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Activity Number:
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77
- Contributed Poster Presentations: Biopharmaceutical Section
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #314037
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Title:
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A Multiomics Statistical Framework for Drug Repositioning
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Author(s):
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Zhaolong Yu* and Kexuan Liang and Hongyu Zhao
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Companies:
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Yale University and Peking University and Yale University
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Keywords:
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Drug repositioning;
Integrative Analysis;
Multiomics ;
TWAS;
NASH
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Abstract:
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Drug repositioning refers to identifying new therapeutic uses for currently existing drugs, which dramatically lowers the risk of drug development by skipping the early-stage trials and thusly shortening the time investment and cutting down the capital investment. We propose a novel multiomics drug repositioning framework that uses both transcriptome data and GWAS summary statistics to screen for repurposed drug candidates in a signature matching fashion. In this framework, signature genes are identified by comparing both differentially expressed genes in case/control and before/after intervention studies and performing transcriptome-wide association studies (TWAS) to disease-related traits. The signatures genes will be further mapped to the perturbation database LINCS to calculate the final repositioning scores. We implemented the multiomics drug repositioning framework to find potential drug candidates for non-alcoholic steatohepatitis (NASH) and the enrichment analysis on the top-ranked drugs has proved that our approach is an effective strategy to discover repurposing drugs. Moreover, our proposed method could also be applied to biomarker identification for complex diseases.
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Authors who are presenting talks have a * after their name.
