LC-MS/MS Detection of Tryptophan, Kynurenine, Kynurenic Acid, and Quinolinic Acid in Urine Samples from Drug-Positive and Illicit Drug-Negative Patients with a Known History of Substance Use Disorder

Abstract

Introduction: Currently, there are few tools for monitoring recovery in substance use disorder. As substance use has increased in prevalence, tools for measuring recovery are needed to improve therapeutic outcomes. Measuring the kynurenine pathway for imbalances in metabolites could be a possible solution to monitor recovery.

Methods: We developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify tryptophan, kynurenine, kynurenic acid, and quinolinic acid in urine. Metabolites were separated using a stepwise gradient and detected with an Agilent 6460 triple quadrupole mass analyzer. The samples were extracted using a simple protein precipitation protocol. Method validation was performed using routine toxicology urine samples and laboratory contrived samples. The performance characteristics assessed included precision, linearity, stability, interference, and matrix effects. Additionally, urine samples from two cohorts (illicit drug-negative and drug-positive; n = 120 per cohort) were analyzed for significant concentration differences in the four metabolites using Mann-Whitney, PCA, and Area Under the Receiver Operating Characteristic Curve statistical analysis.

Results: The LC-MS/MS assay was linear from 195 to 100,000 ng/mL for tryptophan, 6 to 3000 ng/mL for kynurenine, 14 to 7200 ng/mL for kynurenic acid, and 125 to 64,000 ng/mL for quinolinic acid using an 8-point calibration curve. Imprecision ranged from 1.17% to 12.46% CV using two controls that spanned the analytical measurement range. Matrix effects were observed; however, the use of labeled internal standards matching the metabolites of interest minimized the impact on quantification. The extraction recovery efficiency was acceptable for the analytical validation. Ambient stability extended to 10 days, resulting in individual sample biases of up to 22%. A statistically significant increase in TRP, KYN, and QA was observed in drug-positive urine compared to illicit drug-negative urine (p < 0.01).

Conclusion: We developed a rapid and sensitive LC-MS/MS method for quantifying tryptophan, kynurenine, kynurenic acid, and quinolinic acid in urine that can aid in future research elucidating the relationship between substance use disorders and tryptophan metabolism.

Keywords: LC-MS/MS; kynurenine; serotonin; substance use disorder; tryptophan; urine.

Figure 1

Metabolism of TRP by the kynurenine pathway showing the two main branches: the neurotoxic pathway and the neuroprotective pathway. Abbreviations: TDO: indoleamine 2,3-dioxygenase-1; IDO1/2: indoleamine 2,3-dioxygenase-1/2; TDO: tryptophan 2,3-dioxygenase; KATs: kynurenine aminotransferases; KMO: kynurenine 3-monooxygenase; KYNU: kynureninase; NE: nonenzymatic; HAAO: 3-hydroxy anthranilate 3,4-dioxygenase; NAD+: nicotinamide adenine dinucleotide.

Figure 2

Boxplot of concentrations (µg/mg) of tryptophan, kynurenine, kynurenic acid, and quinolinic acid in the samples from the illicit drug-negative (n = 120) and drug-positive cohorts (n = 120). * p < 0.05, ** p < 0.005, *** p < 0.001, **** p < 0.0005, and ns = not significant.

Figure 3

Principal component analysis (PCA) of the KYN pathway metabolites tryptophan, kynurenine, kynurenic acid, and quinolinic acid. The first two principal components explain 66.3% of the variance. Control samples cluster tightly, while the SUD samples are more dispersed.