Emerging chemicals framework – curation of a database of chemicals of emerging concern

Abstract

TPS 624: Exposures to pops, voc and other chemicals, Johan Friso Foyer, Floor 1, August 26, 2019, 3:00 PM - 4:30 PM As part of the HBM4EU project, a generic framework is proposed for the detection and annotation of chemicals of emerging concern (CECs) in human samples. This framework incorporates both suspect screening in untargeted high-resolution mass spectrometry (HRMS) data and effect-directed analysis (EDA). In order to support suspect screening and EDA, a comprehensive database of CECs is required. Advances in untargeted HRMS techniques and computational tools facilitate the measurement and annotation of thousands of small molecules in environmental and biological samples. These techniques are also used in metabolomics. A putative identification can be acquired by comparing the masses of the measured features with the masses of known compounds. Therefore, the first element of the framework was the curation of a list of CECs to be used for suspect screening in untargeted HRMS data. This list is a compilation of 51 databases from various international sources reporting on CECs, resulting in more than 70 000 unique compounds both in terms of structure and stereochemistry. The CECs list includes chemical information generated from SMILES strings including molecular formula, charge, masses. Furthermore, information on toxicity and exposure will be included by making use of QSARs and web-based search of existing data. Finally, CEC metabolites will be simulated, which is of major importance for suspect screening of human samples. The CECs database aggregates for the first time different sources of information at international level on this topic as well as information on exposure, toxicity and possible metabolites. Metabolomics is progressively more used in epidemiological studies. However, most of the detected features remain unidentified. Therefore, the interpretation is difficult, especially for exogenous compounds. The proposed framework, which incorporates this comprehensive database of CECs, can facilitate the interpretation by identifying a part of the features found.