No abstract

Histamine intolerance is a disorder in the homeostasis of histamine due to a reduced intestinal degradation of this amine, mainly caused by diamine oxidase (DAO) enzyme deficiency, which provokes its accumulation in plasma and the appearance of adverse health affects. A new approach for the diagnosis of this intolerance could be the determination of histamine and its metabolites in urine. The aim of this work was to develop and validate a rapid method to determine histamine and methylhistamine in human urine by Ultra High Performance Liquid Chromatography and Fluorimetric detection (UHPLC-FL). The proposed method is a consistent procedure to determine histamine and methylhistamine in less than 11min with adequate linearity and sensitivity. Relative standard deviation was always lower than 5.5%, ensuring method precision; and mean recovery was greater than 99% for both analytes. The structure of histamine and methylhistamine conjugated with OPA were confirmed by UHPLC-ITD-FTMS which enabled to unequivocally identify both analytes in standards and also in urine samples. The analysis of histamine and methylhistamine in urine samples could be a potential new approach for the routine diagnosis of histamine intolerance, more patient-friendly and with clear advantages in terms of equipment and personnel demand for sample collection in comparison with current plasmatic DAO activity determination.

The profile and level of 11 biogenic amines were evaluated in commercial fruit juices (apple, grapefruit, orange and pineapple) and fruit nectars (apricot, peach and\ud pear) by HPLC/FD after dansyl chloride derivatization. The biogenic amine most present in nectars is cadaverine, followed by putrescine, spermidine and spermine. Fruit juices showed a wider variability in biogenic amines profile and level, with the highest total content in orange juices. The application of chemometric tools as hierarchical cluster analysis and principal component analysis on the biogenic amine profiles of the juice samples succeeded in grouping juices on the basis of the fruit of origin. A Mathematical model with high predictive ability for fruit juices classification was obtained by linear discriminant analysis: orange (100 %), pineapple (100 %), grapefruit (80 %) and apple (70 %). This study represents the first description of biogenic amines content in these beverages. These compounds are well-known important quality parameters and demonstrated to have also a characteristic profile depending on the fruit of origin