Molecular Epidemiological Study Of Peripheral Blood MiRNAs As Biomarkers Of Schizophrenia

Schizophrenia(SCZ)is a chronic,severe mental disorder.According to its characteristics,the symptoms can be divided into positive and negative,and there are great differences in clinical manifestations and outcomes.At present,the diagnosis of SCZ is mainly based on a series of typical syndromes,psychiatric history and clinical observation,and no stable biomarkers are available.Early diagnosis may effectively control clinical symptoms before serious complications and help improve their longterm prognosis.Therefore,it is particularly urgent to explore objective new biomarkers.The use of antipsychotic drugs is the current first-line treatment for schizophrenia.However,individual differences in clinical response to drug therapy remain a key issue in the management of patients with SCZ.Domestic and foreign scholars have proposed a variety of theories on the origin of SCZ,such as genetic factors,environmental risk factors,hypothesis of neurodevelopmental abnormalities,abnormal brain structure changes,neurobiochemical abnormalities and inflammatory response theory,etc.At present,the potential etiology and pathogenic mechanism of schizophrenia are still unclear.Peripheral blood miRNA has the advantages of less trauma,easy monitoring and stability.Therefore,this study will use molecular epidemiological methods to find and verify stable diagnostic miRNA biomarkers for SCZ.The genetic heterogeneity of positive and negative symptoms in SCZ patients was analyzed.To explore the contribution of miRNA to the regulation of its target genes in the etiology of SCZ.To provide clues for the early diagnosis,treatment and etiology of SCZ.Objective:1.To obtain miRNA expression profile data from peripheral blood of schizophrenia(SCZ)patients and healthy controls using miRNA-Seq,screen and validate key differentially expressed miRNAs,construct a diagnostic model for SCZ,and evaluate its performance.2.To analyze the correlation between the expression levels of peripheral blood hub miRNAs and the severity of clinical symptoms as well as the response to antipsychotic drug treatment in patients with schizophrenia(SCZ),and to identify diagnostic biomarkers in peripheral blood of SCZ patients.3.To investigate the heterogeneity of positive and negative symptoms in schizophrenia(SCZ)patients from the perspectives of weighted gene co-expression modules,immune cell composition ratios,and chemical and drug correlations,and to construct a symptom-related miRNA-mRNA regulatory network to analyze the etiology and mechanisms of heterogeneous symptoms.4.To further analyze the temporal and spatial expression patterns,expression locations,and involved pathways of candidate target genes of miR-30e-3p,which exhibited the most significant intergroup difference and the highest fold change identified in the first part.Additionally,to investigate the association between single nucleotide polymorphisms(SNPs)and their interactions with SCZ susceptibility in these candidate target genes.5.To identify the direct target of miR-30e-3p regulation and explore the functional role of their regulatory relationship in SH-SY5Y cell proliferation,apoptosis,differentiation,and neurite formation.Furthermore,to investigate the contribution of miR-30e-3p and its target gene in the etiology of schizophrenia(SCZ).Methods:1.Using high-throughput sequencing data of peripheral blood miRNAs from 15 patients with first-stage SCZ and 15 healthy controls(HC,healthy control),standardized differential analysis was performed to obtain stable and differentially expressed miRNAs(DEMs).The miRNA co-expression module was constructed by weighted gene co-expression network analysis(WGCNA)to verify its conformance.Scz-related modules and key mirnas were screened by module-trait correlation analysis.GO and KEGG pathway enrichment analysis and protein interaction network(PPI)analysis were performed to summarize the biological function of the module.2.Intersection of DEMs with key miRNAs in the modules was conducted using RTqPCR to verify their expression changes(validation samples:51SCZ,51HC),and hub miRNAs were obtained.logistic regression(LR),random forest(RF)and support vector machine(SVM)were respectively used to construct diagnostic models based on hub miRNA,and ROC curves were used to evaluate the effect.3.The basic information of the patients(51 SCZ cases)in the verification samples were collected,including the score of the Concise Psychiatric Scale(BPRS),Psychiatric Nursing Observation Scale(NOSIE),Social Dysfunction Screening Scale(SDSS),brain fluctuation analysis report,and the use of antipsychotic drugs,and the score changes before and after treatment were compared.Spearman correlation analysis was used to calculate the correlation between miRNA expression level and the scores of SCZ patients at admission and before and after treatment.4.The study subjects were divided into high and low expression groups according to miRNA expression levels,and the total score of