There is growing interest in the potential translational applications of omics data. This applies to, e.g. metabolomics, an area in which the Journal published a themed issue in 2016 with an accompanying editorial titled ‘Metabolic profiling—multitude of technologies with great research potential, but (when) will translation emerge?’¹ Despite two decades of extensive investigations with optimistic statements of potential translational applications, there is no metabolomics-derived biomarker (of either an individual metabolite in isolation or multiple metabolites in combination) that has yet to mature into clinical utility. On appraising the recent activity in polygenic risk scores (PRSs) and disease prediction, we notice parallel themes to the decades-old search for conventional (non-genetic) predictive biomarkers. An overwhelming sense of hype and a rush to translate dominates the field of genetic research of disease prediction using genetic risk scores (GRSs).

中文翻译：

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多基因风险评分与常见疾病预测。

人们对组学数据的潜在转化应用越来越感兴趣。这适用于，例如代谢组学，该杂志在 2016 年出版了一个主题问题，并附有一篇题为“代谢分析——具有巨大研究潜力的众多技术，但（何时）会出现翻译？”的社论。¹尽管进行了 20 年对潜在转化应用的乐观陈述的广泛研究，但没有代谢组学衍生的生物标志物（单独的单个代谢物或多种代谢物的组合）尚未成熟到临床应用中。在评估多基因风险评分 (PRS) 和疾病预测方面的近期活动时，我们注意到与数十年来对传统（非遗传）预测性生物标志物的搜索相似的主题。在使用遗传风险评分 (GRS) 进行疾病预测的遗传研究领域中，压倒性的炒作和急于翻译的情绪占据了主导地位。