Identification of traumatic acid as a potential plasma biomarker for sarcopenia using a metabolomics-based approach.

BACKGROUND: The pathogenesis of sarcopenia is complex and has not been well explored. Identifying biomarkers is a promising strategy for exploring the mechanism of sarcopenia. This study aimed to identify potential biomarkers of sarcopenia through a metabolomic analysis of plasma metabolites in elderly subjects (≥65 years of age) vs. younger adults (<65 years of age). METHODS: Of the 168 candidates in the Comprehensive Geriatric Assessment and Frailty Study of Elderly Outpatients, 24 elderly subjects (≥65 years of age) with sarcopenia were age and sex matched with 24 elderly subjects without sarcopenia. In addition, 24 younger adults were recruited for comparison. Muscle strength, gait speed, and metabolic and inflammatory parameters, including plasma tumour necrosis factor-α, C-reactive protein, irisin, and growth differentiation factor 15 (GDF-15) levels were assessed. Metabolomic analysis was carried out using the plasma metabolites. RESULTS: Seventy-two participants were enrolled, including 10 (41.6%) men and 14 (58.3%) women in both groups of elderly subjects. The median ages of elderly subjects with and without sarcopenia were 82 (range: 67-88) and 81.5 (range: 67-87) years, respectively. Among the 242 plasma metabolic peaks analysed among these three groups, traumatic acid was considered as a sarcopenia-related metabolite. The plasma traumatic acid signal intensity level was significantly higher in elderly subjects with sarcopenia than in elderly subjects without sarcopenia [591.5 (inter-quartile range, IQR: 491.5-664.5) vs. 430.0 (IQR: 261.0-599.5), P = 0.0063]. The plasma concentrations of traumatic acid were 15.8 (IQR: 11.5-21.7), 21.1 (IQR: 16.0-25.8), and 24.3 (IQR: 18.0-29.5) ppb in younger adults [age range: 23-37 years, 12 (50%) men], elderly subjects without sarcopenia, and elderly subjects with sarcopenia, respectively, thereby depicting an increasing tendency (P for trend = 0.034). This pattern was similar to that of GDF-15, a recognized sarcopenia-related factor. Plasma traumatic acid concentrations were also positively correlated with the presence of hypertension (r = 0.25, P = 0.034), glucose AC (r = 0.34, P = 0.0035), creatinine (r = 0.40, P = 0.0006), and GDF-15 levels (r = 0.25, P = 0.0376), but negatively correlated with the Modification of Diet in Renal Disease-simplify-glomerular filtration rate (r = -0.50, P < 0.0001). Similarly, plasma GDF-15 concentrations were associated with these factors. CONCLUSIONS: Traumatic acid might represent a potential plasma biomarker of sarcopenia. However, further studies are needed to validate the results and investigate the underlying mechanisms.

Web Server for Peak Detection, Baseline Correction, and Alignment in Two-Dimensional Gas Chromatography Mass Spectrometry-Based Metabolomics Data.

Two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) is superior for chromatographic separation and provides great sensitivity for complex biological fluid analysis in metabolomics. However, GC×GC/TOF-MS data processing is currently limited to vendor software and typically requires several preprocessing steps. In this work, we implement a web-based platform, which we call GC2MS, to facilitate the application of recent advances in GC×GC/TOF-MS, especially for metabolomics studies. The core processing workflow of GC2MS consists of blob/peak detection, baseline correction, and blob alignment. GC2MS treats GC×GC/TOF-MS data as pictures and clusters the pixels as blobs according to the brightness of each pixel to generate a blob table. GC2MS then aligns the blobs of two GC×GC/TOF-MS data sets according to their distance and similarity. The blob distance and similarity are the Euclidean distance of the first and second retention times of two blobs and the Pearson's correlation coefficient of the two mass spectra, respectively. GC2MS also directly corrects the raw data baseline. The analytical performance of GC2MS was evaluated using GC×GC/TOF-MS data sets of Angelica sinensis compounds acquired under different experimental conditions and of human plasma samples. The results show that GC2MS is an easy-to-use tool for detecting peaks and correcting baselines, and GC2MS is able to align GC×GC/TOF-MS data sets acquired under different experimental conditions. GC2MS is freely accessible at http://gc2ms.web.cmdm.tw .

An efficient and robust fatty acid profiling method for plasma metabolomic studies by gas chromatography-mass spectrometry.

BACKGROUND: Targeted metabolomic analysis of fatty acids has linked the dysregulation of fatty acids to many diseases. This study selected five frequently used fatty acid derivatization methods for comparison. METHODS: We compared the method precisions and derivatization efficiencies, the most economical and best performing method was subjected to method validation. Twenty-four fatty acid standards were used to validate the method, which was later applied to the investigation of potential fatty acid markers of breast cancer. RESULTS: The acetyl chloride method was demonstrated to provide the best derivatization efficiency and lowest cost for plasma samples. The ionic liquid column successfully separated positional and geometric fatty acid isomers within 26 min under the optimized conditions. Intra-day and inter-day CVs for most of the fatty acids were <10%. Over 90% of the results showed recoveries within 85%-115%. The validated method was applied to investigate potential fatty acid markers of breast cancer. The fatty acid profiling results revealed that 3 fatty acids (C22:0, C24:0, C18:2n6) were significantly lower in both pre- and post-menopausal breast cancer patients (P<0.05). CONCLUSIONS: We demonstrated that the proposed method is an accurate, efficient and economical method for plasma metabolomic studies of fatty acids.

Metabolomic characterization of laborers exposed to welding fumes.

The complex composition of welding fumes, multiplicity of molecular targets, diverse cellular effects, and lifestyles associated with laborers vastly complicate the assessment of welding fume exposure. The urinary metabolomic profiles of 35 male welders and 16 male office workers at a Taiwanese shipyard were characterized via (1)H NMR spectroscopy and pattern recognition methods. Blood samples for the same 51 individuals were also collected, and the expression levels of the cytokines and other inflammatory markers were examined. This study dichotomized the welding exposure variable into high (welders) versus low (office workers) exposures to examine the differences of continuous outcome markers-metabolites and inflammatory markers-between the two groups. Fume particle assessments showed that welders were exposed to different concentrations of chromium, nickel, and manganese particles. Multivariate statistical analysis of urinary metabolomic patterns showed higher levels of glycine, taurine, betaine/TMAO, serine, S-sulfocysteine, hippurate, gluconate, creatinine, and acetone and lower levels of creatine among welders, while only TNF-α was significantly associated with welding fume exposure among all cytokines and other inflammatory markers measured. Of the identified metabolites, the higher levels of glycine, taurine, and betaine among welders were suspected to play some roles in modulating inflammatory and oxidative tissue injury processes. In this metabolomics experiment, we also discovered that the association of the identified metabolites with welding exposure was confounded by smoking, but not with drinking, which is a finding consistent with known modified response of inflammatory markers among smokers. Our results correspond with prior studies that utilized nonmetabolomic analytical techniques and suggest that the metabolomic profiling is an efficient method to characterize the overall effect of welding fume exposure and other confounders.