Rosen Vollmar Ana K, Rattray Nicholas J W, Cai Yuping, Santos-Neto Álvaro J, Deziel Nicole C, Jukic Anne Marie Z, Johnson Caroline H
Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06510, USA.
Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, G4 0RE Glasgow, UK.
Metabolites. 2019 Sep 21;9(10):198. doi: 10.3390/metabo9100198.
Metabolomics studies of the early-life exposome often use maternal urine specimens to investigate critical developmental windows, including the periconceptional period and early pregnancy. During these windows changes in kidney function can impact urine concentration. This makes accounting for differential urinary dilution across samples challenging. Because there is no consensus on the ideal normalization approach for urinary metabolomics data, this study's objective was to determine the optimal post-analytical normalization approach for untargeted metabolomics analysis from a periconceptional cohort of 45 women. Urine samples consisted of 90 paired pre- and post-implantation samples. After untargeted mass spectrometry-based metabolomics analysis, we systematically compared the performance of three common approaches to adjust for urinary dilution-creatinine adjustment, specific gravity adjustment, and probabilistic quotient normalization (PQN)-using unsupervised principal components analysis, relative standard deviation (RSD) of pooled quality control samples, and orthogonal partial least-squares discriminant analysis (OPLS-DA). Results showed that creatinine adjustment is not a reliable approach to normalize urinary periconceptional metabolomics data. Either specific gravity or PQN are more reliable methods to adjust for urinary concentration, with tighter quality control sample clustering, lower RSD, and better OPLS-DA performance compared to creatinine adjustment. These findings have implications for metabolomics analyses on urine samples taken around the time of conception and in contexts where kidney function may be altered.
早期生命暴露组的代谢组学研究通常使用母体尿液样本，以调查关键的发育窗口期，包括受孕前后时期和妊娠早期。在这些窗口期，肾功能的变化会影响尿液浓缩。这使得考虑不同样本间尿液稀释差异具有挑战性。由于对于尿液代谢组学数据的理想标准化方法尚无共识，本研究的目的是确定针对45名女性的受孕前后队列进行非靶向代谢组学分析的最佳分析后标准化方法。尿液样本包括90对植入前和植入后的样本。在基于非靶向质谱的代谢组学分析之后，我们使用无监督主成分分析、混合质量控制样本的相对标准偏差（RSD）以及正交偏最小二乘判别分析（OPLS-DA），系统地比较了三种常见的调整尿液稀释的方法——肌酐调整、比重调整和概率商归一化（PQN）——的性能。结果表明，肌酐调整不是标准化受孕前后尿液代谢组学数据的可靠方法。比重调整或PQN是调整尿液浓缩更可靠的方法，与肌酐调整相比，质量控制样本聚类更紧密、RSD更低且OPLS-DA性能更好。这些发现对于受孕前后时期采集的尿液样本以及肾功能可能改变的情况下的代谢组学分析具有启示意义。
