Plasma fatty acids metabolic profiling analysis of coronary heart disease based on GC–MS and pattern recognition

A validated and optimized method for separation and quantification of total fatty acids by gas chromatography-ion trap mass spectrometry in human plasma

Fatty acids (FAs) are associated with many physiological functions of tissues, and their alteration has been linked with tissue-specific or systemic diseases. The current situation warrants us to have a sensitive and specific method for analysis of total FAs simultaneously from the biological fluid so that the risk prediction, diagnosis or prognosis of the disease can be made effectively. Because of greater sensitivity and resolution, a method of gas chromatography-ion trap mass spectrometry (GC-IT/MS) has been optimized and validated to quantify simultaneously 19 total FAs levels in plasma and compared with GC-triple quadrupole mass spectrometry. FAs have been transesterified by methanolic acetyl chloride to fatty acid methyl esters (FAMEs). A 65 min GC method separated all 19 FAMEs. The calibration curve had good linearity up to 313-922 μM with a correlation coefficient between 0.9882 and 0.9998. The LODs and LOQs of FAMEs were in the range of 0.63 to 9.55 and 2.12 to 31.8 μM, respectively. The method has recovery up to 144 %, stability at 4 °C for 48 h and one freeze-thaw cycle, and good intra-day and inter-day precision. The optimized method has been used to quantify plasma total FAs in type 2 diabetes mellitus patients with and without acute coronary syndrome. Though a significant difference has been found between IT/MS and triple quadrupole mass spectrometry, the GC-IT/MS can help to quantify total FAs in the clinical setting.

Effects of extra virgin olive oil and pecans on plasma fatty acids in patients with stable coronary artery disease

OBJECTIVE

The aim of this study was to determine the effects of a healthy diet supplemented with extra virgin olive oil or pecans on plasma fatty acids (PFAs) in patients with stable coronary artery disease (CAD).

METHODS

Patients 40 to 80 y of age were randomized to one of three dietary interventions (allocation ratio 1: 1: 1): healthy diet based on guidelines (control group [CG]), healthy diet supplemented with 30 g/d of pecans (PNG), or a healthy diet supplemented with 30 mL/d of extra virgin olive oil (OOG). PFAs were identified at baseline and at the end of follow-up (12 wk), and correlations between dietary fatty acids intake, PFAs, and clinical biomarkers of the lipid profile were also assessed before and after the interventions.

RESULTS

Among 149 participants included in the analysis (43 CG; 51 PNG; and 55 OOG), correlations were observed between food intake, PFAs, and lipid profile before and after interventions independent of statins used, but all were considered weak. At the end of the study, the OOG showed increased concentrations of oleic fatty acid independently of the type of statin in use (1.49%; 95% confidence interval, 0.08-2.89; P = 0.029); however, there were no significant differences between the groups regarding the final mean values of oleic fatty acid or in the other PFAs.

CONCLUSIONS

In patients with stable CAD, there were no significant differences in PFAs after 12 wk according to dietary interventions evaluated.

Metabolomics for the masses: The future of metabolomics in a personalized world

Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics '('omic)' approaches have been used for therapeutic interventions previously. Metabolomics now a well-established'omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.

Chemometric analysis of the interactions among different parameters describing health conditions, breast cancer risk and fatty acids profile in serum of rats supplemented with conjugated linoleic acids

We investigated how different doses of conjugated linoleic acids applied for various periods of time influence breast cancer risk and fatty acids profile in serum of rats treated or not with 7,12-dimethylbenz[a]anthracene (DMBA). We also search for interactions among parameters describing health conditions and cancer risk. Animals were divided into 18 groups with different diet modifications (vegetable oil, 1.0%, 2.0% additions of CLA) and different periods of supplementation. In groups treated with DMBA mammary adenocarcinomas appeared. Due to the complexity of experiment apart from statistical analysis a chemometric tool-Partial Least Square method was applied. Analysis of pairs of correlated parameters allowed to identify some regularities concerning the relationships between fatty acid profiles and clinical features of animals. Fatty acids profile was the result of prolonged exposure to high dose of CLA and DMBA administration. These two factors underlined the differences in fatty acids profiles among clusters of animals.

A rapid and sensitive profiling of free fatty acids using liquid chromatography electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) after chemical derivatization

A mass spectrometry method for the improved identification and quantification of free fatty acids (FFAs) based on derivatization using trimethylsilyldiazomethane (TMSD) was developed and validated to be an sensitive and accurate method for analyzing FFAs.

Total Serum Fatty Acid Analysis by GC-MS: Assay Validation and Serum Sample Stability

Analysis of n3 fatty acids in serum samples has clinical applications in supplementation trials, but the analysis can be challenging due to low levels, stability issues and intra-individual variation. This study presents the single laboratory validation of a gas chromatographic-mass spectral (GC-MS) assay for analysis of fatty acid methyl esters (FAME) using sensitive single ion monitoring and provides data on fatty acid stability under different sample handling conditions. Recovery of total fatty acids from serum with Folch extraction was optimized and parallelism tests with spiked samples indicated that the serum matrix did not interfere with mass spectral quantitation. Precision and accuracy of the assay at the lowest limit of quantitation and at low, medium and high levels met with accepted guidelines for single laboratory validation. Several storage conditions that can be encountered with clinical samples also were evaluated for impact on fatty acid levels in serum. Serum from blood that was stored refrigerated for 3 days yielded similar results as serum that was prepared and frozen at -80°C immediately. Serum storage at room temperature for 3-24 hours and serum subjected to one freeze/thaw cycle had minimal effects on fatty acid levels. The intra-individual variability in pregnant women was reasonably small, with significant correlation coefficients ranging from 0.35 to 0.76 for blood drawn between 12-20 weeks versus 34-36 weeks of gestation. These results indicate that GC-MS with single ion monitoring is valid for the analysis of total fatty acids in clinical samples, even when blood processing cannot be performed in a timely manner.

