TY - JOUR
T1 - Chemical Exposure Highlighted without Any A Priori Information in an Epidemiological Study by Metabolomic FT-ICR-MS Fingerprinting at High Throughput and High Resolution
AU - Habchi, Baninia
AU - Alves, Sandra
AU - Streel, Sylvie
AU - Guillaume, Michèle
AU - Donneau, Anne Françoise
AU - Appenzeller, Brice M.R.
AU - Rutledge, Douglas N.
AU - Paris, Alain
AU - Rathahao-Paris, Estelle
N1 - ACKNOWLEDGMENTS
The authors acknowledge Dr. J. Fioramonti (Toxalim, INRAE, Toulouse, France) for his support in this project, Pr. J.P. Chapelle (Service de Chimie médicale, University Hospital Centre of Liège, Belgium) for providing human urine samples, Region Ile-de-France and DIM Analytics for the financial support of B. Habchi’s thesis, the DIM ASTREA program for financing the upgrade of the FT-ICR instrument, the French FR-2054 Infranalytics research infrastructure for access to the FT-ICR instrument, and the French MetaboHUB infrastructure (ANR-11-INBS-0010 grant) for the funding.
PY - 2023/9/20
Y1 - 2023/9/20
N2 - Epidemiological studies aim to assess associations between diseases and risk factors. Such investigations involve a large sample size and require powerful analytical methods to measure the effects of risk factors, resulting in a long analysis time. In this study, chemical exposure markers were detected as the main variables strongly affecting two components coming from a principal component analysis (PCA) exploration of the metabolomic data generated from urinary samples collected on a cohort of about 500 individuals using direct introduction coupled with a Fourier-transform ion cyclotron resonance instrument. The assignment of their chemical identity was first achieved based on their isotopic fine structures detected at very high resolution (Rp > 900,000). Their identification as dimethylbiguanide and sotalol was obtained at level 1, thanks to the available authentic chemical standards, tandem mass spectrometry (MS/MS) experiments, and collision cross section measurements. Epidemiological data confirmed that the subjects discriminated by PCA had declared to be prescribed these drugs for either type II diabetes or cardiac arrhythmia. Concentrations of these drugs in urine samples of interest were also estimated by rapid quantification using an external standard calibration method, direct introduction, and MS/MS experiments. Regression analyses showed a good correlation between the estimated drug concentrations and the scores of individuals distributed on these specific PCs. The detection of these chemical exposure markers proved the potential of the proposed high-throughput approach without any prior drug exposure knowledge as a powerful emerging tool for rapid and large-scale phenotyping of subjects enrolled in epidemiological studies to rapidly characterize the chemical exposome and adherence to medical prescriptions.
AB - Epidemiological studies aim to assess associations between diseases and risk factors. Such investigations involve a large sample size and require powerful analytical methods to measure the effects of risk factors, resulting in a long analysis time. In this study, chemical exposure markers were detected as the main variables strongly affecting two components coming from a principal component analysis (PCA) exploration of the metabolomic data generated from urinary samples collected on a cohort of about 500 individuals using direct introduction coupled with a Fourier-transform ion cyclotron resonance instrument. The assignment of their chemical identity was first achieved based on their isotopic fine structures detected at very high resolution (Rp > 900,000). Their identification as dimethylbiguanide and sotalol was obtained at level 1, thanks to the available authentic chemical standards, tandem mass spectrometry (MS/MS) experiments, and collision cross section measurements. Epidemiological data confirmed that the subjects discriminated by PCA had declared to be prescribed these drugs for either type II diabetes or cardiac arrhythmia. Concentrations of these drugs in urine samples of interest were also estimated by rapid quantification using an external standard calibration method, direct introduction, and MS/MS experiments. Regression analyses showed a good correlation between the estimated drug concentrations and the scores of individuals distributed on these specific PCs. The detection of these chemical exposure markers proved the potential of the proposed high-throughput approach without any prior drug exposure knowledge as a powerful emerging tool for rapid and large-scale phenotyping of subjects enrolled in epidemiological studies to rapidly characterize the chemical exposome and adherence to medical prescriptions.
UR - http://www.scopus.com/inward/record.url?scp=85174284920&partnerID=8YFLogxK
UR - https://pubmed.ncbi.nlm.nih.gov/37729183
U2 - 10.1021/acs.chemrestox.3c00158
DO - 10.1021/acs.chemrestox.3c00158
M3 - Article
C2 - 37729183
SN - 0893-228X
VL - 36
SP - 1592
EP - 1598
JO - Chemical Research in Toxicology
JF - Chemical Research in Toxicology
IS - 10
ER -