Detecting a potential safety signal of antidepressants and type 2 diabetes: a pharmacovigilance-pharmacodynamic study

检测抗抑郁药与2型糖尿病之间潜在的安全信号:一项药物警戒-药效学研究

阅读:1

Abstract

AIMS: Recent data suggest that antidepressants are associated with incident diabetes but the possible pharmacological mechanism is still questioned. The aim of the present study was to evaluate antidepressant's risk for reporting diabetes using disproportionality analysis of the FDA adverse events spontaneous reporting system (FAERS) database and to investigate possible receptor/transporter mechanisms involved. METHODS: Data from 2004 to 2017 were analysed using OpenVigil2 and adjusted reporting odds ratio (aROR) for reporting diabetes was calculated for 22 antidepressants. Events included in the narrow scope of the SMQ 'hyperglycaemia/new-onset diabetes mellitus' were defined as cases and all the other events as non-cases. The pharmacodynamic profile was extracted using the PDSP and IUPHAR/BPS databases and the occupancy on receptors (serotonin, alpha adrenoreceptors, dopamine, muscarinic, histamine) and transporters (SERT, NET, DAT) was estimated. The relationship between aROR for diabetes and receptor occupancy was investigated with Pearson's correlation coefficient (r) and univariate linear regression. RESULTS: Six antidepressants were associated with diabetes: nortriptyline with aROR [95% CI] of 2.01 [1.41-2.87], doxepin 1.97 [1.31-2.97], imipramine 1.82 [1.09-3.06], sertraline 1.47 [1.29-1.68], mirtazapine 1.33 [1.04-1.69] and amitriptyline 1.31 [1.09-1.59]. Strong positive correlation coefficients between occupancy and aROR for diabetes were identified for the receptors M(1) , M(3) , M(4) , M(5) and H(1) . CONCLUSION: Most of the tricyclic antidepressants, mirtazapine and sertraline seem to be associated with reporting diabetes in FAERS. Higher degrees of occupancy on muscarinic receptors and H(1) may be a plausible pharmacological mechanism. Further clinical assessment and pharmacovigilance data is needed to validate this potential safety signal.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。