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摘要

背景:遗传和环境因素对人类疾病都有影响。大多数常见疾病受到大量遗传和环境因素的影响,其中大多数单独对疾病的影响不大。虽然遗传因素对某些单基因疾病的影响相对较好,但没有努力整理环境病因的广泛清单。结果:通过对MEDLINE文章的MeSH注释的全面检索,我们确定了3,342种与3,159种疾病相关的环境病因。我们还从美国国立卫生研究院遗传协会数据库(GAD)(一个遗传关联研究数据库)中确定了1100个与1034种复杂疾病相关的基因。863种疾病既有遗传因素,也有环境因素。将遗传因素和环境因素结合起来形成“时间组”,我们将其定义为疾病病因学的综合纲要。环境因素的聚类可能会提醒临床医生增加暴露的风险,或者在干预措施中协同改变这些因素。遗传和环境因素的聚类使基因以定量的方式置于环境的背景下。结论:本文通过MEDLINE文章的MeSH标注,获得了疾病与环境因素之间的综合关联列表。它是对病因和疾病之间现有知识的总结。通过结合GAD的环境病因和遗传因素,我们计算了863种疾病的“时间组”谱。通过这些特征比较疾病可能对临床医学、基础科学研究和基于人口的科学有实用价值。
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Clustering
Background: Both genetic and environmental factors contribute to human diseases. Most common diseases are influenced by a large number of genetic and environmental factors, most of which individually have only a modest effect on the disease. Though genetic contributions are relatively well characterized for some monogenetic diseases, there has been no effort at curating the extensive list of environmental etiological factors. Results: From a comprehensive search of the MeSH annotation of MEDLINE articles, we identified 3,342 environmental etiological factors associated with 3,159 diseases. We also identified 1,100 genes associated with 1,034 complex diseases from the NIH Genetic Association Database (GAD), a database of genetic association studies. 863 diseases have both genetic and environmental etiological factors available. Integrating genetic and environmental factors results in the "etiome", which we define as the comprehensive compendium of disease etiology. Clustering of environmental factors may alert clinicians of the risks of added exposures, or synergy in interventions to alter these factors. Clustering of both genetic and environmental etiological factors puts genes in the context of environment in a quantitative manner. Conclusion: In this paper, we obtained a comprehensive list of associations between disease and environmental factors using MeSH annotation of MEDLINE articles. It serves as a summary of current knowledge between etiological factors and diseases. By combining the environmental etiological factors and genetic factors from GAD, we computed the "etiome" profile for 863 diseases. Comparing diseases across these profiles may have utility for clinical medicine, basic science research, and population-based science.
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