Lack of genetic association of the TGM2 gene with schizophrenia in a Chinese population

Wang, Jiaxin; Liu, Yang; Wang, Zhenqi; Du, Wei; Li, Hui; Zhao, Xiyang; Zhao, Xiaoxia; Zhang, Xuan; Wei, Jun

doi:10.1097/ypg.0000000000000103

Cited by 6 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…61 TGM2 SNPs and a haplotype showed nominal association ( P ~0.0004) to schizophrenia in a family-based study of 131 British family trios, 62 though no association was found in a Chinese case–control study. 63 TGM2 has been reported (in a patent, US20070015152) to be upregulated in the brain (anterior cingulate cortex) of schizophrenia cases versus controls. Celiac disease has an epidemiological association with schizophrenia; gluten-free diets occasionally reduce psychotic symptoms; and circulating gliadin antibodies are elevated in schizophrenia cases versus controls (reviewed in Wang et al 63 ).…”

Section: Discussionmentioning

confidence: 99%

“…63 TGM2 has been reported (in a patent, US20070015152) to be upregulated in the brain (anterior cingulate cortex) of schizophrenia cases versus controls. Celiac disease has an epidemiological association with schizophrenia; gluten-free diets occasionally reduce psychotic symptoms; and circulating gliadin antibodies are elevated in schizophrenia cases versus controls (reviewed in Wang et al 63 ).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis

et al. 2017

View full text Add to dashboard Cite

We undertook an RNA sequencing (RNAseq)-based transcriptomic profiling study on lymphoblastoid cell lines of a European ancestry sample of 529 schizophrenia cases and 660 controls, and found 1058 genes to be differentially expressed by affection status. These differentially expressed genes were enriched for involvement in immunity, especially the 697 genes with higher expression in cases. Comparing the current RNAseq transcriptomic profiling to our previous findings in an array-based study of 268 schizophrenia cases and 446 controls showed a highly significant positive correlation over all genes. Fifteen (18%) of the 84 genes with significant (false discovery rate<0.05) expression differences between cases and controls in the previous study and analyzed here again were differentially expressed by affection status here at a genome-wide significance level (Bonferroni P<0.05 adjusted for 8141 analyzed genes in total, or P<~6.1 × 10−6), all with the same direction of effect, thus providing corroborative evidence despite each sample of fully independent subjects being studied by different technological approaches. Meta-analysis of the RNAseq and array data sets (797 cases and 1106 controls) showed 169 additional genes (besides those found in the primary RNAseq-based analysis) to be differentially expressed, and provided further evidence of immune gene enrichment. In addition to strengthening our previous array-based gene expression differences in schizophrenia cases versus controls and providing transcriptomic support for some genes implicated by other approaches for schizophrenia, our study detected new genes differentially expressed in schizophrenia. We highlight RNAseq-based differential expression of various genes involved in neurodevelopment and/or neuronal function, and discuss caveats of the approach.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis

et al. 2017

View full text Add to dashboard Cite

show abstract

“…SOX10 [284], MOG (myelin oligodendrocyte glycoprotein) [285], TGM2 [286], LRRK2 [287], CD22 [288], GPR17 [120], TF (transferrin) [289], RELN (reelin) [290], DYSF (dysferlin) [291], HOXA5 [292], REN (renin) [293], CNTN1 [294], SLC1A1 [295], TLR2 [296], WT1 [297], MOBP (myelin associated oligodendrocyte basic protein) [298], MYRF (myelin regulatory factor) [299], IL7R [300], MBP (myelin basic protein) [151], SHH (sonic hedgehog signaling molecule) [301], NTSR1 [302], BMP2 [303], ERMN (ermin) [304], MMP3 [305], HLA-DRB5 [306], HLA-DMB [307], HLA-DRB1 [308], HLA-DRA [309], CASP1 [310], OAS1 [311], DCLK1 [312], EGFR (epidermal growth factor receptor) [313], COMT (catechol-O-methyltransferase) [314] and CIITA (class II major histocompatibility complex transactivator) [315] have a significant prognostic potential in multiple sclerosis. SOX10 [316], MOG (myelin oligodendrocyte glycoprotein) [317], CNGB1 [318], TGM2 [319], LRRK2 [320], CHRNA4 [321], RELN (reelin) [322], HTR2C [323], RIT2 [324], ACSL6 [325], C6 [326], REN (renin) [327], OLIG2 [328], TLR2 [329], SEMA3D [330], PCDH15 [331], FGF14 [332], TSPAN8 [333], ACAN (aggrecan) [334], SHH (sonic hedgehog signaling molecule) [335], P2RX7 [336], NTSR1 [337], RBP4 [338], TACR3 [339], ERBB3 [340], ERMN (ermin) [341], CDH13 [342], CSMD1 [343], NTF3 [344], FRMPD4 [345], GRIA4 [346], GRIA2 [347], SNCB (synuclein beta) [348], NR3C2 [349], MMP3 [350], GABRB2 [351], HLA-DRB1 ...…”

