Progress in toxicogenomics to protect human health.
Matthew J MeierJoshua A HarrillKamin J JohnsonRussell S ThomasWeida TongJulia E RagerCarole L YaukPublished in: Nature reviews. Genetics (2024)
Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose-response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.
Keyphrases
- single cell
- human health
- risk assessment
- artificial intelligence
- high throughput
- big data
- rna seq
- machine learning
- climate change
- electronic health record
- heavy metals
- deep learning
- genome wide
- genome wide identification
- high resolution
- ms ms
- air pollution
- copy number
- dna methylation
- healthcare
- mass spectrometry
- data analysis
- single molecule
- social media
- genome wide analysis