BACKGROUND Diabetic cardiomyopathy(DCM)is a multifaceted cardiovascular disorder in which immune dysregulation plays a pivotal role.The immunological molecular mechanisms underlying DCM are poorly understood.AIM To ex...BACKGROUND Diabetic cardiomyopathy(DCM)is a multifaceted cardiovascular disorder in which immune dysregulation plays a pivotal role.The immunological molecular mechanisms underlying DCM are poorly understood.AIM To examine the immunological molecular mechanisms of DCM and construct diagnostic and prognostic models of DCM based on immune feature genes(IFGs).METHODS Weighted gene co-expression network analysis along with machine learning methods were employed to pinpoint IFGs within bulk RNA sequencing(RNA-seq)datasets.Single-sample gene set enrichment analysis(ssGSEA)facilitated the analysis of immune cell infiltration.Diagnostic and prognostic models for these IFGs were developed and assessed in a validation cohort.Gene expression in the DCM cell model was confirmed through real time-quantitative polymerase chain reaction and western blotting techniques.Additionally,single-cell RNA-seq data provided deeper insights into cellular profiles and interactions.RESULTS The overlap between 69 differentially expressed genes in the DCM-associated module and 2483 immune genes yielded 7 differentially expressed immune-related genes.Four IFGs showed good diagnostic and prognostic values in the validation cohort:Proenkephalin(Penk)and retinol binding protein 7(Rbp7),which were highly expressed,and glucagon receptor and inhibin subunit alpha,which were expressed at low levels in DCM patients(all area under the curves>0.9).SsGSEA revealed that IFG-related immune cell infiltration primarily involved type 2 T helper cells.High expression of Penk(P<0.0001)and Rbp7(P=0.001)was detected in cardiomyocytes and interstitial cells and further confirmed in a DCM cell model in vitro.Intercellular events and communication analysis revealed abnormal cellular phenotype transformation and signaling communication in DCM,especially between mesenchymal cells and macrophages.CONCLUSION The present study identified Penk and Rbp7 as potential DCM biomarkers,and aberrant mesenchymal-immune cell phenotype communication may be an important aspect of DCM pathogenesis.展开更多
基金Supported by National Natural Science Foundation of China,No.82300347Natural Science Foundation of Ningbo,No.2021J296Science Foundation of Lihuili Hospital,No.2022ZD004.
文摘BACKGROUND Diabetic cardiomyopathy(DCM)is a multifaceted cardiovascular disorder in which immune dysregulation plays a pivotal role.The immunological molecular mechanisms underlying DCM are poorly understood.AIM To examine the immunological molecular mechanisms of DCM and construct diagnostic and prognostic models of DCM based on immune feature genes(IFGs).METHODS Weighted gene co-expression network analysis along with machine learning methods were employed to pinpoint IFGs within bulk RNA sequencing(RNA-seq)datasets.Single-sample gene set enrichment analysis(ssGSEA)facilitated the analysis of immune cell infiltration.Diagnostic and prognostic models for these IFGs were developed and assessed in a validation cohort.Gene expression in the DCM cell model was confirmed through real time-quantitative polymerase chain reaction and western blotting techniques.Additionally,single-cell RNA-seq data provided deeper insights into cellular profiles and interactions.RESULTS The overlap between 69 differentially expressed genes in the DCM-associated module and 2483 immune genes yielded 7 differentially expressed immune-related genes.Four IFGs showed good diagnostic and prognostic values in the validation cohort:Proenkephalin(Penk)and retinol binding protein 7(Rbp7),which were highly expressed,and glucagon receptor and inhibin subunit alpha,which were expressed at low levels in DCM patients(all area under the curves>0.9).SsGSEA revealed that IFG-related immune cell infiltration primarily involved type 2 T helper cells.High expression of Penk(P<0.0001)and Rbp7(P=0.001)was detected in cardiomyocytes and interstitial cells and further confirmed in a DCM cell model in vitro.Intercellular events and communication analysis revealed abnormal cellular phenotype transformation and signaling communication in DCM,especially between mesenchymal cells and macrophages.CONCLUSION The present study identified Penk and Rbp7 as potential DCM biomarkers,and aberrant mesenchymal-immune cell phenotype communication may be an important aspect of DCM pathogenesis.
