Free fatty acid metabolic profile and biomarkers of isolated post-challenge diabetes and type 2 diabetes mellitus based on GC-MS and multivariate statistical analysis

Isolated post-challenge diabetes (IPD, 2h-PG ≥11.1mmol/L and FPG <7.0mmol/L) is often ignored in screening for diabetes by fasting plasma glucose (FPG) levels. The aim of this study was to investigate the metabolic profiles of serum free fatty acids (FFAs) and to identify biomarkers that can be used to distinguish patients with IPD from those with type 2 diabetes mellitus (T2DM) or healthy control individuals. FFA profiles of the subjects were investigated using gas chromatography-mass spectrometry (GC-MS). Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used for classification and prediction among the three groups. The predictive correct rates were 92.86% for IPD and healthy control individuals and 90.70% for T2DM and healthy control individuals, indicating that PLS-DA could satisfactorily distinguish IPD individuals from healthy controls and those with T2DM. Finally, palmitic acid, stearic acid, oleic acid, linoleic acid and α-linolenic acid were identified as potential biomarkers for distinguishing IPD from healthy control and T2DM individuals. These potential biomarkers might be helpful for diagnosis and characterization of diabetes.

Fasting serum lipid and dehydroepiandrosterone sulfate as important metabolites for detecting isolated postchallenge diabetes: serum metabolomics via ultra-high-performance LC-MS

BACKGROUND

Isolated postchallenge diabetes (IPD), a subtype of type 2 diabetes mellitus (T2DM) defined as 2-h postprandial plasma glucose ≥ 200 mg/dL (≥ 11.1 mmol/L) and fasting plasma glucose (FPG) <108 mg/dL (<6.0 mmol/L), is often overlooked during screening for diabetes on the basis of FPG concentrations. A key challenge is early identification of IPD by the use of fasting serum, which is critical for large-scale diabetes screening.

METHODS

We applied a nontargeted metabolomic approach using ultra-high-performance liquid chromatography-quadrupole TOF-mass spectrometry (UPLC-QTOF-MS) to analyze serum samples from 51 patients with IPD, 52 with newly diagnosed T2DM, and 49 healthy individuals. We processed metabolite profiles by multivariate analysis to identify potential metabolites, which were further confirmed by tandem MS (MS/MS). We also used GC-MS and ELISA methods to detect potentially important metabolites. A number of independent samples were selected to validate the identified candidates.

RESULTS

We selected 15 metabolites with a view to distinguishing patients with IPD, whereas 11 were identified with an authentic standard. The selected metabolites included linoleic acid, oleic acid, phospholipids, and dehydroepiandrosterone sulfate (DHEA-S). In IPD samples, significantly higher linoleic and oleic acid (P < 0.001) and lower DHEA-S (P < 0.001) concentrations were observed, compared with controls. The area under the curve from a combination of linoleic acid, oleic acid, and DHEA-S in the validation study was 0.849 for the IPD group.

CONCLUSIONS

The current study provides useful information to bridge the gaps in our understanding of the metabolic alterations associated with IPD and might facilitate the characterization of patients with IPD by the use of fasting serum.

Targeted metabolomic analysis reveals the association between the postprandial change in palmitic acid, branched-chain amino acids and insulin resistance in young obese subjects

