Polymorphism in the 3′-UTR of LIF but Not in the ATF6B Gene Associates with Schizophrenia Susceptibility: a Case-Control Study and In Silico Analyses

Moudi, Mahdiyeh; Sargazi, Saman; Nia, Milad Heidari; Saravani, Ramin; Shirvaliloo, Milad; Shakiba, Mansour

doi:10.1007/s12031-020-01616-6

Cited by 14 publications

(6 citation statements)

References 36 publications

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“…The third selected SNP (rs7459185) is a downstream gene variant that is located on the near 3′UTR. Genetic variations in the 3′UTRs of genes can alter their expression by affecting miRNA binding and mRNA stability [ 42 , 44 , 45 ]. Although rs7459185 is outside of the 3′UTR sequence, a bioinformatics analysis showed a decrease in the HSPB1 mRNA expression levels in the presence of the rs7459185 CC genotype [ 46 ].…”

Section: Discussionmentioning

confidence: 99%

HSPB1 Gene Variants and Schizophrenia: A Case-Control Study in a Polish Population

et al. 2022

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Schizophrenia (SCZ) is a severe psychiatric disorder that has a significant genetic component. HSPB1 (HSP27) is known for its neuroprotective functions under stress conditions and appears to play an important role during the development of the central nervous system, which is in agreement with the neurodevelopmental hypothesis of SCZ. The aim of the present case-control study was to investigate whether HSPB1 variants contribute to the risk and clinical features (age of onset, symptoms, and suicidal behavior) of SCZ in a Polish population. To the best of our knowledge, this is the first study that investigated the association between the HSPB1 polymorphisms and SCZ. Three SNPs of HSPB1 (rs2868370, rs2868371, and rs7459185) were genotyped in a total of 1082 (403 patients and 679 controls) unrelated subjects using TaqMan assays. The results showed that the genotypes, alleles, and haplotypes of the three SNPs were not significantly different between the schizophrenic patients and healthy controls either in the overall analysis or in the gender-stratified analysis (all p > 0.05 ). However, we did find a significant effect of the rs2868371 genotype on the age of onset, negative symptoms, and disorganized symptoms in the five-factor model of PANSS (all p < 0.01 ). Post hoc comparisons showed that carriers of the rs2868371 G/G genotype had significantly higher negative and disorganized factor scores than those with the C/G and C/C genotypes, respectively. Further investigations with other larger independent samples are required to confirm our findings and to better explore the effect of the HSPB1 polymorphisms on the risk and symptomatology of SCZ.

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Section: Discussionmentioning

confidence: 99%

HSPB1 Gene Variants and Schizophrenia: A Case-Control Study in a Polish Population

et al. 2022

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“…A previous study has indicated that the LIF gene impairs brain development in mice related to the mature and immature nervous system. 69 Butler and Moudi’s studies showed that genetic variations in the LIF gene may be related to neurodevelopmental disorders and related to increased susceptibility to schizophrenia and the degeneration of working memory function. 69 , 70 Thus, we suggest that the TBX1 and LIF genes may be candidates for ASD and deserve more focus and analysis.…”

Section: Discussionmentioning

confidence: 99%

Multiple Recurrent Copy Number Variations (CNVs) in Chromosome 22 Including 22q11.2 Associated with Autism Spectrum Disorder

Alhazmi¹,

Alzahrani²,

Farsi³

et al. 2022

PGPM

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“…Husemoen et al [52], Zhang et al [53], Hartz et al [54], Słomiń ki et al [55], Johansson et al [56], sPan et al [57], Lopez-Sanz et al [58], Grant, [59], Słomiń i et al [60], Galán et al sk [61], Jordan et al [62], Winkler et al [63], Yip et al [64], Crookshank et al [65], Lempainen et al [66], Qu and Polychronakos, [67], Morrison et al [68], Zhang et al [69], Gerlinger-Romero et al [70], Belanger et al [71], Dieter et al [72], Wanic et al [73], Ushijima Wanic et al [74], Guo et al [75], Davis et al [76], Elbarbary et al [77], Villasenor et al [78], Zhang et al [79], Lee et al [80], Zhi et al [81], Li Calzi et al [82], Sebastiani et al [83], Cherney et al [84], Doggrell, [85] and Yanagihara et al [86] found that FLG (filaggrin), FGF21, PEMT (phosphatidylethanolamine N-methyltransferase) KL (klotho), CEL (carboxyl ester lipase), FOSL2, STAT1, TCF7L2, TP53, EGFR (epidermal growth factor receptor), ETS1, KCNJ8, DEAF1, GCG (glucagon), IKZF4, OAS1, IRS1, ABCG2, FBXO32, PTBP1, BACH2, CNDP2, KLF11, MT1E, DPP4, SLC29A3, RGS16, MAS1, GCGR (glucagon receptor), HLA-C, VASP (vasodilator stimulated phosphoprotein), CCR2, PTGS2, GLP1R and JMJD6 are involved in the progression of T1DM. Vassilev et al [87], Qin et al [88], Ma et al [89], West et al [90], Hoffmann et al [91], Deary et al [92], Belangero et al [93], Jung et al [94], Tang et al [95], Goodier et al [96], Petyuk et al [97], Roux et al [98], Castrogiovanni et al [99], Suleiman et al [100], Haack et al [101], Kwiatkowski et al [102], Pinacho et al [103], Luo et al [104], He et al [105], Moudi et al [106], Thevenon et al [107], Li et al [108], Reitz et al [109], Jenkins and Escayg [110], Letronne et al [111], Ma et al [112], Chabbert et al [113], Abramsson et al [114], Aeby...…”

Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Bm¹,

Cm²

2021

Preprint

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Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were then performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis and RT-PCR confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

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Polymorphism in the 3′-UTR of LIF but Not in the ATF6B Gene Associates with Schizophrenia Susceptibility: a Case-Control Study and In Silico Analyses

Cited by 14 publications

References 36 publications

HSPB1 Gene Variants and Schizophrenia: A Case-Control Study in a Polish Population

HSPB1 Gene Variants and Schizophrenia: A Case-Control Study in a Polish Population

Multiple Recurrent Copy Number Variations (CNVs) in Chromosome 22 Including 22q11.2 Associated with Autism Spectrum Disorder

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

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