Pyrrolizidine alkaloids (PAs) and their N-oxides (PANOs) are natural toxins, exclusively biosynthesized by a wide variety of plant species (>6000). They are secondary plant metabolites against herbivores and are believed to be one of the most widely spread natural toxins. PAs and PANOs can become a significant public human health problem from the intake of contaminated food of botanical or animal origin. Human poisoning cases have been documented; they are characterized by acute and chronic liver damage, pulmonary hypertension, cardiac or kidneys injuries, and can lead to death. Therefore, the development of efficient analytical methods is required to detect and quantify PAs/PANOs in a large range of food items.
The Belgian Scientific Institute of Public Health has directed a project aiming to report occurrence levels of PAs and PANOs in targeted food items to perform a dietary exposure assessment to these natural contaminants and evaluate if they can pose a health problem, filling a data gap at Belgium’s level. Analytical methods based on UHPLC separation and MS/MS detection were developed for the analysis of 16 PAs and 14 PANOs in honey and honey based snacks, meat and meat products, milk and dairy commodities, prepared dishes, sauces, plant based products, infusions and food supplements. The sample preparation protocols were comprised of an acidic solid-liquid extraction of the analytes followed by SPE clean-up to avoid loss of sensitivity due to matrix effect. Several steps were carefully optimized for each targeted food matrices with a specific focus on very low limits of quantification (LOQs < 1 ng/g or ng/mL), taking into account the various interfering compounds to discard. The analytical methods were validated in-house and the method’s performances were within the criteria allowed by Directive 2002/657/CE and SANTE/11945/2015. A structured sampling plan has been established for more than 1,200 samples available on the Belgian market.
The presentation will describe the analytical strategies deployed for the different food matrices, including some original approaches, and will highlight the critical parameters to obtain the best method sensitivity. Then, we will go through the analytical results and the unexpected ones in particular. Finally, the dietary intake of PAs/PANOs for different age groups from the Belgian population and the contribution of each food category will be discussed.
