Oral anti-diabetic drugs as endocrine disruptors in vitro - No evidence for additive effects in binary mixtures

被引:0
作者
Munkboel, Cecilie Hurup [1 ]
Hansen, Helene Stenbaek [1 ]
Jessen, Julie Buchholt [1 ]
Johannsen, Malene Louise [1 ]
Styrishave, Bjarne [1 ]
机构
[1] Univ Copenhagen, Fac Hlth & Med Sci, Dept Pharm, Toxicol & Drug Metab Grp, DK-2100 Copenhagen OE, Denmark
关键词
Anti-diabetics; Cocktail effects; Concentration addition model; Endocrine disruption; Polytherapy; Steroidogenesis; DIPEPTIDYL PEPTIDASE-4 INHIBITOR; STEROID-HORMONES; H295R CELLS; SITAGLIPTIN; METFORMIN; PHARMACOKINETICS; WOMEN; STEROIDOGENESIS; SIMVASTATIN; PREDICTION;
D O I
10.1016/j.tiv.2020.105007
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
Diabetes is one of the World's most concerning health problems and millions of patients are using anti-diabetic drugs (ADDs) in order to control blood glucose. The in vitro H295R steroidogenesis assay was implemented to investigate endocrine effects of three ADDs, metformin (MET), glimepiride (GLIM), sitagliptin (SIT) and the cholesterol-lowering drug simvastatin (SIM) individually and in three binary mixtures. Steroid hormones were analyzed using LC-MS/MS. Mixture effects were assessed by applying the Concentration Addition (CA) model. All tested drugs and binary mixtures interrupted the H295R steroidogenesis with different potency. The effects of MET:GLIM on the steroidogenesis were overall similar to the steroidogenic profile of GLIM, however effects were less pronounced. The binary mixture of MET:SIT showed overall minor effects on steroid production and only at very high concentrations. The SIM:SIT mixture showed inhibition downstream from cholesterol, which was attributed to the effects of SIM. The CA model partly predicted the effect of MET:SIT on some steroids but significantly overestimated the effects of MET:GLIM and SIM:SIT. Thus, the applicability of the CA model was limited and cocktail effects appeared to be intermediate responses of individual drugs, rather than additive. The complexity of dynamic pathways such as steroidogenesis appears to significantly reduce the use of the CA model. In conclusion, more dynamic models are needed to predict mixture effects in complex systems.
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页数:12
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