Quantitative proteomic study of the plasma reveals acute phase response and LXR/RXR and FXR/RXR activation in the chronic unpredictable mild stress mouse model of depression

Yang, Chuangchuang; Zhou, Chanjuan; Li, Jie; Chen, Zhi; Shi, Haiyang; Yang, Wen‐Song; Qin, Yinhua; Lu, Lijun; Zhao, Libo; Fang, Liang; Wang, Haiyang; Hu, Zicheng; Xie, Peng

doi:10.3892/mmr.2017.7855

Cited by 11 publications

(10 citation statements)

References 37 publications

(51 reference statements)

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“…Our IPA analysis results show that LXR/RXR activation is the top-ranking pathway for combined differentially expressed proteins and lipids. Previously, we obtained a similar result in proteomics study of the chronic unpredictable mild stress (CUMS) mouse model of depression, 25 also finding a significant change in the LXR/RXR activation pathway. The RXR is a nuclear receptor that mediates the biological effects of retinoid.…”

Section: Discussionsupporting

confidence: 72%

Plasma disturbance of phospholipid metabolism in major depressive disorder by integration of proteomics and metabolomics

Gui

Liu

Zhong

et al. 2018

NDT

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IntroductionMajor depressive disorder (MDD) is a highly prevalent mental disorder affecting millions of people worldwide. However, a clear causative etiology of MDD remains unknown. In this study, we aimed to identify critical protein alterations in plasma from patients with MDD and integrate our proteomics and previous metabolomics data to reveal significantly perturbed pathways in MDD. An isobaric tag for relative and absolute quantification (iTRAQ)-based quantitative proteomics approach was conducted to compare plasma protein expression between patients with depression and healthy controls (CON).MethodsFor integrative analysis, Ingenuity Pathway Analysis software was used to analyze proteomics and metabolomics data and identify potential relationships among the differential proteins and metabolites.ResultsA total of 74 proteins were significantly changed in patients with depression compared with those in healthy CON. Bioinformatics analysis of differential proteins revealed significant alterations in lipid transport and metabolic function, including apolipoproteins (APOE, APOC4 and APOA5), and the serine protease inhibitor. According to canonical pathway analysis, the top five statistically significant pathways were related to lipid transport, inflammation and immunity.ConclusionCausal network analysis by integrating differential proteins and metabolites suggested that the disturbance of phospholipid metabolism might promote the inflammation in the central nervous system.

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Section: Discussionsupporting

confidence: 72%

Plasma disturbance of phospholipid metabolism in major depressive disorder by integration of proteomics and metabolomics

Gui

Liu

Zhong

et al. 2018

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“…LXRs form heterodimers with RXRs, which regulate the expression of genes controlling sterol/fatty acid metabolism/homeostasis [50]. Interestingly, this pathway was recently demonstrated to be significantly altered in plasma DEPs in a mouse model of depression [51]. Inflammation and immune pathways were also significantly different, and these have been proposed to be involved in mood disorders [52][53][54].…”

Section: Discussionmentioning

confidence: 99%

Comparison of serum protein profiles between major depressive disorder and bipolar disorder

et al. 2020

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Background: Major depressive disorder and bipolar disorder are prevalent and debilitating psychiatric disorders that are difficult to distinguish, as their diagnosis is based on behavioural observations and subjective symptoms. Quantitative protein profile analysis might help to objectively distinguish between these disorders and increase our understanding of their pathophysiology. Thus, this study was conducted to compare the peripheral protein profiles between the two disorders. Methods: Serum samples were collected from 18 subjects with major depressive disorder and 15 subjects with bipolar disorder. After depleting abundant proteins, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification were performed. Data-dependent acquisition data were statistically analysed from the samples of 15 subjects with major depressive disorder and 10 subjects with bipolar disorder who were psychotropic drug-free. Two-sided t-tests were performed for pairwise comparisons of proteomes to detect differentially-expressed proteins (DEPs). Ingenuity Pathway Analysis of canonical pathways, disease and functions, and protein networks based on these DEPs was further conducted. Results: Fourteen DEPs were significant between subjects with major depressive disorder and those with bipolar disorder. Ras-related protein Rab-7a (t = 5.975, p = 4.3 × 10 − 6) and Rho-associated protein kinase 2 (t = 4.782, p = 8.0 × 10 − 5) were significantly overexpressed in subjects with major depressive disorder and Exportin-7 (t =-4.520, p = 1.5 × 10 − 4) was significantly overexpressed in subjects with bipolar disorder after considering multiple comparisons. Bioinformatics analysis showed that cellular functions and inflammation/immune pathways were significantly different. Conclusions: Ras-related protein Rab-7a, Rho-associated protein kinase 2, and Exportin-7 were identified as potential peripheral protein candidates to distinguish major depressive disorder and bipolar disorder. Further large sample studies with longitudinal designs and validation processes are warranted.

