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Incorporating Tissue-Specific Gene Expression Data to Improve Chemical–Disease Inference of in Silico Toxicogenomics Methods

Authors :
Shan-Shan Wang
Chia-Chi Wang
Chien-Lun Wang
Ying-Chi Lin
Chun-Wei Tung
Source :
Journal of Xenobiotics, Vol 14, Iss 3, Pp 1023-1035 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

In silico toxicogenomics methods are resource- and time-efficient approaches for inferring chemical–protein–disease associations with potential mechanism information for exploring toxicological effects. However, current in silico toxicogenomics systems make inferences based on only chemical–protein interactions without considering tissue-specific gene/protein expressions. As a result, inferred diseases could be overpredicted with false positives. In this work, six tissue-specific expression datasets of genes and proteins were collected from the Expression Atlas. Genes were then categorized into high, medium, and low expression levels in a tissue- and dataset-specific manner. Subsequently, the tissue-specific expression datasets were incorporated into the chemical–protein–disease inference process of our ChemDIS system by filtering out relatively low-expressed genes. By incorporating tissue-specific gene/protein expression data, the enrichment rate for chemical–disease inference was largely improved with up to 62.26% improvement. A case study of melamine showed the ability of the proposed method to identify more specific disease terms that are consistent with the literature. A user-friendly user interface was implemented in the ChemDIS system. The methodology is expected to be useful for chemical–disease inference and can be implemented for other in silico toxicogenomics tools.

Details

Language :
English
ISSN :
20394713 and 20394705
Volume :
14
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Journal of Xenobiotics
Publication Type :
Academic Journal
Accession number :
edsdoj.47d03071ba45bc999ce637d3ca8b90
Document Type :
article
Full Text :
https://doi.org/10.3390/jox14030057