Based On RNA-sequencing To Explore The Mechanism Of Clozapine-induced Metabolic Syndrome: A Paired Case-control Study

Background and Objective Schizophrenia is a group of severe mental diseases with unknown etiology,which has the characteristics of high disability rate and heavy social burden.Clozapine has outstanding curative effect in the treatment of schizophrenia,but it is easy to destroy the balance of glucose and lipid metabolism in the body after long-term use,causing secondary adverse reactions such as weight gain,abdominal obesity,hyperglycemia,hypertriglyceridemia and so on,which adds extra medical burden to the patient’s family and society.At present,the mechanism of metabolic syndrome caused by clozapine is not completely clear.Candidate gene association analysis and genome-wide association studies have identified a number of genes that may be associated with clozapine-induced metabolic syndrome.The purpose of this study is to explore the mechanism of metabolic syndrome caused by clozapine by analyzing the difference of gene expression level of schizophrenia patients with or without metabolic syndrome,so as to provide a scientific basis for clinicians to prevent and diagnose metabolic syndrome in the treatment of mental diseases.Methods According to the Diagnostic and Statistical Manual(4th Edition)and the 2016 Chinese adult dyslipidemia prevention guide,the long-term hospitalized chronic patients in Shanghai Mental Health Center were screened.10 schizophrenic patients with metabolic syndrome(case group)and 10 schizophrenic patients without metabolic syndrome(control group)were selected.The two groups were paired according to age and gender,with an age difference of less than 2 years old.All subjects were assessed for mental status on the positive and negative symptom scale and the clinical overall impression scale-severity scale.Meanwhile,peripheral venous blood was extracted for transcriptome sequencing.The T test andχ~2test were used to analyze the subjects’general clinical data and scale scores.The transcriptome sequencing data were analyzed with the R language and the corresponding toolkit,and the differentially expressed gene profiles of the two groups of patients were obtained.The differentially expressed genes were annotated with function and pathway analysis,and the weighted gene co-expression network was used to explore the genetic mechanism of metabolic syndrome caused by antipsychotics.And random forest method was applied to establish prediction model to guide clinical treatment.Results 1.The expression matrix of 57,773 genes was obtained from20 samples.A total of 1019 differentially expressed genes were screened,including 535 up-regulated differentially expressed genes and 484 down-regulated differentially expressed genes.2.Differentially expressed genes were mainly distributed in azurophil granule,primary lysosome,secretory granule,vesicle lumen and cytoplasmic membrane-bounded vesicle lumen,and involved in biological processes including immune response,morphological changes and material metabolism.The reactome pathways involved in differentially expressed genes are biological oxidations and defensins.3.Eight m RNA gene modules,ranging in size from 55 to 271,were identified by weighted gene co-expression network analysis.The yellow,red and turquoise modules were negatively correlated with the metabolic syndrome,while the black,green,blue and brown modules were positively correlated with metabolic syndrome.Hub genes include RP11.611O2.6,ACPL2,TRAV12.2,MMP8,PGBD4P1,TMEM261,and BDNF.4.The prediction model including 7 genes(AP000318.2,MRS2P2,RP11.347C18.5,SLC2A5,RP11.91A18.4,TMEM261,GLIPR1L2)was generated by using random forest method.The area under the curve of the working curve of the model subjects was 1,that is,the sensitivity was 100%,and the specificity was 100%.Conclusions 1.There is gene differential expression between schizophrenics with or without metabolic syndrome.The individual difference of metabolic syndrome caused by clozapine is related to the differential expression gene.2.RP11.611O2.6,ACPL2,TRAV12.2,MMP8,PGBD4P1,TMEM261and BDNF gene expression are closely related to the metabolic syndrome caused by clozapine.3.RNA sequencing combined with random forest can screen out differentially expressed genes with potential clinical application value.