each scale between the groups at admission,the score changes before and after treatment,and the relative power of neurotransmitters were compared.5.According to the decline rate of the patient scale score after treatment,the study subjects were divided into a responding group and a non-responding group,and the basic information and hub miRNA expression levels of patients between the groups were compared.ROC curves were used to evaluate the ability of target mirnas and mrnas to predict antipsychotic response in SCZ patients.6.The expression profiles of miRNA and mRNA in peripheral blood of 15 patients with first-onset SCZ were used to identify the co-expression modules associated with Positive and Negative Syndrome Scale(PANSS)scores by WGCNA.Heterogeneity between positive and negative symptoms was comprehensively confirmed through gene function enrichment of co-expression modules,gene-drug interaction analysis,immune cell composition analysis by Cibersort algorithm,and correlation analysis between hub miRNA expression level and PANSS.By predicting miRNA target genes associated with symptoms and analyzing the correlation between miRNA and mRNA expression levels,a symptom-related mirNA-mrna regulatory network was constructed,regulatory pairs were screened,and binding sites were predicted.7.The mRNA with significantly upregulated expression in the sequencing sample MRNA-SEQ was intersected with the predicted target genes of miR-30e-3p to obtain candidate target genes;RT-qPCR was used to detect the expression of candidate target genes in validated samples.The spatial and temporal expression patterns of miR-30e-3p candidate target genes in Human brain were analyzed using Human Protein Atls(HPA),BrainSpan and PsychENCODE databases.The expression levels of candidate target genes in large and small cell populations were compared using BRAINcode database.Reactome database release was used to predict the active paths of candidate target genes.8.A case-control study design was adopted,410 patients with SCZ and 389 healthy controls were selected as study objects,and the genotypes of miR-30e-3p candidate target genes were detected by MALDI-TOF-MS method.The distribution of SCZ was analyzed by Chi-square test and Logistic regression,and the correlation between relevant SNPS and their interactions with SCZ was discussed.9.Retinoic acid(RA)was used to induce SH-SY5Y cell differentiation,and the differentiation processing time was determined by observing the neurite length,and the differentiation effect was evaluated by examining the expression levels of neuronal marker genes MAPT,TUBB3 and SYP.SH-SY5Y cells were transfected with miR-30e-3p inhibitor,and the expression of candidate target genes was detected by RT-qPCR.Luciferase reporter gene assay was used to identify the binding site of miR-30e-3p and ABI1.10.Cells were transient transfected with miR-30e-3p mimic/mimic NC,miR-30e-3p inhibitor/inhibitor NC,and ABI1 overexpression plasmid/empty vector.siABI1/siNC was used to investigate the effects of miR-30e-3p and ABI1 on SHSY5Y cells.The effects of miR-30e-3p and ABI1 on the proliferation of SH-SY5Y cells were detected by CCK-8 assay.The apoptosis was detected by flow cytometry.The effect of cell differentiation on neurite growth induced by RA was detected.The expression abundance and location of neuron-specific protein β-tubulinⅢ(βtubulinⅢ)were detected by immunofluorescence assay.The rescue experiment verified the regulation of ABI1 by miR-30e-3p in the biological function of SHSY5Y cells.Results:1.Differential analysis showed that 49 miRNAs were up-regulated and 30 downregulated in peripheral blood of patients with SCZ.WGCNA consensus has 9 coexpression modules,and the conservative type is good.The blue module has the strongest correlation with SCZ,followed by pink and yellow modules.All three modules are enriched in FOXO,PI3K-Akt signaling pathway.2.In the verification samples,RT-qPCR was used to verify the expression changes of 11 miRNAs,among which the relative expression levels of miR-939-5p,miR4732-3p,let-7d-3p and miR-142-3p were significantly up-regulated in SCZ.miR30e-3p and miR-23a-3p were significantly down-regulated(P<0.05).3.Among the diagnostic models constructed based on miRNA,RF model had the best performance(AUC=0.8281).In the nomogram constructed by LR model,miR-30e-3p was the contribution variable with the highest score.Gini index based on RF model showed that the expression levels of miR-23a-3p and miR-30e-3p were the most important characteristics.4.The BPRS and NOSIE scores of SCZ patients were significantly reduced after 4-8 weeks of antipsychotic drug treatment.miR-30e-3p,miR-23a-3p and let-7d-3p were significantly negatively correlated with Δ BPRS(P<0.05).5.Among the 50 patients with SCZ,31 responded and 19 did not respond.The levels of miR-30e-3p and let-7d-3p in peripheral blood of response group were significantly lower than those of non-response group(P<0.05).ROC curve showed that miR-30e-3p had a good predictive effect on SCZ drug therapy response(AUC=0.774).The