Metabolomics-based discrimination of patients with remitted depression from healthy controls using 1H-NMR spectroscopy.
Ontology highlight
ABSTRACT:
SUBMITTER: Hung CI
PROVIDER: S-EPMC8329159 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Identifying different species of the genus Atractylodes which are commonly used in Chinese and Japanese traditional medicine, using chromatographic approaches can be difficult. 1H NMR metabolic profiling of DNA-authenticated, archived rhizomes of the genus Atractylodes was performed for genetic and chemical evaluation. The ITS region of the nuclear rDNA was sequenced for five species, A. japonica, A. macrocephala, A. lancea, A. chinensis, and A. koreana. Our samples had nucleotide sequences as previously reported, except that part of the A. lancea cultivated in Japan had a type 5, hybrid DNA sequence. Principal component analysis (PCA) using 1H NMR spectra of extracts with two solvent systems (CD3OD, CDCl3) was performed. When CDCl3 extracts were utilized, the chemometric analysis enabled the identification and classification of Atractylodes species according to their composition of major sesquiterpene compounds. The 1H NMR spectra using CD3OD contained confounding sugar peaks. PCA removal of these peaks gave the same result as that obtained using CDCl3 and allowed species distinction. Such chemometric methods with multivariate analysis of NMR spectra will be useful for the discrimination of plant species, without specifying the index components and quantitative analysis on multi-components.
| S-EPMC8924082 | biostudies-literature
Project description:ContextThe characterization of the urinary metabolome may yield biomarkers indicative of pancreatitis.ObjectivesWe establish a non-invasive technique to compare urinary metabolic profiles in patients with acute and chronic pancreatitis to healthy controls.MethodsUrine was obtained from healthy controls (HC, n=5), inpatients with mild acute pancreatitis (AP, n=5), and outpatients with chronic pancreatitis (CP, n=5). Proton nuclear magnetic resonance spectra were obtained for each sample. Metabolites were identified and quantified in each spectrum; resulting concentrations were normalized to account for differences in dilution among samples. Kruskal-Wallis test, post-hoc Mann-Whitney U tests, and principal component analysis were performed to identify metabolites that discriminate healthy controls, acute pancreatitis, and chronic pancreatitis.ResultsSixty metabolites were identified and quantified; five were found to differ significantly (P<0.05) among the three groups. Of these, citrate and adenosine remained significant after validation by random permutation. Principal component analysis demonstrated that healthy control urine samples can be differentiated from patients with chronic pancreatitis or acute pancreatitis; chronic pancreatitis patients could not be distinguished from acute pancreatitis patients.ConclusionsThis metabolomic investigation demonstrates that this non-invasive technique offers insight into the metabolic states of pancreatitis. Although the identified metabolites cannot conclusively be defined as biomarkers of disease, future studies will validate our findings in larger patient cohorts.
| S-EPMC4500934 | biostudies-literature
Project description:With the increase in soybean trade between countries, the intentional mislabeling of the origin of soybeans has become a serious problem worldwide. In this study, metabolic profiling of soybeans from the Republic of Korea and China was performed by nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to predict the geographical origin of soybeans. The optimal orthogonal partial least squares-discriminant analysis (OPLS-DA) model was obtained using total area normalization and unit variance (UV) scaling, without applying the variable influences on projection (VIP) cut-off value, resulting in 96.9% sensitivity, 94.4% specificity, and 95.6% accuracy in the leave-one-out cross validation (LOO-CV) test for discriminating between Korean and Chinese soybeans. Soybeans from the northeastern, middle, and southern regions of China were successfully differentiated by standardized area normalization and UV scaling with a VIP cut-off value of 1.0, resulting in 100% sensitivity, 91.7%-100% specificity, and 94.4%-100% accuracy in a LOO-CV test. The methods employed in this study can be used to obtain essential information for the authentication of soybean samples from diverse geographical locations in future studies.
