June 2021
Volume 62, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2021
A transcriptome based computational drug repurposing analysis to target the RPE/choroid abnormality in advanced age-related macular degeneration
Author Affiliations & Notes
  • Dhanach Dhirachaikulpanich
    Eye and Vision Science, Institute of Life Course and Medical Sciences, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, Merseyside, United Kingdom
    Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
  • Luminita I Paraoan
    Eye and Vision Science, Institute of Life Course and Medical Sciences, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, Merseyside, United Kingdom
  • Footnotes
    Commercial Relationships   Dhanach Dhirachaikulpanich, None; Luminita Paraoan, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2021, Vol.62, 245. doi:
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      Dhanach Dhirachaikulpanich, Luminita I Paraoan; A transcriptome based computational drug repurposing analysis to target the RPE/choroid abnormality in advanced age-related macular degeneration. Invest. Ophthalmol. Vis. Sci. 2021;62(8):245.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Advanced age-related macular degeneration (AMD) is a devastating blinding disease centring on the retinal pigment epithelium (RPE)/choroid. The current treatments can only slow the progress of the disease. The current big data era affords comparisons of large gene expression datasets generated from large drug perturbation response studies aiming to explore the repurposing of currently available drugs for different diseases. Here, we exemplify the application of such an integrating transcriptomic method to find potential drugs for advanced AMD.

Methods : The publicly available microarray transcriptome (GSE29801) of advanced AMD RPE/choroid was combined with RNAseq (GSE135092) by an integrating quantitative method to extend the assessment of the differential gene expression in advanced AMD RPE/choroid. The resulting significant genes were subjected to over-representation analysis of KEGG pathways to highlight crucial biological processes in advanced AMD. For the purpose of this study, the differentially expressed genes in the significant pathways were then compared with the drug perturbation profile from the L1000 Connectivity Map (CMap), querying the correlation of a predicted response with the differential gene expression profile in advanced AMD RPE/choroid.

Results : We furthered our previous integrative transcriptomic analysis of RPE/choroid to combine transcriptomic data of 35 advanced AMD RPE/choroid samples. The analysis showed 427 genes differentially expressed (p<0.05) with advanced AMD (276 upregulated and 151 downregulated). Among the differentially expressed genes, over-representation analysis highlighted extracellular matrix (ECM)-receptor interaction and focal adhesion as two significant KEGG pathways (FDR<0.05). The 11 significant upregulated genes in ECM-interaction pathway were used to query the correlated drug perturbation in CMap database and identified dihydrofolate reductase inhibitor, vitamin D receptor agonist and MTOR-PI3K inhibitor as potential drug classes by this computational method (CMap enrichment score>99).

Conclusions : Integrative RPE/choroid transcriptome analysis against the drug perturbation response database predicted three potential drug classes, based on dihydrofolate reductase inhibitor, vitamin D receptor agonist and MTOR-PI3K inhibitor, with potential for repurposing for advanced AMD.

This is a 2021 ARVO Annual Meeting abstract.

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