Novel mutations of TCTN3/LTBP2 with cellular function changes in congenital heart disease associated with polydactyly

Chen, Huanxin; Yang, Ziyue; Hou, Hongying; Wang, Jun; Wang, Xiuli; Yang, Qin; Liu, Lin; He, Guo‐Wei

doi:10.1111/jcmm.15950

Cited by 18 publications

(12 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A large amount of evidence shows that genetic factors conduce to most CHD (Chen et al, 2017; Chen et al, 2020; Saliba et al, 2020; Zaidi & Brueckner, 2017). The promoter is a component of a gene that controls the onset and extent of gene expression, playing a key role in transcriptional regulation.…”

Section: Introductionmentioning

confidence: 99%

Functional significance of novel variants of the MEF2C gene promoter in congenital ventricular septal defects

Zeng

Chen

Liu

et al. 2022

American J of Med Genetics Pt A

Self Cite

View full text Add to dashboard Cite

Ventricular septal defect (VSD) is the most common congenital heart disease.Although the coding region of MEF2C is highly relevant to cardiac malformations, the role of MEF2C gene promoter variants in VSD patients has not been genetically investigated. We investigated the role of MEF2C gene promoter variants in 400 Han Chinese subjects (200 patients with isolated and sporadic VSD and 200 healthy controls). The promoter region of the MEF2C gene was sequenced that identified 10 variants. Expression vectors encompassing the variants and the firefly luciferase reporter gene plasmid (pGL3-basic) were constructed and subsequently transfected into HEK-293 cells. The luciferase activities were measured by Dual-luciferase reporter assay system. MEF2C gene promoter transcriptional activity was significantly reduced in 4 of the 10 variants in HEK-293 cells (P < 0.05). In addition, the JASPAR database was used to perform bioinformatics analysis, which showed that these variants disrupt the putative binding sites of transcription factors and affected the expression of MEF2C protein. This study for the first time identified the variants in the promoter of the MEF2C gene in Han Chinese population and revealed the role of these variants in the formation of VSD.

show abstract

Section: Introductionmentioning

confidence: 99%

Functional significance of novel variants of the MEF2C gene promoter in congenital ventricular septal defects

Zeng

Chen

Liu

et al. 2022

American J of Med Genetics Pt A

Self Cite

View full text Add to dashboard Cite

show abstract

“…Previous studies have reported that RHD (Rh blood group D antigen) [154], S100A12 [155], TXN (thioredoxin) [156], TLR9 [157], S100P [158], TAGLN2 [159], S100A9 [160], CA1 [161], HP (haptoglobin) [162], RPL39 [163], F5 [164], PINK1 [165], B2M [166], S100A11 [167], SLC4A1 [168], CBS (cystathionine beta-synthase) [169], AHSP (alpha hemoglobin stabilizing protein) [170], F12 [171], EPHB4 [172], NFE2 [173], VRK1 [174], GPX1 [175], FOXA1 [176], CYP11B2 [177], NOX1 [178], IL33 [179], NPHS1 [180], OTC (ornithine transcarbamylase) [181], SULF1 [182], CYP1A1 [183], DCN (decorin) [184], ADAMTS7 [185], WNT4 [186], LAMA4 [187], SCN4A [188], CACNB2 [189], GNB3 [190], ENPEP (glutamyl aminopeptidase) [191], WNK4 [192], FOXC1 [193], PAX8 [194], ROBO1 [195], CXCL8 [196], PAPPA2 [197], LOX (lysyl oxidase) [198], NOSTRIN (nitric oxide synthase trafficking) [199], MUC16 [200], MIOX (myo-inositol oxygenase) [201], CYP11A1 [202] and CYP3A5 [203] are involved in the pregnancy complications. Modification in the activity and expression of RHD (Rh blood group D antigen) [204], S100A12 [205], TLR9 [206], ANXA3 [207], S100P [208], TAGLN2 [209], S100A9 [210], KCNH2 [211], HP (haptoglobin) [212], SELENBP1 [213], TANGO2 [214], PINK1 [215], TFR2 [216], B2M [217], LTBP2 [218], PGLYRP1 [219], HRH2 [220], CLEC5A [221], PLSCR4 [222], S100A11 [223], PPBP (pro-platelet basic protein) [224], RAP1GAP […”

Section: Discussionmentioning

confidence: 99%

Identification of Key Genes and Biological Pathways in Bipolar Disorder by Bioinformatics and Next Generation Sequencing Data Analysis

