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Discrimination of Steatotic and Non-Steatotic Chemicals Through Transcriptome Analysis in Primary Human Hepatocytes
by
Callegaro, Giulia
, Ortega-Vallbona, Rita
, Verheijen, Marcha
, Freedman, Jonathan H
, Palomino-Schätzlein, Martina
, Weiss, Carsten
, Cramer von Clausbruch, Christina A
, Caiment, Florian
in
Amino acids
/ Chemicals
/ Datasets
/ Discrimination
/ Fatty Liver - genetics
/ Fatty Liver - metabolism
/ Gene expression
/ Gene Expression Profiling - methods
/ Genes
/ Genomics
/ Hepatocytes - drug effects
/ Hepatocytes - metabolism
/ Humans
/ Inflammation
/ Insulin resistance
/ Lipids
/ Liver
/ Liver cancer
/ Liver cirrhosis
/ Liver diseases
/ Machine learning
/ Metabolism
/ Metabolomics - methods
/ Noise control
/ Oxidative stress
/ Risk assessment
/ Tetracycline
/ Tetracyclines
/ Transcriptome
/ Type 2 diabetes
2026
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Discrimination of Steatotic and Non-Steatotic Chemicals Through Transcriptome Analysis in Primary Human Hepatocytes
by
Callegaro, Giulia
, Ortega-Vallbona, Rita
, Verheijen, Marcha
, Freedman, Jonathan H
, Palomino-Schätzlein, Martina
, Weiss, Carsten
, Cramer von Clausbruch, Christina A
, Caiment, Florian
in
Amino acids
/ Chemicals
/ Datasets
/ Discrimination
/ Fatty Liver - genetics
/ Fatty Liver - metabolism
/ Gene expression
/ Gene Expression Profiling - methods
/ Genes
/ Genomics
/ Hepatocytes - drug effects
/ Hepatocytes - metabolism
/ Humans
/ Inflammation
/ Insulin resistance
/ Lipids
/ Liver
/ Liver cancer
/ Liver cirrhosis
/ Liver diseases
/ Machine learning
/ Metabolism
/ Metabolomics - methods
/ Noise control
/ Oxidative stress
/ Risk assessment
/ Tetracycline
/ Tetracyclines
/ Transcriptome
/ Type 2 diabetes
2026
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Discrimination of Steatotic and Non-Steatotic Chemicals Through Transcriptome Analysis in Primary Human Hepatocytes
by
Callegaro, Giulia
, Ortega-Vallbona, Rita
, Verheijen, Marcha
, Freedman, Jonathan H
, Palomino-Schätzlein, Martina
, Weiss, Carsten
, Cramer von Clausbruch, Christina A
, Caiment, Florian
in
Amino acids
/ Chemicals
/ Datasets
/ Discrimination
/ Fatty Liver - genetics
/ Fatty Liver - metabolism
/ Gene expression
/ Gene Expression Profiling - methods
/ Genes
/ Genomics
/ Hepatocytes - drug effects
/ Hepatocytes - metabolism
/ Humans
/ Inflammation
/ Insulin resistance
/ Lipids
/ Liver
/ Liver cancer
/ Liver cirrhosis
/ Liver diseases
/ Machine learning
/ Metabolism
/ Metabolomics - methods
/ Noise control
/ Oxidative stress
/ Risk assessment
/ Tetracycline
/ Tetracyclines
/ Transcriptome
/ Type 2 diabetes
2026
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Discrimination of Steatotic and Non-Steatotic Chemicals Through Transcriptome Analysis in Primary Human Hepatocytes
Journal Article
Discrimination of Steatotic and Non-Steatotic Chemicals Through Transcriptome Analysis in Primary Human Hepatocytes
2026
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Overview
Steatosis, characterized by excessive fat accumulation in the liver, is a significant precursor to chronic liver disease and hepatocarcinoma. This condition is influenced by multiple contributing factors such as obesity, alcohol consumption, and exposure to chemicals or drugs. Systems biology approaches including transcriptomics and metabolomics can aid in grouping chemicals according to their mode of action. In this study, we analyze transcriptomic and metabolomic data from primary human and transformed hepatocytes, respectively, to differentiate between steatotic and non-steatotic chemicals. Rather than assessing each steatotic compound individually, we pooled several steatotic chemicals in order to minimize compound-specific noise and better identify features associated with the underlying process of steatosis. Differential gene expression analysis revealed established mechanisms involved in steatosis, consistent with the recently updated adverse outcome pathway. Likewise, metabolomic data enabled clear discrimination between steatotic and non-steatotic chemicals. These findings highlight the potential of omics technologies to support chemical grouping based on insights into the molecular mechanisms that drive steatosis development.
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