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This study aims to develop a novel urine test to estimate MPA exposure based using metabolomics.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Urine samples obtained on the same day of MPA pharmacokinetic testing from two prospective cohorts of pediatric kidney transplant recipients were assayed for 133 unique metabolites by mass spectrometry. Partial least squares (PLS) discriminate analysis was used to develop a top 10 urinary metabolite classifier that estimates MPA exposure. An independent cohort was used to test pharmacodynamic validity for allograft inflammation (urinary CXCL10 levels) and eGFR ratio (12mo\/1mo eGFR) at 1\u2009year.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Fifty\u2010two urine samples from separate children (36.5% female, 12.0\u00a0\u00b1\u20095.3\u2009years at transplant) were evaluated at 1.6\u00a0\u00b1\u20092.5\u2009years post\u2010transplant. Using all detected metabolites (<jats:italic>n<\/jats:italic>\u00a0=\u200990), the classifier exhibited strong association with MPA AUC by principal component regression (<jats:italic>r<\/jats:italic>\u00a0=\u20090.56, <jats:italic>p<\/jats:italic>\u00a0&lt;\u2009.001) and PLS (<jats:italic>r<\/jats:italic>\u00a0=\u20090.75, <jats:italic>p<\/jats:italic>\u00a0&lt;\u2009.001). A practical classifier (top 10 metabolites; <jats:italic>r<\/jats:italic>\u00a0=\u20090.64, <jats:italic>p<\/jats:italic>\u00a0&lt;\u2009.001) retained similar accuracy after cross\u2010validation (LOOCV; <jats:italic>r<\/jats:italic>\u00a0=\u20090.52, <jats:italic>p<\/jats:italic>\u00a0&lt;\u2009.001). When applied to an independent cohort (<jats:italic>n<\/jats:italic>\u00a0=\u200997 patients, 1053 samples), estimated mean MPA exposure over Year 1 was inversely associated with mean urinary CXCL10:Cr (<jats:italic>r<\/jats:italic>\u00a0=\u2009\u22120.28, 95% CI \u22120.45, \u22120.08) and exhibited a trend for association with eGFR ratio (<jats:italic>r<\/jats:italic>\u00a0=\u20090.35, <jats:italic>p<\/jats:italic>\u00a0=\u2009.07), over the same time period.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>This urinary metabolite classifier can estimate MPA exposure and correlates with allograft inflammation. Future studies with larger samples are required to validate and evaluate its clinical application.<\/jats:p><\/jats:sec>","DOI":"10.1111\/petr.14460","type":"journal-article","created":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T06:15:50Z","timestamp":1672380950000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Noninvasive testing for mycophenolate exposure in children with renal transplant using urinary metabolomics"],"prefix":"10.1111","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3271-8098","authenticated-orcid":false,"given":"Khalid","family":"Taha","sequence":"first","affiliation":[{"name":"Department of Pediatrics University of British Columbia, BC Children's Hospital Vancouver  Vancouver British Columbia 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