Quantifying catecholamines using multi-way kinetic modelling

• Published in: Analytica chimica acta Vol. 475; no. 1; pp. 137 - 150
• Main Authors: Nikolajsen, Rikke P.H, Booksh, Karl S, Hansen, Åse M, Bro, Rasmus
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 03.01.2003; Elsevier
• Subjects: Analysis of complex biological substances; Analytical, structural and metabolic biochemistry; Biological and medical sciences; Blood and biological fluids; Catecholamines; Fundamental and applied biological sciences. Psychology; Kinetics; PARAFAC; Stress; Trihydroxyindole; Urine; Urine; Catecholamines; Kinetics; Trihydroxyindole; Stress; PARAFAC; Epinephrine; Biological fluid; Parallel algorithm; Data analysis; Biochemical analysis; Factor analysis; Catecholamine; Fluorescence spectrometry; PLS regression; Multicomponent analysis; Analytical reagent; Norepinephrine; Indole derivatives; Chemometrics; Quantitative analysis
• ISSN: 0003-2670; 1873-4324
• DOI: 10.1016/S0003-2670(02)01256-4

A new method for quantifying adrenaline and noradrenaline concentrations from mixtures of catecholamine standards is described. The method derives selectivity from the different rates, at which the fluorescing 3,5,6-trihydroxyindole derivatives (lutines) of the catecholamines are formed and degraded for adrenaline and noradrenaline. The standards used had the concentration ranges 50–1200 nmol/l for adrenaline and 30–1400 nmol/l for noradrenaline. Fluorescence landscapes were measured at consecutive time points for every sample hereby creating a four-way data array. It is shown that the raw dataset can be dramatically reduced in size without loosing significant information hereby making calculations much faster and lessening instrumental performance requirements. The data follow a two-component four-way parallel factor analysis model (PARAFAC), from which quantitative information is also obtained. Two-component multilinear partial least squares regression ( N-PLSR) was also employed for the quantification of the catecholamines. The results for PARAFAC and N-PLSR were very similar with root mean squared errors of cross-validation (RMSECV) being in the range 24–30 nmol/l. Several improvements of the method are suggested, and it is expected that the method will be suitable for determination of catecholamines in urine from healthy subjects.