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“…IPA revealed that the top significantly changed canonical pathways are related to FXR/RXR activation, LXR/RXR activation, and LPS/IL-1-mediated inhibition of RXR function, and this was consistent with that of the previous reports in the literature. We found that FXR/RXR and LXR/RXR are involved in many diseases, such as hypothalamic dysfunction [ 18 ], germ cell development [ 19 ], adipose stem cells (ASCs) [ 20 ], colorectal cancer (CRC) [ 21 ], and major depressive disorder [ 22 ]. A study has found that the stimulation of glutamine to ASCT2 expression partly involves the binding of FXR/RXR to the ASCT2 promoter [ 23 ], which might be the key to the proliferation and survival of HepG2 cells.…”

Section: Discussionmentioning

confidence: 99%

Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma

Chen

Ling

et al. 2020

BioMed Research International

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Background. The molecular mechanism by which hepatitis B virus (HBV) induces hepatocellular carcinoma (HCC) is still unknown. The genomic expression profile and bioinformatics methods were used to investigate the potential pathogenesis and therapeutic targets for HBV-associated HCC (HBV-HCC). Methods. The microarray dataset GSE55092 was downloaded from the Gene Expression Omnibus (GEO) database. The data was analyzed by the bioinformatics software to find differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, ingenuity pathway analysis (IPA), and protein-protein interaction (PPI) network analysis were then performed on DEGs. The hub genes were identified using Centiscape2.2 and Molecular Complex Detection (MCODE) in the Cytoscape software (Cytoscape_v3.7.2). The survival data of these hub genes was downloaded from the Gene Expression Profiling Interactive Analysis (GEPIA). Results. A total of 2264 mRNA transcripts were differentially expressed, including 764 upregulated and 1500 downregulated in tumor tissues. GO analysis revealed that these DEGs were related to the small-molecule metabolic process, xenobiotic metabolic process, and cellular nitrogen compound metabolic process. KEGG pathway analysis revealed that metabolic pathways, complement and coagulation cascades, and chemical carcinogenesis were involved. Diseases and biofunctions showed that DEGs were mainly associated with the following diseases or biological function abnormalities: cancer, organismal injury and abnormalities, gastrointestinal disease, and hepatic system disease. The top 10 upstream regulators were predicted to be activated or inhibited by Z-score and identified 25 networks. The 10 genes with the highest degree of connectivity were defined as the hub genes. Cox regression revealed that all the 10 genes (CDC20, BUB1B, KIF11, TTK, EZH2, ZWINT, NDC80, TPX2, MELK, and KIF20A) were related to the overall survival. Conclusion. Our study provided a registry of genes that play important roles in regulating the development of HBV-HCC, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of HCC.

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Quantitative proteomic study of the plasma reveals acute phase response and LXR/RXR and FXR/RXR activation in the chronic unpredictable mild stress mouse model of depression

Cited by 11 publications

References 37 publications

Plasma disturbance of phospholipid metabolism in major depressive disorder by integration of proteomics and metabolomics

Plasma disturbance of phospholipid metabolism in major depressive disorder by integration of proteomics and metabolomics

Comparison of serum protein profiles between major depressive disorder and bipolar disorder

Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma

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