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通过靶向衰老和与年龄相关疾病的汇聚子网发现人类 geroprotector。

Human geroprotector discovery by targeting the converging subnetworks of aging and age-related diseases.

机构信息

Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York City, USA.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, IMI 3-70F, New York City, NY, 10029, USA.

出版信息

Geroscience. 2020 Feb;42(1):353-372. doi: 10.1007/s11357-019-00106-x. Epub 2019 Oct 21.

Abstract

A key goal of geroscience research is to identify effective interventions to extend human healthspan, the years of healthy life. Currently, majority of the geroprotectors are found by screening compounds in model organisms; whether they will be effective in humans is largely unknown. Here we present a new strategy called ANDRU (aging network based drug discovery) to help the discovery of human geroprotectors. It first identifies human aging subnetworks that putatively function at the interface between aging and age-related diseases; it then screens for pharmacological interventions that may "reverse" the age-associated transcriptional changes occurred in these subnetworks. We applied ANDRU to human adipose gene expression data from the Genotype Tissue Expression (GTEx) project. For the top 31 identified compounds, 19 of them showed at least some evidence supporting their function in improving metabolic traits or lifespan, which include type 2 diabetes drugs such as pioglitazone. As the query aging genes were refined to the ones with more intimate links to diseases, ANDRU identified more meaningful drug hits than the general approach without considering the underlying network structures. In summary, ANDRU represents a promising human data-driven strategy that may speed up the discovery of interventions to extend human healthspan.

摘要

衰老科学研究的一个关键目标是确定有效的干预措施来延长人类的健康寿命,即健康的生活年限。目前,大多数的衰老防护剂是通过在模式生物中筛选化合物发现的;它们在人类中是否有效还很大程度上未知。在这里,我们提出了一种称为 ANDRU(基于衰老网络的药物发现)的新策略,以帮助发现人类的衰老防护剂。它首先识别出人类衰老的子网络,这些子网络推测在衰老和与年龄相关的疾病之间起作用;然后筛选可能“逆转”这些子网络中与年龄相关的转录变化的药物干预措施。我们将 ANDRU 应用于来自基因型组织表达 (GTEx) 项目的人类脂肪基因表达数据。对于前 31 种鉴定出的化合物,其中 19 种至少有一些证据支持它们在改善代谢特征或寿命方面的作用,其中包括吡格列酮等 2 型糖尿病药物。随着查询衰老基因被细化为与疾病有更密切联系的基因,ANDRU 比不考虑潜在网络结构的一般方法鉴定出更有意义的药物靶点。总之,ANDRU 代表了一种有前途的人类数据驱动策略,可能会加速发现延长人类健康寿命的干预措施。

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