Mass spectrometry-based quantitative analysis and biomarker discovery

Plasma metabolite profiling reveals potential biomarkers of giant cell tumor of bone by using NMR-based metabolic profiles: A cross-sectional study

Giant cell tumor (GCT) of bone is a locally aggressive bone tumor, which accounts for 4% to 5% of all primary bone tumors. At present, the early diagnosis and postoperative recurrence monitoring are still more difficult due to the lack of effective biomarkers in GCT. As an effective tool, metabolomics has played an essential role in the biomarkers research of many tumors. However, there has been no related study of the metabolomics of GCT up to now. The purpose of this study was to identify several key metabolites as potential biomarkers for GCT by using nuclear magnetic resonance (NMR)-based metabolic profiles.Patients with GCT in our hospital were recruited in this study and their plasma was collected as the research sample, and plasma collected from healthy subjects was considered as the control. NMR was then utilized to detect all samples. Furthermore, based on correlation coefficients, variable importance for the projection values and P values of metabolites obtained from multidimensional statistical analysis, the most critical metabolites were selected as potential biomarkers of GCT. Finally, relevant metabolic pathways involved in these potential biomarkers were determined by database retrieval, based on which the metabolic pathways were plotted.Finally, 28 GCT patients and 26 healthy volunteers agreed to participate in the study. In the multidimensional statistical analysis, all results showed that there was obvious difference between the GCT group and the control group. Ultimately, 18 metabolites with significant differences met the selection condition, which were identified as potential biomarkers. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) and Human Metabolome Database (HMD) database searching and literature review, these metabolites were found to be mainly correlated with glucose metabolism, fat metabolism, amino acid metabolism, and intestinal microbial metabolism. These metabolic disorders might, in turn, reflect important pathological processes such as proliferation and migration of tumor cells and immune escape in GCT.Our work showed that these potential biomarkers identified appeared to have early diagnostic and relapse monitoring values for GCT, which deserve to be further investigated. In addition, it also suggested that metabolomics profiling approach is a promising screening tool for the diagnosis and relapse monitoring of GCT patients.

Detection of Lipid Mediators of Inflammation in the Human Tear Film

PURPOSE

Lipid mediators of inflammation are a group of signaling molecules produced by various cells under physiological conditions and modulate the inflammatory process during various pathologic conditions. Although eicosanoids and F2-isoprostanes are recognized lipid mediators of inflammation, there is no consensus yet on the extraction and mass spectrometry (MS) method for their analysis in individual human tear samples. Thus, the aim of this study was to develop an optimal method for extraction of lipid mediators of inflammation in the tear film and evaluate MS techniques for their analysis.

METHODS

Basal tears were collected from each eye of 19 subjects using glass microcapillaries. Lipid extraction was performed using either varying concentrations of acidified methanol, a modified Folch method, or solid-phase extraction. Initially, an untargeted analysis of the extracts was performed using SCIEX TripleTOF 5600 mass spectrometer to identify any lipid mediators of inflammation (eicosanoids) and later a targeted analysis was performed using the SCIEX 6500 Qtrap to identify and quantify prostaglandins and isoprostanes. Mass spectra and chromatograms were analyzed using Peakview, XCMS, and Multiquant software.

RESULTS

Prostaglandins and isoprostanes were observed and quantified using the Qtrap mass spectrometer under multiple reaction monitoring (MRM) mode after solid-phase extraction. Extraction with acidified methanol along with the Folch method produced cleaner spectra during MS with the Triple time of flight (TOF) mass spectrometer. Lipid mediators of inflammation were not observed in any of the tear samples using the Triple TOF mass spectrometer.

CONCLUSIONS

Solid-phase extraction may be the method of choice for extraction of prostaglandins and isoprostanes in low volumes of tears. The SCIEX Qtrap 6500 in MRM mode may be suitable to identify and quantify similar lipid mediators of inflammation.

