Multi-omics integration reveals molecular networks and regulators of psoriasis
Multi-omics integration reveals molecular networks and regulators of psoriasis
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DOI：
10.1186/s12918-018-0671-x
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发表时间：
2019-01-14
影响因子：
--
通讯作者：
Yang, Xia
中科院分区：
文献类型：
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作者：
Zhao, Yuqi;Jhamb, Deepali;Yang, Xia
银屑病是一种复杂的多因素疾病，涉及遗传易感性和环境诱因。已经进行了全基因组关联研究（GWAS）和表观基因组关联研究（EWAS），以确定与银屑病相关的遗传和表观遗传变异。为了全面了解银屑病的发病机制，我们进行了系统生物学研究，整合了多组学数据集，包括GWAS，EWAS，组织特异性转录组，表达数量性状位点（eQTL），基因网络和生物学途径，以确定关键基因，过程，以及与银屑病风险相关的遗传学和表观遗传学网络。结果这项整合基因组学研究鉴定了两种具有良好特征的（例如，GWAS和EWAS中的IL 17途径）和新的生物过程（例如，GWAS中的支链氨基酸催化过程和EWAS中的血小板和凝血途径）参与银屑病。最后，通过利用组织特异性基因调控网络，我们解开了银屑病相关基因和通路之间的相互作用，在组织特异性的方式和检测潜在的关键调控基因在银屑病networks.ConclusionsThe整合和收敛的多组学信号提供了更深入和全面的了解与银屑病易感性的生物学机制。
BackgroundPsoriasis is a complex multi-factorial disease, involving both genetic susceptibilities and environmental triggers. Genome-wide association studies (GWAS) and epigenome-wide association studies (EWAS) have been carried out to identify genetic and epigenetic variants that are associated with psoriasis. However, these loci cannot fully explain the disease pathogenesis.MethodsTo achieve a comprehensive mechanistic understanding of psoriasis, we conducted a systems biology study, integrating multi-omics datasets including GWAS, EWAS, tissue-specific transcriptome, expression quantitative trait loci (eQTLs), gene networks, and biological pathways to identify the key genes, processes, and networks that are genetically and epigenetically associated with psoriasis risk.ResultsThis integrative genomics study identified both well-characterized (e.g., the IL17 pathway in both GWAS and EWAS) and novel biological processes (e.g., the branched chain amino acid catabolism process in GWAS and the platelet and coagulation pathway in EWAS) involved in psoriasis. Finally, by utilizing tissue-specific gene regulatory networks, we unraveled the interactions among the psoriasis-associated genes and pathways in a tissue-specific manner and detected potential key regulatory genes in the psoriasis networks.ConclusionsThe integration and convergence of multi-omics signals provide deeper and comprehensive insights into the biological mechanisms associated with psoriasis susceptibility.