Network Modeling of Crohn’s Disease Incidence

BackgroundNumerous genetic and environmental risk factors play a role in human complex genetic disorders (CGD). However, their complex interplay remains to be modelled and explained in terms of disease mechanisms.Methods and findingsCrohn's Disease (CD) was modeled as a modular network of patho-physiological functions, each summarizing multiple gene-gene and gene-environment interactions. The disease resulted from one or few specific combinations of module functional states. Network aging dynamics was able to reproduce age-specific CD incidence curves as well as their variations over the past century in Western countries. Within the model, we translated the odds ratios (OR) associated to at-risk alleles in terms of disease propensities of the functional modules. Finally, the model was successfully applied to other CGD including ulcerative colitis, ankylosing spondylitis, multiple sclerosis and schizophrenia.ConclusionModeling disease incidence may help to understand disease causative chains, to delineate the potential of personalized medicine, and to monitor epidemiological changes in CGD.背景 众多遗传与环境风险因子共同参与人类复杂遗传疾病（complex genetic disorders, CGD）的发生发展，但其复杂的交互作用仍有待结合疾病机制进行建模与阐释。 方法与结果 本研究将克罗恩病（Crohn's Disease, CD）建模为病理生理功能的模块化网络，每个模块概括了多组基因-基因及基因-环境交互作用。疾病的发生源于一个或少数几个特定的模块功能状态组合。该网络的衰老动力学模型能够复现西方国家特定年龄层的克罗恩病发病曲线，以及近一个世纪以来该病发病率的变化趋势。在本模型中，我们将风险等位基因对应的比值比（odds ratios, OR）转化为功能模块的疾病易感性。最终，该模型被成功应用于其他复杂遗传疾病，包括溃疡性结肠炎、强直性脊柱炎、多发性硬化及精神分裂症。 结论 对疾病发病率进行建模，有助于解析疾病的致病链条，阐明个性化医疗的应用潜力，并助力监测复杂遗传疾病的流行病学变化。