| S-EPMC7922469 | biostudies-literature
Project description:Enantiomers of a few new amides containing two stereogenic centers have been derived from d- and l-α-amino acids as guests for chiral recognition by 1H NMR spectroscopy. A variety of chiral amides with two or more stereogenic centers often exist in the products of catalytic asymmetric synthesis, natural products or their total synthetic products, and chiral drugs. It would be a challenging and meaningful work to explore their chiral recognition. For this purpose, a class of novel chiral bisthiourea derivatives 1-9 has been synthesized from (1S,2S)-(+)-1,2-diaminocyclohexane, d-α-amino acids, and isothiocyanates as chiral solvating agents (CSAs). CSAs 1-9 proved to afford better chiral discriminating results towards most amides with two stereogenic centers, which have been rarely studied as chiral substrates by 1H NMR spectroscopy. In particular, CSAs 7, 8 and 9, featuring 3,5-bis(trifluoromethyl)benzene residues, exhibit outstanding chiral discriminating capabilities towards all amides, providing well-separated 1H NMR signals and sufficiently large nonequivalent chemical shifts. To test their practical application in the determination of enantiomeric excess, 1H NMR spectra of chiral amides (G16) with different optical purities were measured in the presence of CSAs 7 and 8, respectively. Their ee values (up to 90%) were accurately calculated by the integration of the NH proton of the CONHPh group of G16. To better understand the chiral discriminating behavior, Job plots of (±)-G16 with CSA 7 and (±)-G17 with CSA 8 and the association constants (Ka) of (S,R)-G16 and (R,S)-G16 with CSA 7 were evaluated, respectively. In order to further reveal any underlying intermolecular hydrogen bonding interactions, theoretical calculations of the enantiomers of (S,R)-G16 and (R,S)-G16 with CSA 7 were performed by means of the hybrid density functional theory (B3LYP) with the standard basis sets of 3-21G of the Gaussian 03 program, respectively.
| S-EPMC9420356 | biostudies-literature
Project description:Sea buckthorn (Hippophaë; Elaeagnaceae) berries are widely consumed in traditional folk medicines, nutraceuticals, and as a source of food. The growing demand of sea buckthorn berries and morphological similarity of Hippophaë species leads to confusions, which might cause misidentification of plants used in natural products. Detailed information and comparison of the complete set of metabolites of different Hippophaë species are critical for their objective identification and quality control. Herein, the variation among seven species and seven subspecies of Hippophaë was studied using proton nuclear magnetic resonance (1H NMR) metabolomics combined with multivariate data analysis, and the important metabolites were quantified by quantitative 1H NMR (qNMR) method. The results showed that different Hippophaë species can be clearly discriminated and the important interspecific discriminators, including organic acids, L-quebrachitol, and carbohydrates were identified. Statistical differences were found among most of the Hippophaë species and subspecies at the content levels of the aforementioned interspecific discriminators via qNMR and one-way analysis of variance (ANOVA) test. These findings demonstrated that 1H NMR-based metabolomics is an applicable and effective approach for simultaneous metabolic profiling, species differentiation and quality assessment.
| S-EPMC5431470 | biostudies-literature
Project description:Polymorphisms in the FK506 binding protein 5 (FKBP5) gene have been shown to influence glucocorticoid receptor sensitivity, stress response regulation, and depression risk in traumatized subjects, with most consistent findings reported for the functional variant rs1360780. In the present study, we investigated whether the FKBP5 polymorphism rs1360780 and lifetime history of major depression are associated with DNA methylation and FKBP5 gene expression after psychosocial stress. A total of 116 individuals with a positive (n = 61) and negative (n = 55) lifetime history of major depression participated in the Trier Social Stress Test. We assessed plasma cortisol concentrations, FKBP5 mRNA expression, and CpG methylation of FKBP5 intron 7 in peripheral blood cells. Genotype-dependent plasma cortisol response to psychosocial stress exposure was observed in healthy controls, with the highest and longest-lasting cortisol increase in subjects with the TT genotype of the FKBP5 polymorphism rs1360780, and healthy controls carrying the T risk allele responded with a blunted FKBP5 mRNA expression after psychosocial stress. No genotype effects could be found in remitted depression. The FKBP5 rs1360780 polymorphism is associated with plasma cortisol and FKBP5 mRNA expression after psychosocial stress in healthy controls but not in remitted depression. Preliminary results of the DNA methylation analysis suggest that epigenetic modifications could be involved.
| S-EPMC4360217 | biostudies-literature
Project description:Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies.
