scholarly journals Sebum: a window into dysregulation of lipid metabolism in Parkinson’s disease

2020 ◽  
Author(s):  
Eleanor Sinclair ◽  
Drupad Trivedi ◽  
Depanjan Sarkar ◽  
Caitlin Walton-Doyle ◽  
Joy Milne ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
Acid Metabolism ◽  
Enrichment Analysis ◽  
Arachidonic Acid Metabolism ◽  
Sphingolipid Metabolism ◽  
Pathway Enrichment Analysis ◽  
Liquid Chromatography Mass Spectrometry ◽  
Diagnostic Biomarkers ◽  
Pathway Enrichment ◽  
Drug Naïve

<p>A metabolomics profiling approach was conducted to identify diagnostic biomarkers of PD from sebum, a non-invasively available biofluid. In this study, we used liquid chromatography-mass spectrometry (LC-MS) to analyse 274 samples from participants (80 drug naïve PD, 138 medicated PD and 56 well matched control subjects) and detected metabolites that could predict PD phenotype. Partial least squares-discriminant analysis (PLS-DA) models based on this sebum metabolome had correct classification rates of 70.4% and 69.7% to distinguish between drug naïve PD and medicated PD from control, respectively. Variable importance in projection (VIP) scores indicate compounds with significance belonged to sphingolipid, triacylglycerol and fatty acid/ester lipid classes. Pathway enrichment analysis showed alterations in lipid metabolism and mitochondrial dysfunction <i>viz.</i> the carnitine shuttle, sphingolipid metabolism and arachidonic acid metabolism. This study unveiled novel diagnostic sebum-based biomarkers for PD, and provides insight towards our current understanding of the pathogenesis of PD.</p>

Sebum: a window into dysregulation of lipid metabolism in Parkinson’s disease

2020 ◽  
Author(s):  
Eleanor Sinclair ◽  
Drupad Trivedi ◽  
Depanjan Sarkar ◽  
Caitlin Walton-Doyle ◽  
Joy Milne ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
Acid Metabolism ◽  
Enrichment Analysis ◽  
Arachidonic Acid Metabolism ◽  
Sphingolipid Metabolism ◽  
Pathway Enrichment Analysis ◽  
Liquid Chromatography Mass Spectrometry ◽  
Diagnostic Biomarkers ◽  
Pathway Enrichment ◽  
Drug Naïve

<p>A metabolomics profiling approach was conducted to identify diagnostic biomarkers of PD from sebum, a non-invasively available biofluid. In this study, we used liquid chromatography-mass spectrometry (LC-MS) to analyse 274 samples from participants (80 drug naïve PD, 138 medicated PD and 56 well matched control subjects) and detected metabolites that could predict PD phenotype. Partial least squares-discriminant analysis (PLS-DA) models based on this sebum metabolome had correct classification rates of 70.4% and 69.7% to distinguish between drug naïve PD and medicated PD from control, respectively. Variable importance in projection (VIP) scores indicate compounds with significance belonged to sphingolipid, triacylglycerol and fatty acid/ester lipid classes. Pathway enrichment analysis showed alterations in lipid metabolism and mitochondrial dysfunction <i>viz.</i> the carnitine shuttle, sphingolipid metabolism and arachidonic acid metabolism. This study unveiled novel diagnostic sebum-based biomarkers for PD, and provides insight towards our current understanding of the pathogenesis of PD.</p>

scholarly journals Sebum: A Window into Dysregulation of Mitochondrial Metabolism in Parkinson’s Disease

2020 ◽  
Author(s):  
Eleanor Sinclair ◽  
Drupad Trivedi ◽  
Depanjan Sarkar ◽  
Caitlin Walton-Doyle ◽  
Joy Milne ◽  
...  
Keyword(s):  
Acid Metabolism ◽  
Matched Control ◽  
Enrichment Analysis ◽  
Arachidonic Acid Metabolism ◽  
Sphingolipid Metabolism ◽  
Pathway Enrichment Analysis ◽  
Liquid Chromatography Mass Spectrometry ◽  
Diagnostic Biomarkers ◽  
Pathway Enrichment ◽  
Drug Naïve

<p>A metabolomics profiling approach was conducted to identify diagnostic biomarkers of PD from sebum, a non-invasively available biofluid. In this study, we used liquid chromatography-mass spectrometry (LC-MS) to analyse 274 samples from participants (80 drug naïve PD, 138 medicated PD and 56 well matched control subjects) and detected metabolites that could predict PD phenotype. Partial least squares-discriminant analysis (PLS-DA) models based on this sebum metabolome had correct classification rates of 70.4% and 69.7% to distinguish between drug naïve PD and medicated PD from control, respectively. Variable importance in projection (VIP) scores indicate compounds with significance belonged to sphingolipid, triacylglycerol and fatty acid/ester lipid classes. Pathway enrichment analysis showed alterations in lipid metabolism and mitochondrial dysfunction <i>viz.</i> the carnitine shuttle, sphingolipid metabolism and arachidonic acid metabolism. This study unveiled novel diagnostic sebum-based biomarkers for PD, and provides insight towards our current understanding of the pathogenesis of PD.</p>

scholarly journals Metabolomics of sebum reveals lipid dysregulation in Parkinson’s disease

