Nandania Jatin, Peddinti Gopal, Pessia Alberto, Kokkonen Meri, Velagapudi Vidya
Metabolomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, HiLIFE, Tukholmankatu 8, Biomedicum 2U, 00290 Helsinki, Finland.
Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany.
Metabolites. 2018 Aug 5;8(3):44. doi: 10.3390/metabo8030044.
The use of metabolomics profiling to understand the metabolism under different physiological states has increased in recent years, which created the need for robust analytical platforms. Here, we present a validated method for targeted and semiquantitative analysis of 102 polar metabolites that cover major metabolic pathways from 24 classes in a single 17.5-min assay. The method has been optimized for a wide range of biological matrices from various organisms, and involves automated sample preparation and data processing using an inhouse developed R-package. To ensure reliability, the method was validated for accuracy, precision, selectivity, specificity, linearity, recovery, and stability according to European Medicines Agency guidelines. We demonstrated an excellent repeatability of retention times (CV < 4%), calibration curves (R² ≥ 0.980) in their respective wide dynamic concentration ranges (CV < 3%), and concentrations (CV < 25%) of quality control samples interspersed within 25 batches analyzed over a period of one year. The robustness was demonstrated through a high correlation between metabolite concentrations measured using our method and the NIST reference values (R² = 0.967), including cross-platform comparability against the BIOCRATES AbsoluteIDQp180 kit (R² = 0.975) and NMR analyses (R² = 0.884). We have shown that our method can be successfully applied in many biomedical research fields and clinical trials, including epidemiological studies for biomarker discovery. In summary, a thorough validation demonstrated that our method is reproducible, robust, reliable, and suitable for metabolomics studies.
近年来，利用代谢组学分析来了解不同生理状态下的代谢情况日益增多，这就需要强大的分析平台。在此，我们提出一种经过验证的方法，可在单次17.5分钟的分析中对102种极性代谢物进行靶向和半定量分析，这些代谢物涵盖了24类主要代谢途径。该方法已针对来自各种生物体的广泛生物基质进行了优化，包括使用内部开发的R包进行自动化样品制备和数据处理。为确保可靠性，根据欧洲药品管理局的指导方针，对该方法的准确性、精密度、选择性、特异性、线性、回收率和稳定性进行了验证。我们证明了保留时间具有出色的重复性（CV < 4%），校准曲线在各自较宽的动态浓度范围内（CV < 3%）的R² ≥ 0.980，以及在一年时间内分析的25批次中穿插的质量控制样品浓度的重复性（CV < 25%）。通过我们的方法测得的代谢物浓度与美国国家标准与技术研究院（NIST）参考值之间的高度相关性（R² = 0.967）证明了该方法的稳健性，包括与BIOCRATES AbsoluteIDQ p180试剂盒的跨平台可比性（R² = 0.975）以及核磁共振分析（R² = 0.884）。我们已经表明，我们的方法可以成功应用于许多生物医学研究领域和临床试验，包括用于生物标志物发现的流行病学研究。总之，全面的验证表明我们的方法具有可重复性、稳健性、可靠性，适用于代谢组学研究。
