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. 2018 Sep 7:12:433-442.
doi: 10.1016/j.omtn.2018.05.026. Epub 2018 Jul 11.

Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia

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Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia

Lei Cai et al. Mol Ther Nucleic Acids. .

Abstract

Schizophrenia (SCZ) is a devastating genetic mental disorder. Identification of the SCZ risk genes in brains is helpful to understand this disease. Thus, we first used the minimum Redundancy-Maximum Relevance (mRMR) approach to integrate the genome-wide sequence analysis results on SCZ and the expression quantitative trait locus (eQTL) data from ten brain tissues to identify the genes related to SCZ. Second, we adopted the variance inflation factor regression algorithm to identify their interacting genes in brains. Third, using multiple analysis methods, we explored and validated their roles. By means of the aforementioned procedures, we have found that (1) the cerebellum may play a crucial role in the pathogenesis of SCZ and (2) ITIH4 may be utilized as a clinical biomarker for the diagnosis of SCZ. These interesting findings may stimulate novel strategy for developing new drugs against SCZ. It has not escaped our notice that the approach reported here is of use for studying many other genome diseases as well.

Keywords: EIF2; GO; GTEx; ITIH4; SNP; YWHA; brain; eQTL; mRMR; schizophrenia.

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Figures

Figure 1
Figure 1
Association of eQTL with Corresponding Genes Based on the BrainCloud eQTL Database (A) rs17693963 with ZNF 192P1. (B) rs67682613 with CYP21A1P.
Figure 2
Figure 2
Venn Diagram Comparison among Three Groups of Genes Known SCZ genes reported by GWASs, identified SCZ candidate genes in the present study, and differentially expressed genes in PBMCs. Error bars mean SD.
Figure 3
Figure 3
The Top Eight Signaling Pathways in which All Identified Genes in the Present Study Are Enriched
Figure 4
Figure 4
Flow Chart Detailing the Inclusion Process to the Present Study

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References

    1. Cai L., Chen T., Yang J., Zhou K., Yan X., Chen W., Sun L., Li L., Qin S., Wang P. Serum trace element differences between Schizophrenia patients and controls in the Han Chinese population. Sci. Rep. 2015;5:15013. - PMC - PubMed
    1. Cai L., Yang Y.H., He L., Chou K.C. Modulation of Cytokine Network in the Comorbidity of Schizophrenia and Tuberculosis. Curr. Top. Med. Chem. 2016;16:655–665. - PubMed
    1. Flint J., Munafò M. Schizophrenia: genesis of a complex disease. Nature. 2014;511:412–413. - PubMed
    1. Huang T., Liu C.L., Li L.L., Cai M.H., Chen W.Z., Xu Y.F., O’Reilly P.F., Cai L., He L. A new method for identifying causal genes of schizophrenia and anti-tuberculosis drug-induced hepatotoxicity. Sci. Rep. 2016;6:32571. - PMC - PubMed
    1. Jansen R.C., Nap J.P. Genetical genomics: the added value from segregation. Trends Genet. 2001;17:388–391. - PubMed

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