Benchmarking Untargeted Metabolomics Data Quality with Allopurinol-Induced Perturbations and Concordance Tests

We present two simple benchmark tests to assess whether a metabolomics dataset is fit-for-purpose. In a study unrelated to allopurinol therapy, 1,000 serum samples were analyzed with three metabolomics panels. Endogenous metabolite markers of allopurinol therapy were evaluated based on hypotheses derived from literature. The hypothesis of upregulation was supported for xanthine, orotate, and orotidine (p < 0.0001) in allopurinol-positive cases (N=19). Secondly, the paired concordance of methionine measurements ranged from 0.88-0.92 (Spearman's rho), indicating a low error rate in laboratory workflows. These findings demonstrate the value of targeted exposomics and cross-method concordance as practical benchmarking tests for untargeted metabolomics.