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Novel Insight of N-methyladenosine Modified Subtypes in Abdominal Aortic Aneurysm

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Journal Front Genet
Date 2022 Dec 9
PMID 36482903
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Abstract

N-methyladenosine (m6A) is the most prevalent non-cap reversible modification present in messenger RNAs and long non-coding RNAs, and its dysregulation has been linked to multiple cardiovascular diseases, including cardiac hypertrophy and atherosclerosis. Although limited studies have suggested that m6A modification contributes to abdominal aortic aneurysm (AAA) development, the full landscape of m6A regulators that mediate modification patterns has not been revealed. To distinguish the m6A methylation subtypes in AAA patients, an unsupervised clustering method was carried out, based on the mRNA levels of 17 m6A methylation regulators. Differentially expressed genes were identified by comparing clusters. An m6Ascore model was calculated using principal component analysis and structured to assess the m6A methylation patterns of single samples. Subsequently, the relationship between the m6Ascore and immune cells and the hallmark gene set was analyzed. Finally, pairs of circRNA-m6A regulators and m6A regulators-m6A related genes were used to establish a network. We identified three m6A methylation subtypes in the AAA samples. The m6Acluster A and C were characterized as more immunologically activated because of the higher abundance of immune cells than that in m6Acluster B. The m6Acluster B was less enriched in inflammatory pathways and more prevalent in pathways related to extracellular matrix stability. Subsequently, we divided the individual samples into two groups according to the m6Ascore, which suggested that a high m6Ascore predicted more active inflammatory pathways and higher inflammatory cell infiltration. A network consisting of 9 m6A regulators and 37 circRNAs was constructed. This work highlighted that m6A methylation modification was highly correlated with immune infiltration of AAA, which may promote the progression of AAA. We constructed an individualized m6Ascore model to provide evidence for individualized treatments in the future.

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