expression level of miR-30e-3p was negatively correlated with PANSS negative symptom score(r=-0.486,P=0.045).The expression of let-7d-3p was negatively correlated with positive symptoms(r=-0.548,P=0.046)and positively correlated with negative symptoms(r=0.685,P=0.027).6.WGCNA screened 6 mRNA co-expression modules,2 miRNA co-expression modules,and 10 hub genes were significantly correlated with SCZ positive symptoms.Five mRNA coexpression modules and eight hub genes were significantly associated with negative symptoms(P<0.05).Positive symptom related modules were significantly enriched in axonal guidance and actin skeleton regulatory pathways,while negative symptom related modules were significantly enriched in adaptive immune response,leukocyte migration and dopaminergic synapses(P<0.05).The symptom-related miRNA-mRNA regulatory network was confocal to 18 regulatory pairs that might be associated with positive symptoms in patients with SCZ.7.The mRNA significantly upregulated in MRNA-SEQ intersected with the target gene of miR-30e-3p to obtain 4 mrnas.RT-qPCR showed that ABI1,HMGBl and NMT1 were significantly up-regulated in verified SCZ samples(P<0.05).The temporal and spatial expression pattern analysis showed that ABI1 showed an obvious upward trend in the brain tissue within one year after birth.HMGB1 was highest at birth and then continued to decline,while NMT1 expression showed a significant upward trend 300 days after birth.Overexpression analysis showed that ABI1 protein may affect axon growth inhibition,nervous system development and other related pathways.8.Case-control studies showed that under the optimal model of ABI1-rs72629721,the risk of SCZ in subjects with genotype T/C was 1.42 times that of TT(95%CI:1.05-1.91,P=0.022).Under the optimal genetic model of NMT1rs2239923,the prevalence of SCZ in subjects with C/T genotype was 0.73 times that of TT or CC(95%CI:0.55-0.98,P=0.035).Gene interaction analysis showed that rs1360485/rs1053733/rs72629721 was the best model,and its interaction was not significantly associated with the risk of SCZ.9.After 5 days of RA treatment,SH-SY5Y cells showed mature neuronal phenotype,and the expression level of neuronal marker genes was significantly increased(P<0.05).RT-qPCR assay and double luciferase reporter gene assay confirmed the regulatory relationship between miR-30e-3p and ABI1 and identified the binding site.10.CCK-8 and apoptosis experiments showed that transfection of miR-30e-3p mimic or silence of ABI1 promoted the proliferation and apoptosis of SH-SY5Y cells,while miR-30e-3p inhibitor or overexpression of ABI1 inhibited cell proliferation and apoptosis.The cell differentiation experiment showed that the expression level of miR-30e-3p was significantly increased and the expression level of ABI1 was significantly decreased in RA treated cells.The expression of neuronal marker genes was significantly decreased after treatment with miR-30e-3p inhibitor or ABI1 overexpression plasmid,and the cells did not differentiate significantly(P<0.05).Immunofluorescence assay showed that β-tubulinⅢ was significantly decreased in SH-SY5Y cells transfected with miR-30e-3p inhibitor or overexpression of ABI1,and the expression location was limited to a small amount of cytoplasm.The expression of β-tubulinIII was significantly increased in cells transfected with miR-30e-3p mimic or silent ABI1,and the expression was located in the cytoplasm and neurite(P<0.05).The rescue series of experiments showed that silencing ABI1 mitigated the decline in cell viability,apoptosis,and inhibitory effect on neurite growth caused by down-regulation of miR-30e-3p.Conclusion:1.In this study,six hub mirnas(miR-30e-3p,miR-23a-3p,miR-939-5p,miR-4732-3p,miR-142-3p and let-7d-3p)were screened and verified as potential new blood diagnostic markers for SCZ.Among them,miR-30e-3p has a good predictive effect on the response to antipsychotic drugs in patients with SCZ,and can be used as a potential diagnostic biomarker in peripheral blood of SCZ.2.In this study,the random forest model constructed based on miRNA has the best prediction performance for SCZ.This model is expected to provide clues for the early diagnosis of SCZ,but it still needs further verification.3.The mutation from T to C at rs72629721 of ABI1 gene increased the risk of SCZ by 42.0%.The mutation from T to C at rs2239923 of NMT1 gene reduced the risk of SCZ by 27%.4.Gene co-expression analysis,functional prediction and enrichment analysis,immune cell infiltration analysis,correlation analysis of drugs and chemicals with genes,and hub miRNA expression levels all suggested heterogeneity of positive and negative symptoms of schizophrenia.5.Individual differences in sensitivity to antipsychotic drugs in SCZ patients may be influenced by differences in miRNA expression.6.Down-regulation of miR-30e-3p and up-regulation of ABI1 can promote apoptosis of SH-SY5Ys cells,inhibit cell proliferation and neurite growth.miR-30e-3p induces disruption of neurite development in SH-SY5Y cells by targeting ABI1.