Meta‐analysis reveals differential gene expression in tetralogy of Fallot versus controls

• Published in: Birth defects research 2024-01, Vol.116 (1), p.e2293-n/a
• Main Authors: Voskamp, Sarah Mae, Hammonds, Maya Alexis, Knapp, Thomas M., Pekmezian, Ashley L., Hadley, Dexter, Nelson, Jennifer S.
• Format: Article
• Language: English
• Subjects: Big Data; Cardiovascular disease; Cardiovascular diseases; Cardiovascular system; Congenital diseases; congenital heart disease; Disease control; DNA microarrays; Down-regulation; Estrogen receptors; Estrogens; Gene expression; Genes; Genetic diversity; genetic expression; Genetic resources; Heart diseases; Hypertrophy; Meta-analysis; NF-AT protein; Receptors; Signal transduction; Statistical analysis; Tetralogy of Fallot; Ventricle
• ISSN: 2472-1727; 2472-1727
• DOI: 10.1002/bdr2.2293

Objectives Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart defect in the United States. We aimed to identify genetic variations associated with TOF using meta‐analysis of publicly available digital samples to spotlight targets for prevention, screening, and treatment strategies. Methods We used the Search Tag Analyze Resource for Gene Expression Omnibus (STARGEO) platform to identify 39 TOF and 19 non‐TOF right ventricle tissue samples from microarray data and identified upregulated and downregulated genes. Associated gene expression data were analyzed using ingenuity pathway analysis and restricted to genes with a statistically significant (p 0.1 between disease and control samples. Results Our analysis identified 220 genes whose expression profiles were significantly altered in TOF vs. non‐TOF samples. The most striking differences identified in gene expression included genes FBXO32, PTGES, MYL12a, and NR2F2. Some top associated canonical pathways included adrenergic signaling, estrogen receptor signaling, and the role of NFAT in cardiac hypertrophy. In general, genes involved in adaptive, defensive, and reparative cardiovascular responses showed altered expression in TOF vs. non‐TOF samples. Conclusions We introduced the interpretation of open “big data” using the STARGEO platform to define robust genomic signatures of congenital heart disease pathology of TOF. Overall, our meta‐analysis results indicated increased metabolism, inflammation, and altered gene expression in TOF patients. Estrogen receptor signaling and the role of NFAT in cardiac hypertrophy represent unique pathways upregulated in TOF patients and are potential targets for future pharmacologic treatments.