Metabolic Syndrome Plasma Lipidomics
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Blood
DISEASE(S): Metabolic Syndrome
PROVIDER: ST000663 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
Dataset's files
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Project description:ObjectiveTo identify plasma lipid characteristics associated with premetabolic syndrome (pre-MetS) and metabolic syndrome (MetS) and provide biomarkers through machine learning methods.MethodsPlasma lipidomics profiling was conducted using samples from healthy individuals, pre-MetS patients, and MetS patients. Orthogonal partial least squares-discriminant analysis (OPLS-DA) models were employed to identify dysregulated lipids in the comparative groups. Biomarkers were selected using support vector machine recursive feature elimination (SVM-RFE), random forest (rf), and least absolute shrinkage and selection operator (LASSO) regression, and the performance of two biomarker panels was compared across five machine learning models.ResultsIn the OPLS-DA models, 50 and 89 lipid metabolites were associated with pre-MetS and MetS patients, respectively. Further machine learning identified two sets of plasma metabolites composed of PS(38:3), DG(16:0/18:1), and TG(16:0/14:1/22:6), TG(16:0/18:2/20:4), and TG(14:0/18:2/18:3), which were used as biomarkers for the pre-MetS and MetS discrimination models in this study.ConclusionIn the initial lipidomics analysis of pre-MetS and MetS, we identified relevant lipid features primarily linked to insulin resistance in key biochemical pathways. Biomarker panels composed of lipidomics components can reflect metabolic changes across different stages of MetS, offering valuable insights for the differential diagnosis of pre-MetS and MetS.
| S-EPMC10979736 | biostudies-literature
Project description:BackgroundKallmann syndrome (KS) is a rare developmental disorder. Our previous metabolomics work showed substantial changes in linoleic acid and glycerophospholipid metabolism in KS. Here, we performed targeted lipidomics to further identify the differential lipid species in KS.MethodsTwenty-one patients with KS (treatment group) and twenty-two age-matched healthy controls (HC, control group) were enrolled. Seminal plasma samples and medical records were collected. Targeted lipidomics analysis of these samples was performed using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS).ResultsLipidomics profiling of patients with KS and the HCs showed clear separation in the orthogonal projections to latent structures-discriminant analysis (OPLS-DA). There were many differential lipids identified, with the main differential lipid species being triacylglycerols (TAGs), phosphatidylcholines (PCs) and phosphatidylethanolamine (PE).ConclusionsThe lipidomics profile of patients with KS changed. It was also determined that TAGs, PCs and PE are promising biomarkers for KS diagnosis. To our knowledge, this is the first report to analyze lipidomics in men with Kallmann syndrome.
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Project description:MicroRNAs are important negative regulators of protein coding gene expression, and have been studied intensively over the last few years. To this purpose, different measurement platforms to determine their RNA abundance levels in biological samples have been developed. In this study, we have systematically compared 12 commercially available microRNA expression platforms by measuring an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from homologous microRNA family members. We developed novel quality metrics in order to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, quantitative performance, and specificity. The results indicate that each method has its strengths and weaknesses, which helps guiding informed selection of a quantitative microRNA gene expression platform in function of particular study goals.
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Project description:Comparison between miRNA expression in plasma of women with and without metabolic syndrome. We used microarrays to compare the composition of miRNAs in plasma of participants with and without metabolic syndrome (ATP III criteria).
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Project description:BackgroundAbnormal lipid metabolism is common in patients with primary biliary cholangitis (PBC). PBC and Sjögren's syndrome (SS) frequently coexist in clinical practice; however, the lipid characteristics of both diseases are unknown. Therefore, we aimed to analyze the plasma lipid profiles of both diseases.MethodsPlasma samples from 60 PBC patients, 30 SS patients, and 30 healthy controls (HC) were collected, and untargeted lipidomics was performed using ultrahigh-performance liquid chromatography high-resolution mass spectrometry. Potential lipid biomarkers were screened through an orthogonal projection to latent structure discriminant analysis and further evaluated using receiver operating characteristic (ROC) analysis.ResultsA total of 115 lipids were differentially upregulated in PBC patients compared with HC. Seventeen lipids were positively associated with the disease activity of PBC, and ROC analysis showed that all of these lipids could differentiate between ursodeoxycholic acid (UDCA) responders and UDCA non-responders. The top six lipids based on the area under the curve (AUC) values were glycerophosphocholine (PC) (16:0/16:0), PC (18:1/18:1), PC (42:2), PC (16:0/18:1), PC (17:1/14:0), and PC (15:0/18:1). In comparison with SS, 44 lipids were found to be differentially upregulated in PBC. Additionally, eight lipids were found to have a good diagnostic performance of PBC because of the AUC values of more than 0.9 when identified from SS and HC groups, which were lysophosphatidylcholines (LysoPC) (16:1), PC (16:0/16:0), PC (16:0/16:1), PC (16:1/20:4), PC (18:0/20:3), PC (18:1/20:2), PC (20:0/22:5), and PC (20:1/22:5).ConclusionOur study revealed differentially expressed lipid signatures in PBC compared with HC and SS. PC is the main lipid species associated with disease activity and the UDCA response in patients with PBC.
