NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland.
Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.
Int J Epidemiol. 2019 Jun 1;48(3):978-993. doi: 10.1093/ije/dyy287.
Quantitative molecular data from urine are rare in epidemiology and genetics. NMR spectroscopy could provide these data in high throughput, and it has already been applied in epidemiological settings to analyse urine samples. However, quantitative protocols for large-scale applications are not available.
We describe in detail how to prepare urine samples and perform NMR experiments to obtain quantitative metabolic information. Semi-automated quantitative line shape fitting analyses were set up for 43 metabolites and applied to data from various analytical test samples and from 1004 individuals from a population-based epidemiological cohort. Novel analyses on how urine metabolites associate with quantitative serum NMR metabolomics data (61 metabolic measures; n = 995) were performed. In addition, confirmatory genome-wide analyses of urine metabolites were conducted (n = 578). The fully automated quantitative regression-based spectral analysis is demonstrated for creatinine and glucose (n = 4548).
Intra-assay metabolite variations were mostly <5%, indicating high robustness and accuracy of urine NMR spectroscopy methodology per se. Intra-individual metabolite variations were large, ranging from 6% to 194%. However, population-based inter-individual metabolite variations were even larger (from 14% to 1655%), providing a sound base for epidemiological applications. Metabolic associations between urine and serum were found to be clearly weaker than those within serum and within urine, indicating that urinary metabolomics data provide independent metabolic information. Two previous genome-wide hits for formate and 2-hydroxyisobutyrate were replicated at genome-wide significance.
Quantitative urine metabolomics data suggest broad novelty for systems epidemiology. A roadmap for an open access methodology is provided.
尿液中的定量分子数据在流行病学和遗传学中较为少见。NMR 光谱技术可高通量提供此类数据，并且已经在流行病学环境中用于分析尿液样本。然而，目前尚无适用于大规模应用的定量方案。
我们详细描述了如何准备尿液样本并进行 NMR 实验，以获取定量代谢信息。针对 43 种代谢物建立了半自动定量线拟合分析，并将其应用于来自各种分析测试样本以及来自基于人群的流行病学队列中的 1004 位个体的尿液数据。对尿液代谢物与定量血清 NMR 代谢组学数据（61 种代谢物指标；n=995）之间的关联进行了新的分析。此外，还对尿液代谢物进行了全基因组确认性分析（n=578）。对肌酐和葡萄糖（n=4548）进行了全自动基于回归的定量光谱分析。
代谢物的日内分析变异大多<5%，表明尿液 NMR 光谱学方法本身具有很高的稳健性和准确性。个体内代谢物变异较大，范围为 6%至 194%。然而，基于人群的个体间代谢物变异更大（14%至 1655%），为流行病学应用提供了良好的基础。尿液与血清之间的代谢关联明显弱于血清内和尿液内的代谢关联，表明尿液代谢组学数据提供了独立的代谢信息。先前对甲酸盐和 2-羟基异丁酸的两项全基因组命中在全基因组水平上得到了显著复制。
定量尿液代谢组学数据为系统流行病学提供了广泛的新颖性。本文提供了一个开放获取方法的路线图。
