Detection of catecholamine metabolites in urine based on ultra‐high‐performance liquid chromatography–tandem mass spectrometry

Abstract

The excretion of neurotransmitter metabolites in normal individuals is of great significance for health monitoring. A rapid quantitative method was developed with ultra‐performance liquid chromatography–tandem mass spectrometry. The method was further applied to determine catecholamine metabolites vanilymandelic acid (VMA), methoxy hydroxyphenyl glycol (MHPG), dihydroxy‐phenyl acetic acid (DOPAC), and homovanillic acid (HVA) in the urine. The urine was collected from six healthy volunteers (20–22 years old) for 10 consecutive days. It was precolumn derivatized with dansyl chloride. Subsequently, the sample was analyzed using triple quadrupole mass spectrometry with an electrospray ion in positive and multireaction monitoring modes. The method was sensitive and repeatable with the recoveries 92.7–104.30%, limits of detection (LODs) 0.01–0.05 μg/mL, and coefficients no less than 0.9938. The excretion content of four target compounds in random urine samples was 0.20 ± 0.086 μg/mL (MHPG), 1.27 ± 1.24 μg/mL (VMA), 3.29 ± 1.36 μg/mL (HVA), and 1.13 ± 1.07 μg/mL (DOPAC). In the urine, the content of VMA, the metabolite of norepinephrine and adrenaline, was more than MHPG, and the content of HVA, the metabolite of dopamine, was more than DOPAC. This paper detected the levels of catecholamine metabolites and summarized the characteristics of excretion using random urine samples, which could provide valuable information for clinical practice.

A highly explicit electrochemical biosensor for catechol detection in real samples based on copper-polypyrrole

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A Magnetite Composite of Molecularly Imprinted Polymer and Reduced Graphene Oxide for Sensitive and Selective Electrochemical Detection of Catechol in Water and Milk Samples: An Artificial Neural Network (ANN) Application

“…So far, huge number of physicochemical analytical tools such as gas chromatography (GC) and liquid chromatography (LC) have been used to investigate CC. [7][8][9][10][11][12] These techniques are considered sensitive and accurate analytical tools however; they suffer from several drawbacks since they are time-consuming, complicated to operate, expensive, and need sample pretreatment. On the other hand, electrochemical techniques may overcome these challenges because they offer highly sensitive, simple, and more selective detection of CC and they don't require sample pretreatment.…”