Literature DB >> 25239558

An in silico toxicogenomics approach for inferring potential diseases associated with maleic acid.

Ying-Chi Lin1, Chia-Chi Wang2, Chun-Wei Tung3.   

Abstract

Maleic acid is a multi-functional chemical widely applied in the manufacturing of polymer products including food packaging. However, the contamination of maleic acid in modified starch has raised the concerns about the effects of chronic exposure to maleic acid on human health. This study proposed a novel toxicogenomics approach for inferring functions, pathways and diseases potentially affected by maleic acid on humans by using known interactions between maleic acid and proteins. Neuronal signal transmission and cell metabolism were identified to be most influenced by maleic acid in this study. The top disease categories inferred to be associated with maleic acid were mental disorder, nervous system diseases, cardiovascular diseases, and cancers. The results from the in silico analysis showed that maleic acid could penetrate the blood-brain barrier to affect the nervous system. Several functions and pathways were further analyzed and identified to give insights into the mechanisms of maleic acid-associated diseases. The toxicogenomics approach may offer both a better understanding of the potential risks of maleic-acid exposure to humans and a direction for future toxicological investigation.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Diseases; In silico analysis; Maleic acid; Toxicogenomics

Mesh:

Substances:

Year:  2014        PMID: 25239558     DOI: 10.1016/j.cbi.2014.09.004

Source DB:  PubMed          Journal:  Chem Biol Interact        ISSN: 0009-2797            Impact factor:   5.192


  7 in total

1.  Leveraging complementary computational models for prioritizing chemicals of developmental and reproductive toxicity concern: an example of food contact materials.

Authors:  Chun-Wei Tung; Hsien-Jen Cheng; Chia-Chi Wang; Shan-Shan Wang; Pinpin Lin
Journal:  Arch Toxicol       Date:  2020-01-02       Impact factor: 5.153

2.  ChemDIS: a chemical-disease inference system based on chemical-protein interactions.

Authors:  Chun-Wei Tung
Journal:  J Cheminform       Date:  2015-06-15       Impact factor: 5.514

3.  Identification of informative features for predicting proinflammatory potentials of engine exhausts.

Authors:  Chia-Chi Wang; Ying-Chi Lin; Yuan-Chung Lin; Syu-Ruei Jhang; Chun-Wei Tung
Journal:  Biomed Eng Online       Date:  2017-08-18       Impact factor: 2.819

4.  Profiling transcriptomes of human SH-SY5Y neuroblastoma cells exposed to maleic acid.

Authors:  Chia-Chi Wang; Yin-Chi Lin; Yin-Hua Cheng; Chun-Wei Tung
Journal:  PeerJ       Date:  2017-04-05       Impact factor: 2.984

5.  ChemDIS 2: an update of chemical-disease inference system.

Authors:  Chun-Wei Tung; Shan-Shan Wang
Journal:  Database (Oxford)       Date:  2018-01-01       Impact factor: 3.451

6.  ChemDIS-Mixture: an online tool for analyzing potential interaction effects of chemical mixtures.

Authors:  Chun-Wei Tung; Chia-Chi Wang; Shan-Shan Wang; Pinpin Lin
Journal:  Sci Rep       Date:  2018-07-03       Impact factor: 4.379

7.  Network Analysis Reveals TNF as a Major Hub of Reactive Inflammation Following Spinal Cord Injury.

Authors:  Weiping Zhu; Xuning Chen; Le Ning; Kan Jin
Journal:  Sci Rep       Date:  2019-01-30       Impact factor: 4.379

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.