Circulating CTRP7 Is a Potential Predictor for Metabolic Syndrome

Hu, Wenjing; Zhan, Bin; Li, Qinge; Yang, Gangyi; Tan, Minghong; Geng, Shan; Liu, Hua; Chen, Chen; Liu, Dongfang; Li, Ling

doi:10.3389/fendo.2021.774309

Cited by 10 publications

(13 citation statements)

References 38 publications

(42 reference statements)

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“…OGTT was performed for study individuals at 8:00 am. after fasting for 12 h. Venous blood samples were drawn for GPHB5, adiponectin, glucose, and insulin ( 19 ).…”

Section: Methodsmentioning

confidence: 99%

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GPHB5 Is a Biomarker in Women With Metabolic Syndrome: Results From Cross-Sectional and Intervention Studies

Xiang

Zhang

et al. 2022

Front. Endocrinol.

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BackgroundAnimal studies have found that GPHB5 has a similar effect on system metabolism as TSH. However, the relationship between GPHB5 and metabolic diseases remains unknown. This study investigates the relationship between GPHB5 and MetS in young women.MethodsBioinformatics analysis was undertaken to explore the relationship between GPHB5 and metabolic-related genes and signaling pathways. EHC and OGTT were performed on all individuals. Lipid-infusion, physical activity, and cold-exposure tests were performed on healthy individuals. Serum GPHB5 concentrations were measured by an ELISA kit.ResultsPPI network showed that 11 genes interacted with GPHB5, in which POMC and KISS1R were involved in glucose and lipid metabolism. GO analysis showed 56 pathways for BP and 16 pathways for MF, in which OPRM1 and MCR families were related to energy metabolism. KEGG analysis found that GPHB5 is associated with lipolysis and neuroactive ligand-receptor interaction pathways. The levels of circulating GPHB5 were significantly increased, while serum adiponectin levels were lower in MetS women compared with healthy women. Obese/overweight individuals had lower adiponectin levels and higher GPHB5 levels. Circulating GPHB5 levels were positively correlated with BMI, WHR, blood pressure, FBG, 2 h-BG, HbA1c, FIns, 2h-Ins, LDL-C, FFA, HOMA-IR, and AUCg, etc. but negatively correlated with HDL-C, adiponectin, and M-values. Serum GPHB5 levels did not change significantly during the OGTT, EHC, and lipid infusion. Physical activity and cold-exposure tests did not lead to changes in GPHB5 levels. GLP-1RA treatment resulted in a significant decrease in serum GPHB5 levels.ConclusionsGPHB5 may be a biomarker for MetS.

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“…OGTT was performed for study individuals at 8:00 am. after fasting for 12 h. Venous blood samples were drawn for GPHB5, adiponectin, glucose, and insulin ( 19 ).…”

Section: Methodsmentioning

confidence: 99%

“…The kit is highly sensitive and specific for the determination of human GPHB5 and is not interfered with by other cytokines. Serum adiponectin levels were also measured by an ELISA kit from Aviscerabio science Inc., USA (sk00010-01), with intra- and inter-assay CV of 4% - 8% and 8% - 12%, respectively, as previously reported ( 19 ).…”

Section: Methodsmentioning

confidence: 99%

GPHB5 Is a Biomarker in Women With Metabolic Syndrome: Results From Cross-Sectional and Intervention Studies

Xiang

Zhang

et al. 2022

Front. Endocrinol.

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“…The cluster Profiler package was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Visualization of the PPI network was constructed by Cytoscape ( 18 ).…”

Section: Methodsmentioning

confidence: 99%

“…Euglycemic-hyperinsulinemic clamp (EHC) studies were performed in all individuals as previously published (18). Experimental design.…”

Section: Ogtts and Ehcsmentioning

confidence: 99%

Elevated circulating GPHB5 levels in women with insulin resistance and polycystic ovary syndrome: A cross-sectional study and multiple intervention studies

Wang

Xiang²,

Zhang³

et al. 2022

Front. Endocrinol.