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Eleanor Sinclair ◽  
Drupad K. Trivedi ◽  
Depanjan Sarkar ◽  
Caitlin Walton-Doyle ◽  
Joy Milne ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Fatty Acid Biosynthesis ◽  
Neurodegenerative Disorder ◽  
Enrichment Analysis ◽  
Arachidonic Acid Metabolism ◽  
Sphingolipid Metabolism ◽  
Pathway Enrichment Analysis ◽  
Neuronal Populations ◽  
Drug Naïve

AbstractParkinson’s disease (PD) is a progressive neurodegenerative disorder, which is characterised by degeneration of distinct neuronal populations, including dopaminergic neurons of the substantia nigra. Here, we use a metabolomics profiling approach to identify changes to lipids in PD observed in sebum, a non-invasively available biofluid. We used liquid chromatography-mass spectrometry (LC-MS) to analyse 274 samples from participants (80 drug naïve PD, 138 medicated PD and 56 well matched control subjects) and detected metabolites that could predict PD phenotype. Pathway enrichment analysis shows alterations in lipid metabolism related to the carnitine shuttle, sphingolipid metabolism, arachidonic acid metabolism and fatty acid biosynthesis. This study shows sebum can be used to identify potential biomarkers for PD.

scholarly journals Comprehensive Circulatory Metabolomics in ME/CFS Reveals Disrupted Metabolism of Acyl Lipids and Steroids

Metabolites ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 34 ◽  
Author(s):  
Arnaud Germain ◽  
Dinesh K. Barupal ◽  
Susan M. Levine ◽  
Maureen R. Hanson
Keyword(s):  
Metabolic Pathways ◽  
Acid Metabolism ◽  
Enrichment Analysis ◽  
Chronic Fatigue ◽  
Organ System ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Fatigue Syndrome ◽  
Organ Systems ◽  
Acyl Lipids

The latest worldwide prevalence rate projects that over 65 million patients suffer from myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), an illness with known effects on the functioning of the immune and nervous systems. We performed an extensive metabolomics analysis on the plasma of 52 female subjects, equally sampled between controls and ME/CFS patients, which delivered data for about 1750 blood compounds spanning 20 super-pathways, subdivided into 113 sub-pathways. Statistical analysis combined with pathway enrichment analysis points to a few disrupted metabolic pathways containing many unexplored compounds. The most intriguing finding concerns acyl cholines, belonging to the fatty acid metabolism sub-pathway of lipids, for which all compounds are consistently reduced in two distinct ME/CFS patient cohorts. We compiled the extremely limited knowledge about these compounds and regard them as promising in the quest to explain many of the ME/CFS symptoms. Another class of lipids with far-reaching activity on virtually all organ systems are steroids; androgenic, progestin, and corticosteroids are broadly reduced in our patient cohort. We also report on lower dipeptides and elevated sphingolipids abundance in patients compared to controls. Disturbances in the metabolism of many of these molecules can be linked to the profound organ system symptoms endured by ME/CFS patients.

scholarly journals Mechanism of Curcuma wenyujin Rhizoma on Acute Blood Stasis in Rats Based on a UPLC-Q/TOF-MS Metabolomics and Network Approach

Molecules ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 82 ◽  
Author(s):  
Min Hao ◽  
De Ji ◽  
Lin Li ◽  
Lianlin Su ◽  
Wei Gu ◽  
...  
Keyword(s):  
Arachidonic Acid ◽  
Lipid Metabolism ◽  
Linoleic Acid ◽  
Acid Metabolism ◽  
Blood Stasis ◽  
Arachidonic Acid Metabolism ◽  
Sphingolipid Metabolism ◽  
Network Pharmacology ◽  
Therapeutic Mechanism ◽  
Linoleic Acid Metabolism

Rhizome of Curcuma wenyujin, which is called EZhu in China, is a traditional Chinese medicine used to treat blood stasis for many years. However, the underlying mechanism of EZhu is not clear at present. In this study, plasma metabolomics combined with network pharmacology were used to elucidate the therapeutic mechanism of EZhu in blood stasis from a metabolic perspective. The results showed that 26 potential metabolite markers of acute blood stasis were screened, and the levels were all reversed to different degrees by EZhu preadministration. Metabolic pathway analysis showed that the improvement of blood stasis by Curcuma wenyujin rhizome was mainly related to lipid metabolism (linoleic acid metabolism, ether lipid metabolism, sphingolipid metabolism, glycerophospholipid metabolism, and arachidonic acid metabolism) and amino acid metabolisms (tryptophan metabolism, lysine degradation). The component-target-pathway network showed that 68 target proteins were associated with 21 chemical components in EZhu. Five metabolic pathways of the network, including linoleic acid metabolism, sphingolipid metabolism, glycerolipid metabolism, arachidonic acid metabolism, and steroid hormone biosynthesis, were consistent with plasma metabolomics results. In conclusion, plasma metabolomics combined with network pharmacology can be helpful to clarify the mechanism of EZhu in improving blood stasis and to provide a literature basis for further research on the therapeutic mechanism of EZhu in clinical practice.

