Psoriatic arthritis (PsA) is a chronic, systemic, immune-mediated inflammatory disease causing cutaneous and musculoskeletal inflammation that affects 25% of patients with psoriasis. Current methods ...for evaluating PsA disease activity are not accurate enough for precision medicine. A metabolomics-based approach can elucidate psoriatic disease pathogenesis, providing potential objective biomarkers. With the hypothesis that serum metabolites are associated with skin disease activity, we aimed to identify serum metabolites associated with skin activity in PsA patients. We obtained serum samples from patients with PsA (n = 150) who were classified into mild, moderate and high disease activity groups based on the Psoriasis Area Severity Index. We used solid-phase microextraction (SPME) for sample preparation, followed by data acquisition via an untargeted liquid chromatography—mass spectrometry (LC-MS) approach. Disease activity levels were predicted using identified metabolites and machine learning algorithms. Some metabolites tentatively identified include eicosanoids with anti- or pro-inflammatory properties, like 12-Hydroxyeicosatetraenoic acid, which was previously implicated in joint disease activity in PsA. Other metabolites of interest were associated with dysregulation of fatty acid metabolism and belonged to classes such as bile acids, oxidized phospholipids, and long-chain fatty acids. We have identified potential metabolites associated with skin disease activity in PsA patients.
Tranexamic acid (TXA) is an antifibrinolytic used during cardiac surgery that presents high inter-patient variability. High plasma concentrations have been associated with post-operative seizures. ...Due to the difficulties with maintaining acceptable concentrations of TXA during surgery, implementation of a point-of-care strategy for testing TXA plasma concentration would allow for close monitoring of its concentration during administration. This would facilitate timely corrections to the dosing schedule, and in effect tailor treatment for individual patient needs. In this work, a method for the rapid monitoring of TXA from plasma samples was subsequently carried out via biocompatible solid-phase microextraction (Bio-SPME) coupled directly to tandem mass spectrometry via a microfluidic open interface (MOI). MOI operates under the concept of a flow-isolated desorption volume and was designed with aims to directly hyphenate Bio-SPME to different detection and ionization systems. In addition, it allows the desorption of Bio-SPME fibers in small volumes while it concurrently continues feeding the ESI with a constant flow to minimize cross-talking and instabilities. The methodology was used to monitor six patients with varying degrees of renal dysfunction, at different time points during cardiac surgery. MOI proves to be a reliable and feasible tool for rapid therapeutic drug monitoring. Affording total times of analysis as low as 30 seconds per sample in its high throughput mode configuration while the single sample turn-around time was 15 minutes, including sample preparation. In addition, cross-validation against a standard thin film solid phase microextraction using liquid chromatography coupled to tandem mass spectrometry (TFME-LC-MS/MS) method was performed. Bland-Altman analysis was used to cross-validate the results obtained by the two methods. Data analysis demonstrated that 92% of the compared data pairs (n = 63) were distributed within the acceptable range. The data was also validated by the Passing Bablok regression, demonstrating good statistical agreement between these two methods. Finally, the currently presented method offers comparable results to the conventional liquid chromatography with acceptable RSDs, while only necessitating a fraction of the time. In this way, TXA concentration in plasma can be monitored in a close to real time throughput during surgery.
As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many ...potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in clinics. Awareness of the challenges present can facilitate the development and advancement of innovative strategies that allow improved and more efficient applications of metabolite-based markers in clinical settings. This minireview provides a comprehensive summary of the pre-analytical factors, required analytical validation studies, and kit development challenges that must be resolved before the successful translation of novel metabolite biomarkers originating from research. We discuss the necessity for strict protocols for sample collection, storage, and the regulatory requirements to be fulfilled for a bioanalytical method to be considered as analytically validated. We focus especially on the blood as a biological matrix and liquid chromatography coupled with tandem mass spectrometry as the analytical platform for biomarker validation. Furthermore, we examine the challenges of developing a commercially viable metabolomics kit for distribution. To bridge the gap between the research lab and clinical implementation and utility of relevant metabolites, the understanding of the translational challenges for a biomarker panel is crucial for more efficient development of metabolomics-based precision medicine.
Approximately 25% of psoriasis patients have an inflammatory arthritis termed psoriatic arthritis (PsA). There is strong interest in identifying and validating biomarkers that can accurately and ...reliably predict conversion from psoriasis to PsA using novel technologies such as metabolomics. Lipids, in particular, are of key interest in psoriatic disease. We sought to develop a liquid chromatography-mass spectrometry (LC-MS) method to be used in conjunction with solid-phase microextraction (SPME) for analyzing fatty acids and similar molecules. A total of 25 chromatographic methods based on published lipid studies were tested on two LC columns. As a proof of concept, serum samples from psoriatic disease patients (n = 27 psoriasis and n = 26 PsA) were processed using SPME and run on the selected LC-MS method. The method that was best for analyzing fatty acids and fatty acid-like molecules was optimized and applied to serum samples. A total of 18 tentatively annotated features classified as fatty acids and other lipid compounds were statistically significant between psoriasis and PsA groups using both multivariate and univariate approaches. The SPME-LC-MS method developed and optimized was capable of detecting fatty acids and similar lipids that may aid in differentiating psoriasis and PsA patients.