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ObjectiveGPHB5 has been found to be associated with glucose and lipid metabolism in animal studies. However, the association of GPHB5 with IR and metabolic disorders remains unknown, and there is a lack of research in humans. Our aim in this study was to investigate the relationship between circulating GPHB5 and metabolic disorders in humans.MethodsBioinformatics analysis was performed to understand the relationship between GPHB5 and metabolic disorders. GPHB5 mRNA expression in mice and rats was determined using RT-qPCR. Circulating GPHB5 concentrations were measured with an ELISA kit. EHC and OGTT were performed in humans.ResultsBioinformatics analysis shows that GPHB5 is associated with metabolic disorders and PCOS. GPHB5 mRNA expression levels in the metabolic-related tissues of HFD-fed mice, db/db and ob/ob mice, and PCOS rats were significantly higher than those of WT mice or rats. In human studies, we find that circulating GPHB5 levels were significantly higher in women with IR and PCOS. GPHB5 levels were positively correlated with age, BMI, WHR, BP, FBG, 2 h-BG, FIns, 2 h-Ins, TC, LDL-C, HbA1c, and FFA, but negatively correlated with adiponectin. Furthermore, GPHB5 was positively correlated with DHEAS and FAI, while negatively correlated with SHBG, FSH, SHBG and FSH. The increased GPHB5 concentration was related to IR and PCOS. After the treatment of metformin, GLP-1RA (Lira), and TZDs, circulating GPHB5 levels were decreased.ConclusionsOur results reveal that circulating GPHB5 could be a biomarker and potential therapeutic target for IR and PCOS in women.

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“…Metabolic syndrome (MetS), also known as insulin resistance (IR) syndrome, is one of the metabolic disorders with a high risk of negative cardiovascular outcomes, including obesity, hypertension, dyslipidemia, and impaired glucose tolerance (IGT) (7,8). Recent studies indicated that genes like CTRP7 and SPTAN1 are associated with the occurrence of MetS (9,10). In addition, various serological indicators were proved to be the potential biomarkers for the diagnosis of MetS (11)(12)(13).…”

Section: Introductionmentioning

confidence: 99%

The shared biomarkers and pathways of systemic lupus erythematosus and metabolic syndrome analyzed by bioinformatics combining machine learning algorithm and single-cell sequencing analysis

et al. 2022

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BackgroundSystemic lupus erythematosus (SLE) is one of the most prevalent systemic autoimmune diseases, and metabolic syndrome (MetS) is the most common metabolic disorder that contains hypertension, dyslipidemia, and obesity. Despite clinical evidence suggested potential associations between SLE and MetS, the underlying pathogenesis is yet unclear.MethodsThe microarray data sets of SLE and MetS were obtained from the Gene Expression Omnibus (GEO) database. To identify the shared genes between SLE and MetS, the Differentially Expressed Genes (DEGs) analysis and the weighted gene co-expression network analysis (WGCNA) were conducted. Then, the GO and KEGG analyses were performed, and the protein-protein interaction (PPI) network was constructed. Next, Random Forest and LASSO algorithms were used to screen shared hub genes, and a diagnostic model was built using the machine learning technique XG-Boost. Subsequently, CIBERSORT and GSVA were used to estimate the correlation between shared hub genes and immune infiltration as well as metabolic pathways. Finally, the significant hub genes were verified using single-cell RNA sequencing (scRNA-seq) data.ResultsUsing limma and WGCNA, we identified 153 shared feature genes, which were enriched in immune- and metabolic-related pathways. Further, 20 shared hub genes were screened and successfully used to build a prognostic model. Those shared hub genes were associated with immunological and metabolic processes in peripheral blood. The scRNA-seq results verified that TNFSF13B and OAS1, possessing the highest diagnostic efficacy, were mainly expressed by monocytes. Additionally, they showed positive correlations with the pathways for the metabolism of xenobiotics and cholesterol, both of which were proven to be active in this comorbidity, and shown to be concentrated in monocytes.ConclusionThis study identified shared hub genes and constructed an effective diagnostic model in SLE and MetS. TNFSF13B and OAS1 had a positive correlation with cholesterol and xenobiotic metabolism. Both of these two biomarkers and metabolic pathways were potentially linked to monocytes, which provides novel insights into the pathogenesis and combined therapy of SLE comorbidity with MetS.

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Circulating CTRP7 Is a Potential Predictor for Metabolic Syndrome

Cited by 10 publications

References 38 publications

GPHB5 Is a Biomarker in Women With Metabolic Syndrome: Results From Cross-Sectional and Intervention Studies

GPHB5 Is a Biomarker in Women With Metabolic Syndrome: Results From Cross-Sectional and Intervention Studies

Elevated circulating GPHB5 levels in women with insulin resistance and polycystic ovary syndrome: A cross-sectional study and multiple intervention studies

The shared biomarkers and pathways of systemic lupus erythematosus and metabolic syndrome analyzed by bioinformatics combining machine learning algorithm and single-cell sequencing analysis

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