哮喘患儿肺功能的整合转录组学和代谢组学研究

2018/07/09

   摘要
   背景:单组学分析提供了一些关于哮喘儿童肺功能基础的见解,但潜在的生物学途径仍然知之甚少。
   方法:加权基因共表达网络分析(WGCNA)被用来鉴定来自哥斯达黎加哮喘遗传流行病学研究的325名哮喘儿童血液中的共调节基因转录物和代谢物模块。探讨FEV1,FEV1/FVC比值,支气管扩张剂反应和对乙酰甲胆碱的气道反应性与肺功能相关的生物学模块。然后鉴定显著相关的基因-代谢物模块对,并对其组成特征进行了生物途径富集分析。
   结果:WGCNA将25,060个基因探针和8,185个代谢物特征聚类为八个基因模块和八个代谢模块,其中四个和六个分别与肺功能相关(p≤0.05)。基因模块富含免疫,有丝分裂和代谢过程以及哮喘相关的microRNA靶点。代谢物模块富含脂质和氨基酸代谢。相关基因-代谢物模块的整合扩展了单一发现,将FEV1/FVC比值与ORMDL3和脂质代谢失调联系起来。这一发现被复制到独立的人群中。
   结论:该假设产生研究的结果提示了多种哮喘基因包括ORMDL3的机制基础,以及脂质代谢的作用。他们证明,与单一分析相比,整合多种技术可以提供更具信息性的哮喘肺功能生物学图像。


(中日友好医院呼吸与危重症医学科 王瑞茵 摘译 林江涛 审校)
(Chest. 2018 Jun 13. pii: S0012-3692(18)30892-4. doi: 10.1016/j.chest.2018.05.038. [Epub ahead of print])

 
 
An Integrative Transcriptomic and Metabolomic Study of Lung Function in Asthmatic Children.
 
Kelly RS, Chawes BL, Blighe K, Virkud YV, Croteau-Chonka DC, McGeachie MJ, Clish CB, Bullock K, Celedón JC, Weiss ST, Lasky-Su JA.
 
Abstract
BACKGROUND:Single-omic analyses have provided some insight into the basis of lung function in asthmatic children, but the underlying biological pathways are still poorly understood.
METHODS:Weighted gene co-expression network analysis (WGCNA) was used to identify modules of co-regulated gene transcripts and metabolites in blood, among 325 children with asthma from the 'Genetic Epidemiology of Asthma in Costa Rica' study. The biology of modules associated with lung function; as measured by FEV1, FEV1/FVC-ratio, bronchodilator response, and airway responsiveness to methacholine, was explored. Significantly correlated gene-metabolite module pairs were then identified and their constituent features were analyzed for biological pathway enrichments.
RESULTS:WGCNA clustered 25,060 gene probes and 8,185 metabolite features into eight gene modules and eight metabolite modules, where four and six, respectively, were associated with lung function (p≤0.05). The gene modules were enriched for immune, mitotic and metabolic processes and asthma-associated microRNA targets. The metabolite modules were enriched for lipid and amino acid metabolism. Integration of correlated gene-metabolite modules expanded the single-omic findings, linking FEV1/FVC-ratio with ORMDL3 and dysregulated lipid metabolism. This finding was replicated in an independent population.
CONCLUSIONS:The results of this hypothesis-generating study suggest a mechanistic basis for multiple asthma genes, including ORMDL3, and a role for lipid metabolism. They demonstrate that integrating multiple omic technologies may provide a more informative picture of asthmatic lung function biology than single-omic analyses.


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