High-Precision Automated Workflow for Urinary Untargeted Metabolomic Epidemiology

28 December 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


Urine is a non-invasive biofluid that is rich in polar metabolites and well-suited for metabolomic epidemiology. However, due to individual variability in health and hydration status, the physiological concentration of urine can differ >15-fold, which can pose major challenges in untargeted LC-MS metabolomics. Although numerous urine normalization methods have been implemented (e.g., creatinine, specific gravity – SG), most are manual and therefore not practical for population-based studies. To address this issue, we developed a method to measure SG in 96-well-plates using a refractive index detector (RID), which exhibited accuracy within 85-115% and <3.4% precision. Bland-Altman statistics showed a mean deviation of -0.0001 SG units (limits of agreement: -0.0014-0.0011) relative to a hand held refractometer. Using this RID-based SG normalization, we developed an automated LC MS workflow for untargeted urinary metabolomics in 96-well-plate format. The workflow uses positive and negative ionization HILIC chromatography and acquires mass spectra in data independent acquisition (DIA) mode at 3 collision energies. Five technical internal standards (tISs) were used to monitor data quality in each method, all of which demonstrated raw coefficients of variation (CVs) <10% in the quality controls (QCs) and <20% in the samples for a small cohort (n=87 samples, n=22 QCs). Application in a large cohort (n=842 urine samples, n=248 QCs), demonstrated CVQC<5% and CVsamples<16% for 4/5 tISs after signal drift correction by cubic spline regression. The workflow identified >540 urinary metabolites including endogenous and exogenous compounds. This platform is suitable for performing urinary untargeted metabolomic epidemiology and will be useful for applications in population-based molecular phenotyping.


untargeted metabolomics application
Molecular epidemiology studies
metabolomics analyses
Metabolomics Profiling
High-Throughput Assay Development
Refractive index
Specific Gravity
Automation Protocols

Supplementary materials

20201224 UrineMethodSupplTables-ChemRXiv


Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.