Related Risk Factors And Bioinformatics Analysis Of Diabetic Cardiomyopathy

Objective :Diabetic cardiomyopathy(DCM)is insidious and a lack of effective diagnosis and treatment.In this study,we will observe the differences in related risk factors and the expression profile of miRNAs between healthy controls and patients with diabetic cardiomyopathy(DCM).This study will not only provide new clues for the diagnosis and treatment of DCM,but also analyze the role of immune inflammation in the development of DCM through bioinformatics.Methods:1.Patients admitted to the Department of Cardiology or the Department of Endocrinology of the First Affiliated Hospital of Kunming Medical University for DCM and treated from January 2021 to December 2022 were used as study subjects,and individual files were built after signing an informed consent form.2.Collect basic patient data,mainly including demographic data,test data,cardiac ultrasound,CT of coronary or coronary angiography indicators,etc.3.Analysis of clinical indicators by univariate analysis and multi-factor logistic regression analysis in order to explore independent risk factors for DCM.4.Peripheral blood was selected from four patients in each group.And mRNAs and miRNAs expression profiles were respectively obtained by microarray and high-throughput sequencing;the expression of differential mRNAs was analyzed by the "limma" package and the "DESeq2" package to miRNAs.5.GO and KEGG enrichment analysis of differential mRNAs by "Clusterprofiler" and "GSVA" packages in R 4.2 were to identify protein functional annotations and potential signaling pathways.6.Based on the Cibersort algorithm,we analyzed the differential expression of immune inflammatory cells and explored the role of immune inflammation in DCM.7.Combine with Immport immune database to obtain IRGs and validate the data by GSE161052 dataset.8.The target miRNAs of IRHGs were obtained by miRNA-mRNA interaction databases,and then the miRNA-mRNA immune mechanism axis of DCM was constructed.Results:1.A total of 104 cases were enrolled in this study and were divided into 43 cases in the DCM group and 61 cases in the control group.There were no differences in age,sex,drinking or BMI between the two groups,and the proportion of smoking was higher in the DCM group(p<0.05).2.Between the two groups,clinical parameters revealed higher in the DCM as follows: WBC,absolute neutrophil,absolute monocyte,absolute lymphocyte,absolute basophil,AST,ALP,GGT,fasting glucose,left ventricular end-diastolic internal diameter,and left ventricular posterior wall thickness.Multifactorial logistic regression analysis revealed that WBC was significant(p<0.05),but only blood glucose was a risk factor for DCM after correction.3.Bioinformatics analysis identified 125 differential mRNAs,of which 88 mRNAs were down-regulated and 37 mRNAs were up-regulated;and 10 differential miRNAs were identified,of which 4 miRNAs were up-regulated and 6 miRNAs were down-regulated.4.GO terms of DEGs include: positive regulation of T-helper cell differentiation(GO:0045624),α-β T cell activation involved in immune response(GO:0002287),G-protein β/γ subunit complex binding(GO:0031683),ribosome(GO:0005840),etc.;KEGG pathways include: c GMP-PKG signaling,oxidative stress signaling,myocardial contraction,Alzheimer’s disease,etc.5.Immune analysis revealed statistically significant(p < 0.05)in neutrophils,M2 type macrophages,Treg T cells,and naive B cells.6.We obtained a total of 3 IRGs(STAT3,ZAP70,ZC3HAV1L);and STAT3 was identified as the key gene after validation by dataset GSE161052.The upstream miRNA of STAT3 was found to be hsa-miR-125b-5p according to database prediction combined with sequencing results,thus constructing the hsa-miR-125b-5p/STAT3 immune mechanism axis.Conclusions:1.Patients with DCM have a higher inflammatory response than controls,and inflammation plays an important role in the development and progression of DCM.3.Hsa-miR-125b-5p expression was down-regulated in the DCM,and may be important in the immune mechanism of DCM through the hsa-miR-125b-5p/STAT3 axis,which may provide new clues for the diagnosis and treatment of diabetic cardiomyopathy.