Background: The role of N6-methyladenosine (m6A) modification in abdominal aortic aneurysm (AAA) has not been extensively studied. This study therefore aimed to investigate m6A RNA methylation and the expressions of the corresponding modulators in AAA. Methods: A comparative study between AAA tissue samples (n=32) and healthy aortas (n=12) was performed using m6A methylation quantification for messenger RNA (mRNA) m6A status, quantitative polymerase chain reaction (qPCR), and western blot for the expressions of m6A modulators and immunohistochemistry (IHC) to detect locations of the modulators in AAA tissues. Results: The m6A level significantly increased in AAA as compared to healthy aorta tissues. Among AAA patients, the high m6A level represented an even greater risk of AAA rupture as compared to non-ruptured AAA [odds ratio (OR), 1.370; 95% confidence interval (CI), 1.007–1.870]. The major N6-adenosine modulators, including YTHDF1, YTHDF3, FTO, and METTL14, are the main factors involved in aberrant m6A modification and the expression of both was significantly correlated to the proportion of m6A in total mRNA. Clinically, YTHDF3 represented an even greater risk of rupture (OR, 1.036; 95% CI, 1.001–1.072). Regarding the cellular location, METTL14 seemed to be associated with inflammatory infiltrates and neovascularization. Furthermore, a strong correlation was seen between FTO and aneurysmal smooth muscle cells (SMCs), YTHDF3, and macrophage infiltrate. Conclusions: We were first to observe m6A modification in human AAA tissues. The results also reveal the important roles of m6A modulators, including YTHDF3, FTO, and METTL14, in the pathogenesis of human AAA and provide a new view on m6A modification in AAA. Our findings suggest a potential mechanism of epigenetic alterations in clinical AAA.

Background: Most studies related to food addiction have focused on assessing food addiction among adult populations. However, evidence in adolescents has been limited. The aim of this study was to investigate the prevalence of food addiction in a non-clinical adolescent sample. Psychosocial correlations of food addiction and associations with different quality of life dimensions were also tested. Methods: The sample included 593 Chinese adolescents (51.9% female; age range: 13–17 years). All participants provided sociodemographic information and completed questionnaires regarding food addiction, depression, self-esteem, loneliness, psychosocial problems, and quality of life (QoL). Results: The prevalence of food addiction was 6.91% in our sample. A multivariable logistic regression indicated that food addiction was associated with depression (AOR = 2.58; 95% CI: 1.32–5.05), low self-esteem (AOR = 2.75; 95% CI: 1.31–5.78), and loneliness (AOR = 2.30; 95% CI: 1.14–4.65). After multivariable adjustments for sociodemographic and psychological variables, food addiction was associated with lower overall QoL and psychosocial health of QoL. Conclusions: Food addiction may be common among Chinese adolescents. Food addiction was associated with depression, low self-esteem, and loneliness. Lastly, food addiction was also associated with lower overall QoL and psychosocial health of QoL. Future public health programs and interventions consider targeting the factors associated with food addiction to increase healthy eating behaviors among adolescents.

Objectives: This study aimed to identify key AAA-related m1A RNA methylation regulators and their association with immune infiltration in AAA. Furthermore, we aimed to explore the mechanism that m1A regulators modulate the functions of certain immune cells as well as the downstream target genes, participating in the progression of AAA.Methods: Based on the gene expression profiles of the GSE47472 and GSE98278 datasets, differential expression analysis focusing on m1A regulators was performed on the combined dataset to identify differentially expressed m1A regulatory genes (DEMRGs). Additionally, CIBERSORT tool was utilized in the analysis of the immune infiltration landscape and its correlation with DEMRGs. Moreover, we validated the expression levels of DEMRGs in human AAA tissues by real-time quantitative PCR (RT-qPCR). Immunofluorescence (IF) staining was also applied in the validation of cellular localization of YTHDF3 in AAA tissues. Furthermore, we established LPS/IFN-γ induced M1 macrophages and ythdf3 knockdown macrophages in vitro, to explore the relationship between YTHDF3 and macrophage polarization. At last, RNA immunoprecipitation-sequencing (RIP-Seq) combined with PPI network analysis was used to predict the target genes of YTHDF3 in AAA progression.Results: Eight DEMRGs were identified in our study, including YTHDC1, YTHDF1-3, RRP8, TRMT61A as up-regulated genes and FTO, ALKBH1 as down-regulated genes. The immune infiltration analysis showed these DEMRGs were positively correlated with activated mast cells, plasma cells and M1 macrophages in AAA. RT-qPCR analysis also verified the up-regulated expression levels of YTHDC1, YTHDF1, and YTHDF3 in human AAA tissues. Besides, IF staining result in AAA adventitia indicated the localization of YTHDF3 in macrophages. Moreover, our in-vitro experiments found that the knockdown of ythdf3 in M0 macrophages inhibits macrophage M1 polarization but promotes macrophage M2 polarization. Eventually, 30 key AAA-related target genes of YTHDF3 were predicted, including CD44, mTOR, ITGB1, STAT3, etc.Conclusion: Our study reveals that m1A regulation is significantly associated with the pathogenesis of human AAA. The m1A “reader,” YTHDF3, may participate in the modulating of macrophage polarization that promotes aortic inflammation, and influence AAA progression by regulating the expression of its target genes.

Background: Many studies on long chain non-coding RNAs (lncRNAs) are published in recent years. But the roles of lncRNAs in aortic dissection (AD) are still unclear and should be further examined. The present work focused on determining the molecular mechanisms underlying lncRNAs regulation in aortic dissection on the basis of the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network. Methods: This study collected the lncRNAs (GSE52093), mRNAs (GSE52093) and miRNAs (GSE92427) expression data within human tissue samples with aortic dissection group and normal group based on Gene Expression Omnibus (GEO) database. Results: This study identified three differentially expressed lncRNAs (DELs), 19 differentially expressed miRNAs (DEmiRs) and 1046 differentially expressed mRNAs (DEGs) identified regarding aortic dissection. Furthermore, we constructed a lncRNA-miRNA-mRNA network through three lncRNAs (including two with up-regulation and one with down-regulation), five miRNAs (five with up-regulation), as well as 211 mRNAs (including 103 with up-regulation and 108 with down-regulation). Simultaneously, we conducted functional enrichment and pathway analyses on genes within the as-constructed ceRNA network. According to our PPI/ceRNA network and functional enrichment analysis results, four critical genes were found (E2F2, IGF1R, BDNF and PPP2R1B). In addition, E2F2 level was possibly modulated via lncRNA FAM87A-hsa-miR-31-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p. The expression of IGF1R may be regulated by lncRNA FAM87A-hsa-miR-16-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p. Conclusion: In conclusion, the ceRNA interaction axis we identified is a potentially critical target for treating AD. Our results shed more lights on the possible pathogenic mechanism in AD using a lncRNA-associated ceRNA network.