Liver metabolomics in a mouse model of erythropoietic protoporphyria

Wang, Pengcheng; Sachar, Madhav; Guo, Grace L.; Shehu, Amina I.; Lu, Jie; Zhong, Xiao‐bo; Ma, Xiaochao

doi:10.1016/j.bcp.2018.06.011

Cited by 5 publications

(3 citation statements)

References 46 publications

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“…Ferrochelatase (FECH) is the terminal enzyme in heme biosynthesis and plays vital roles in choroidal neovascularization, retinal neovascularization, and erythropoietic protoporphyria [ 32 – 34 ]. It was reported that FECH was involved in the metabolic pathway [ 35 ], and our work concurs with this. Glycophorins (GYPA) are one of the primary sialoglycoproteins of the human erythrocyte membrane and serve as receptors for pathogens, including Plasmodium falciparum erythrocyte-binding antigen 175 (EBA-175), influenza virus, and hepatitis A virus (HAV).…”

Section: Discussionsupporting

confidence: 92%

Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis

Fan

Jin

Wang

et al. 2021

BMC Cardiovasc Disord

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Background The pathogenic mechanisms of venous thromboembolism (VT) remain to be defined. This study aimed to identify differentially expressed genes (DEGs) that could serve as potential therapeutic targets for VT. Methods Two human datasets (GSE19151 and GSE48000) were analyzed by the robust rank aggregation method. Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were conducted for the DEGs. To explore potential correlations between gene sets and clinical features and to identify hub genes, we utilized weighted gene coexpression network analysis (WGCNA) to build gene coexpression networks incorporating the DEGs. Then, the levels of the hub genes were analyzed in the GSE datasets. Based on the expression of the hub genes, the possible pathways were explored by gene set enrichment analysis and gene set variation analysis. Finally, the diagnostic value of the hub genes was assessed by receiver operating characteristic (ROC) analysis in the GEO database. Results In this study, we identified 54 upregulated and 10 downregulated genes that overlapped between normal and VT samples. After performing WGCNA, the magenta module was the module with the strongest negative correlation with the clinical characteristics. From the key module, FECH, GYPA, RPIA and XK were chosen for further validation. We found that these genes were upregulated in VT samples, and high expression levels were related to recurrent VT. Additionally, the four hub genes might be highly correlated with ribosomal and metabolic pathways. The ROC curves suggested a diagnostic value of the four genes for VT. Conclusions These results indicated that FECH, GYPA, RPIA and XK could be used as promising biomarkers for the prognosis and prediction of VT.

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Section: Discussionsupporting

confidence: 92%

Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis

Fan

Jin

Wang

et al. 2021

BMC Cardiovasc Disord

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“…Target tissue-based metabolomics have been performed in cancer tissues and other tissues such as the liver and brain, extracted from experimental animals and humans with liver metabolism disorders or brain injuries and diseases [47,48,49,50]. In spite of the limitations of tissue sample accessibility and the complexity of sample preparation, target tissue-based metabolomics still represents the most direct way to gain insights into the metabolomic changes in the cells of the target tissue [47,50].…”

Section: Biological Samples Used In Metabolomicsmentioning

confidence: 99%

Current Understanding of Methamphetamine-Associated Metabolic Changes Revealed by the Metabolomics Approach

et al. 2019

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Metabolomics is a powerful tool used in the description of metabolic system perturbations caused by diseases or abnormal conditions, and it usually involves qualitative and/or quantitative metabolome determination, accompanied by bioinformatics assessment. Methamphetamine is a psychostimulant with serious abuse potential and due to the absence of effective pharmacotherapy and a high recurrence potential, methamphetamine addiction is a grave issue. Moreover, its addiction mechanisms remain unclear, probably due to the lack of experimental models that reflect personal genetic variances and environmental factors determining drug addiction occurrence. The metabolic approach is only recently being used to study the metabolic effects induced by a variety of methamphetamine exposure statuses, in order to investigate metabolic disturbances related to the adverse effects and discover potential methamphetamine addiction biomarkers. To provide a critical overview of methamphetamine-associated metabolic changes revealed in recent years using the metabolomics approach, we discussed methamphetamine toxicity, applications of metabolomics in drug abuse and addiction studies, biological samples used in metabolomics, and previous studies on metabolic alterations in a variety of biological samples—including the brain, hair, serum, plasma, and urine—following methamphetamine exposure in animal studies. Metabolic alterations observed in animal brain and other biological samples after methamphetamine exposure were associated with neuronal and energy metabolism disruptions. This review highlights the significance of further metabolomics studies in the area of methamphetamine addiction research. These findings will contribute to a better understanding of metabolic changes induced by methamphetamine addiction progress and to the design of further studies targeting the discovery of methamphetamine addiction biomarkers and therapeutic targets.

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“…The main clinical manifestation is painful skin inflammation after short exposure to sunlight. However, because the heme formation mainly occurs in the bone marrow and liver, mutations affecting FECH activity lead to PPIX accumulation in the bone marrow, erythrocytes, plasma, and liver and it has been estimated that up to 20% of the EPP patients have liver injury and approximately 2–5% develop serious liver damage or even liver failure ( Wang et al, 2018 ).…”

Section: Zebrafish Models Of Blood Diseasementioning

confidence: 99%

Rare Genetic Blood Disease Modeling in Zebrafish

Rissone

Burgess

2018

Front. Genet.

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Hematopoiesis results in the correct formation of all the different blood cell types. In mammals, it starts from specific hematopoietic stem and precursor cells residing in the bone marrow. Mature blood cells are responsible for supplying oxygen to every cell of the organism and for the protection against pathogens. Therefore, inherited or de novo genetic mutations affecting blood cell formation or the regulation of their activity are responsible for numerous diseases including anemia, immunodeficiency, autoimmunity, hyper- or hypo-inflammation, and cancer. By definition, an animal disease model is an analogous version of a specific clinical condition developed by researchers to gain information about its pathophysiology. Among all the model species used in comparative medicine, mice continue to be the most common and accepted model for biomedical research. However, because of the complexity of human diseases and the intrinsic differences between humans and other species, the use of several models (possibly in distinct species) can often be more helpful and informative than the use of a single model. In recent decades, the zebrafish (Danio rerio) has become increasingly popular among researchers, because it represents an inexpensive alternative compared to mammalian models, such as mice. Numerous advantages make it an excellent animal model to be used in genetic studies and in particular in modeling human blood diseases. Comparing zebrafish hematopoiesis to mammals, it is highly conserved with few, significant differences. In addition, the zebrafish model has a high-quality, complete genomic sequence available that shows a high level of evolutionary conservation with the human genome, empowering genetic and genomic approaches. Moreover, the external fertilization, the high fecundity and the transparency of their embryos facilitate rapid, in vivo analysis of phenotypes. In addition, the ability to manipulate its genome using the last genome editing technologies, provides powerful tools for developing new disease models and understanding the pathophysiology of human disorders. This review provides an overview of the different approaches and techniques that can be used to model genetic diseases in zebrafish, discussing how this animal model has contributed to the understanding of genetic diseases, with a specific focus on the blood disorders.

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Liver metabolomics in a mouse model of erythropoietic protoporphyria

Cited by 5 publications

References 46 publications

Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis

Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis

Current Understanding of Methamphetamine-Associated Metabolic Changes Revealed by the Metabolomics Approach

Rare Genetic Blood Disease Modeling in Zebrafish

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