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利用遗传信息进行炎症性肠病的药物重新利用计算

Computational drug repurposing for inflammatory bowel disease using genetic information.

作者信息

Grenier Liam, Hu Pingzhao

机构信息

Department of Biochemistry and Medical Genetics and The George and Fay Yee Centre for Healthcare Innovation, University of Manitoba, Winnipeg, MB, Canada.

Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, Canada.

出版信息

Comput Struct Biotechnol J. 2019 Jan 7;17:127-135. doi: 10.1016/j.csbj.2019.01.001. eCollection 2019.

Abstract

As knowledge of the genetics behind inflammatory bowel disease (IBD) has continually improved, there has been a demand for methods that can use this data in a clinically significant way. Genome-wide association analyses for IBD have identified 232 risk genetic loci for the disorder. While identification of these risk loci enriches our understanding of the underlying biology of the disorder, their identification does not serve a clinical purpose. A potential use of this genetic information is to look for potential IBD drugs that target these loci in a procedure known as drug repurposing. The demand for new drug treatments for IBD is high due to the side effects and high costs of current treatments. We hypothesize that IBD genetic variants obtained from GWAS and the candidate genes prioritized from the variants have a causal relationship with IBD drug targets. A computational drug repositioning study was done due to its efficiency and inexpensiveness compared to traditional in vitro or biochemical approaches. Our approach for drug repurposing was multi-layered; it not only focused on the interactions between drugs and risk IBD genes, but also the interactions between drugs and all of the biological pathways the risk genes are involved in. We prioritized IBD candidate genes using identified genetic variants and identified potential drug targets and drugs that can be potentially repositioned or developed for IBD using the identified candidate genes. Our analysis strategy can be applied to repurpose drugs for other complex diseases using their risk genes identified from genetic analysis.

摘要

随着对炎症性肠病(IBD)背后遗传学知识的不断完善,人们对能够以具有临床意义的方式利用这些数据的方法产生了需求。IBD的全基因组关联分析已经确定了该疾病的232个风险基因位点。虽然这些风险位点的识别丰富了我们对该疾病潜在生物学机制的理解,但它们的识别并无临床用途。这种遗传信息的一种潜在用途是在一种称为药物重新利用的过程中寻找针对这些位点的潜在IBD药物。由于当前治疗方法的副作用和高成本,对IBD新药物治疗的需求很高。我们假设从全基因组关联研究(GWAS)获得的IBD基因变异以及从这些变异中优先排序的候选基因与IBD药物靶点存在因果关系。由于与传统的体外或生化方法相比,计算药物重新定位研究具有高效性和低成本,因此进行了这项研究。我们的药物重新利用方法是多层面的;它不仅关注药物与IBD风险基因之间的相互作用,还关注药物与风险基因所涉及的所有生物途径之间的相互作用。我们利用已识别的基因变异对IBD候选基因进行优先排序,并利用已识别的候选基因识别潜在的药物靶点以及可用于IBD的潜在重新利用或开发的药物。我们的分析策略可应用于利用从遗传分析中识别的风险基因对其他复杂疾病进行药物重新利用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/020d/6352300/1ad8f35b9df3/ga1.jpg

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