Introduction Despite the advances in genetic analysis and the increasing availability of analytical technologies, the genetic aetiology of Idiopathic (non-familial) Dilated Cardiomyopathy is poorly understood. Microarray analysis allows the simultaneous analysis of up to 40,000 gene products, effectively describing the entire expression profile of a biological sample. Public gene expression repositories (PGER) house microarray expression data from over 50,000 individual experiments comprising 1,300,000 samples. This offers a powerful, and as of yet not fully utilised, resource in establishing an intracellular pathogenesis in poorly understood disease states.
Objective The main aim was to utilise PGERs to generate and test genetic expression profiles differentiating normal and cardiomyopathic hearts, and use this data to identify key intracellular pathways which have become dysfunctional.
Methods A search was conducted across PGERs for experiments differentiating hearts with idiopathic cardiomyopathy and normal controls. Following a filtration process, nine experiments were considered suitable for analysis. Raw genetic expression data was extracted from the microarray repositories and analysed for each experiment using R statistical software. The frequencies of genes which were significantly dysregulated from controls were compared across all nine experiments using de novo visual basic script (VBS) code. Enrichment analysis was conducted using Ingenuity pathway software.
Results A total of 23,967 genes were dysregulated in dilated cardiomyopathy across all experiments (Table 1). Frequency analysis identified genes occuring most commonly, and these were categorised whether the genes were up-regulated or down-regulated (Table 2). Enrichment analysis allowed the identification of specific pathways which were observed to become up- and down-regulated in at least 66% (6 out of nine experiments) (Figure 1). Pathways which were seen to be up-regulated in DCM have been associated with: 1) Immune cell infiltration effects seen in rheumatoid arthritis, 2) c-AMP signalling, 3) Cardiac B-Adrenergic signalling, 4) Glucocorticoid receptor signalling, 5) VDR/RXR activation, and 6) HGF signalling (Figure 1). Pathways down-regulated were 1) PTEN signalling, 2) Protein Kinase A signalling, and 3) the STAT3 Pathway.
Conclusions Microarray data in PGER was used successfully to establish genetic consensus in identifying key intracellular pathways which have become dysregulated in idiopathic dilated cardiomyopathy. This novel type of meta-analytical technique shows promise in establishing intracellular aetiology in systemic pathology.
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