哮喘相关的复杂特征的重新识别
2023/09/21
摘要
引言：哮喘是一种异质性炎症性疾病，通常与其他复杂表型有关。识别哮喘相关疾病并揭示介导其相互作用的分子机制有助于揭示哮喘的异质性。网络分析是解开这种疾病间关系的有力方法。
方法：本文中，我们将常见单核苷酸多态性（SNP）和基因表达之间的物理接触信息与来自肺和全血的表达定量性状基因座（eQTL）数据相结合，构建两个组织特异性空间基因调控网络（GRN）。然后，我们通过鉴定受哮喘相关空间eQTL功能影响的基因，在每个组织特异性GRN中定位哮喘GRN（0级）。随后，在远离哮喘GRN的四个边缘或水平处鉴定出了Curated蛋白质相互作用伴侣。
结果：我们分别鉴定了80个和82个在肺和血液GRN中显著富集的性状。除8个与哮喘相关的性状（如网织红细胞计数）尚待证实外，所有已鉴定的性状均与哮喘（如抑郁症状和肺癌癌症）共病或相关（阳性或阴性）。我们的分析还精确定位了将哮喘与已确定的哮喘相关特征联系起来的变异和基因，其中一个子集在新西兰26781名哮喘患者的健康记录的共病分析中得到了重现。
讨论：我们的发现方法在感兴趣的组织中，在哮喘附近的调节空间中识别出富集的特征，而无需事先选择相互作用的特征。它所做的预测扩大了我们对哮喘可能存在的共同分子相互作用和治疗靶点的理解，而哮喘目前还没有治愈方法。
De novo identification of complex traits associated with asthma
Roan E Zaied, Tayaza Fadason, Justin M O'Sullivan
Abstract
Introduction: Asthma is a heterogeneous inflammatory disease often associated with other complex phenotypes. Identifying asthma-associated diseases and uncovering the molecular mechanisms mediating their interaction can help detangle the heterogeneity of asthma. Network analysis is a powerful approach for untangling such inter-disease relationships.
Methods: Here, we integrated information on physical contacts between common single nucleotide polymorphisms (SNPs) and gene expression with expression quantitative trait loci (eQTL) data from the lung and whole blood to construct two tissue-specific spatial gene regulatory networks (GRN). We then located the asthma GRN (level 0) within each tissue-specific GRN by identifying the genes that are functionally affected by asthma-associated spatial eQTLs. Curated protein interaction partners were subsequently identified up to four edges or levels away from the asthma GRN. The eQTLs spatially regulating genes on levels 0-4 were queried against the GWAS Catalog to identify the traits enriched (hypergeometric test; FDR ≤ 0.05) in each level.
Results: We identified 80 and 82 traits significantly enriched in the lung and blood GRNs, respectively. All identified traits were previously reported to be comorbid or associated (positively or negatively) with asthma (e.g., depressive symptoms and lung cancer), except 8 traits whose association with asthma is yet to be confirmed (e.g., reticulocyte count). Our analysis additionally pinpoints the variants and genes that link asthma to the identified asthma-associated traits, a subset of which was replicated in a comorbidity analysis using health records of 26,781 asthma patients in New Zealand.
Discussion: Our discovery approach identifies enriched traits in the regulatory space proximal to asthma, in the tissue of interest, without a priori selection of the interacting traits. The predictions it makes expand our understanding of possible shared molecular interactions and therapeutic targets for asthma, where no cure is currently available.
引言：哮喘是一种异质性炎症性疾病，通常与其他复杂表型有关。识别哮喘相关疾病并揭示介导其相互作用的分子机制有助于揭示哮喘的异质性。网络分析是解开这种疾病间关系的有力方法。
方法：本文中，我们将常见单核苷酸多态性（SNP）和基因表达之间的物理接触信息与来自肺和全血的表达定量性状基因座（eQTL）数据相结合，构建两个组织特异性空间基因调控网络（GRN）。然后，我们通过鉴定受哮喘相关空间eQTL功能影响的基因，在每个组织特异性GRN中定位哮喘GRN（0级）。随后，在远离哮喘GRN的四个边缘或水平处鉴定出了Curated蛋白质相互作用伴侣。
结果：我们分别鉴定了80个和82个在肺和血液GRN中显著富集的性状。除8个与哮喘相关的性状（如网织红细胞计数）尚待证实外，所有已鉴定的性状均与哮喘（如抑郁症状和肺癌癌症）共病或相关（阳性或阴性）。我们的分析还精确定位了将哮喘与已确定的哮喘相关特征联系起来的变异和基因，其中一个子集在新西兰26781名哮喘患者的健康记录的共病分析中得到了重现。
讨论：我们的发现方法在感兴趣的组织中，在哮喘附近的调节空间中识别出富集的特征，而无需事先选择相互作用的特征。它所做的预测扩大了我们对哮喘可能存在的共同分子相互作用和治疗靶点的理解，而哮喘目前还没有治愈方法。
(中日友好医院呼吸与危重症医学科 顾宪民 摘译 林江涛 审校)
(Front Immunol. 2023 Aug 23;14:1231492. doi: 10.3389/fimmu.2023.1231492. eCollection 2023.)
(Front Immunol. 2023 Aug 23;14:1231492. doi: 10.3389/fimmu.2023.1231492. eCollection 2023.)
De novo identification of complex traits associated with asthma
Roan E Zaied, Tayaza Fadason, Justin M O'Sullivan
Abstract
Introduction: Asthma is a heterogeneous inflammatory disease often associated with other complex phenotypes. Identifying asthma-associated diseases and uncovering the molecular mechanisms mediating their interaction can help detangle the heterogeneity of asthma. Network analysis is a powerful approach for untangling such inter-disease relationships.
Methods: Here, we integrated information on physical contacts between common single nucleotide polymorphisms (SNPs) and gene expression with expression quantitative trait loci (eQTL) data from the lung and whole blood to construct two tissue-specific spatial gene regulatory networks (GRN). We then located the asthma GRN (level 0) within each tissue-specific GRN by identifying the genes that are functionally affected by asthma-associated spatial eQTLs. Curated protein interaction partners were subsequently identified up to four edges or levels away from the asthma GRN. The eQTLs spatially regulating genes on levels 0-4 were queried against the GWAS Catalog to identify the traits enriched (hypergeometric test; FDR ≤ 0.05) in each level.
Results: We identified 80 and 82 traits significantly enriched in the lung and blood GRNs, respectively. All identified traits were previously reported to be comorbid or associated (positively or negatively) with asthma (e.g., depressive symptoms and lung cancer), except 8 traits whose association with asthma is yet to be confirmed (e.g., reticulocyte count). Our analysis additionally pinpoints the variants and genes that link asthma to the identified asthma-associated traits, a subset of which was replicated in a comorbidity analysis using health records of 26,781 asthma patients in New Zealand.
Discussion: Our discovery approach identifies enriched traits in the regulatory space proximal to asthma, in the tissue of interest, without a priori selection of the interacting traits. The predictions it makes expand our understanding of possible shared molecular interactions and therapeutic targets for asthma, where no cure is currently available.
上一篇：
成人中重度哮喘患者的饮食炎症指数和临床转归指标
下一篇：
与NSAID加重呼吸道疾病症状序列相关的性别、种族、BMI和环境暴露
