对英国生物库中约 12 万名参与者的 NMR 代谢生物标志物数据的质量控制和技术变异去除。

Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants.

机构信息

Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Cambridge Baker Systems Genomics Initiative, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia.

出版信息

Sci Data. 2023 Jan 31;10(1):64. doi: 10.1038/s41597-023-01949-y.

Metabolic biomarker data quantified by nuclear magnetic resonance (NMR) spectroscopy in approximately 121,000 UK Biobank participants has recently been released as a community resource, comprising absolute concentrations and ratios of 249 circulating metabolites, lipids, and lipoprotein sub-fractions. Here we identify and characterise additional sources of unwanted technical variation influencing individual biomarkers in the data available to download from UK Biobank. These included sample preparation time, shipping plate well, spectrometer batch effects, drift over time within spectrometer, and outlier shipping plates. We developed a procedure for removing this unwanted technical variation, and demonstrate that it increases signal for genetic and epidemiological studies of the NMR metabolic biomarker data in UK Biobank. We subsequently developed an R package, ukbnmr, which we make available to the wider research community to enhance the utility of the UK Biobank NMR metabolic biomarker data and to facilitate rapid analysis.

最近，英国生物样本库（UK Biobank）发布了一项社区资源，其中包含了大约 121000 名参与者的基于核磁共振（NMR）光谱的代谢生物标志物数据，这些数据量化了 249 种循环代谢物、脂质和脂蛋白亚组分的绝对浓度和比值。在这里，我们鉴定并描述了其他一些会影响可从 UK Biobank 下载的数据集内单个生物标志物的非期望技术变异源。这些变异源包括样本制备时间、板孔的运输、光谱仪批次效应、光谱仪内随时间的漂移以及异常运输板。我们开发了一种去除这种非期望技术变异的程序，并证明它增加了 UK Biobank NMR 代谢生物标志物数据的遗传和流行病学研究的信号。随后，我们开发了一个 R 包，ukbnmr，我们将其提供给更广泛的研究社区，以增强 UK Biobank NMR 代谢生物标志物数据的实用性，并促进快速分析。