IAC - Istituto per le Applicazioni del Calcolo "Mauro Picone," CNR - Consiglio Nazionale delle Ricerche Rome, Italy ; Group of Clinical Genomic Networks, Key Laboratory of Computational Biology, Chinese Academy of Sciences - Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences Shanghai, China.
Group of Clinical Genomic Networks, Key Laboratory of Computational Biology, Chinese Academy of Sciences - Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences Shanghai, China.
Front Cell Dev Biol. 2014 Nov 4;2:59. doi: 10.3389/fcell.2014.00059. eCollection 2014.
To provide a frame to estimate the systemic impact (side/adverse events) of (novel) therapeutic targets by taking into consideration drugs potential on the numerous districts involved in rheumatoid arthritis (RA) from the inflammatory and immune response to the gut-intestinal (GI) microbiome.
We curated the collection of molecules from high-throughput screens of diverse (multi-omic) biochemical origin, experimentally associated to RA. Starting from such collection we generated RA-related protein-protein interaction (PPI) networks (interactomes) based on experimental PPI data. Pharmacological treatment simulation, topological and functional analyses were further run to gain insight into the proteins most affected by therapy and by multi-omic modeling.
Simulation on the administration of MTX results in the activation of expected (apoptosis) and adverse (nitrogenous metabolism alteration) effects. Growth factor receptor-bound protein 2 (GRB2) and Interleukin-1 Receptor Associated Kinase-4 (IRAK4, already an RA target) emerge as relevant nodes. The former controls the activation of inflammatory, proliferative and degenerative pathways in host and pathogens. The latter controls immune alterations and blocks innate response to pathogens.
This multi-omic map properly recollects in a single analytical picture known, yet complex, information like the adverse/side effects of MTX, and provides a reliable platform for in silico hypothesis testing or recommendation on novel therapies. These results can support the development of RA translational research in the design of validation experiments and clinical trials, as such we identify GRB2 as a robust potential new target for RA for its ability to control both synovial degeneracy and dysbiosis, and, conversely, warn on the usage of IRAK4-inhibitors recently promoted, as this involves potential adverse effects in the form of impaired innate response to pathogens.
通过考虑药物对类风湿关节炎（RA）多个涉及炎症和免疫反应到肠道（GI）微生物组的区域的潜在影响，为（新型）治疗靶点的系统影响（副作用/不良反应）提供一个框架。
我们从高通量筛选的多种（多组学）生化起源的分子中进行筛选，这些分子与 RA 相关。从该集合中，我们基于实验 PPI 数据生成了与 RA 相关的蛋白质 - 蛋白质相互作用（PPI）网络（相互作用组）。进一步进行药物治疗模拟、拓扑和功能分析，以深入了解受治疗和多组学模型影响最大的蛋白质。
模拟 MTX 的给药会导致预期的（细胞凋亡）和不良（氮代谢改变）作用的激活。生长因子受体结合蛋白 2（GRB2）和白细胞介素 1 受体相关激酶 4（IRAK4，已经是 RA 的靶点）作为相关节点出现。前者控制宿主和病原体中炎症、增殖和退行性途径的激活。后者控制免疫改变并阻止对病原体的先天反应。
该多组学图谱在单个分析图中恰当地收集了已知但复杂的信息，如 MTX 的不良反应/副作用，并为计算机模拟假设测试或新型治疗方法提供了可靠的平台。这些结果可以支持 RA 转化研究在验证实验和临床试验设计中的发展，因为 GRB2 作为一个控制滑膜退变和微生态失调的强大的潜在新靶点，以及相反地，警告 IRAK4 抑制剂的使用，因为这会以对病原体先天反应受损的形式导致潜在的不良反应。
