Abstract
Metabolic phenotyping using mass spectrometry (MS) is being applied to ever increasing sample numbers in clinical and epidemiology studies. High-throughput and robust methods are being developed for the accurate measurement of metabolites associated with disease. Traditionally, quantitative assays have utilized triple quadrupole (QQQ) MS based methods; however, the use of such focused methods removes the ability to perform discovery-based metabolic phenotyping. An integrated workflow for the hybrid simultaneous quantification of 34 biogenic amines in combination with full scan high-resolution accurate mass (HRAM) exploratory metabolic phenotyping is presented. Primary and secondary amines are derivatized with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate prior to revered-phase liquid chromatographic separation and mass spectrometric detection. Using the HRAM-MS data, retrospective phenotypic data mining could be performed, demonstrating the versatility of HRAM-MS instrumentation in a clinical and molecular epidemiological environment. Quantitative performance was assessed using two MS detector platforms: Waters TQ-XS (QQQ; n = 3) and Bruker Impact II QToF (HRAMS-MS; n = 2) and three human biofluids (plasma, serum and urine). Finally, each platform was assessed using a certified external reference sample (NIST SRM 1950 plasma). Intra- and inter-day accuracy and precision were comparable between the QQQ and QToF instruments (<15%), with excellent linearity (R2 > 0.99) over the quantification range of 1–400 μmol L−1. Quantitative values were comparable across all instruments for human plasma, serum and urine samples, and calculated concentrations were verified against certified reference values for NIST SRM 1950 plasma as an external reference. As a real-life biological exemplar, the method was applied to plasma samples obtained from SARS-CoV-2 positive patients versus healthy controls. Both the QQQ and QToF approaches were equivalent in being able to correctly classify SARS-CoV-2 positivity. Critically, the use of HRAM full scan data was also assessed for retrospective exploratory mining of data to extract additional biogenic amines of biomarker interest beyond the 34 quantified targets.
Highlights
IntroductionThe metabolic phenotype (or metabotype [1]) of an individual is determined by their complex history of gene-environment interactions
The metabolic phenotype of an individual is determined by their complex history of gene-environment interactions
The high-resolution accurate mass (HRAM) paradigm has become crucial for understanding the complexity of biological systems and for delivering better personalized diagnostics and medicine, with combined capabilities of recording a global and quantitative view of the metabolome simultaneously
Summary
The metabolic phenotype (or metabotype [1]) of an individual is determined by their complex history of gene-environment interactions. Such metabotypes are linked to disease risks at both the individual and population levels and are strongly influenced by disease processes themselves [1,2]. Mass spectrometry is one of the most commonly adopted techniques for the detection and investigation of metabolic changes, often combined with directly-coupled chromato graphic separation [9,10]. In discovery studies the majority of mass spectrometric metabolite phenotyping studies take advantage of high-resolution accurate mass (HRAM) instrumentation (mass resolu tion > 10,000), commonly quadrupole-time-of-flight (QToF) and Orbi trap technologies, for the detection and characterization of unknown analytes. A key advantage of full scan HRAM data is the ability to revisit the dataset to perform retrospective mining and analysis should future unanswered questions arise
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