Abstract 13941: RNA-Sequencing Reveals a Distinct Transcriptomic Signature for Giant Cell Myocarditis and Identifies Novel Druggable Targets

• Published in: Circulation (New York, N.Y.) Vol. 144; no. Suppl_1; p. A13941
• Main Authors: Qin, Juan, Amancherla, Kaushik, Moslehi, Javid
• Format: Journal Article
• Language: English
• Published: Lippincott Williams & Wilkins 16.11.2021
• ISSN: 0009-7322; 1524-4539
• DOI: 10.1161/circ.144.suppl_1.13941

IntroductionGiant cell myocarditis (GCM) is a rare inflammatory heart muscle disease that is often rapidly progressive and carries a poor prognosis. The pathogenesis of GCM is incompletely understood, but is thought to be autoimmune in nature. An improved mechanistic understanding of GCM is critical for identifying novel therapeutic targets and improving survival. HypothesisWe hypothesized that GCM exhibits a distinct transcriptomic profile. By querying database of drug-gene interactions, novel drug targets could be identified. MethodsWe performed RNA-seq utilizing FFPE tissues. ResultsDemographics and clinical characteristics of the groups are highlighted in Panel A. Principal component analysis (B) based on complete expression profiles and unsupervised hierarchical cluster analysis of significant differentially expressed genes identified a distinct transcriptomic profile for GCM (C). Consistent with shared histological features, overlap is noted between rejection and lymphocytic myocarditis. Pathway enrichment analysis (D) in GCM showed that upregulated pathways were enriched for neutrophil degranulation, multiple cytokine signaling pathways, and phagocytosis, while downregulated pathways included those involved in muscle contraction and cardiac conduction. The most significantly upregulated genes play roles in innate and adaptive immune responses (E). Querying the Drug Gene Interaction Database (DGIdb) identified several novel biologically-plausible therapeutic targets (F). ConclusionsTo our knowledge, this is the first study using RNA-seq to interrogate the transcriptomic profile of GCM. Our results demonstrate that GCM has a gene expression profile that mirrors clinical and histopathological features of GCM, and is distinct from the transcriptomic profiles seen in other healthy and inflammatory cardiac diseases. By querying a drug-gene interaction database, several novel drug targets were identified.