Obesity is the result of a positive energy balance and often leads to difficulties in maintaining normal postprandial metabolism. The changes in postprandial metabolites after an oral glucose tolerance test (OGTT) in young obese Chinese men are unclear. In this work, the aim is to investigate the complex metabolic alterations in obesity provoked by an OGTT using targeted metabolomics. We used gas chromatography-mass spectrometry and ultra high performance liquid chromatography-triple quadrupole mass spectrometry to analyze serum fatty acids, amino acids and biogenic amines profiles from 15 control and 15 obese subjects at 0, 30, 60, 90 and 120 min during an OGTT. Metabolite profiles from 30 obese subjects as independent samples were detected in order to validate the change of metabolites. There were the decreased levels of fatty acid, amino acids and biogenic amines after OGTT in obesity. At 120 min, percent change of 20 metabolites in obesity has statistical significance when comparing with the controls. The obese parameters was positively associated with changes in arginine and histidine (P<0.05) and the postprandial change in palmitic acid (PA), branched-chain amino acids (BCAAs) and phenylalanine between 1 and 120 min were positively associated with fasting insulin and HOMA-IR (all P<0.05) in the obese group. The postprandial metabolite of PA and BCAAs may play important role in the development and onset of insulin resistance in obesity. Our findings offer new insights in the complex physiological regulation of the metabolism during an OGTT in obesity.

Postprandial Differences in the Amino Acid and Biogenic Amines Profiles of Impaired Fasting Glucose Individuals after Intake of Highland Barley

The aim of this study was to measure the postprandial changes in amino acid and biogenic amine profiles in individuals with impaired fasting glucose (IFG) and to investigate the changes of postprandial amino acid and biogenic amine profiles after a meal of highland barley (HB). Firstly, 50 IFG and 50 healthy individuals were recruited for the measurement of 2 h postprandial changes of amino acid and biogenic amine profiles after a glucose load. Secondly, IFG individuals received three different loads: Glucose (GL), white rice (WR) and HB. Amino acid and biogenic amine profiles, glucose and insulin were assayed at time zero and 30, 60, 90 and 120 min after the test load. The results showed fasting and postprandial amino acid and biogenic amine profiles were different between the IFG group and the controls. The level of most amino acids and their metabolites decreased after an oral glucose tolerance test, while the postprandial level of γ-aminobutyric acid (GABA) increased significantly in IFG individuals. After three different test loads, the area under the curve for glucose, insulin, lysine and GABA after a HB load decreased significantly compared to GL and WR loads. Furthermore, the postprandial changes in the level of GABA between time zero and 120 min during a HB load were associated positively with 2 h glucose and fasting insulin secretion in the IFG individuals. Thus, the HB load produced low postprandial glucose and insulin responses, which induced changes in amino acid and biogenic amine profiles and improved insulin sensitivity.

Metabolomics strategy assisted by transcriptomics analysis to identify biomarkers associated with schizophrenia

BACKGROUND

Metabolomics strategy was perform to identify the novel serum biomarkers linked to schizophrenia with the assistance of transcriptomics analysis.

METHODS

Two analytical platforms, UPLC-Q-TOF MS/MS and 1H NMR, were used to acquire the serum fingerprinting profiles from a total of 112 participants (57 healthy controls and 55 schizophrenia patients). The differential metabolites were primarily selected after statistical analyses. Meanwhile, GSE17612 dataset downloaded from GEO database was implemented WGCNA analysis to discover crucial genes and corresponding biological processes. Based on metabolomics analysis, the metabolic distinctions were explored under the aid of transcriptomics. Then using Boruta algorithm identified the biomarkers, and LASSO regression analysis and Random Forest algorithm were used to evaluate the performance of the diagnostic model constructed by biomarkers selected.

RESULTS

A total of four metabolites (α-CEHC, neuraminic acid, glyceraldehyde and asparagine) were selected as the biomarkers to establish diagnosis model. The performance of this model showed a higher accuracy rate to distinguish schizophrenia patients from healthy controls (area under the receive operating characteristic curve, 0.992; precision recall curve, 1.000, the mean accuracy of random forest algorithm, 95.00%).

CONCLUSIONS

A four-biomarker model (α-CEHC, neuraminic acid, glyceraldehyde and asparagine) seems to be a good model for diagnosing schizophrenia patients. It might be helpful to guide the future studies on permitting early intervention designed to prevent disease progression.

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.