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Project description:Cannabis use disorder affects up to 42% of individuals with schizophrenia, correlating with earlier onset, increased positive symptoms, and more frequent hospitalizations. This study employed an untargeted lipidomics approach to identify biomarkers in plasma samples from subjects with schizophrenia, cannabis use disorder, or both (dual diagnosis), aiming to elucidate the metabolic underpinnings of cannabis abuse and schizophrenia development. The use of liquid chromatography-high resolution mass spectrometry enabled the annotation of 119 metabolites, with the highest identification confidence level achieved for 16 compounds. Notably, a marked reduction in acylcarnitines, including octanoylcarnitine and decanoylcarnitine, was observed across all patient groups compared to controls. In cannabis use disorder patients, N-acyl amino acids (NAAAs), particularly N-palmitoyl threonine and N-palmitoyl serine, showed a strong downregulation, a pattern also seen in schizophrenia and dual diagnosis patients. Conversely, elevated levels of 7-dehydrodesmosterol were detected in schizophrenia and dual diagnosis patients relative to controls. These findings suggest a potential link between metabolic disruptions and the pathophysiology of both disorders. The untargeted lipidomics approach offers a powerful tool to identify novel biomarkers, enhancing our understanding of the biological relationship between cannabis abuse and schizophrenia, and paving the way for future therapeutic strategies targeting metabolic pathways in these conditions.
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Project description:Plasma of metabolic syndrome patients will be checked for lipidomic profiles
2018-08-02 | MSV000082716 | GNPS
Project description:MicroRNAs in plasma in metabolic syndrome.
| PRJNA1001303 | ENA
Project description:Background Pituitary stalk interruption syndrome (PSIS) is a rare disease caused by congenital pituitary anatomical defects. The underlying mechanisms remain unclear, and the diagnosis is difficult. Here, integrated metabolomics and lipidomics profiling were conducted to study the pathogenesis of PSIS. Methods Twenty-one patients with PSIS (BD group) and twenty-three healthy controls (HC group) were enrolled. Basal information and seminal plasma samples were collected. Untargeted metabolomics and lipidomics analyses were performed using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS). Results The metabolomics and lipidomics profiles of patients with PSIS changed. The prolactin signaling pathway and biosynthesis of amino acids were the main differentially modified metabolic pathways. The main differentially modified metabolites were triacylglycerols (TGs), phosphatidylethanolamine (PE), sphingomyelin (SM), ceramide (Cer) and phosphatidylcholines (PCs). Pregnenolones and L-saccharopine could achieve a diagnosis of PSIS. Conclusions Pregnenolones and L-saccharopine are potential biomarkers for a PSIS diagnosis. Supplementary Information The online version contains supplementary material available at 10.1186/s13023-022-02408-4.
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Project description:Cancer-associated fibroblasts (CAFs) have been recognized as important contributors to cancer development and progression. However, opposing evidence has been published whether CAFs, in addition to epigenetic, also undergo somatic genetic alterations and whether these changes contribute to carcinogenesis and tumour progression. We combined multiparameter DNA flow cytometry, flow-sorting and 6K SNP-arrays to study DNA aneuploidy, % S-phase, loss of heterozygosity (LOH) and copy number alterations (CNAs) to study somatic genetic alterations in cervical cancer-associated stromal cell fractions (n = 58) from formalin-fixed, paraffin-embedded (FFPE) samples. Tissue sections were examined for the presence of CAFs. Microsatellite analysis was used to study LOH. By flow cytometry we found no proof for DNA aneuploidy in the vimentin-positive stromal cell fractions of any samples (CV G0G1 population 3.7% +/- 1.2; S-phase 1.4% +/- 1.8). The genotype concordance between the stromal cells and the paired normal endometrium samples was > 99.9%. No evidence for CNAs or LOH was found in the stromal cell fractions. In contrast, high frequencies of DNA content abnormalities (43/57), a significant higher S-phase (14.6% +/- 8.5)(p = 0.0001) and substantial numbers of CNAs and LOH were identified in the keratin-positive epithelial cell fractions (CV G0G1 population 4.1% +/- 1.0). Smooth muscle actin and vimentin immunohistochemistry verified the presence of CAFs in all cases tested. LOH hot-spots on chromosomes 3p, 4p and 6p were confirmed by microsatellite analysis but the stromal cell fractions showed retention of heterozygosity only. From our study we conclude that stromal cell fractions from cervical carcinomas are DNA diploid, have a genotype undistinguishable from patient-matched normal tissue and are genetically stable. Stromal genetic changes do not seem to play a role during cervical carcinogenesis and progression. In addition, the stromal cell fraction of cervical carcinomas can be used as reference allowing large retrospective studies of archival FFPE tissues for which no normal reference tissue is available. Paired experiment, Endometrial (non-tumor) cells vs stromal cells from cervical tumors. Biological replicates: 58 patients. From 5 tumors also the tumor fraction was profiled.
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