Plasma, urine and ligament tissue metabolite profiling reveals potential biomarkers of ankylosing spondylitis using NMR-based metabolic profiles

Background

Ankylosing spondylitis (AS) is an autoimmune rheumatic disease mostly affecting the axial skeleton. Currently, anti-tumour necrosis factor α (anti-TNF-α) represents an effective treatment for AS that may delay the progression of the disease and alleviate the symptoms if the diagnosis can be made early. Unfortunately, effective diagnostic biomarkers for AS are still lacking; therefore, most patients with AS do not receive timely and effective treatment. The intent of this study was to determine several key metabolites as potential biomarkers of AS using metabolomic methods to facilitate the early diagnosis of AS.

Methods

First, we collected samples of plasma, urine, and ligament tissue around the hip joint from AS and control groups. The samples were examined by nuclear magnetic resonance spectrometry, and multivariate data analysis was performed to find metabolites that differed between the groups. Subsequently, according to the correlation coefficients, variable importance for the projection (VIP) and P values of the metabolites obtained in the multivariate data analysis, the most crucial metabolites were selected as potential biomarkers of AS. Finally, metabolic pathways involving the potential biomarkers were determined using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and the metabolic pathway map was drawn.

Results

Forty-four patients with AS agreed to provide plasma and urine samples, and 30 provided ligament tissue samples. An equal number of volunteers were recruited for the control group. Multidimensional statistical analysis suggested significant differences between the patients with AS and control subjects, and the models exhibited good discrimination and predictive ability. A total of 20 different metabolites ultimately met the requirements for potential biomarkers. According to KEGG analysis, these marker metabolites were primarily related to fat metabolism, intestinal microbial metabolism, glucose metabolism and choline metabolism pathways, and they were also probably associated with immune regulation.

Conclusions

Our work demonstrates that the potential biomarkers that were identified appeared to have diagnostic value for AS and deserve to be further investigated. In addition, this work also suggests that the metabolomic profiling approach is a promising screening tool for the diagnosis of patients with AS.

Analysis of cytochrome P450 metabolites of arachidonic acid by stable isotope probe labeling coupled with ultra high-performance liquid chromatography/mass spectrometry

Cytochrome P450 metabolites of arachidonic acid (AA) belong to eicosanoids and are potent lipid mediators of inflammation. It is well-known that eicosanoids play an important role in numerous pathophysiological processes. Therefore, quantitative analysis of cytochrome P450 metabolites of AA, including hydroxyeicosatetraenoic acids (HETEs), epoxyeicosatreinoic acids (EETs), and dihydroxyeicosatrienoic acids (DHETs) can provide crucial information to uncover underlying mechanisms of cytochrome P450 metabolites of AA related diseases. Herein, we developed a highly sensitive method to identify and quantify HETEs, EETs, and DHETs in lipid extracts of biological samples based on stable isotope probe labeling coupled with ultra high-performance liquid chromatography/mass spectrometry. To this end, a pair of stable isotope probes, 2-dimethylaminoethylamine (DMED) and d4-2-dimethylaminoethylamine (d4-DMED), were utilized to facilely label eicosanoids. The heavy labeled eicosanoid standards were prepared and used as internal standards for quantification to minimize the matrix and ion suppression effects in mass spectrometry analysis. In addition, the detection sensitivities of DMED labeled eicosanoids improved by 3-104 folds in standard solution and 5-138 folds in serum matrix compared with unlabeled analytes. Moreover, a good separation of eicosanoids isomers was achieved upon DMED labeling. The established method provided substantial sensitivity (limit of quantification at sub-picogram), high specificity, and broad linear dynamics range (3 orders of magnitude). We further quantified cytochrome P450 metabolites of AA in rat liver, heart, brain tissues and human serum using the developed method. The results showed that 19 eicosanoids could be distinctly detected and the contents of 11-, 15-, 16-, 20-HETE, 5,6-EET, and 14,15-EET in type 2 diabetes mellitus patients and 5-, 11-, 12-, 15-, 16-, 20-HETE, 8,9-EET, and 5,6-DHET in myeloid leukemia patients had significant changes, demonstrating that these eicosanoids may have important roles on the pathogenesis of type 2 diabetes mellitus and myeloid leukemia.

