Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity

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Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity. / Aguayo-Orozco, Alejandro; Bois, Frederic Yves; Brunak, Søren; Taboureau, Olivier.

In: Frontiers in Genetics, Vol. 9, 396, 2018, p. 1-15.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Aguayo-Orozco, A, Bois, FY, Brunak, S & Taboureau, O 2018, 'Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity', Frontiers in Genetics, vol. 9, 396, pp. 1-15. https://doi.org/10.3389/fgene.2018.00396

APA

Aguayo-Orozco, A., Bois, F. Y., Brunak, S., & Taboureau, O. (2018). Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity. Frontiers in Genetics, 9, 1-15. [396]. https://doi.org/10.3389/fgene.2018.00396

Vancouver

Aguayo-Orozco A, Bois FY, Brunak S, Taboureau O. Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity. Frontiers in Genetics. 2018;9:1-15. 396. https://doi.org/10.3389/fgene.2018.00396

Author

Aguayo-Orozco, Alejandro ; Bois, Frederic Yves ; Brunak, Søren ; Taboureau, Olivier. / Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity. In: Frontiers in Genetics. 2018 ; Vol. 9. pp. 1-15.

Bibtex

@article{2d59e41b8c824f6fb2f0ec350404d68d,
title = "Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity",
abstract = "Non-alcoholic fatty liver disease (NAFLD) represents a wide spectrum of disease, ranging from simple fatty liver through steatosis with inflammation and necrosis to cirrhosis. One of the most challenging problems in biomedical research and within the chemical industry is to understand the underlying mechanisms of complex disease, and complex adverse outcome pathways (AOPs). Based on a set of 28 steatotic chemicals with gene expression data measured on primary hepatocytes at three times (2, 8, and 24 h) and three doses (low, medium, and high), we identified genes and pathways, defined as molecular initiating events (MIEs) and key events (KEs) of steatosis using a combination of a time series and pathway analyses. Among the genes deregulated by these compounds, the study highlighted OSBPL9, ALDH7A1, MYADM, SLC51B, PRDX6, GPAT3, TMEM135, DLGDA5, BCO2, APO10LA, TSPAN6, NEURL1B, and DUSP1. Furthermore, pathway analysis indicated deregulation of pathways related to lipid accumulation, such as fat digestion and absorption, linoleic and linolenic acid metabolism, calcium signaling pathway, fatty acid metabolism, peroxisome, retinol metabolism, and steroid metabolic pathways in a time dependent manner. Such transcription profile analysis can help in the understanding of the steatosis evolution over time generated by chemical exposure.",
keywords = "hepatic steatosis, gene expression, transcriptomics, time-series analysis, pathways analysis, drug induced liver injury, DILI",
author = "Alejandro Aguayo-Orozco and Bois, {Frederic Yves} and S{\o}ren Brunak and Olivier Taboureau",
year = "2018",
doi = "10.3389/fgene.2018.00396",
language = "English",
volume = "9",
pages = "1--15",
journal = "Frontiers in Genetics",
issn = "1664-8021",
publisher = "Frontiers Media S.A.",

}

RIS

TY - JOUR

T1 - Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity

AU - Aguayo-Orozco, Alejandro

AU - Bois, Frederic Yves

AU - Brunak, Søren

AU - Taboureau, Olivier

PY - 2018

Y1 - 2018

N2 - Non-alcoholic fatty liver disease (NAFLD) represents a wide spectrum of disease, ranging from simple fatty liver through steatosis with inflammation and necrosis to cirrhosis. One of the most challenging problems in biomedical research and within the chemical industry is to understand the underlying mechanisms of complex disease, and complex adverse outcome pathways (AOPs). Based on a set of 28 steatotic chemicals with gene expression data measured on primary hepatocytes at three times (2, 8, and 24 h) and three doses (low, medium, and high), we identified genes and pathways, defined as molecular initiating events (MIEs) and key events (KEs) of steatosis using a combination of a time series and pathway analyses. Among the genes deregulated by these compounds, the study highlighted OSBPL9, ALDH7A1, MYADM, SLC51B, PRDX6, GPAT3, TMEM135, DLGDA5, BCO2, APO10LA, TSPAN6, NEURL1B, and DUSP1. Furthermore, pathway analysis indicated deregulation of pathways related to lipid accumulation, such as fat digestion and absorption, linoleic and linolenic acid metabolism, calcium signaling pathway, fatty acid metabolism, peroxisome, retinol metabolism, and steroid metabolic pathways in a time dependent manner. Such transcription profile analysis can help in the understanding of the steatosis evolution over time generated by chemical exposure.

AB - Non-alcoholic fatty liver disease (NAFLD) represents a wide spectrum of disease, ranging from simple fatty liver through steatosis with inflammation and necrosis to cirrhosis. One of the most challenging problems in biomedical research and within the chemical industry is to understand the underlying mechanisms of complex disease, and complex adverse outcome pathways (AOPs). Based on a set of 28 steatotic chemicals with gene expression data measured on primary hepatocytes at three times (2, 8, and 24 h) and three doses (low, medium, and high), we identified genes and pathways, defined as molecular initiating events (MIEs) and key events (KEs) of steatosis using a combination of a time series and pathway analyses. Among the genes deregulated by these compounds, the study highlighted OSBPL9, ALDH7A1, MYADM, SLC51B, PRDX6, GPAT3, TMEM135, DLGDA5, BCO2, APO10LA, TSPAN6, NEURL1B, and DUSP1. Furthermore, pathway analysis indicated deregulation of pathways related to lipid accumulation, such as fat digestion and absorption, linoleic and linolenic acid metabolism, calcium signaling pathway, fatty acid metabolism, peroxisome, retinol metabolism, and steroid metabolic pathways in a time dependent manner. Such transcription profile analysis can help in the understanding of the steatosis evolution over time generated by chemical exposure.

KW - hepatic steatosis

KW - gene expression

KW - transcriptomics

KW - time-series analysis

KW - pathways analysis

KW - drug induced liver injury

KW - DILI

U2 - 10.3389/fgene.2018.00396

DO - 10.3389/fgene.2018.00396

M3 - Journal article

C2 - 30279702

VL - 9

SP - 1

EP - 15

JO - Frontiers in Genetics

JF - Frontiers in Genetics

SN - 1664-8021

M1 - 396

ER -

ID: 203558812