Serum untargeted metabolomics delineates the metabolic status in different subtypes of non-alcoholic fatty liver disease

AIMS

The aim of this study was to identify novel serum metabolites associated with non-alcoholic fatty liver disease (NAFLD), and to explore the metabolic discrepancies between Lean-NAFLD and Obese-NAFLD.

METHODS

Serum samples from patients with NAFLD (n = 161) and healthy participants (n = 149) were collected, and metabolites were analyzed with UPLC-Q-TOF MS/MS. Subgroup analyses were performed to explore the metabolic differences among Lean-NAFLD, Obese-NAFLD and healthy controls RESULTS: A total of 24 differentially present metabolites were found between patients with NAFLD and healthy controls. Marked metabolic pathway differences were observed among the NAFLD subtypes, including in fatty acid and amino acid metabolism. Ultimately, five metabolites (prasterone, indoxylsulfuric acid, sebacic acid, arachidonic acid and pregnenolone sulfate) were used to establish a diagnostic model to distinguish patients with NAFLD regardless of Lean- or Obese-NAFLD type.

CONCLUSIONS

This study suggested that significant metabolic differences existed among subtypes of NAFLD, and our model might be useful to distinguish patients with NAFLD. These findings may lay a foundation for the detection and treatment of NAFLD subtypes.

Integration of metabolomics and proteomics to highlight altered neural development related pathways in the adult offspring after maternal folic acid supplement

BACKGROUND & AIMS

Maternal folic acid (FA) supplement (FolS) programs the early development of an offspring. The onset of complex diseases at a later stage of life has been evidently linked with maternal FA ingestion. However, little is known regarding the underlying molecule fingerprints of the offspring. Here, we analyze the influence of maternal FolS on the metabolism of the adult offspring rats using the integrated metabolomics-proteomics.

METHODS

Twenty pregnant female rats were randomly assigned to a FA supplement (FolS group) or control group which were fed AIN93G diet with 2 or 5 mg/kg FA, respectively. The blood samples from the offspring at 0, 3 and 7 weeks after birth were collected. The brain samples were obtained from the offspring at 7 weeks after birth. Serum and brain metabolite profiles were performed by UPLC-MS/MS and the brain proteomics analysis was obtained using iTRAQ-based quantitative proteomics.

RESULTS

The metabolic change of the offspring for the maternal FA supplement is characterized by the phospholipids, fatty acid and amino acids, which are involved in linoleic acid, docosahexaenoic acid, glycerophosphocholine, lysophosphatidylcholine, tryptophan, glycine, arachidonic acid, γ-aminobutyric acid, and so on. Using iTRAQ-based quantitative proteomics analysis, 51 differential proteins in the brain are identified, which provides valuable insight into the underlying mechanisms of the offspring after the maternal FolS. These results demonstrate neural development related metabolites and proteins, such as docosahexaenoic acid, glycine, tryptophan, γ-aminobutyric acid, dopaminergic synapse related proteins including G protein, PPP1R1B and CAMK2G, are significantly altered, which suggests that the active neural conduction occurs in the offspring after maternal FA supplement. The behavioral testing demonstrates that the high level of memory is observed in rats with FA supplement.

CONCLUSIONS

We conceive that the alterations of metabolites and protein in the offspring are associated with the maternal FA supplement and these alterations are involved in the neural development, although such animal data are limited in their ability to mimic metabolic outcomes in humans.