A Method of Pathway Enrichment Analysis Based Gene Expression Variability

2013 ◽  
Vol 40 (12) ◽  
pp. 1256
Author(s):  
XiaoDong JIA ◽  
XiuJie CHEN ◽  
Xin WU ◽  
JianKai XU ◽  
FuJian TAN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Variability ◽  
Pathway Enrichment

Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

2019 ◽  
Vol 22 (6) ◽  
pp. 411-420 ◽  
Author(s):  
Xian-Jun Wu ◽  
Xin-Bin Zhou ◽  
Chen Chen ◽  
Wei Mao
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Pathway Enrichment ◽  
Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

scholarly journals Signature RNAS and related regulatory roles in type 1 diabetes mellitus based on competing endogenous RNA regulatory network analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qinghong Shi ◽  
Hanxin Yao
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Network Analysis ◽  
Type 1 Diabetes Mellitus ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Competing Endogenous Rna ◽  
Pathway Enrichment

Abstract Background Our study aimed to investigate signature RNAs and their potential roles in type 1 diabetes mellitus (T1DM) using a competing endogenous RNA regulatory network analysis. Methods Expression profiles of GSE55100, deposited from peripheral blood mononuclear cells of 12 T1DM patients and 10 normal controls, were downloaded from the Gene Expression Omnibus to uncover differentially expressed long non-coding RNAs (lncRNAs), mRNAs, and microRNAs (miRNAs). The ceRNA regulatory network was constructed, then functional and pathway enrichment analysis was conducted. AT1DM-related ceRNA regulatory network was established based on the Human microRNA Disease Database to carry out pathway enrichment analysis. Meanwhile, the T1DM-related pathways were retrieved from the Comparative Toxicogenomics Database (CTD). Results In total, 847 mRNAs, 41 lncRNAs, and 38 miRNAs were significantly differentially expressed. The ceRNA regulatory network consisted of 12 lncRNAs, 10 miRNAs, and 24 mRNAs. Two miRNAs (hsa-miR-181a and hsa-miR-1275) were screened as T1DM-related miRNAs to build the T1DM-related ceRNA regulatory network, in which genes were considerably enriched in seven pathways. Moreover, three overlapping pathways, including the phosphatidylinositol signaling system (involving PIP4K2A, INPP4A, PIP4K2C, and CALM1); dopaminergic synapse (involving CALM1 and PPP2R5C); and the insulin signaling pathway (involving CBLB and CALM1) were revealed by comparing with T1DM-related pathways in the CTD, which involved four lncRNAs (LINC01278, TRG-AS1, MIAT, and GAS5-AS1). Conclusion The identified signature RNAs may serve as important regulators in the pathogenesis of T1DM.

Identification of novel cardiovascular disease associated metabolites using untargeted metabolomics

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shams Tabrez ◽  
Mohammed Razeeth Shait Mohammed ◽  
Nasimudeen R. Jabir ◽  
Mohammad Imran Khan
Keyword(s):  
Cardiovascular Disease ◽  
Metabolic Pathways ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Healthy Individuals ◽  
Great Opportunity ◽  
Pathway Enrichment ◽  
Pathophysiological Role ◽  
The World ◽  
Metabolomic Approach

Abstract Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality around the world. Early diagnosis of CVD could provide the opportunity for sensible management and better clinical outcome along with the prevention of further progression of the disease. In the current study, we used an untargeted metabolomic approach to identify possible metabolite(s) that associate well with the CVD and could serve either as therapeutic target or disease-associated metabolite. We identified 26 rationally adjusted unique metabolites that were differentially present in the serum of CVD patients compared with healthy individuals, among them 15 were found to be statistically significant. Out of these metabolites, we identified some novel metabolites like UDP-l-rhamnose and N1-acetylspermidine that have not been reported to be linked with CVD directly. Further, we also found that some metabolites like ethanolamide, solanidine, dimethylarginine, N-acetyl-l-tyrosine, can act as a discriminator of CVD. Metabolites integrating pathway enrichment analysis showed enrichment of various important metabolic pathways like histidine metabolism, methyl histidine metabolism, carnitine synthesis, along with arginine and proline metabolism in CVD patients. Our study provides a great opportunity to understand the pathophysiological role and impact of the identified unique metabolites and can be extrapolated as specific CVD specific metabolites.

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