Introduction
Psoriatic arthritis (PsA), an inflammatory arthritis that develops in individuals with psoriasis, is associated with reduced quality of life. Identifying biomarkers associated with ...development of PsA as well as with PsA disease activity may help management of psoriatic disease.
Objectives
To use metabolomic fingerprinting to determine potential candidate markers of disease conversion (psoriasis to PsA) and/or PsA activity.
Methods
A novel sample preparation protocol based on solid-phase microextraction (SPME) was used to prepare serum samples obtained from: (1) individuals with psoriasis, some of whom develop psoriatic arthritis (n = 20); (2) individuals with varying PsA activity (mild, moderate, severe; n = 10 each) and (3) healthy controls (n = 10). Metabolomic fingerprinting of the obtained extracts was performed using reversed-phase liquid chromatography coupled to high resolution mass spectrometry.
Results
Psoriasis patients who developed PsA had similar metabolomic profiles to patients with mild PsA and were also indistinguishable from patients with psoriasis who did not develop PsA. Elevated levels of selected long-chain fatty acids (e.g., 3-hydroxytetradecanedioic acid) that are associated with dysregulation of fatty acid metabolism, were observed in patients with severe PsA. In addition, 1,11-undecanedicarboxylic acid—an unusual fatty acid associated with peroxisomal disorders—was also identified as a classifier in PsA patients vs. healthy individuals. Furthermore, a number of different eicosanoids with either pro- or anti-inflammatory properties were detected solely in serum samples of patients with moderate and severe PsA.
Conclusion
A global metabolomics approach was employed to analyze the serum metabolome of patients with psoriasis, PsA, and healthy controls in order to examine potential differences in the biochemical profiles at a metabolite level. A closer examination of circulating metabolites may potentially provide markers of PsA activity.
Metabolomics investigates a broad range of small molecules, allowing researchers to understand disease-related changes downstream of the genome and proteome in response to external environmental ...stimuli. It is an emerging technology that holds promise in identifying biomarkers and informing the practice of precision medicine. In this review, we summarize the studies that have examined endogenous metabolites in patients with psoriasis and/or psoriatic arthritis using nuclear magnetic resonance (NMR) or mass spectrometry (MS) and were published through 26 January 2021. A standardized protocol was used for extracting data from full-text articles identified by searching OVID Medline ALL, OVID Embase, OVID Cochrane Central Register of Controlled Trials and BIOSIS Citation Index in Web of Science. Thirty-two studies were identified, investigating various sample matrices and employing a wide variety of methods for each step of the metabolomics workflow. The vast majority of studies identified metabolites, mostly amino acids and lipids that may be associated with psoriasis diagnosis and activity. Further exploration is needed to identify and validate metabolomic biomarkers that can accurately and reliably predict which psoriasis patients will develop psoriatic arthritis, differentiate psoriatic arthritis patients from patients with other inflammatory arthritides and measure psoriatic arthritis activity.
Normothermic ex vivo lung perfusion (NEVLP) has emerged as a modernized organ preservation technique that allows for detailed assessment of donor lung function prior to transplantation. The main goal ...of this study was to identify potential biomarkers of lung function and/or injury during a prolonged (19 h) NEVLP procedure using in vivo solid-phase microextraction (SPME) technology followed by liquid chromatography-high resolution mass spectrometry (LC-HRMS). The use of minimally invasive in vivo SPME fibers for repeated sampling of biological tissue permits the monitoring and evaluation of biochemical changes and alterations in the metabolomic profile of the lung. These in vivo SPME fibers were directly introduced into the lung and were also used to extract metabolites (on-site SPME) from fresh perfusate samples collected alongside lung samplings. A subsequent goal of the study was to assess the feasibility of SPME as an in vivo method in metabolomics studies, in comparison to the traditional in-lab metabolomics workflow. Several upregulated biochemical pathways involved in pro- and anti-inflammatory responses, as well as lipid metabolism, were observed during extended lung perfusion, especially between the 11th and 12th hours of the procedure, in both lung and perfusate samples. However, several unstable and/or short-lived metabolites, such as neuroprostanes, have been extracted from lung tissue in vivo using SPME fibers. On-site monitoring of the metabolomic profiles of both lung tissues through in vivo SPME and perfusate samples on site throughout the prolonged NEVLP procedure can be effectively performed using in vivo SPME technology.
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•In vivo SPME monitors metabolic changes in porcine lung during 19-h NEVLP.•On-site SPME for perfusate sampling monitors metabolite composition during NEVLP.•SPME-LC-HRMS permits identification of potential metabolic markers of lung function.•Stored perfusate provides less relevant metabolome information compared to on-site perfusate samples.•In vivo SPME of the lung provides more metabolomic information than perfusate sampling.
