Polymorphisms in drug metabolism genes predict the risk of refractory myasthenia gravis.
Polymorphisms in drug metabolism genes predict the risk of refractory myasthenia gravis.
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药物代谢基因多态性预测难治性重症肌无力的风险
DOI:
10.21037/atm-22-2543
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发表时间:
2022-11
影响因子:
--
通讯作者:
Bu, Bitao
中科院分区:
文献类型:
--
作者:
Zhang, Qing;Ge, Huizhen;Gui, Mengcui;Yang, Mengge;Bi, Zhuajin;Ma, Xue;Gu, Zhongya;Peng, Shu;Chen, Tao;Bu, Bitao
Background Nearly 10% to 20% of myasthenia gravis (MG) patients are refractory to conventional treatment for unclear reasons. The study aimed to explore the relationship between drug metabolism gene polymorphisms and refractory MG. Methods One hundred and thirty-one MG patients (33 in the refractory group; 98 in the non-refractory group) admitted to Tongji Hospital were included in this retrospective study. Improved multiplex ligation detection reaction (iMLDR) was used to genotype 13 polymorphisms (NR3C1 rs17209237, rs9324921; FKBP5 rs1360780, rs4713904, rs9296158; HSP90AA1 rs10873531, rs2298877, rs7160651; MDR1 rs1045642, rs1128503, rs2032582; CYP3A4 rs2242480; and CYP3A5 rs776746). We applied multivariable logistic regression to investigate the association between refractory MG and nucleotide polymorphisms. Generalized multifactor dimensionality reduction (GMDR) was used to examine gene-gene interactions. Results CC genotype of HSP90AA1 rs7160651 was associated with the increased risk of refractory MG than CT genotype [odds ratio (OR) =0.26; P=0.041] and CT + TT genotype (dominant model, OR =0.24; P=0.022). For CYP3A5 rs776746, AA genotype was associated with refractory MG compared with AG genotype (OR =0.11; P=0.017), GG genotype (OR =0.18; P=0.033), and AG + GG genotype (dominant model, OR =0.16; P=0.020). The frequency of CAT haplotype of HSP90AA1 rs10873531, rs2298877, rs7160651 was less common in refractory patients (OR =0.33; P=0.044). No significant gene-gene interactions were observed. Conclusions HSP90AA1 rs7160651 and CYP3A5 rs776746 were significantly associated with refractory MG. Further studies are warranted to confirm the results and investigate the use of polymorphisms for treatment individualization.
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影响因子:
9
作者:
Zhou, Zhaohui;Xiong, Longbin;Wu, Zeshen;Jiang, Lijuan;Li, Yonghong;Li, Zhiyong;Peng, Yulu;Ning, Kang;Zou, Xiangpeng;Liu, Zefu;Wang, Jun;Li, Zhen;Zhou, Fangjian;Liu, Zhuowei;Zhang, Zhiling;Yu, Chunping
通讯作者:
Yu, Chunping
影响因子:
2.8
作者:
Maltese, P.;Palma, L.;Magnani, M.
通讯作者:
Magnani, M.
影响因子:
6.7
作者:
通讯作者:
--
影响因子:
5.6
作者:
Ouyang, Juan;Chen, Peisong;Li, Junxun
通讯作者:
Li, Junxun
影响因子:
6
作者:
Gui, Mengcui;Luo, Xuan;Bu, Bitao
通讯作者:
Bu, Bitao