Pharmacogenomic and clinical data link non-pharmacokinetic metabolic dysregulation to drug side effect pathogenesis.
Pharmacogenomic and clinical data link non-pharmacokinetic metabolic dysregulation to drug side effect pathogenesis.
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DOI：
10.1038/ncomms8101
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发表时间：
2015-06-09
影响因子：
16.6
通讯作者：
Palsson, Bernhard O.
中科院分区：
文献类型：
--
作者：
Zielinski, Daniel C.;Filipp, Fabian V.;Bordbar, Aarash;Jensen, Kasper;Smith, Jeffrey W.;Herrgard, Markus J.;Mo, Monica L.;Palsson, Bernhard O.
药物副作用造成严重的临床和经济负担。然而，药物的作用机制、副作用和发病机制仍不清楚。在这里，我们将药物基因组学和临床数据与人类代谢网络相结合，发现药物失调的非药代动力学代谢途径与副作用的发生有关。我们发现，这种失调的代谢途径包含影响副作用发生率的序列变异基因，在病理生理学中发挥既定作用，在相应疾病中具有显着改变的活性，易受代谢抑制剂的影响，是治疗性营养补充的有效靶点。我们的研究结果表明，代谢失调代表了一个共同的机制，潜在的副作用发病机制，不同于代谢在药物清除中的作用。我们建议，阐明细胞对药物的反应、患者的遗传变异和细胞代谢之间的关系，可能有助于通过个性化药物处方和营养干预策略来控制副作用。药物不良反应是一个重要的临床问题。在这里，作者将药物诱导的基因表达变化和患者遗传变异的信息与基因组尺度的代谢模型结合起来，以确定药物诱导的细胞代谢变化可能与药物副作用有关。
Drug side effects cause a significant clinical and economic burden. However, mechanisms of drug action underlying side effect pathogenesis remain largely unknown. Here, we integrate pharmacogenomic and clinical data with a human metabolic network and find that non-pharmacokinetic metabolic pathways dysregulated by drugs are linked to the development of side effects. We show such dysregulated metabolic pathways contain genes with sequence variants affecting side effect incidence, play established roles in pathophysiology, have significantly altered activity in corresponding diseases, are susceptible to metabolic inhibitors and are effective targets for therapeutic nutrient supplementation. Our results indicate that metabolic dysregulation represents a common mechanism underlying side effect pathogenesis that is distinct from the role of metabolism in drug clearance. We suggest that elucidating the relationships between the cellular response to drugs, genetic variation of patients and cell metabolism may help managing side effects by personalizing drug prescriptions and nutritional intervention strategies. Adverse drug reactions are an important clinical problem. Here the authors combine information about drug-induced gene expression changes and genetic variability of patients with a genome-scale metabolic model to identify drug-induced changes in cellular metabolism that may be linked to drug side effects.
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影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
影响因子：
56.9
作者：
Campillos, Monica;Kuhn, Michael;Bork, Peer
通讯作者：
Bork, Peer
影响因子：
4.1
作者：
Kim, S;Shin, HJ;Lee, MO
通讯作者：
Lee, MO
影响因子：
9.9
作者：
Kuhn M;Campillos M;Letunic I;Jensen LJ;Bork P
通讯作者：
Bork P
影响因子：
5.1
作者：
Chakraborty, Arpita;Chowdhury, Subhankar;Bhattacharyya, Maitree
通讯作者：
Bhattacharyya, Maitree