In vivo lung perfusion (IVLP) is a novel isolated lung technique developed to enable the local, in situ administration of high-dose chemotherapy to treat metastatic lung cancer. Combination therapy ...using folinic acid (FOL), 5-fluorouracil (F), and oxaliplatin (OX) (FOLFOX) is routinely employed to treat several types of solid tumours in various tissues. However, F is characterized by large interpatient variability with respect to plasma concentration, which necessitates close monitoring during treatments using of this compound. Since plasma drug concentrations often do not reflect tissue drug concentrations, it is essential to utilize sample-preparation methods specifically suited to monitoring drug levels in target organs. In this work, in vivo solid-phase microextraction (in vivo SPME) is proposed as an effective tool for quantitative therapeutic drug monitoring of FOLFOX in porcine lungs during pre-clinical IVLP and intravenous (IV) trials. The concomitant extraction of other endogenous and exogenous small molecules from the lung and their detection via liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) enabled an assessment of FOLFOX's impact on the metabolomic profile of the lung and revealed the metabolic pathways associated with the route of administration (IVLP vs. IV) and the therapy itself. This study also shows that the immediate instrumental analysis of metabolomic samples is ideal, as long-term storage at −80 °C results in changes in the metabolite content in the sample extracts.
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•Use of in vivo SPME during FOLFOX administration in pre-clinical IVLP and IV trials.•Therapeutic drug monitoring of FOLFOX and metabolites in porcine lung.•Pharmacometabolomic fingerprinting of porcine lung during FOLFOX administration.•In vivo SPME facilitates in situ monitoring of lung function with no tissue biopsy.
Development of a novel in vivo lung perfusion (IVLP) procedure allows localized delivery of high-dose doxorubicin (DOX) for targeting residual micrometastatic disease in the lungs. However, DOX ...delivery via IVLP requires careful monitoring of drug level to ensure tissue concentrations of this agent remain in the therapeutic window. A small dimension nitinol wire coated with a sorbent of biocompatible morphology (Bio-SPME) has been clinically evaluated for in vivo lung tissue extraction and determination of DOX and its key metabolites. The in vivo Bio-SPME-IVLP experiments were performed on pig model over various (150 and 225 mg/m2) drug doses, and during human clinical trial. Two patients with metastatic osteosarcoma were treated with a single 5 and 7 μg/mL (respectively) dose of DOX during a 3-h IVLP. In both pig and human cases, DOX tissue levels presented similar trends during IVLP. Human lung tissue concentrations of drug ranged between 15 and 293 μg/g over the course of the IVLP procedure. In addition to DOX levels, Bio-SPME followed by liquid chromatography-mass spectrometry analysis generated 64 metabolic features during endogenous metabolite screening, providing information about lung status during drug administration. Real-time monitoring of DOX levels in the lungs can be performed effectively throughout the IVLP procedure by in vivo Bio-SPME chemical biopsy approach. Bio-SPME also extracted various endogenous molecules, thus providing a real-time snapshot of the physiology of the cells, which might assist in the tailoring of personalized treatment strategy.
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•A minimally invasive Bio-SPME chemical biopsy sampling tool was proposed for DOX quantification throughout IVLP.•SPME probes enabled analytes’ extraction not causing tissue injury nor disrupting the equilibrium of the living system.•The level and biodistribution of the drug in the lung were monitored together with metabolites associated with its activity.
Introduction
Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis, affecting approximately a quarter of patients with psoriasis. Accurate assessment of disease activity is difficult. ...There are currently no clinically validated biomarkers to stratify PsA patients based on their disease activity, which is important for improving clinical management.
Objectives
To identify metabolites capable of classifying patients with PsA according to their disease activity.
Methods
An in-house solid-phase microextraction (SPME)—liquid chromatography-high resolution mass spectrometry (LC-HRMS) method for lipid analysis was used to analyze serum samples obtained from patients classified as having low (n = 134), moderate (n = 134) or high (n = 104) disease activity, based on psoriatic arthritis disease activity scores (PASDAS). Metabolite data were analyzed using eight machine learning methods to predict disease activity levels. Top performing methods were selected based on area under the curve (AUC) and significance.
Results
The best model for predicting high disease activity from low disease activity achieved AUC 0.818. The best model for predicting high disease activity from moderate disease activity achieved AUC 0.74. The best model for classifying low disease activity from moderate and high disease activity achieved AUC 0.765. Compounds confirmed by MS/MS validation included metabolites from diverse compound classes such as sphingolipids, phosphatidylcholines and carboxylic acids.
Conclusion
Several lipids and other metabolites when combined in classifying models predict high disease activity from both low and moderate disease activity. Lipids of key interest included lysophosphatidylcholine and sphingomyelin. Quantitative MS assays based on selected reaction monitoring, are required to quantify the candidate biomarkers identified.
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