Optimization and Validation of Plasma-Based Assay for Detection and Quantification of Monoamine Neurotransmitter Metabolites Using LC-MS/MS.

One of the essential subclasses of biogenic amines is monoamine neurotransmitters, which include dopamine, serotonin, norepinephrine, and epinephrine neurotransmitters. The biosynthesis pathways of these neurotransmitters share several common substrates, metabolites, cofactors, and enzymes. Genetic mutations in these components lead to a group of rare inherited conditions termed monoamine neurotransmitter metabolic disorders (mNMDs). Existing studies report methods for measurement of a particular set of metabolites belonging to this pathway for diagnosis, frequently across different biological matrices such as cerebrospinal fluid (CSF), plasma, serum, or urine. Hence, the available assays and data are methodologically heterogeneous. In a biochemical pathway, disorder-specific metabolic patterns arise from paired alterations in multiple upstream and downstream metabolites, and these patterns can be captured only when these metabolites are measured simultaneously from the same biological matrix under similar analytical conditions. The lack of concurrent measurement limits the use of metabolite ratios, which can be of diagnostic value and pattern-based interpretation in the case of mNMDs. In this study, we report the development, optimization, and validation of a plasma-based targeted liquid chromatography-mass spectrometry (LC-MS/MS) method for the simultaneous detection and quantification of 11 key metabolites of the monoamine biosynthesis pathway. The assay was optimized for sample preparation, chromatographic separation, MS detection, and validated according to the M10 Bioanalytical Method Validation and Study Sample Analysis, US -FDA guidelines (November 2022). The method demonstrates good linearity across a broad range, high sensitivity and specificity, acceptable interday- and intraday-precision and accuracy, acceptable coefficient of variation, and lower limit of detection and quantification. The applicability of the method was further validated using plasma samples from healthy participants. As mNMDs are potentially treatable if identified early, this validated plasma-based method can provide a quick and predictive alternative to currently used different biological matrices or invasive CSF sampling for diagnosis with additional utility for longitudinal therapeutic monitoring of these treatable conditions.