Metabonomic analysis of urine from rats after low-dose exposure to 3-chloro-1,2-propanediol using UPLC-MS

To study the toxic effect of chronic exposure to 3-chloro-1,2-propanediol (3-MCPD) at low doses, a metabonomics approach based on ultrahigh-performance liquid chromatography and quadruple time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was performed. Two different doses of 3-MCPD (1.1 and 5.5mg/kg bw/d) were administered to Wistar rats for 120 days (1.1mg/kg bw/d: lowest observed adverse effect level [LOAEL]). The metabolite profiles and biochemical parameters were obtained at five time points after treatment. For the 3-MCPD-treated groups, a significant change in urinary N-acetyl-β-d-glucosaminidase and β-d-galactosidase was detected on day 90, while some biomarkers based on the metabonomics, such as N-acetylneuraminic acid, N-acetyl-l-tyrosine, and gulonic acid, were detected on day 30. These results suggest that these biomarkers changed more sensitively and earlier than conventional biochemical parameters and were thus considered early and sensitive biomarkers of exposure to 3-MCPD; these biomarkers provide more information on toxicity than conventional biochemical parameters. These results might be helpful to investigate the toxic mechanisms of 3-MCPD and provide a scientific basis for assessing the effect of chronic exposure to low-dose 3-MCPD on human health.

An ultrasonic assisted extraction procedure to free fatty acids from the liver samples of mice

A procedure was evaluated for the extraction of 16 free fatty acids (FFAs) from liver. Ultrasonic energy was used for the extraction and the variables affecting the extraction efficiency were investigated. The best conditions for extraction were: 2 mL isopropanol-n-hexane (3:2, v/v), 20 min and 80 w. Recoveries ranging from 87.00 to 120.00% were obtained under the optimum conditions, and the linearity as correlation coefficient was higher than 0.9914. Analytical results for the 16 FFAs in the same liver sample, analyzed by ultrasound-assisted and conventional extraction, showed acceptable agreement, thus suggesting the possibility of using ultrasound-assisted extraction instead of the conventional procedure. Moreover, the ultrasound-assisted extraction was successfully applied to the determination of FFAs in the liver of mice with hyperlipidemia and normal mice.

Decreasing high postprandial stearic acid in impaired fasting glucose by dietary regulation

BACKGROUND/OBJECTIVES

The objective of this study was to determine the postprandial change in free fatty acid (FFA) profiles in subjects with impaired fasting glucose (IFG), and to evaluate the effect of low glycemic index (GI) load on postprandial FFA profiles and inflammation.

SUBJECTS/METHODS

First, 50 IFG and 50 healthy subjects were recruited; and 2 -h postprandial changes in FFA profiles were determined. Second, the 50 IFG subjects then received three different loads: glucose load (GL), high glycemic index (HGI) load and low glycemic index (LGI) load, respectively. FFA profile, glucose, insulin, glucagon-like peptide 1 (GLP-1) and inflammatory biomarkers were assayed at 0, 30, 60, 90 and 120 min.

RESULTS

Postprandial stearic acid (C18:0) increased compared with baseline in all subjects, whereas the change in postprandial C18:0 was more marked in IFG subjects than in healthy subjects. Compared with subjects who received the GL and HGI load, the area under the curve for insulin, GLP-1, C18:0 and tumor necrosis factor-alpha significantly decreased and adiponectin increased in subjects who received the LGI load.

CONCLUSIONS

The rise in postprandial C18:0 in IFG subjects was inhibited by LGI load.

[Determination of serum vitamin B1 and B2 with HPLC]

OBJECTIVE

To develop a HPLC method for the determination of serum vitamin B1 (VB1) and vitamin B2 (VB2) simultaneously.

METHODS

Serum samples were pretreated at ambient temperature on a C18 reversed phase chromatographic column, methanol plus phosphate buffer was used for mobile phase, vitamin B1 and B2 contents of serum samples eluted from a Sep-park C18 column were detected with a photodiode array detector. The influences of retention time, the volume and the proportion of eluent on the recovery of samples were investigated.

RESULTS

Recoveries were ranged from 82.67 to 96.89%. The coefficient of variation was < 10%. The linearity and correlation coefficient was 0.9985 and 0.9995, respectively. The contents of serum VB1 and VB2 in obese people were lower than those in healthy controls.

CONCLUSION

A HPLC method of determining serum VB1 and VB2 was established. Serum VB1 and VB2 level in obese people was low.