PDF(Pubmed)
Abstract：
Aim: Hypotheses about what phenotypes to include in causal analyses, that in turn can have clinical and policy implications, can be guided by hypothesis-free approaches leveraging the epigenome, for example.Materials & methods: Minimally adjusted epigenome-wide association studies (EWAS) using ALSPAC data were performed for example conditions, dysmenorrhea and heavy menstrual bleeding (HMB). Differentially methylated CpGs were searched in the EWAS Catalog and associated traits identified. Traits were compared between those with and without the example conditions in ALSPAC.Results: Seven CpG sites were associated with dysmenorrhea and two with HMB. Smoking and adverse childhood experience score were associated with both conditions in the hypothesis-testing phase.Conclusion: Hypothesis-generating EWAS can help identify associations for future analyses.
To inform policy and improve clinical practice, it is important that researchers who study people\'s health find out which traits might increase the risk of illness. However, it can be difficult to know which traits should be looked at. In this study, we wanted to look for traits that might increase the risk of painful and heavy periods, using data about the switches that turn our genes on and off. There are some people in the Children of the 90s study that have data on gene switches. We compared all the switches between those with and without painful or heavy periods. For painful periods, we found links with seven switches and for heavy periods, we found two. We then used another data source, called the EWAS Catalog, to see which traits were associated with these switches. The traits we found included body size, smoking and child abuse. Finally, when using data on traits from the wider Children of the 90s group, we found that smoking and more difficult childhoods were some of the traits related to painful and heavy periods. A good thing about this approach is that we could find new traits that might increase the risk of painful or heavy periods; these should be looked at in future studies.
To inform policy and improve clinical practice, it is important that researchers who study people\'s health find out which traits might increase the risk of illness. However, it can be difficult to know which traits should be looked at. In this study, we wanted to look for traits that might increase the risk of painful and heavy periods, using data about the switches that turn our genes on and off. There are some people in the Children of the 90s study that have data on gene switches. We compared all the switches between those with and without painful or heavy periods. For painful periods, we found links with seven switches and for heavy periods, we found two. We then used another data source, called the EWAS Catalog, to see which traits were associated with these switches. The traits we found included body size, smoking and child abuse. Finally, when using data on traits from the wider Children of the 90s group, we found that smoking and more difficult childhoods were some of the traits related to painful and heavy periods. A good thing about this approach is that we could find new traits that might increase the risk of painful or heavy periods; these should be looked at in future studies.
摘要：
目的：关于因果分析中应包括哪些表型的假设，这反过来会产生临床和政策影响，可以通过利用表观基因组的无假设方法来指导，例如。材料和方法：使用ALSPAC数据进行最小调整的表观基因组范围关联研究（EWAS），例如条件，痛经和月经大出血（HMB）。在EWAS目录中搜索差异甲基化的CpG并鉴定相关性状。在具有和不具有ALSPAC中的示例条件的那些之间比较了性状。结果：7个CpG位点与痛经相关，2个与HMB相关。在假设检验阶段，吸烟和不良儿童经历评分与这两种情况有关。结论：假设生成EWAS可以帮助识别未来分析的关联。
为了告知政策并改善临床实践，研究人们健康的研究人员发现哪些特征可能会增加患病风险，这一点很重要。然而,很难知道应该看哪些特征。在这项研究中,我们想寻找可能增加痛苦和沉重时期风险的特征，使用有关开关的数据来打开和关闭我们的基因。90年代儿童研究中的一些人拥有基因开关的数据。我们比较了有和没有痛苦或沉重时期的所有开关。在痛苦的时期，我们发现了与七个交换机的链接，在繁重的时期，我们找到了两个.然后我们使用了另一个数据源，叫做EWAS目录，看看哪些特征与这些开关相关。我们发现的特征包括体型，吸烟和虐待儿童。最后,当使用来自更广泛的90年代儿童群体的特征数据时，我们发现，吸烟和更困难的童年是一些与痛苦和沉重时期有关的特征。这种方法的一个好处是，我们可以找到可能增加痛苦或沉重时期风险的新特征;这些应该在未来的研究中进行研究。
为了告知政策并改善临床实践，研究人们健康的研究人员发现哪些特征可能会增加患病风险，这一点很重要。然而,很难知道应该看哪些特征。在这项研究中,我们想寻找可能增加痛苦和沉重时期风险的特征，使用有关开关的数据来打开和关闭我们的基因。90年代儿童研究中的一些人拥有基因开关的数据。我们比较了有和没有痛苦或沉重时期的所有开关。在痛苦的时期，我们发现了与七个交换机的链接，在繁重的时期，我们找到了两个.然后我们使用了另一个数据源，叫做EWAS目录，看看哪些特征与这些开关相关。我们发现的特征包括体型，吸烟和虐待儿童。最后,当使用来自更广泛的90年代儿童群体的特征数据时，我们发现，吸烟和更困难的童年是一些与痛苦和沉重时期有关的特征。这种方法的一个好处是，我们可以找到可能增加痛苦或沉重时期风险的新特征;这些应该在未来的研究中进行研究。
