Dermatopontin, A Novel Adipokine Promoting Adipose Tissue Extracellular Matrix Remodelling and Inflammation in Obesity

Unamuno, Xabier; Gómez-Ambrosi, Javier; Ramírez, Beatriz; Rodríguez, Amaia; Becerril, Sara; Valentí, Víctor; Moncada, Rafael; Silva, Camilo; Salvador, Javier; Frühbeck, Gema; Catalán, Victoria

doi:10.3390/jcm9041069

Cited by 33 publications

(23 citation statements)

References 49 publications

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“…The circulating soluble receptor for advanced glycation end products (AGER) is negatively associated with BMI 57 , as we also observed in KORA. In addition, recent evidence suggests a role of adipokine dermatopontin (DPT) in obesity by regulation of adipose tissue remodeling and inflammation 58 . A Dpt knockout mouse model showed increased subcutaneous adipose tissue 59 , and effects on skin elasticity, dermis thickness, and collagen accumulation.…”

Section: Discussionmentioning

confidence: 99%

Revealing the role of the human blood plasma proteome in obesity using genetic drivers

et al. 2021

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Blood circulating proteins are confounded readouts of the biological processes that occur in different tissues and organs. Many proteins have been linked to complex disorders and are also under substantial genetic control. Here, we investigate the associations between over 1000 blood circulating proteins and body mass index (BMI) in three studies including over 4600 participants. We show that BMI is associated with widespread changes in the plasma proteome. We observe 152 replicated protein associations with BMI. 24 proteins also associate with a genome-wide polygenic score (GPS) for BMI. These proteins are involved in lipid metabolism and inflammatory pathways impacting clinically relevant pathways of adiposity. Mendelian randomization suggests a bi-directional causal relationship of BMI with LEPR/LEP, IGFBP1, and WFIKKN2, a protein-to-BMI relationship for AGER, DPT, and CTSA, and a BMI-to-protein relationship for another 21 proteins. Combined with animal model and tissue-specific gene expression data, our findings suggest potential therapeutic targets further elucidating the role of these proteins in obesity associated pathologies.

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Section: Discussionmentioning

confidence: 99%

Revealing the role of the human blood plasma proteome in obesity using genetic drivers

et al. 2021

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“…CCDC80 [ 139 ], CMA1 [ 140 ], MDK (midkine) [ 141 ], GNA14 [ 142 ], SCG2 [ 143 ], NPPB (natriuretic peptide B) [ 144 ], FGF10 [ 145 ], ARNTL (aryl hydrocarbon receptor nuclear translocator like) [ 146 ], WNK3 [ 147 ], EDNRB (endothelin receptor type B) [ 148 ], THBS1 [ 149 ], SELE (selectin E) [ 150 ], SLC4A7 [ 151 ], AQP4 [ 152 ] and KCNK3 [ 153 ] are thought to be responsible for progression of hypertension, but these genes might to be associated with progression of HF. CNTNAP2 [ 154 ], GLI2 [ 155 ], DPT (dermatopontin) [ 156 ], AEBP1 [ 157 ], ITIH5 [ 158 ], CXCL11 [ 159 ], GDNF (glial cell derived neurotrophic factor) [ 160 ], MCHR1 [ 161 ], FLT3 [ 162 ], ELANE (elastase, neutrophil expressed) [ 163 ], OSMR (oncostatin M receptor) [ 164 ] and IL15RA [ 165 ] are involved in development of obesity, but these genes might be key for progression of HF. CTSG (cathepsin G) is a protein coding gene plays important roles in aortic aneurysms [ 166 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Kolur¹,

Vastrad²,

Vastrad

et al. 2021

BMC Cardiovasc Disord

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Introduction Heart failure (HF) is a heterogeneous clinical syndrome and affects millions of people all over the world. HF occurs when the cardiac overload and injury, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental HF as well as to explore active drug molecules. Methods The expression profiling by high throughput sequencing of GSE141910 dataset was downloaded from the Gene Expression Omnibus (GEO) database, which contained 366 samples, including 200 heart failure samples and 166 non heart failure samples. The raw data was integrated to find differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. Gene ontology (GO) and REACTOME enrichment analyses were performed via ToppGene; protein–protein interaction (PPI) networks of the DEGs was constructed based on data from the HiPPIE interactome database; modules analysis was performed; target gene—miRNA regulatory network and target gene—TF regulatory network were constructed and analyzed; hub genes were validated; molecular docking studies was performed. Results A total of 881 DEGs, including 442 up regulated genes and 439 down regulated genes were observed. Most of the DEGs were significantly enriched in biological adhesion, extracellular matrix, signaling receptor binding, secretion, intrinsic component of plasma membrane, signaling receptor activity, extracellular matrix organization and neutrophil degranulation. The top hub genes ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 were identified from the PPI network. Module analysis revealed that HF was associated with adaptive immune system and neutrophil degranulation. The target genes, miRNAs and TFs were identified from the target gene—miRNA regulatory network and target gene—TF regulatory network. Furthermore, receiver operating characteristic (ROC) curve analysis and RT-PCR analysis revealed that ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 might serve as prognostic, diagnostic biomarkers and therapeutic target for HF. The predicted targets of these active molecules were then confirmed. Conclusion The current investigation identified a series of key genes and pathways that might be involved in the progression of HF, providing a new understanding of the underlying molecular mechanisms of HF.

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“…Recently, we explored the role of dermatopontin (DPT), a non-collagenous ECM component dynamically involved in myogenesis, finding that it increases cell adhesion, decreases proliferation, and enhances differentiation [20]. In another study, DPT increased expression of ECM-related genes (COL6A3, TNMD, MMP-9, and ELN) and inflammation-associated factors (TNF, IL-6, and IL-8) in human visceral adipocytes, indicating a role for DPT in the regulation of ECM remodeling [25].…”

Section: Skeletal Muscle Ecm: Composition Structure and Functionmentioning

confidence: 99%

Implications of Skeletal Muscle Extracellular Matrix Remodeling in Metabolic Disorders: Diabetes Perspective

Ahmad

Choi

Lee

2020

IJMS

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The extracellular matrix (ECM) provides a scaffold for cells, controlling biological processes and providing structural as well as mechanical support to surrounding cells. Disruption of ECM homeostasis results in several pathological conditions. Skeletal muscle ECM is a complex network comprising collagens, proteoglycans, glycoproteins, and elastin. Recent therapeutic approaches targeting ECM remodeling have been extensively deliberated. Various ECM components are typically found to be augmented in the skeletal muscle of obese and/or diabetic humans. Skeletal muscle ECM remodeling is thought to be a feature of the pathogenic milieu allied with metabolic dysregulation, obesity, and eventual diabetes. This narrative review explores the current understanding of key components of skeletal muscle ECM and their specific roles in the regulation of metabolic diseases. Additionally, we discuss muscle-specific integrins and their role in the regulation of insulin sensitivity. A better understanding of the importance of skeletal muscle ECM remodeling, integrin signaling, and other factors that regulate insulin activity may help in the development of novel therapeutics for managing diabetes and other metabolic disorders.

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Dermatopontin, A Novel Adipokine Promoting Adipose Tissue Extracellular Matrix Remodelling and Inflammation in Obesity

Cited by 33 publications

References 49 publications

Revealing the role of the human blood plasma proteome in obesity using genetic drivers

Revealing the role of the human blood plasma proteome in obesity using genetic drivers

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Implications of Skeletal Muscle Extracellular Matrix Remodeling in Metabolic Disorders: Diabetes Perspective

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