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Toxicogenomic module associations with pathogenesis: A network based approach to understanding drug toxicity (ChIP-Seq)

ABSTRACT: Despite investment in toxicogenomics, nonclinical safety studies are still used to predict clinical liabilities for new drug candidates. Network-based approaches for genomic analysis help overcome challenges with whole-genome transcriptional profiling using limited numbers of treatments for phenotypes of interest. Herein, we apply co-expression network analysis to safety assessment using rat liver gene expression data to define 415 modules, exhibiting unique transcriptional control, organized in a visual representation of the transcriptome (the ‘TXG-MAP’). Accounting for the overall transcriptional activity resulting from treatment, we explain mechanisms of toxicity and predict distinct toxicity phenotypes using module associations. We demonstrate that early network responses compliment traditional histology-based assessment in predicting outcomes for longer studies and identify a novel mechanism of hepatotoxicity involving endoplasmic reticulum stress and Nrf2 activation. Module-based molecular subtypes of cholestatic injury derived using rat translate to human. Moreover, compared to gene-level analysis alone, combining module and gene-level analysis performed in sequence identifies significantly more phenotype-gene associations, including established and novel biomarkers of liver injury.

ORGANISM(S): Rattus norvegicus

PROVIDER: GSE87730 | GEO | 2017/04/12

SECONDARY ACCESSION(S): PRJNA345636

REPOSITORIES: GEO

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Project description:Genome-wide association studies (GWASs) for bone mineral density (BMD), one of the most significant predictors of osteoporotic fracture, have identified over 1100 independent associations; however, few of the causal genes have been identified. Recently, the “omnigenic” model of the genetic architecture of complex traits proposed two general categories of causal genes, core and peripheral. Core genes play a direct role in regulating traits; thus, their identification is key to revealing critical regulators and potential therapeutic targets. Here, we identified a co-expression module enriched for genes exhibiting properties consistent with core genes for BMD by analyzing GWAS data through the lens of a cell-type and timepoint-specific gene co-expression network for mineralizing osteoblasts. We identified multiple co-expression modules enriched for genes implicated by BMD GWAS and prioritized modules based on their enrichment for genes with core-like properties. Only one module, the purple module, was enriched for genes correlated with in vitro mineralization (r = 0.49; FDR = 0.012), with known roles in skeletal development (P <2.2 x 10-16), that when perturbed produce a bone phenotype in mice (OR = 4.1; P = 2.14 x 10-9), and are monogenic bone disease genes in humans (OR=21.3; P=6.94 x 10-9). Furthermore, the purple module contained genes from two distinct transcriptional profiles with regards to osteoblast differentiation, one of which, termed the late differentiation cluster (LDC), was more highly enriched for genes with core-like properties. Within the LDC, we found that the most highly connected genes were more likely to overlap a BMD GWAS association and associations that contained LDC genes overlapped enhancers and promoters in osteoblasts. Finally, we identified four LDC genes (B4GALNT3, CADM1, DOCK9, and GPR133) with colocalizing expression quantitative trait loci (eQTL) and altered BMD in mouse knockouts. Our network-based approach identified a “core” module for BMD and has provided a resource for expanding our understanding of the genetics of bone mass.

Project description:The Göttingen Minipig is gaining ground as nonrodent species in safety testing of drugs for pediatric indications. Due to developmental changes in pharmacokinetics (PK) and pharmacodynamics (PD), physiologically-based pharmacokinetic (PBPK) models are built to better predict drug exposure in children and to aid species selection for nonclinical safety studies. These PBPK models require high quality physiological and PK/PD data such as protein abundance of drug metabolizing enzymes. These data are available for man and rat, but scarce for the Göttingen Minipig. The aim of this study was to assess hepatic cytochrome P450 (CYP) protein abundance in the developing Göttingen Minipig by using mass spectrometry. In addition, sex-related differences in CYP protein abundance and correlation of CYP enzyme activity with CYP protein abundance were assessed. The following age groups were included: gestational day (GD) 84 - 86 (n = 8), GD 108 (n = 6), postnatal day (PND) 1 (n = 8), PND 3 (n = 8), PND 7 (n = 8), PND 28 (n = 8) and adult (n = 8). Liver microsomes were extracted and protein abundance was compared to that in adult animals. Next, the CYP protein abundance was correlated to CYP enzyme activity in the same biological samples. In general, CYP protein abundance gradually increased during development. However, we observed a stable protein expression over time for CYP4A24 and CYP20A1 and for CYP51A1, a high protein expression during the fetal stages was followed by a decrease during the first month of life and an increase towards adulthood. Sex-related differences were observed for CYP4V2_2a and CYP20A1 at PND 1 with highest expression in females for both isoforms. In the adult samples, sex-related differences were detected for CYP1A1, CYP1A2, CYP2A19, CYP2E1_2, CYP3A22, CYP4V2_2a and CYP4V2_2b with higher values in female compared to male Göttingen Minipigs. The correlation analysis between CYP protein abundance and CYP enzyme activity showed that CYP3A22 protein abundance correlated clearly with the metabolism of midazolam at PND 7. These data are remarkably comparable to human data and provide a valuable step forward in the construction of a neonatal and juvenile Göttingen Minipig PBPK model.

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Toxicogenomic module associations with pathogenesis: A network based approach to understanding drug toxicity (ChIP-Seq)

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