哮喘控制的代谢组学：遗传学与疾病之间的潜在联系。
The metabolomics of asthma control: a promising link between genetics and disease.
机构信息
Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School Boston, Massachusetts, USA.
Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School Boston, Massachusetts, USA ; Children's Hospital and Harvard Medical School Boston, Massachusetts, USA ; Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute Boston, Massachusetts, USA.
出版信息
Immun Inflamm Dis. 2015 Sep;3(3):224-38. doi: 10.1002/iid3.61. Epub 2015 May 7.
Short-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative "omics" approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), - using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites-monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.
短效 β 受体激动剂（如沙丁胺醇）是治疗哮喘最常用的药物之一，全世界有超过 3 亿人患有哮喘。对使用β受体激动剂的哮喘患者进行代谢组学分析，为识别哮喘控制的分子决定因素提供了新的、有前途的资源。本研究的目的是利用综合“组学”方法，确定哮喘控制的新型遗传和生化预测因子。我们通过液相色谱串联质谱法（LC-MS）生成脂质组学数据，使用 20 名哮喘患者的血浆样本。感兴趣的结果是通过在前一周使用沙丁胺醇吸入器来定义哮喘控制的二元指标。我们将代谢组学数据与该队列的全基因组基因型、基因表达和甲基化数据进行整合，以确定哮喘控制的基因组和分子指标。使用来自这些分析的最强预测因子生成条件高斯贝叶斯网络（CGBN）。综合代谢途径过表达分析（ORA）鉴定了最强分子决定因素中已知生物学途径的富集。在测量的 64 种代谢物中，有 32 种具有已知身份。基于四个 SNP（rs9522789、rs7147228、rs2701423、rs759582）和两种代谢物-单 HETE_0863 和鞘氨醇-1-磷酸（S1P）的 CGBN 模型可以预测哮喘控制，AUC 为 95%。综合 ORA 确定了 17 个与细胞免疫反应、干扰素信号和细胞因子相关信号相关的显著富集途径，除了六个基因（CHN1、PRKCE、GNA12、OASL、OAS1 和 IFIT3）之外，花生四烯酸、PGE2 和 S1P 似乎也推动了这些途径的结果。在这些预测因子中，S1P、GNA12 和 PRKCE 在整合和代谢 ORA 的结果中富集。通过对一小批哮喘患者的代谢组学、基因组学和甲基化数据进行综合分析，我们发现与鞘脂代谢相关的代谢途径发生改变与哮喘控制有关。这些结果为哮喘控制的病理生理学提供了新的见解。
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