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Molecular networking for drug toxicities studies: The case of hydroxychloroquine in covid-19 patients

Abstract : Using drugs to treat COVID-19 symptoms may induce adverse effects and modify patient outcomes. These adverse events may be further aggravated in obese patients, who often present different illnesses such as metabolic-associated fatty liver disease. In Rennes University Hospital, several drug such as hydroxychloroquine (HCQ) have been used in the clinical trial HARMONICOV to treat COVID-19 patients, including obese patients. The aim of this study is to determine whether HCQ metabolism and hepatotoxicity are worsened in obese patients using an in vivo/in vitro approach. Liquid chromatography high resolution mass spectrometry in combination with untargeted screening and molecular networking were employed to study drug metabolism in vivo (patient’s plasma) and in vitro (HepaRG cells and RPTEC cells). In addition, HepaRG cells model were used to reproduce pathophysiological features of obese patient metabolism, i.e., in the condition of hepatic steatosis. The metabolic signature of HCQ was modified in HepaRG cells cultured under a steatosis condition and a new metabolite was detected (carboxychloroquine). The RPTEC model was found to produce only one metabolite. A higher cytotoxicity of HCQ was observed in HepaRG cells exposed to exogenous fatty acids, while neutral lipid accumulation (steatosis) was further enhanced in these cells. These in vitro data were compared with the biological parameters of 17 COVID-19 patients treated with HCQ included in the HARMONICOV cohort. Overall, our data suggest that steatosis may be a risk factor for altered drug metabolism and possibly toxicity of HCQ. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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Submitted on : Friday, May 6, 2022 - 11:31:49 AM
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P.-J. Ferron, B. Le Daré, J. Bronsard, C. Steichen, E. Babina, et al.. Molecular networking for drug toxicities studies: The case of hydroxychloroquine in covid-19 patients. International Journal of Molecular Sciences, MDPI, 2022, 23 (1), pp.82. ⟨10.3390/ijms23010082⟩. ⟨hal-03515202⟩

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