VCAM-1, ICAM-1 and Selectins in Gestational Diabetes Mellitus and the Risk for Vascular Disorders

Siddiqui, Khalid; George, Teena P.; Nawaz, Shaik Sarfaraz; Joy, Salini Scaria

doi:10.2217/fca-2018-0042

Cited by 20 publications

(17 citation statements)

References 32 publications

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“…Transient hyperglycemia may provoke a persistent modification to the memory cells and hence, women with GDM are more prone to develop future complications than controls. Likewise, an increased levels of ICAM-1, VCAM-1, and selectins in women with GDM are a reflection of endothelial dysfunction contemplating the future metabolic risks via metabolic memory effects [67][68][69]. Studies showed that circulating levels of AGEs were positively associated with severity of aortic calcification and diabetes-related…”

Section: Plos Onementioning

confidence: 99%

The relationship between advanced glycation end products and gestational diabetes: A systematic review and meta-analysis

et al. 2020

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Introduction Gestational Diabetes Mellitus (GDM) is a condition in which women without history of diabetes experience hyperglycemia during pregnancy, especially at the second and third trimesters. In women who have had GDM, an elevated body mass index (BMI) may have a substantial impact for persistent hyperglycemia in their lives after gestation. Beyond hyperglycemia, increased local oxidative stress directly promotes the formation of Advanced Glycation End-products (AGEs). Hence, this systematic review and meta-analysis was aimed to determine the relationship between the level of AGEs and/or related metabolic biomarkers with GDM. Methods Literature search was carried out through visiting electronic databases, indexing services, and directories including PubMed/MEDLINE (Ovid ®), EMBASE (Ovid ®), google scholar and WorldCat to retrieve studies without time limit. Following screening and eligibility evaluation, relevant data were extracted from included studies and analyzed using Rev-Man 5.3 and STATA 15.0. Inverse variance method with random effects pooling model was used for the analysis of outcome measures at 95% confidence interval. Hedge's adjusted g statistics was applied to calculate the standardized mean difference (SMD) to consider the small sample bias. Besides, meta-regression, meta-influence, and publication bias analyses were conducted. The protocol has been registered on PROSPERO with ID: CRD42020173867. Results A total of 16 original studies were included for the systematic review and meta-analysis.

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Section: Plos Onementioning

confidence: 99%

The relationship between advanced glycation end products and gestational diabetes: A systematic review and meta-analysis

et al. 2020

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“…Endothelial activation increases the expression of adhesion molecules and promotes the attachment and migration of adherent monocytes, which precede the endothelial damage [ 119 , 120 ]. Significantly increased serum concentrations of soluble VCAM-1 have been noted in patients with gestational diabetes mellitus (GDM) and type 1 diabetes (T1D) compared with the control group [ 121 , 122 , 123 , 124 ]. Furthermore, the prolonged increase in concentrations of adhesion molecules in the peripheral blood were noted in patients with diabetes progression after pregnancy and in women with a history of GDM [ 118 , 125 , 126 ].…”

Section: Discussionmentioning

confidence: 99%

Endothelial Dysfunction in Pregnancy Complications

et al. 2021

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The endothelium, which constitutes the inner layer of blood vessels and lymphatic structures, plays an important role in various physiological functions. Alterations in structure, integrity and function of the endothelial layer during pregnancy have been associated with numerous gestational complications, including clinically significant disorders, such as preeclampsia, fetal growth restriction, and diabetes. While numerous experimental studies have focused on establishing the role of endothelial dysfunction in pathophysiology of these gestational complications, their mechanisms remain unknown. Numerous biomarkers of endothelial dysfunction have been proposed, together with the mechanisms by which they relate to individual gestational complications. However, more studies are required to determine clinically relevant markers specific to a gestational complication of interest, as currently most of them present a significant overlap. Although the independent diagnostic value of such markers remains to be insufficient for implementation in standard clinical practice at the moment, inclusion of certain markers in predictive multifactorial models can improve their prognostic value. The future of the research in this field lies in the fine tuning of the clinical markers to be used, as well as identifying possible therapeutic techniques to prevent or reverse endothelial damage.

