This project started with a pilot study aimed at developing and refining a state-of-the-art 'LC-SWATH/MS'-based metabolomics workflow followed by its application to relatively small numbers of clinical samples. A key aim in this study was to get a baseline understanding of this technique's capability to profile 'foreign' (exogenous) compounds and to subsequently expand this capability, as would be needed given the fact that metabolomics techniques were originally designed for studying our 'body's own' (endogenous) compounds. Therapeutic drugs were the initial targets in this pilot study as these chemicals could be found with relative ease and high confidence while also because information on drug use was already available for the study samples. The latter information was, however, derived from patient records that relied on doctor-patient interviews, and it was thus likely not surprising that considerable discrepancies were between the metabolomics-derived drug use information and the patient record-derived drug use information, particularly for diuretic drugs [1]. In fact, the newly-developed analytical workflow soon proved to be very helpful in complementing and strengthening patient-derived drug use information and was employed to support an existing pharmacoepidemiological study on diuretic drug use [2].
Building upon the lessons learned from the pilot study, an improved version of the pilot study's metabolomics workflow was applied to a full clinical study, namely the TransplantLines Food and Nutrition Biobank and Cohort Study (NCT identifier ‘NCT02811835’), which includes renal transplant recipients, potential living kidney donors, and living kidney donors (post-donation). This work yielded a wealth of information, ranging from interesting clinical findings to newly-discovered drug metabolites, while it also brought to light several analytical and post-analytical challenges associated with the upscaling of profiling studies and the substantial difference between endogenous and exogenous compounds (and how to deal with them). With regard to the latter, compounds that are present continuously like endogenous metabolites require different identification strategies than compounds of intermittent nature, which applies to most exogenous compounds. However, the corresponding challenge has long been unaddressed or even ignored, hence the EU-funded researchers of this project developed a novel data processing strategy to better study intermittent exposures. In addition, they developed a practical identification strategy to identify larger numbers of continuous exposures thereby contributing to increasing data usefulness in lifestyle and exposure research [3].
1. DOI: 10.1016/j.jclinepi.2021.02.008
2. DOI: 10.1093/ndt/gfac012
3. Manuscript submitted in January 2022