Fluoroacetylation/fluoroethylesterification as a derivatization approach for gas chromatography-mass spectrometry in metabolomics: preliminary study of lymphohyperplastic diseases

Metabolic fingerprinting in combination with gas chromatography and multivariate analysis is being extensively employed for the improved understanding of biological changes induced by endogenous or exogenous factors. Chemical derivatization increases the sensitivity and specificity of gas chromatography-mass spectrometry (GC-MS) for polar or thermally labile biological compounds, which bear derivatizable groups. Thus, there is a constant demand for simple methods of derivatization and separation that satisfy the need for metabolite analysis, identifying as many chemical classes of compounds as possible. In this study, an optimized protocol of extraction and derivatization is established as a generally applicable method for the analysis of a wide range of classes of metabolites in urine, whole blood and saliva. Compounds of biological relevance bearing hydroxyl- carboxyl- and amino-groups are derivatized using single-step fluoroacetylation/fluoroethylesterification after proper optimization of the protocol. Subsequently, the developed derivatization procedure is engaged in finding blood metabolic biomarkers, induced by lymphohyperplastic disease, through the metabolomic fingerprinting approach, the multivariate modeling (hierarchical cluster analysis) and GC-MS. Our preliminary, GC-MS-based metabolomic fingerprinting study underlines the contribution of certain metabolites to the discrimination of patients with lymphohyperplastic diseases.

Multi-marker network in ST-elevation myocardial infarction patients undergoing primary percutaneous coronary intervention: when and what to measure

BACKGROUND

Data on the correlations between biomarkers to suggest cost-effective multi-marker (MM) panels predictive for ST-elevation myocardial infarction (STEMI) patients are lacking. We sought to explore the relationship between cardiac troponin I (cTnI), C-reactive protein (CRP), B-type natriuretic peptide (BNP), and chromogranin A (CgA) accounting for biomarkers' profiles detected within 48h from successful primary percutaneous coronary intervention (PPCI).

METHODS

In 73 STEMI patients cTnI, CRP, BNP, and CgA were measured before PPCI and 6, 24, and 48h later. STATIS methods generalizing Principal Component Analysis on three-way data sets were employed to extract information about: 1) similarities between patients, 2) contribution of each time of sampling and 3) correlations between biomarkers' profiles.

RESULTS

STEMI patients who underwent successful PPCI emerged to have a homogeneous profile tailored on biomarkers' evaluation within 48h. Their measurements at 24h contributed the most variability and information both to patients' and to biomarkers' profiles. BNP and cTnI were highly correlated and explained the 40.1% of the total variance, whereas CgA resulted independent and explained the 26.3% of the total variance.

CONCLUSIONS

Markers' measurements at 24h after PPCI contributed most information to the definition of patients' profile. BNP and cTnI resulted interchangeable in a MM panel for reporting about the extent of necrosis.

Apolipoprotein A-I mimetic peptide inhibits atherosclerosis by altering plasma metabolites in hypercholesterolemia

An apolipoprotein A-I mimetic peptide, D-4F, has been shown to improve vasodilation and inhibit atherosclerosis in hypercholesterolemic low-density lipoprotein receptor-null (LDLr(-/-)) mice. To study the metabolic variations of D-4F ininhibiting atherosclerosis, metabonomics, a novel system biological strategy to investigate the pathogenesis, was developed. Female LDLr(-/-) mice were fed a Western diet and injected with or without D-4F intraperitoneally. Atherosclerotic lesion formation was measured, whereas plasma metabolic profiling was obtained on the basis of ultra-high-performance liquid chromatography in tandem with time-of-flight mass spectrometry operating in both positive and negative ion modes. Data were processed by multivariate statistical analysis to graphically demonstrate metabolic changes. The partial least-squares discriminate analysis model was validated with cross-validation and permutation tests to ensure the model's reliability. D-4F significantly inhibited the formation of atherosclerosis in a time-dependent manner. The metabolic profiling was altered dramatically in hypercholesterolemic LDLr(-/-) mice, and a significant metabolic profiling change in response to D-4F treatment was observed in both positive and negative ion modes. Thirty-six significantly changed metabolites were identified as potential biomarkers. A series of phospholipid metabolites, including lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE), phosphatidylcholine (PC), phatidylethanolamine (PE), sphingomyelin (SM), and diacylglycerol (DG), particularly the long-chain LysoPC, was elevated dramatically in hypercholesterolemic LDLr(-/-) mice but reduced by D-4F in a time-dependent manner. Quantitative analysis of LysoPC, LysoPE, PC, and DG using HPLC was chosen to validate the variation of these potential biomarkers, and the results were consistent with the metabonomics findings. Our findings demonstrated that D-4F may inhibit atherosclerosis by regulating phospholipid metabolites specifically by decreasing plasma long-chain LysoPC.

Direct ultrasound-assisted methylation of fatty acids in serum for free fatty acid determinations

A method for simultaneous determination of 16 free fatty acids (FFAs) in serum is described. The method involves conversion of FFAs to fatty acid methyl esters (FAMEs) using the heat of ultrasonic waves followed by gas chromatography and mass spectrometry (GC–MS) analysis. Optimum levels of the variables affecting the yield of FAMEs were investigated. The results indicate that the optimal levels are 55 °C, 60 W, 10% H2SO4/CH3OH, and 50 min. Recoveries ranged from 85.32% to 112.11%, with a detection limit ranging from 0.03 to 0.08 μg mL–1. The linearity, using the linear correlation coefficient, was higher than 0.9914.