Biological Functions and Clinical Prospects of Extracellular Non-Coding RNAs in Diabetic Cardiomyopathy: an Updated Review

Construction and analysis of a network of exercise-induced mitochondria-related non-coding RNA in the regulation of diabetic cardiomyopathy

Diabetic cardiomyopathy (DCM) is a major factor in the development of heart failure. Mitochondria play a crucial role in regulating insulin resistance, oxidative stress, and inflammation, which affect the progression of DCM. Regular exercise can induce altered non-coding RNA (ncRNA) expression, which subsequently affects gene expression and protein function. The mechanism of exercise-induced mitochondrial-related non-coding RNA network in the regulation of DCM remains unclear. This study seeks to construct an innovative exercise-induced mitochondrial-related ncRNA network. Bioinformatic analysis of RNA sequencing data from an exercise rat model identified 144 differentially expressed long non-coding RNA (lncRNA) with cutoff criteria of p< 0.05 and fold change ≥1.0. GSE6880 and GSE4745 were the differentially expressed mRNAs from the left ventricle of DCM rat that downloaded from the GEO database. Combined with the differentially expressed mRNA and MitoCarta 3.0 dataset, the mitochondrial located gene Pdk4 was identified as a target gene. The miRNA prediction analysis using miRanda and TargetScan confirmed that 5 miRNAs have potential to interact with the 144 lncRNA. The novel lncRNA-miRNA-Pdk4 network was constructed for the first time. According to the functional protein association network, the newly created exercise-induced ncRNA network may serve as a promising diagnostic marker and therapeutic target, providing a fresh perspective to understand the molecular mechanism of different exercise types for the prevention and treatment of diabetic cardiomyopathy.

Identification of important modules and biomarkers in diabetic cardiomyopathy based on WGCNA and LASSO analysis

Background

Diabetic cardiomyopathy (DCM) lacks specific and sensitive biomarkers, and its diagnosis remains a challenge. Therefore, there is an urgent need to develop useful biomarkers to help diagnose and evaluate the prognosis of DCM. This study aims to find specific diagnostic markers for diabetic cardiomyopathy.

Methods

Two datasets (GSE106180 and GSE161827) from the GEO database were integrated to identify differentially expressed genes (DEGs) between control and type 2 diabetic cardiomyopathy. We assessed the infiltration of immune cells and used weighted coexpression network analysis (WGCNA) to construct the gene coexpression network. Then we performed a clustering analysis. Finally, a diagnostic model was built by the least absolute shrinkage and selection operator (LASSO).

Results

A total of 3066 DEGs in the GSE106180 and GSE161827 datasets. There were differences in immune cell infiltration. According to gene significance (GS) > 0.2 and module membership (MM) > 0.8, 41 yellow Module genes and 1474 turquoise Module genes were selected. Hub genes were mainly related to the "proteasomal protein catabolic process", "mitochondrial matrix" and "protein processing in endoplasmic reticulum" pathways. LASSO was used to construct a diagnostic model composed of OXCT1, CACNA2D2, BCL7B, EGLN3, GABARAP, and ACADSB and verified it in the GSE163060 and GSE175988 datasets with AUCs of 0.9333 (95% CI: 0.7801-1) and 0.96 (95% CI: 0.8861-1), respectively. H9C2 cells were verified, and the results were similar to the bioinformatics analysis.

Conclusion

We constructed a diagnostic model of DCM, and OXCT1, CACNA2D2, BCL7B, EGLN3, GABARAP, and ACADSB were potential biomarkers, which may provide new insights for improving the ability of early diagnosis and treatment of diabetic cardiomyopathy.

Therapeutic Potential of EVs: Targeting Cardiovascular Diseases

Due to their different biological functions, extracellular vesicles (EVs) have great potential from a therapeutic point of view. They are released by all cell types, carrying and delivering different kinds of biologically functional cargo. Under pathological events, cells can increase their secretion of EVs and can release different amounts of cargo, thus making EVs great biomarkers as indicators of pathological progression. Moreover, EVs are also known to be able to transport and deliver cargo to different recipient cells, having an important role in cellular communication. Interestingly, EVs have recently been explored as biological alternatives for the delivery of therapeutics, being considered natural drug delivery carriers. Because cardiovascular disorders (CVDs) are the leading cause of death worldwide, in this review, we will discuss the up-to-date knowledge regarding the biophysical properties and biological components of EVs, focusing on myocardial infarction, diabetic cardiomyopathy, and sepsis-induced cardiomyopathy, three very different types of CVDs.

Targeting non-coding RNAs in sEVs: The biological functions and potential therapeutic strategy of diabetic cardiomyopathy

Diabetic cardiomyopathy (DCM) is defined as abnormalities in myocardial structure and function in the setting of diabetes and in the absence of cardiovascular diseases, such as coronary artery disease, hypertension, and valvular heart disease. DCM is one of the leading causes of mortality in patients with diabetes. However, the underlying pathogenesis of DCM has not been fully elucidated. Recent studies have revealed that non-coding RNAs (ncRNAs) in small extracellular vesicles (sEVs) are closely associated with DCM and may act as potential diagnostic and therapeutic targets. Here, we introduced the role of sEV-ncRNAs in DCM, summarized the current therapeutic advancements and limitations of sEV-related ncRNAs against DCM, and discussed their potential improvement.