Section: Discussionmentioning

confidence: 99%

Identification of key genes and signaling pathway in the pathogenesis of Huntington's disease via bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2024

Preprint

View full text Add to dashboard Cite

Huntington's disease (HD) is the primary cause of progressive motor deficits, psychiatric symptoms, and cognitive impairment. The exact molecular mechanisms of HD pathogenesis are largely unknown. This investigation aims to identify the hub genes, miRNA and TFs in HD and explore their potential molecular regulatory network. Next generation sequencing (NGS) dataset (GSE105041) was extracted from the Gene Expression Omnibus (GEO) database. An integrated bioinformatics pipeline including identification of differentially expressed genes (DEGs), Gene ontology and REACTOME pathway enrichment analysis, protein-protein interaction (PPI) network and module analysis, miRNA-hub gene regulatory network analysis and TF-hub gene regulatory network analysis, and receiver operating characteristic curve (ROC) analysis were applied to identify hub genes, miRNA and TFs, and key drivers of HD pathogenesis. We identified 958 DEGs in the discovery phase, consisting of 479 up regulated genes and 479 down regulated genes. GO and REACTOME enrichment analyses of the 479 up regulated genes and 479 down regulated genes showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and MHC class II antigen presentation. Further analysis of the PPI network using Cytoscape and PEWCC plugins identified 10 hub genes, including LRRK2, MTUS2, HOXA1, IL7R, ERBB3, EGFR, TEX101, WDR76, NEDD4L and COMT. Possible target miRNAs and TFs, including hsa-mir-1292-5p, hsa-mir-4521, ESRRB and SREBF1, were predicted by constructing a miRNA-hub gene regulatory network analysis and TF-hub gene regulatory network. This investigation used bioinformatics methods to explore the molecular pathogenesis of HD, and identified potential molecular markers. These molecular markers might provide novel ideas and methods for the early diagnosis, treatment, and monitoring of HD.

show abstract

“…Immune system [51], axon guidance [52], metabolism [53], diseases of metabolism [54] and neuronal system [55] were lined with advancement of BD. Altered expression of SLC6A9 [56] and RHD (Rh blood group D antigen) [57], CHRFAM7A [58], ANXA3 [59], SLC1A5 [60], KCNH2 [61], HP (haptoglobin) [62], SELENBP1 [63], SNCA (synuclein alpha) [64], TGM2 [65], PINK1 [66], B2M [67], QPCT (glutaminyl-peptide cyclotransferase) [68], CBS (cystathionine beta-synthase) [69], NQO2 [70], GLRX5 [71], BASP1 [72], GAS7 [73], GPX1 [74], OLIG2 [75], RPTN (repetin) [76], IL33 [77], SOX10 [78], GRIK1 [79], ZFPM2 [80], SHANK3 [81], ERBB3 [82], ARC (activity regulated cytoskeleton associated protein) [83], GFAP (glial fibrillary acidic protein) [84], PLAT (plasminogen activator, tissue type) [85], GRIK5 [86], CACNB2 [87], NRXN2 [88], TERT (telomerase reverse transcriptase) [89], GNB3 [90], L1CAM [91], EGR3 [92], CAV1 [93], CACNA1B [94], MAGI1 [95], KIR2DL1 [96], PAH (phenylalanine hydroxylase) [97] and CYP3A5 [98] have been shown in schizophrenia. Recent studies showed that SLC6A9 [99], FKBP1B [100], S100A12 [101], SLC6A19 [102], TXN (thioredoxin) [103], TLR9 [104], HP (haptoglobin) [105], ARG1 [106], PINK1 [107], B2M [108], C5AR1 [109], MYADM (myeloid associated differentiation marker) [110], CBS (cystathionine beta-synthase) [111], GPX1 [112], SIAH2 [113], PRDX2 [114], RDH8 [115], CYP11B2 [116], RARRES2 [117], NOX1 [118], IL33 [119], OTC (ornithine transcarbamylase) [120], CYP1A1 […”

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

Lack of genetic association of the TGM2 gene with schizophrenia in a Chinese population

Cited by 6 publications

References 21 publications

Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis

Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis

Identification of key genes and signaling pathway in the pathogenesis of Huntington's disease via bioinformatics and next generation sequencing data analysis

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

Contact Info

Product

Resources

About