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Data-driven integration of epidemiological and toxicological data to select candidate interacting genes and environmental factors in association with disease

机译:数据驱动的流行病学和毒理学数据整合,以选择与疾病相关的候选相互作用基因和环境因素

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Motivation: Complex diseases, such as Type 2 Diabetes Mellitus (T2D), result from the interplay of both environmental and genetic factors. However, most studies investigate either the genetics or the environment and there are a few that study their possible interaction in context of disease. One key challenge in documenting interactions between genes and environment includes choosing which of each to test jointly. Here, we attempt to address this challenge through a data- driven integration of epidemiological and toxicological studies. Specifically, we derive lists of candidate interacting genetic and environmental factors by integrating findings from genome- wide and environment- wide association studies. Next, we search for evidence of toxicological relationships between these genetic and environmental factors that may have an etiological role in the disease. We illustrate our method by selecting candidate interacting factors for T2D.
机译:动机:复杂的疾病,例如2型糖尿病(T2D),是环境和遗传因素共同作用的结果。但是,大多数研究都对遗传学或环境进行了研究,很少有人研究其在疾病背景下的可能相互作用。记录基因和环境之间相互作用的一个关键挑战包括选择要共同测试的每个。在这里,我们尝试通过流行病学和毒理学研究的数据驱动整合来应对这一挑战。具体来说,我们通过整合全基因组和全环境关联研究的结果,得出候选相互作用的遗传和环境因素的列表。接下来,我们寻找这些遗传和环境因素之间可能在该病中起病因作用的毒理关系的证据。我们通过选择T2D的候选相互作用因子来说明我们的方法。

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