| S-EPMC5450811 | biostudies-literature
Project description:Cell metabolism is a key determinant factor for the pluripotency and fate commitment of Stem Cells (SCs) during development, ageing, pathological onset and progression. We derived and cultured selected subpopulations of rodent fetal, postnatal, adult Neural SCs (NSCs) and postnatal glial progenitors, Olfactory Ensheathing Cells (OECs), respectively from the subventricular zone (SVZ) and the olfactory bulb (OB). Cell lysates were analyzed by proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy leading to metabolites identification and quantitation. Subsequent multivariate analysis of NMR data by Principal Component Analysis (PCA), and Partial Least Square Discriminant Analysis (PLS-DA) allowed data reduction and cluster analysis. This strategy ensures the definition of specific features in the metabolic content of phenotypically similar SCs sharing a common developmental origin. The metabolic fingerprints for selective metabolites or for the whole spectra demonstrated enhanced peculiarities among cell types. The key result of our work is a neat divergence between OECs and the remaining NSC cells. We also show that statistically significant differences for selective metabolites characterizes NSCs of different ages. Finally, the retrived metabolome in cell cultures correlates to the physiological SC features, thus allowing an integrated bioengineering approach for biologic fingerprints able to dissect the (neural) SC molecular specificities.
| S-EPMC5693937 | biostudies-literature
Project description:(1) Background: The ability to determine the age of ginseng is very important because the price of ginseng depends on the cultivation period. Since morphological observation is subjective, a new scientific and systematic method for determining the age of ginseng is required. (2) Methods: Three techniques were used for a metabolomics approach. High-resolution magic-angle-spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy was used to analyze powdered ginseng samples without extraction. Ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) and gas chromatography quadrupole time-of-fight mass spectrometry (GC-TOF/MS) were used to analyze the extracts of 4-, 5-, and 6-year-old ginseng. (3) Results: A metabolomics approach has the potential to discriminate the age of ginseng. Among the primary metabolites detected from NMR spectroscopy, the levels of fumarate and choline showed moderate prediction with an area under the curve (AUC) value of more than 0.7. As a result of UPLC-QTOF/MS-based profiling, 61 metabolites referring to the VIP (variable importance in the projection) score contributed to discriminating the age of ginseng. The results of GC×GC-TOF/MS showed clear discrimination of 4-, 5-, and 6-year-old ginseng using orthogonal partial least-squares discriminant analysis (OPLS-DA) to 100% of the discrimination rate. The results of receiver operating characteristic (ROC) analysis, 16 metabolites between 4- and 5-year-old ginseng, and 18 metabolites between 5- and 6-year-old ginseng contributed to age discrimination in all regions. (4) Conclusions: These results showed that metabolic profiling and multivariate statistical analyses can distinguish the age of ginseng. Especially, it is meaningful that ginseng samples from different areas had the same metabolites for age discrimination. In future studies, it will be necessary to identify the unknown variables and to collaboratively study with other fields the biochemistry of aging in ginseng.
| S-EPMC6651322 | biostudies-literature
Project description:The tissue metabolomic characteristics associated with endometrial cancer (EC) at different grades were studied using high resolution (400 MHz) magic angle spinning (HR-MAS) proton spectroscopy. The metabolic profiles were obtained from 64 patients (14 with grade 1 (G1), 33 with grade 2 (G2) and 17 with grade 3 (G3) tumors) and compared with the profile acquired from 10 patients with the benign disorders. OPLS-DA revealed increased valine, isoleucine, leucine, hypotaurine, serine, lysine, ethanolamine, choline and decreased creatine, creatinine, glutathione, ascorbate, glutamate, phosphoethanolamine and scyllo-inositol in all EC grades in reference to the non-transformed tissue. The increased levels of taurine was additionally detected in the G1 and G2 tumors in comparison to the control tissue, while the elevated glycine, N-acetyl compound and lactate-in the G1 and G3 tumors. The metabolic features typical for the G1 tumors are the increased dimethyl sulfone, phosphocholine, and decreased glycerophosphocholine and glutamine levels, while the decreased myo-inositol level is characteristic for the G2 and G3 tumors. The elevated 3-hydroxybutyrate, alanine and betaine levels were observed in the G3 tumors. The differences between the grade G1 and G3 malignances were mainly related to the perturbations of phosphoethanolamine and phosphocholine biosynthesis, inositol, betaine, serine and glycine metabolism. The statistical significance of the OPLS-DA modeling was also verified by an univariate analysis. HR-MAS NMR based metabolomics provides an useful insight into the metabolic reprogramming in endometrial cancer.
| S-EPMC8438077 | biostudies-literature