Identification of immune feature genes and intercellular profiles in diabetic cardiomyopathy.

IF 4.2 3区 医学 Q1 ENDOCRINOLOGY & METABOLISM World Journal of Diabetes Pub Date : 2024-10-15 DOI:10.4239/wjd.v15.i10.2093
Ze-Qun Zheng, Di-Hui Cai, Yong-Fei Song
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Abstract

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.

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鉴定糖尿病心肌病的免疫特征基因和细胞间特征。
背景:糖尿病心肌病(DCM)是一种多发性心血管疾病,免疫失调在其中起着关键作用。目的:研究 DCM 的免疫学分子机制,并根据免疫特征基因(IFGs)构建 DCM 的诊断和预后模型:方法:采用加权基因共表达网络分析和机器学习方法,在大容量RNA测序(RNA-seq)数据集中精确定位IFGs。单样本基因组富集分析(ssGSEA)有助于分析免疫细胞浸润。针对这些 IFGs 开发了诊断和预后模型,并在验证队列中进行了评估。通过实时定量聚合酶链反应和 Western 印迹技术确认了 DCM 细胞模型中的基因表达。此外,单细胞RNA-seq数据提供了对细胞特征和相互作用的更深入了解:结果:DCM 相关模块中的 69 个差异表达基因与 2483 个免疫基因重叠,产生了 7 个差异表达的免疫相关基因。在验证队列中,4 个 IFGs 显示出良好的诊断和预后价值:高表达的原脑啡肽(Penk)和视黄醇结合蛋白 7(Rbp7),以及在 DCM 患者中低水平表达的胰高血糖素受体和抑制素亚基 alpha(所有曲线下面积均大于 0.9)。SsGSEA 显示,与 IFG 相关的免疫细胞浸润主要涉及 2 型 T 辅助细胞。在心肌细胞和间质细胞中检测到 Penk(P < 0.0001)和 Rbp7(P = 0.001)的高表达,并在体外 DCM 细胞模型中得到进一步证实。细胞间事件和通讯分析揭示了DCM中异常的细胞表型转化和信号通讯,尤其是间质细胞和巨噬细胞之间的通讯:本研究发现,Penk 和 Rbp7 是潜在的 DCM 生物标记物,间质-免疫细胞表型异常交流可能是 DCM 发病机制的一个重要方面。
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来源期刊
World Journal of Diabetes
World Journal of Diabetes ENDOCRINOLOGY & METABOLISM-
自引率
2.40%
发文量
909
期刊介绍: The WJD is a high-quality, peer reviewed, open-access journal. The primary task of WJD is to rapidly publish high-quality original articles, reviews, editorials, and case reports in the field of diabetes. In order to promote productive academic communication, the peer review process for the WJD is transparent; to this end, all published manuscripts are accompanied by the anonymized reviewers’ comments as well as the authors’ responses. The primary aims of the WJD are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in diabetes. Scope: Diabetes Complications, Experimental Diabetes Mellitus, Type 1 Diabetes Mellitus, Type 2 Diabetes Mellitus, Diabetes, Gestational, Diabetic Angiopathies, Diabetic Cardiomyopathies, Diabetic Coma, Diabetic Ketoacidosis, Diabetic Nephropathies, Diabetic Neuropathies, Donohue Syndrome, Fetal Macrosomia, and Prediabetic State.
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