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10 February 2020 : Clinical Research  

Peripheral Blood Leukocyte RNA-Seq Identifies a Set of Genes Related to Abnormal Psychomotor Behavior Characteristics in Patients with Schizophrenia

Yunqiao Zhang1ABCDEF, Xu You1ABCF, Siwu Li2ABCD, Qing Long1BCD, Yun Zhu1BC, Zhaowei Teng1AEFG*, Yong Zeng1ABEFG

DOI: 10.12659/MSM.922426

Med Sci Monit 2020; 26:e922426

Abstract

BACKGROUND: Schizophrenia is a multigene disease with a complex etiology and different clinical manifestations. It is of great significance to understand the etiology and pathogenesis of schizophrenia patients from different clinical dimensions and to interpret the potential molecular changes of schizophrenia patients from different clinical dimensions.

MATERIAL AND METHODS: RNA-Seq was performed on peripheral blood leukocytes of 50 patients with schizophrenia and 50 healthy controls. Phenotypic information of patients with schizophrenia was collected during blood sampling. Differentially expressed genes (DEGs) were screened by the edgeR package of R software. To better analyze the correlation between DEG expression values, explore the potential association between differential genes and clinical dimensions of schizophrenia, and identify hub genes, we constructed a DEG co-expression network using weighted gene co-expression network analysis (WGCNA).

RESULTS: We provide the transcription profiles of peripheral blood leukocytes in patients with schizophrenia and found a gene module (including 89 genes) closely related to the clinical dimension of abnormal psychomotor behavior in schizophrenia.

CONCLUSIONS: The findings enhance our understanding of the biological processes of schizophrenia, enabling us to identify specific clinical dimensions of genes for diagnosis and prognostic markers and possibly for targeted therapy.

Keywords: Gene Expression Profiling, Leukocytes, Schizophrenia, Behavior, Cluster Analysis, Gene Expression Regulation, gene ontology, Gene Regulatory Networks, Genome-Wide Association Study, Protein Interaction Maps, Psychomotor Performance, RNA, Messenger, RNA-Seq

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750