Biochemical and biophysical research communications · 2026
Identifying a fatty acid metabolic gene signature in diabetic cardiomyopathy through integrated bioinformatics and machine learning.
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Wei Aoyun, Zhang Haozhi, He Oudie, Zhang Na, Wang Min, Pang Aiming, Cui Yujie, Xi Pengjiao
Аннотация
BACKGROUND: Diabetic cardiomyopathy (DCM) is a major cardiovascular complication of diabetes mellitus, ultimately progressing to heart failure and increased mortality. Its pathogenesis involves multifactorial mechanisms, and the key causative genes remain to be fully elucidated.
METHODS: We merged and batch-corrected seven Gene Expression Omnibus (GEO) datasets. A combination of differential expression analysis, protein-protein interaction (PPI) networks, and machine learning pinpointed seven core candidates. Cellular expression patterns were delineated using single-nucleus RNA-seq data. Experimental validation in the DCM mouse model confirmed alterations in gene and protein expression in myocardial tissue via RT-qPCR and Western blot. To uncover underlying mechanisms, we conducted a multi-omics analysis (RNA-seq, proteomics, and untargeted metabolomics).
RESULTS: In this study, seven genes upregulated in DCM were identified, including Hmgcs2, Ech1, Acot2, Acot1, Fbp2, Fkbp5, and Decr1. The single-nucleus RNA sequencing results revealed that these genes were mainly differentially expressed in cardiomyocytes. In vivo analysis revealed upregulated mRNA expression of Hmgcs2, Ech1, Acot1, Fbp2, and Decr1 in the DCM group and Western blot results consistently confirmed that the protein levels of ECH1, FBP2, and ACOT1 were also significantly increased in the hearts of DCM mice. Metabolomics analysis showed that the levels of nicotinamide adenine dinucleotide and cyclic ADP-ribose in the myocardial tissue of DCM mice decreased, while the levels of free fatty acids increased, indicating enhanced fatty acid metabolism.
CONCLUSIONS: Our study innovatively establishes the involvement of Ech1 and Fbp2 in the development and progression of DCM. These findings provide novel molecular targets and a theoretical basis for the clinical diagnosis of DCM, offering new perspectives for future research.
METHODS: We merged and batch-corrected seven Gene Expression Omnibus (GEO) datasets. A combination of differential expression analysis, protein-protein interaction (PPI) networks, and machine learning pinpointed seven core candidates. Cellular expression patterns were delineated using single-nucleus RNA-seq data. Experimental validation in the DCM mouse model confirmed alterations in gene and protein expression in myocardial tissue via RT-qPCR and Western blot. To uncover underlying mechanisms, we conducted a multi-omics analysis (RNA-seq, proteomics, and untargeted metabolomics).
RESULTS: In this study, seven genes upregulated in DCM were identified, including Hmgcs2, Ech1, Acot2, Acot1, Fbp2, Fkbp5, and Decr1. The single-nucleus RNA sequencing results revealed that these genes were mainly differentially expressed in cardiomyocytes. In vivo analysis revealed upregulated mRNA expression of Hmgcs2, Ech1, Acot1, Fbp2, and Decr1 in the DCM group and Western blot results consistently confirmed that the protein levels of ECH1, FBP2, and ACOT1 were also significantly increased in the hearts of DCM mice. Metabolomics analysis showed that the levels of nicotinamide adenine dinucleotide and cyclic ADP-ribose in the myocardial tissue of DCM mice decreased, while the levels of free fatty acids increased, indicating enhanced fatty acid metabolism.
CONCLUSIONS: Our study innovatively establishes the involvement of Ech1 and Fbp2 in the development and progression of DCM. These findings provide novel molecular targets and a theoretical basis for the clinical diagnosis of DCM, offering new perspectives for future research.