Functional interpretation of metabolomics data as a new method for predicting long-term side effects: treatment of atopic dermatitis in infants

Topical steroids are used for the treatment of primary atopic dermatitis (AD); however, their associated risk of serious complications is great due to the presence of vulnerable lesions in young children with AD. Topical calcineurin inhibitors (TCIs) are steroid-free, anti-inflammatory agents used for topical AD therapy. However, their use is prohibited in infants <2 years of age because of their carcinogenic potential. We conducted a randomized, double-blind trial to evaluate the efficacy of TCIs as a secondary AD treatment for children <2 years of age by comparing 1% pimecrolimus cream with 0.05% desonide cream. We performed urinary metabolomics to predict long-term side effects. The 1% pimecrolimus cream displayed similar efficacy and exceptional safety compared with the 0.05% desonide cream. Metabolomics-based long-term toxicity tests effectively predicted long-term side effects using short-term clinical models. This applicable method for the functional interpretation of metabolomics data sets the foundation for future studies involving the prediction of the toxicity and systemic reactions caused by long-term medication administration.

Serum metabolic signatures of four types of human arthritis

Similar symptoms of the different types of arthritis have continued to confound the clinical diagnosis and represent a clinical dilemma making treatment choices with a more personalized or generalized approach. Here we report a mass spectrometry-based metabolic phenotyping study to identify the global metabolic defects associated with arthritis as well as metabolic signatures of four major types of arthritis--rheumatoid arthritis (n = 27), osteoarthritis (n = 27), ankylosing spondylitis (n = 27), and gout (n = 33)--compared with healthy control subjects (n = 60). A total of 196 metabolites were identified from serum samples using a combined gas chromatography coupled with time-of-flight mass spectrometry (GC-TOF MS) and ultraperformance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-QTOF MS). A global metabolic profile is identified from all arthritic patients, suggesting that there are common metabolic defects resulting from joint inflammation and lesion. Meanwhile, differentially expressed serum metabolites are identified constituting an unique metabolic signature of each type of arthritis that can be used as biomarkers for diagnosis and patient stratification. The results highlight the applicability of metabonomic phenotyping as a novel diagnostic tool for arthritis complementary to existing clinical modalities.

Elevated level of pro-inflammatory eicosanoids and EPC dysfunction in diabetic patients with cardiac ischemia

BACKGROUND

Circulating endothelial progenitor cells (EPCs) are recruited from the blood system to sites of ischemia and endothelial damage, where they contribute to the repair and development of blood vessels. Since numerous eicosanoids including leukotrienes (LTs) and hydroxyeicosatetraenoic acids (HETEs) have been shown to exert potent pro-inflammatory activities, we examined their levels in chronic diabetic patients with severe cardiac ischemia in conjunction with the level and function of EPCs.

RESULTS

Lipidomic analysis revealed a diabetes-specific increase (p<0.05) in inflammatory and angiogenic eicosanoids including the 5-lipoxygenase-derived LTB (4.11±1.17 vs. 0.96±0.27 ng/ml), the lipoxygenase/CYP-derived 12-HETE (117.08±35.05 vs. 24.34±10.03 ng/ml), 12-HETrE (17.56±4.43 vs. 4.15±2.07 ng/ml), and the CYP-derived 20-HETE (0.32±0.04 vs. 0.06±0.05 ng/ml) the level of which correlated with BMI (p=0.0027). In contrast, levels of the CYP-derived EETs were not significantly (p=0.36) different between these two groups. EPC levels and their colony-forming units were lower (p<0.05) with a reduced viability in diabetic patients compared with non-diabetics. EPC function (colony-forming units (CFUs) and MTT assay) also negatively correlated with the circulating levels of HgA1C.

CONCLUSION

This study demonstrates a close association between elevated levels of highly pro-inflammatory eicosonoids, diabetes and EPC dysfunction in patients with cardiac ischemia, indicating that chronic inflammation impact negatively on EPC function and angiogenic capacity in diabetes.