Association of chemokines IP-10/CXCL10 and I-TAC/CXCL11 with insulin resistance and enhance leukocyte endothelial arrest in obesity

Moreno, Beatriz; Hueso, Luisa; Ortega, Rebeca; Benito, Esther; Martínez-Hervás, Sergio; Peiró, Marta; Civera, Miguel; Sanz, María-Jesús; Piqueras, Laura; Real, José T.

doi:10.1016/j.mvr.2021.104254

Cited by 17 publications

(10 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Different from T1D, type 2 diabetes (T2D) is mainly the result of insulin resistance (IR). Moreno et al had studied many obese patients and ultimately found that CXCL10 and CXCL11 were associated with IR in obesity [ 119 ]. Another study showed that in T2D the migration in responses to CXCL12 was declined by diabetic fibrocytes while the migratory of fibrocytes contributed to wound healing and chronic ulcer caused by diabetes [ 120 ].…”

Section: Cxcl Family and Diseasesmentioning

confidence: 99%

The role of CXCL family members in different diseases

et al. 2023

View full text Add to dashboard Cite

Chemokines are a large family mediating a lot of biological behaviors including chemotaxis, tumor growth, angiogenesis and so on. As one member of this family, CXC subfamily possesses the same ability. CXC chemokines can recruit and migrate different categories of immune cells, regulate tumor’s pathological behaviors like proliferation, invasion and metastasis, activate angiogenesis, etc. Due to these characteristics, CXCL subfamily is extensively and closely associated with tumors and inflammatory diseases. As studies are becoming more and more intensive, CXCLs’ concrete roles are better described, and CXCLs’ therapeutic applications including biomarkers and targets are also deeply explained. In this review, the role of CXCL family members in various diseases is summarized.

show abstract

Section: Cxcl Family and Diseasesmentioning

confidence: 99%

The role of CXCL family members in different diseases

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Signaling pathways include GPCR ligand binding [89], neutrophil degranulation [90], immune system [91], metabolism of lipids [92] and signal transduction [93] made great contribution to the development of IPF. MAP3K15 [94], PRTN3 [95], CX3CR1 [96], AGRP (agouti related neuropeptide) [97], MPO (myeloperoxidase) [98], CD5L [99], S100A8 [100], NPR3 [101], VEGFD (vascular endothelial growth factor D) [102], CXCL11 [103], IL1A [104], CBS (cystathionine beta-synthase) [105], WNT7A [106], SCD (stearoyl-CoA desaturase) [107], LRP2 [108], SLC6A4 [109], BDNF (brain derived neurotrophic factor) [110], CXCL10 [111], ANGPTL7 [112], S100A9 [113], NPY1R [114], IL1B [115], GPIHBP1 [116], CYP1B1 [117], CD36 [118], MACROD2 [119], TRIB3 [120], SPX (spexin hormone) [121], PCSK9 [122], GPD1 [123], CDH13 [124], FFAR4 [125], FGF2 [126], FASN (fatty acid synthase) [127], DGAT2 [128], DACH1 [129], PNPLA3 [130], FGF9 [131], SLC7A11 [132], CLIC5 [133], VIP (vasoactive intestinal peptide) [134], SMAD6 [135], BMPR2 [136], APOA1 [137], INSIG1 [138], TLR3 [139], NLRP12 [140], ADRB1 [141], TLR8 [142], GATA3 [143], CCR2 [144], TLR7 [145], CCRL2 [146], BMPER (BMP binding endothelial regulator) [147], CAV1 [148], TFPI (tissue factor pathway inhibitor) [149], FADS1 [150], SUCNR1 [151], CADM2 [152], SLC19A3 [153], SGCG (sarcoglycan gamma) [154], ADH1B [155], NEGR1 [156], HSD17B12 [157], OXTR (oxytocin receptor) [158] and ANKK1 […”

Section: Discussionmentioning

confidence: 99%

Study on potential differentially expressed genes in idiopathic pulmonary fibrosis by bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2023

Preprint

View full text Add to dashboard Cite

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analysis of DEGs were performed. Then, a protein protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst database was used to construct the targeted microRNAs (miRNAs) and transcription factors (TFs) of the hub genes. Finally receiver operating characteristic (ROC) curve analysis was used to validates the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8 and EFHC2 were selected. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

show abstract

“…IL-17 can increase the expression and the production of CCL2 and CXCL10 to enhance its pro-inflammatory effect ( Matsui and Yoshida, 2016 ). CCL2 ( Elmarakby and Sullivan, 2012 ; Ota, 2013 ), CCL8 ( Sarkar et al., 2012 ), and CXCL10 ( Antonelli et al., 2014 ; Hueso et al., 2018 ; Moreno et al., 2022 ) have also been demonstrated to play a role in the development of diabetes. Along with the elevation of IL-17, the gingival mRNA expressions of CCL2 , CCL8 , and CXCL10 were upregulated.…”

Section: Discussionmentioning

confidence: 99%

Periodontitis induced by Porphyromonas gingivalis drives impaired glucose metabolism in mice

Kang

Zhang

Xue

et al. 2022

Front. Cell. Infect. Microbiol.

View full text Add to dashboard Cite

Periodontitis has been demonstrated to be bidirectionally associated with diabetes and has been recognized as a complication of diabetes. As a periodontal pathogen, Porphyromonas gingivalis is a possible pathogen linking periodontal disease and systemic diseases. It has also been found to be involved in the occurrence and development of diabetes. In this study, 6-week-old male C57BL/6 mice were orally administered the P. gingivalis strain ATCC381 for 22 weeks. Histological analysis of the gingival tissue and quantified analysis of alveolar bone loss were performed to evaluate periodontal destruction. Body weight, fasting glucose, glucose tolerance test (GTT), and insulin tolerance test (ITT) were used to evaluate glucose metabolism disorder. We then analyzed the expression profiles of inflammatory cytokines and chemokines in gingival tissue, the liver, and adipose tissue, as well as in serum. The results showed that mice in the P. gingivalis-administered group developed apparent gingival inflammation and more alveolar bone loss compared to the control group. After 22 weeks of P. gingivalis infection, significant differences were observed at 30 and 60 min for the GTT and at 15 min for the ITT. P. gingivalis-administered mice showed an increase in the mRNA expression levels of the pro-inflammatory cytokines (TNF-α, IL-6, IL-17, and IL-23) and chemokines (CCL2, CCL8, and CXCL10) in the gingiva and serum. The expression levels of the glucose metabolism-related genes were also changed in the liver and adipose tissue. Our results indicate that oral administration of P. gingivalis can induce changes in the inflammatory cytokines and chemokines in the gingiva and blood, can lead to alveolar bone loss and to inflammatory changes in the liver and adipose tissues, and can promote glucose metabolism disorder in mice.

show abstract

Association of chemokines IP-10/CXCL10 and I-TAC/CXCL11 with insulin resistance and enhance leukocyte endothelial arrest in obesity

Cited by 17 publications

References 27 publications

The role of CXCL family members in different diseases

The role of CXCL family members in different diseases

Study on potential differentially expressed genes in idiopathic pulmonary fibrosis by bioinformatics and next generation sequencing data analysis

Periodontitis induced by Porphyromonas gingivalis drives impaired glucose metabolism in mice

Contact Info

Product

Resources

About