiles among psoriasis patients with or without psoriatic arthritis and healthy controls.DesignWe employed a global metabolomics approach to compare circulating metabolites from patients with psoriasis, psoriasis and psoriatic arthritis, and healthy controls.SettingStudy participants were recruited from the general community and from the Psoriasis Clinic at the University of California Davis in United States.ParticipantsWe examined metabolomic profiles using blood serum samples from 30 patients age and gender matched into three groups: 10 patients with psoriasis, 10 patients with psoriasis and psoriatic arthritis and 10 control participants. Main outcome(s) and measures(s): Metabolite levels were measured calculating the mean peak intensities from gas chromatography time-of-flight mass spectrometry.ResultsMultivariate analyses of metabolomics profiles revealed altered serum metabolites among the study population. Compared to control patients, psoriasis patients had a higher level of alpha ketoglutaric acid (Pso: 288 ± 88;Control209 ± 69; p=0.03), a lower level of asparagine (Pso: 5460 ± 980;Control7260 ± 2100; p=0.02), and a lower level of glutamine (Pso: 86000 ± 20000;Control111000 ± 27000; p=0.02). Compared to control patients, patients with psoriasis and psoriatic arthritis had increased levels of glucuronic acid (Pso + PsA: 638 ± 250;Control347 ± 61; p=0.001). Compared to patients with psoriasis alone, patients with both psoriasis and psoriatic arthritis had a decreased level of alpha ketoglutaric acid (Pso + PsA: 186 ± 80; Pso: 288 ± 88; p=0.02) and an increased level of lignoceric acid (Pso + PsA: 442 ± 280; Pso: 214 ± 64; p=0.02).Conclusions and relevanceThe metabolite differences help elucidate the pathogenesis of psoriasis and psoriatic arthritis and they may provide insights for therapeutic development

Cathepsin S in tumours, regional lymph nodes and sera of patients with lung cancer: relation to prognosis

Cysteine proteinase cathepsin S (Cat S) is expressed mainly in lymphatic tissues and has been characterised as a key enzyme in major histocompatibility complex class II (MHC-II) mediated antigen presentation. Cat S has been measured in tissue cytosols of lung parenchyma, lung tumours and lymph nodes and in sera of patients with lung tumours and of healthy controls, by specific enzyme-linked immunosorbent assay (ELISA). A difference in Cat S level was found between tumour and adjacent control tissue cytosols of 60 lung cancer patients (median 4.3 vs. 2.8 ng mg−1protein). In lymph nodes obtained from 24 patients of the same group, the level of Cat S was significantly higher than in tumours or lung parenchyma (P< 0.001). Additionally, significantly higher levels were found in non-infiltrated than in infiltrated lymph nodes (median 16.6 vs 7.5 ng mg−1protein). Patients with low levels of Cat S in tumours and lung parenchyma exhibited a significantly higher risk of death than those with high levels of Cat S (P= 0.025 – tumours;P= 0.02 – parenchyma). Immunohistochemical analysis (IHA) of lung parenchyma revealed a staining reaction in alveolar type II cells, macrophages and bronchial epithelial cells. In regional lymph node tissue, strong staining of Cat S was found in lymphocytes and histiocytes. Nevertheless, Cat S was detected also in tumour cells, independently of their origin. Our results provide evidence that Cat S may be involved in malignant progression. Its role, however, differs from that of the related Cats B and L and could be associated with the immune response rather than with remodelling of extracellular matrix. © 2001 Cancer Research Campaign  http://www.bjcancer.co

Inter-laboratory reproducibility of fast gas chromatography–electron impact–time of flight mass spectrometry (GC–EI–TOF/MS) based plant metabolomics

The application of gas chromatography–mass spectrometry (GC–MS) to the ‘global’ analysis of metabolites in complex samples (i.e. metabolomics) has now become routine. The generation of these data-rich profiles demands new strategies in data mining and standardisation of experimental and reporting aspects across laboratories. As part of the META-PHOR project’s (METAbolomics for Plants Health and OutReach: http://www.meta-phor.eu/) priorities towards robust technology development, a GC–MS ring experiment based upon three complex matrices (melon, broccoli and rice) was launched. All sample preparation, data processing, multivariate analyses and comparisons of major metabolite features followed standardised protocols, identical models of GC (Agilent 6890N) and TOF/MS (Leco Pegasus III) were also employed. In addition comprehensive GC×GC–TOF/MS was compared with 1 dimensional GC–TOF/MS. Comparisons of the paired data from the various laboratories were made with a single data processing and analysis method providing an unbiased assessment of analytical method variants and inter-laboratory reproducibility. A range of processing and statistical methods were also assessed with a single exemplary dataset revealing near equal performance between them. Further investigations of long-term reproducibility are required, though the future generation of global and valid metabolomics databases offers much promise

Indoxyl sulfate, a gut microbiome-derived uremic toxin, is associated with psychic anxiety and its functional magnetic resonance imaging-based neurologic signature

Background: It is unknown whether indoles, metabolites of tryptophan that are derived entirely from bacterial metabolism in the gut, are associated with symptoms of depression and anxiety. Methods: Serum samples (baseline, 12 weeks) were drawn from participants (n=196) randomized to treatment with cognitive behavioral therapy (CBT), escitalopram, or duloxetine for major depressive disorder. Results: Baseline indoxyl sulfate abundance was positively correlated with severity of psychic anxiety and total anxiety and with resting state functional connectivity to a network that processes aversive stimuli (which includes the subcallosal cingulate cortex (SCC-FC), bilateral anterior insula, right anterior midcingulate cortex, and the right premotor areas). The relation between indoxyl sulfate and psychic anxiety was mediated only through the metabolite's effect on the SCC-FC with the premotor area. Baseline indole abundances were unrelated to post-treatment outcome measures, which suggests that CBT and antidepressant medications relieve anxiety via mechanisms unrelated to gut microbiota. Conclusions: A peripheral gut microbiome-derived metabolite was associated with altered neural processing and with psychiatric symptom (anxiety) in humans, which provides further evidence that gut microbiome disruption can contribute to neuropsychiatric disorders that may require different therapeutic approaches

Multiple metabolomics of uropathogenic E. coli reveal different information content in terms of metabolic potential compared to virulence factors.

No single analytical method can cover the whole metabolome and the choice of which platform to use may inadvertently introduce chemical selectivity. In order to investigate this we analysed a collection of uropathogenic Escherichia coli. The selected strains had previously undergone extensive characterisation using classical microbiological methods for a variety of metabolic tests and virulence factors. These bacteria were analysed using Fourier transform infrared (FT-IR) spectroscopy; gas chromatography mass spectrometry (GC-MS) after derivatisation of polar non-volatile analytes; as well as reversed-phase liquid chromatography mass spectrometry in both positive (LC-MS(+ve)) and negative (LC-MS(-ve)) electrospray ionisation modes. A comparison of the discriminatory ability of these four methods with the metabolic test and virulence factors was made using Procrustes transformations to ascertain which methods produce congruent results. We found that FT-IR and LC-MS(-ve), but not LC-MS(+ve), were comparable with each other and gave highly similar clustering compared with the virulence factors tests. By contrast, FT-IR and LC-MS(-ve) were not comparable to the metabolic tests, and we found that the GC-MS profiles were significantly more congruent with the metabolic tests than the virulence determinants. We conclude that metabolomics investigations may be biased to the analytical platform that is used and reflects the chemistry employed by the methods. We therefore consider that multiple platforms should be employed where possible and that the analyst should consider that there is a danger of false correlations between the analytical data and the biological characteristics of interest if the full metabolome has not been measured