Vastrad¹,

Vastrad²

2022

Preprint

View full text Add to dashboard Cite

Bipolar disorder (BD), also known as psychiatric disorder, affects millions of people all over the world. The aim of this investigation was to screen and verify hub genes involved in BD as well as to explore potential molecular mechanisms. The next generation sequencing (NGS) dataset GSE124326 was downloaded from the Gene Expression Omnibus (GEO) database, which contained 480 samples, including 240 BD and 240 normal controls. Differentially expressed genes (DEGs) were filtered and subjected to gene ontology (GO) and pathway enrichment analyses. A protein–protein interaction (PPI) network and module analysis were used to identify hub genes. The miRNA-hub gene regulatory network and TF-hub gene regulatory network were also constructed. Receiver operating characteristic curve (ROC) analysis was used to validate hub genes. In this work, 957 DEGs, including 477 up regulated and 480 down regulated, were obtained from NGS data. The GO and pathway enrichment analyses of the DEGs showed that the up regulated genes were enriched in the neutrophil degranulation, immune system, transport, cytoplasm and enzyme regulator activity, and the down regulated genes were enriched in extracellular matrix organization, diseases of metabolism, multicellular organismal process, cell periphery and metal ion binding. Finally, through analyzing the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, we screened hub genes UBB, UBE2D1, TUBA1A, RPL11, RPS24, NOTCH3, CAV1, CNBD2, CCNA1 and MYH11 by the Cytoscape software. The current investigation illustrates a characteristic NGS data in BD, which might contribute to the interpretation of the progression of BD and provide novel biomarkers and therapeutic targets for BD.

show abstract

“…HLA-DRA [148], SERPINA1 [149], ABHD12 [150], IMPA2 [151], ARSA (arylsulfatase A) [152], LRFN5 [153], PLXNA4 [154], CHL1 [155], ITPKB (inositol-trisphosphate 3-kinase B) [156], PTN (pleiotrophin) [157], LAMA2 [158], CDH6 [159] and A2M [160] have been shown to have an important role in neurological disorders, but these genes might be associated with progression of T2DM. HLA-F [161], HLA-H [162], FGA (fibrinogen alpha chain) [163], HSPA1B [164], MRC1 [165], DAB2IP [166], KCNJ8 [167], KLKB1 [168], CXCL2 [169], SERPINE2 [170], ADH1C [171], AMBP (alpha-1-microglobulin/bikunin precursor) [172], NR4A2 [173], TYMP (thymidine phosphorylase) [174], TFRC (transferrin receptor) [175], PLAU (plasminogen activator, urokinase) [176], COL6A2 [177], COL15A1 [178], ABI3BP [179], NEXN (nexilin F-actin binding protein) [180], S1PR1 [181], THY1 [182], COL4A1 [183], COL5A2 [184], ADAMTS2 [185], ECM1 [186] and LTBP2 [187] have been found to be differentially expressed in cardiovascular diseases, but these genes might be linked with progression of T2DM. CCL20 [188], CRH (corticotropin releasing hormone) [189], SPP1 [190], LDLR (low density lipoprotein receptor) [191], RORA (RAR related orphan receptor A) [192], LYZ (lysozyme) [193], PTPRN2 [194], DAPK2 [195], OIP5 [196], PON3 [197], NR4A3 [198], VCAN (versican) [199], CNTNAP2 [200], IL1RAP [201], GLI2 [202], CDH13 [203], AEBP1 [204], BGN (biglycan) [205], LOX (lysyl oxidase) [206], IL1RL1 [207] and LUM (lumican) [208] were found to be involved in advancement of obesity, but these genes might be key for development of T2DM.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics analysis of potential key genes and mechanisms in type 2 diabetes mellitus

Vastrad¹,

Vastrad²

2021

Preprint

View full text Add to dashboard Cite

Type 2 diabetes mellitus (T2DM) is etiologically related to metabolic disorder. The aim of our study was to screen out candidate genes of T2DM and to elucidate the underlying molecular mechanisms by bioinformatics methods. Expression profiling by high throughput sequencing data of GSE154126 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between T2DM and normal control were identified. And then, functional enrichment analyses of gene ontology (GO) and REACTOME pathway analysis was performed. Protein protein interaction (PPI) network and module analyses were performed based on the DEGs. Additionally, potential miRNAs of hub genes were predicted by miRNet database. Transcription factors (TFs) of hub genes were detected by NetworkAnalyst database. Further, validations were performed by receiver operating characteristic curve (ROC) analysis and real time polymerase chain reaction (RT PCR). In total, 925 DEGs were identified in T2DM, including 447 up regulated genes and 478 down-regulated genes. Functional enrichment analysis results showed that up regulated DEGs were significantly enriched in defense response, neutrophil degranulation, cell adhesion and extracellular matrix organization. The top 10 hub genes, JUN, VCAM1, RELA, U2AF2, ADRB2, FN1, CDK1, TK1, A2M and ACTA2 were identified from the PPI network, modules, miRNA hub gene regulatory network and TF hub gene regulatory network. Furthermore, ROC analysis and RT PCR revealed that JUN, VCAM1, RELA, U2AF2, ADRB2, FN1, CDK1, TK1, A2M and ACTA2 might serve as biomarkers in T2DM. Bioinformatics analysis is a useful tool to explore the molecular mechanism and pathogenesis of T2DM. The identified hub genes may participate in the onset and advancement of T2DM and serve as therapeutic targets.

show abstract

Novel mutations of TCTN3/LTBP2 with cellular function changes in congenital heart disease associated with polydactyly

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 18 publications

References 31 publications

Functional significance of novel variants of the MEF2C gene promoter in congenital ventricular septal defects

Functional significance of novel variants of the MEF2C gene promoter in congenital ventricular septal defects

Identification of Key Genes and Biological Pathways in Bipolar Disorder by Bioinformatics and Next Generation Sequencing Data Analysis

Bioinformatics analysis of potential key genes and mechanisms in type 2 diabetes mellitus

Contact Info

Product

Resources

About