Dilated cardiomyopathy (DCM) is a common type of non-ischemic cardiomyopathy, of which the underlying mechanisms have not yet been fully elucidated. Long noncoding RNAs (lncRNAs) have been reported to serve crucial physiological roles in various cardiac diseases. However, the genome-wide expression profile of lncRNAs remains to be elucidated in DCM. In the present study, a case-control study was performed to identify expression deviations in circulating lncRNAs between patients with DCM and controls by RNA sequencing. Partial dysregulated lncRNAs were validated by reverse transcription-polymerase chain reaction. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, and lncRNA-messenger RNA (mRNA) co-expression network analyses were employed to probe potential functions of these dysregulated lncRNAs in DCM. Comparison between 8 DCM and 8 control samples demonstrated that there were alterations in the expression levels of 988 lncRNAs and 1,418 mRNAs in total. The dysregulated lncRNAs were found to be mainly associated with system development, organ morphogenesis and metabolic regulation in terms of ‘biological processes’. Furthermore, the analysis revealed that the gap junction pathway, phagosome, and dilated and hypertrophic cardiomyopathy pathways may serve crucial roles in the development of DCM. The lncRNA-mRNA co-expression network also suggested that the target genes of the lncRNAs were different in patients with DCM as compared with those in the controls. In conclusion, the present study revealed the genome-wide profile of circulating lncRNAs in DCM by RNA sequencing, and explored the potential functions of these lncRNAs in DCM using bioinformatics analysis. These findings provide a theoretical foundation for future studies of lncRNAs in DCM.
The etiology of Keshan disease (KD), an endemic myocardiopathy in regions of China, is largely unknown. To show the protein changes in serum from KD patients versus controls and idiopathic dilated cardiomyopathy (IDCM) and to search specific biological markers for differential diagnosis for KD. Serum of 65 patients with KD was compared with 29 patients with IDCM, 62 controls from KD areas and 28 controls from non-KD areas by ClinProt/MALDI-ToF technique. The genetic algorithm, quick classifier algorithm and supervised neural network algorithm methods were used to screen marker proteins and establish diagnostic model. Thirty-four differential peaks were identified in KD patients compared with the healthy controls from non-KD areas. Thirty-eight differentially peaks were identified in KD patients and controls from KD areas; and sixty-seven differentially peaks were identified in patients with KD and patients with IDCM. We believe that marker protein peaks screened in KD patients, healthy controls and IDCM patients may provide clues for the differential diagnosis and treatment of KD.
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