PDF(Pubmed)
Abstract：
Metabolomics has gained much attention due to its potential to reveal molecular disease mechanisms and present viable biomarkers. This work uses a panel of untargeted serum metabolomes from 602 children from the COPSAC2010 mother-child cohort. The annotated part of the metabolome consists of 517 chemical compounds curated using automated procedures. We created a filtering method for the quantified metabolites using predicted quantitative structure-bioactivity relationships for the Tox21 database on nuclear receptors and stress response in cell lines. The metabolites measured in the children\'s serums are predicted to affect specific targeted models, known for their significance in inflammation, immune function, and health outcomes. The targets from Tox21 have been used as targets with quantitative structure-activity relationships (QSARs). They were trained for ~7000 structures, saved as models, and then applied to the annotated metabolites to predict their potential bioactivities. The models were selected based on strict accuracy criteria surpassing random effects. After application, 52 metabolites showed potential bioactivity based on structural similarity with known active compounds from the Tox21 set. The filtered compounds were subsequently used and weighted by their bioactive potential to show an association with early childhood hs-CRP levels at six months in a linear model supporting a physiological adverse effect on systemic low-grade inflammation.
摘要：
代谢组学由于其揭示分子疾病机制和提供可行的生物标志物的潜力而受到广泛关注。这项工作使用了一组来自COPSAC2010母子队列的602名儿童的非靶向血清代谢组。代谢组的注释部分由使用自动化程序管理的517种化合物组成。我们使用Tox21数据库中关于细胞系中核受体和应激反应的预测的定量结构-生物活性关系，为定量代谢物创建了一种过滤方法。预测在儿童血清中测量的代谢物会影响特定的目标模型，以它们在炎症中的重要性而闻名，免疫功能，和健康结果。来自Tox21的靶标已被用作具有定量结构-活性关系(QSAR)的靶标。他们接受了7000个结构的训练，保存为模型,然后应用于注释的代谢物以预测其潜在的生物活性。这些模型是根据超过随机效应的严格准确性标准选择的。申请后,基于与Tox21组的已知活性化合物的结构相似性，52种代谢物显示出潜在的生物活性。随后使用过滤的化合物并通过其生物活性潜力加权,以在支持对全身性低度炎症的生理不利影响的线性模型中在六个月时显示与早期儿童hs-CRP水平的关联。
