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整合分析确定了介导 DNA 甲基化对哮喘严重程度和肺功能影响的基因特征。

Integrative analysis identifies gene signatures mediating the effect of DNA methylation on asthma severity and lung function.

机构信息

Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA.

Division of Biostatistics and Epidemiology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA.

出版信息

Clin Epigenetics. 2024 Jan 20;16(1):15. doi: 10.1186/s13148-023-01611-9.

Abstract

DNA methylation (DNAm) changes play a key role in regulating gene expression in asthma. To investigate the role of epigenetics and transcriptomics change in asthma, we used publicly available DNAm (asthmatics, n = 96 and controls, n = 46) and gene expression (asthmatics, n = 79 and controls, n = 39) data derived from bronchial epithelial cells (BECs). We performed differential methylation/expression and weighted co-methylation/co-expression network analyses to identify co-methylated and co-expressed modules associated with asthma severity and lung function. For subjects with both DNAm and gene expression data (asthmatics, n = 79 and controls, n = 39), machine-learning technique was used to prioritize CpGs and differentially expressed genes (DEGs) for asthma risk prediction, and mediation analysis was used to uncover DEGs that mediate the effect of DNAm on asthma severity and lung function in BECs. Finally, we validated CpGs and their associated DEGs and the asthma risk prediction model in airway epithelial cells (AECs) dataset. The asthma risk prediction model based on 18 CpGs and 28 DEGs showed high accuracy in both the discovery BEC dataset with area under the receiver operating characteristic curve (AUC) = 0.99 and the validation AEC dataset (AUC = 0.82). Genes in the three co-methylated and six co-expressed modules were enriched in multiple pathways including WNT/beta-catenin signaling and notch signaling. Moreover, we identified 35 CpGs correlated with DEGs in BECs, of which 17 CpGs including cg01975495 (SERPINE1), cg10528482 (SLC9A3), cg25477769 (HNF1A) and cg26639146 (CD9), cg17945560 (TINAGL1) and cg10290200 (FLNC) were replicated in AECs. These DEGs mediate the association between DNAm and asthma severity and lung function. Overall, our study investigated the role of DNAm and gene expression change in asthma and provided an insight into the mechanisms underlying the effects of DNA methylation on asthma, asthma severity and lung function.

摘要

DNA 甲基化 (DNAm) 变化在调节哮喘中的基因表达中起着关键作用。为了研究表观遗传学和转录组变化在哮喘中的作用,我们使用了公开的支气管上皮细胞 (BEC) 中 DNAm(哮喘患者,n=96;对照组,n=46)和基因表达(哮喘患者,n=79;对照组,n=39)数据。我们进行了差异甲基化/表达和加权共甲基化/共表达网络分析,以鉴定与哮喘严重程度和肺功能相关的共甲基化和共表达模块。对于同时具有 DNAm 和基因表达数据的受试者(哮喘患者,n=79;对照组,n=39),我们使用机器学习技术来确定用于哮喘风险预测的 CpG 和差异表达基因 (DEG),并进行中介分析以揭示介导 BEC 中 DNAm 对哮喘严重程度和肺功能影响的 DEG。最后,我们在气道上皮细胞 (AEC) 数据集上验证了 CpG 及其相关的 DEG 和哮喘风险预测模型。基于 18 个 CpG 和 28 个 DEG 的哮喘风险预测模型在发现 BEC 数据集(AUC=0.99)和验证 AEC 数据集(AUC=0.82)中均具有较高的准确性。三个共甲基化和六个共表达模块中的基因在多个途径中被富集,包括 WNT/β-连环蛋白信号和 Notch 信号。此外,我们在 BEC 中鉴定了与 DEG 相关的 35 个 CpG,其中包括 cg01975495(SERPINE1)、cg10528482(SLC9A3)、cg25477769(HNF1A)和 cg26639146(CD9)、cg17945560(TINAGL1)和 cg10290200(FLNC),这些 CpG 在 AEC 中得到了复制。这些 DEG 介导了 DNAm 与哮喘严重程度和肺功能之间的关联。总体而言,我们的研究调查了 DNAm 和基因表达变化在哮喘中的作用,并深入了解了 DNA 甲基化对哮喘、哮喘严重程度和肺功能影响的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce33/10800055/6ff11ad9df09/13148_2023_1611_Fig1_HTML.jpg

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