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“…In a previous report, Santiago et al [128], Auburger et al [129], Qu et al [130], Ś et al [131] and Hjortebjerg et al [132] reported that SLC22A5, SH2B3, ITPR3, CALD1 and IGFBP4 expression might be regarded as an indicator of susceptibility to type 1 diabetes mellitus, but these genes might be associated with progression of GDM. Krishnan et al [133], Hu et al [134], Martins et al [135], Prieto-Sánchez et al [136], Sugulle et al [137], Zhao et al [138], Siddiqui et al [139], Han et al [140], Lappas et al [141], Wang et al [142], Artunc-Ulkumen et al [143], Blois et al [144], Vacínová et al [145] and Vilmi-Kerälä et al [146] demonstrated that the expression of CREBRF (CREB3 regulatory factor), STRA6, EGFR (epidermal growth factor receptor), MFSD2A, GDF15, PAK1, VCAM1, IGFBP2, IGFBP7, PRKCA (protein kinase C alpha), ADAMTS9, LGALS1, BIN1, TIMP1 and are associated with progression of GDM. Aquila et al, [147],Chen et al [148], Xie et al [149], Zhang et al [150], Aspit et al [151], Akadam-Teker et al [152], Jiang et al [153], Cetinkaya et al [154], Grond-Ginsbach et al [155], Dong et al [156], Chardon et al [157], Chen et al [158], Yamada et al [159], Hu et al [160], Bobik and Kalinina [161], Schwanekamp et al [162], Liu et al [163], Schroer et al [164], Raza et al [165], Yang et al [166], Azuaje et al [167], Durbin et al [168], Chowdhury et al [169], Wang et al [170], Li et al [171], Lv et al [172], Bertoli-Avella et al [173], Grossman et al [174], Andenæs et al [175] and Chen et al [176] demonstrated that HES1, SPIN1, TBX3, EVA1A, CAP2, BMP1, HSPB8, RDX (radixin), COL5A1, LIMS2, PARVA (parvin alpha), EGFLAM (EGF like, fibronectin type III and laminin G domains), NEXN (nexilin F-actin binding protein), TNFRSF14, TGFBI (transforming growth factor beta induced), HAVCR2, CDH11, COL4A1, COL4A2, COL5A2, SHROOM3, HYAL2, PDLIM3, ETS2, PLSCR4, TGFB3, COL6A2 and LTBP2 could induce cardiovascular diseases, but these genes might be essential for progression of GDM.…”

Section: Discussionmentioning

confidence: 99%

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

Vastrad¹,

Vastrad²,

Tengli

2021

Preprint

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Gestational diabetes mellitus (GDM) is one of the metabolic diseases during pregnancy. The identification of the central molecular mechanisms liable for the disease pathogenesis might lead to the advancement of new therapeutic options. The current investigation aimed to identify central differentially expressed genes (DEGs) in GDM. The transcription profiling by array data (E-MTAB-6418) was obtained from the ArrayExpress database. The DEGs between GDM samples and non GDM samples were analyzed with limma package. Gene ontology (GO) and REACTOME enrichment analysis were performed using ToppGene. Then we constructed the protein-protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING) and module analysis was performed. Subsequently, we constructed the miRNA-hub gene network and TF-hub gene regulatory network by the miRNet database and NetworkAnalyst database. The validation of hub genes was performed through receiver operating characteristic curve (ROC). Finally, the candidate small molecules as potential drugs to treat GDM were predicted by using molecular docking. Through transcription profiling by array data, a total of 869 DEGs were detected including 439 up regulated and 430 down regulated genes. Biological process analysis of GO enrichment analysis showed these DEGs were mainly enriched in reproduction, nuclear outer membrane-endoplasmic reticulum membrane network, identical protein binding, cell adhesion, supramolecular complex and signaling receptor binding. Signaling pathway enrichment analysis indicated that these DEGs played a vital in cell surface interactions at the vascular wall and extracellular matrix organization. Ten genes, HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3, and PRKCA in the center of the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network were associated with GDM, according to ROC analysis. Finally, the most significant small molecules were predicted based on molecular docking. Our results indicated that HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3, and PRKCA could be the potential novel biomarkers for GDM diagnosis, prognosis and the promising therapeutic targets. The current might be essential to understanding the molecular mechanism of GDM initiation and development.

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VCAM-1, ICAM-1 and Selectins in Gestational Diabetes Mellitus and the Risk for Vascular Disorders

Cited by 20 publications

References 32 publications

The relationship between advanced glycation end products and gestational diabetes: A systematic review and meta-analysis

The relationship between advanced glycation end products and gestational diabetes: A systematic review and meta-analysis

Endothelial Dysfunction in Pregnancy Complications

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

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