Abstract：
BACKGROUND: Although mounting evidence supports that aberrant DNA methylation occurs in the hearts of patients with atrial fibrillation (AF), noninvasive epigenetic characterization of AF has not yet been defined.
METHODS: We investigated DNA methylome changes in peripheral blood CD4+ T cells isolated from 10 patients with AF relative to 11 healthy subjects (HS) who were enrolled in the DIANA clinical trial (NCT04371809) via reduced-representation bisulfite sequencing (RRBS).
RESULTS: An atrial-specific PPI network revealed 18 hub differentially methylated genes (DMGs), wherein ROC curve analysis revealed reasonable diagnostic performance of DNA methylation levels found within CDK5R1 (AUC = 0.76; p = 0.049), HSPG2 (AUC = 0.77; p = 0.038), WDFY3 (AUC = 0.78; p = 0.029), USP49 (AUC = 0.76; p = 0.049), GSE1 (AUC = 0.76; p = 0.049), AIFM1 (AUC = 0.76; p = 0.041), CDK5RAP2 (AUC = 0.81; p = 0.017), COL4A1 (AUC = 0.86; p < 0.001), SEPT8 (AUC = 0.90; p < 0.001), PFDN1 (AUC = 0.90; p < 0.01) and ACOT7 (AUC = 0.78; p = 0.032). Transcriptional profiling of the hub DMGs provided a significant overexpression of PSDM6 (p = 0.004), TFRC (p = 0.01), CDK5R1 (p < 0.001), HSPG2 (p = 0.01), WDFY3 (p < 0.001), USP49 (p = 0.004) and GSE1 (p = 0.021) in AF patients vs HS.
CONCLUSIONS: CDK5R1, GSE1, HSPG2 and WDFY3 resulted the best discriminatory genes both at methylation and gene expression level. Our results provide several candidate diagnostic biomarkers with the potential to advance precision medicine in AF.
METHODS: We investigated DNA methylome changes in peripheral blood CD4+ T cells isolated from 10 patients with AF relative to 11 healthy subjects (HS) who were enrolled in the DIANA clinical trial (NCT04371809) via reduced-representation bisulfite sequencing (RRBS).
RESULTS: An atrial-specific PPI network revealed 18 hub differentially methylated genes (DMGs), wherein ROC curve analysis revealed reasonable diagnostic performance of DNA methylation levels found within CDK5R1 (AUC = 0.76; p = 0.049), HSPG2 (AUC = 0.77; p = 0.038), WDFY3 (AUC = 0.78; p = 0.029), USP49 (AUC = 0.76; p = 0.049), GSE1 (AUC = 0.76; p = 0.049), AIFM1 (AUC = 0.76; p = 0.041), CDK5RAP2 (AUC = 0.81; p = 0.017), COL4A1 (AUC = 0.86; p < 0.001), SEPT8 (AUC = 0.90; p < 0.001), PFDN1 (AUC = 0.90; p < 0.01) and ACOT7 (AUC = 0.78; p = 0.032). Transcriptional profiling of the hub DMGs provided a significant overexpression of PSDM6 (p = 0.004), TFRC (p = 0.01), CDK5R1 (p < 0.001), HSPG2 (p = 0.01), WDFY3 (p < 0.001), USP49 (p = 0.004) and GSE1 (p = 0.021) in AF patients vs HS.
CONCLUSIONS: CDK5R1, GSE1, HSPG2 and WDFY3 resulted the best discriminatory genes both at methylation and gene expression level. Our results provide several candidate diagnostic biomarkers with the potential to advance precision medicine in AF.
摘要：
背景：尽管越来越多的证据支持在房颤（AF）患者的心脏中发生异常DNA甲基化，房颤的非侵入性表观遗传学特征尚未确定.
方法：我们通过减少代表性的亚硫酸氢盐测序（RRBS）研究了10例房颤患者外周血CD4+T细胞相对于11例纳入DIANA临床试验（NCT04371809）的健康受试者（HS）的DNA甲基化变化。
结果：心房特异性PPI网络显示18个集线器差异甲基化基因（DMG），其中ROC曲线分析揭示了在CDK5R1内发现的DNA甲基化水平的合理诊断性能（AUC=0.76;p=0.049），HSPG2（AUC=0.77；p=0.038），WDFY3（AUC=0.78；p=0.029），USP49（AUC=0.76；p=0.049），GSE1（AUC=0.76；p=0.049），AIFM1（AUC=0.76；p=0.041），CDK5RAP2（AUC=0.81；p=0.017），COL4A1（AUC=0.86；p<0.001），SEPT8（AUC=0.90；p<0.001），PFDN1(AUC=0.90;p<0.01)和ACOT7(AUC=0.78;p=0.032)。hubDMGs的转录谱提供了PSDM6的显著过表达(p=0.004),TFRC(p=0.01)，CDK5R1（p<0.001），HSPG2（p=0.01），WDFY3（p<0.001），房颤患者与HS患者的USP49（p=0.004）和GSE1（p=0.021）。
结论：CDK5R1，GSE1，HSPG2和WDFY3在甲基化和基因表达水平上都产生了最佳的区分基因。我们的结果提供了几种候选诊断生物标志物，有可能在房颤中推进精准医学。
方法：我们通过减少代表性的亚硫酸氢盐测序（RRBS）研究了10例房颤患者外周血CD4+T细胞相对于11例纳入DIANA临床试验（NCT04371809）的健康受试者（HS）的DNA甲基化变化。
结果：心房特异性PPI网络显示18个集线器差异甲基化基因（DMG），其中ROC曲线分析揭示了在CDK5R1内发现的DNA甲基化水平的合理诊断性能（AUC=0.76;p=0.049），HSPG2（AUC=0.77；p=0.038），WDFY3（AUC=0.78；p=0.029），USP49（AUC=0.76；p=0.049），GSE1（AUC=0.76；p=0.049），AIFM1（AUC=0.76；p=0.041），CDK5RAP2（AUC=0.81；p=0.017），COL4A1（AUC=0.86；p<0.001），SEPT8（AUC=0.90；p<0.001），PFDN1(AUC=0.90;p<0.01)和ACOT7(AUC=0.78;p=0.032)。hubDMGs的转录谱提供了PSDM6的显著过表达(p=0.004),TFRC(p=0.01)，CDK5R1（p<0.001），HSPG2（p=0.01），WDFY3（p<0.001），房颤患者与HS患者的USP49（p=0.004）和GSE1（p=0.021）。
结论：CDK5R1，GSE1，HSPG2和WDFY3在甲基化和基因表达水平上都产生了最佳的区分基因。我们的结果提供了几种候选诊断生物标志物，有可能在房颤中推进精准医学。
