建立人类基因数据湖，以扩大对药物发现的见解。

IF 7.5 2区医学 Q1 PHARMACOLOGY & PHARMACY

Drug Discovery Today Pub Date : 2025-06-01 DOI:10.1016/j.drudis.2025.104385

Clement Chatelain , Samuel Lessard , Katherine Klinger , Shameer Khader , Emanuele de Rinaldis

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引用次数: 0

摘要

全基因组关联研究（GWAS）已经确定了许多与疾病相关的变异，但遗传数据的有效存储和分析仍然是一个挑战。在这里，我们提出了一个可扩展的遗传数据湖（GDL），将GWAS、分子数量性状位点（mQTL）和表观遗传数据集成在一个大数据基础设施中，以实现快速分析。该框架允许大规模计算，优先排序54 586个基因性状关联，其中34 779个仅在联盟数据集中发现。通过利用公共、联盟和私人数据，这种方法增强了靶点发现和适应症选择，加速了药物开发。

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Building a human genetic data lake to scale up insights for drug discovery

Genome-wide association studies (GWAS) have identified numerous disease-associated variants, yet efficient storage and analysis of genetic data remain a challenge. Here, we propose a scalable genetic data lake (GDL) integrating GWAS, molecular quantitative trait loci (mQTL), and epigenetic data within a big data infrastructure to enable rapid analysis. This framework allows large-scale computations, prioritizing 54 586 gene–trait associations, including 34 779 found exclusively in consortium data sets. By leveraging public, consortium, and private data, this approach enhances target discovery and indication selection, accelerating drug development.

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来源期刊

Drug Discovery Today 医学-药学

CiteScore

14.80

自引率

2.70%

发文量

293

审稿时长

6 months

期刊介绍： Drug Discovery Today delivers informed and highly current reviews for the discovery community. The magazine addresses not only the rapid scientific developments in drug discovery associated technologies but also the management, commercial and regulatory issues that increasingly play a part in how R&D is planned, structured and executed. Features include comment by international experts, news and analysis of important developments, reviews of key scientific and strategic issues, overviews of recent progress in specific therapeutic areas and conference reports.