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代谢组学数据的功能解释作为预测长期副作用的新方法:婴儿特应性皮炎的治疗

Functional interpretation of metabolomics data as a new method for predicting long-term side effects: treatment of atopic dermatitis in infants.

作者信息

Lee Seul Ji, Woo Sung-il, Ahn Soo Hyun, Lim Dong Kyu, Hong Ji Yeon, Park Jeong Hill, Lim Johan, Kim Mi-kyeong, Kwon Sung Won

机构信息

College of Pharmacy, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea.

Department of Pediatrics, College of Medicine, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, Cheongju 361-763, Korea.

出版信息

Sci Rep. 2014 Dec 10;4:7408. doi: 10.1038/srep07408.

Abstract

Topical steroids are used for the treatment of primary atopic dermatitis (AD); however, their associated risk of serious complications is great due to the presence of vulnerable lesions in young children with AD. Topical calcineurin inhibitors (TCIs) are steroid-free, anti-inflammatory agents used for topical AD therapy. However, their use is prohibited in infants <2 years of age because of their carcinogenic potential. We conducted a randomized, double-blind trial to evaluate the efficacy of TCIs as a secondary AD treatment for children <2 years of age by comparing 1% pimecrolimus cream with 0.05% desonide cream. We performed urinary metabolomics to predict long-term side effects. The 1% pimecrolimus cream displayed similar efficacy and exceptional safety compared with the 0.05% desonide cream. Metabolomics-based long-term toxicity tests effectively predicted long-term side effects using short-term clinical models. This applicable method for the functional interpretation of metabolomics data sets the foundation for future studies involving the prediction of the toxicity and systemic reactions caused by long-term medication administration.

摘要

外用糖皮质激素用于治疗原发性特应性皮炎(AD);然而,由于患有AD的幼儿存在易损皮损,使用外用糖皮质激素会带来严重并发症的巨大风险。外用钙调神经磷酸酶抑制剂(TCIs)是用于AD局部治疗的无激素抗炎药。然而,由于其潜在致癌性,2岁以下婴儿禁用。我们进行了一项随机双盲试验,通过比较1%吡美莫司乳膏和0.05%地奈德乳膏,评估TCIs作为2岁以下儿童AD二线治疗药物的疗效。我们进行了尿液代谢组学研究以预测长期副作用。与0.05%地奈德乳膏相比,1%吡美莫司乳膏显示出相似的疗效和卓越的安全性。基于代谢组学的长期毒性试验使用短期临床模型有效预测了长期副作用。这种适用于代谢组学数据集功能解释的方法为未来涉及预测长期用药所致毒性和全身反应的研究奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c28e/5376984/53a03fac7df1/srep07408-f1.jpg

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