Genomics: applications in mechanism elucidation

Systems toxicology of chemically induced liver and kidney injuries: histopathology-associated gene co-expression modules

Organ injuries caused by environmental chemical exposures or use of pharmaceutical drugs pose a serious health risk that may be difficult to assess because of a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific histopathology outcomes via biomarkers will provide a foundation for designing precise and robust diagnostic tests. We identified co-expressed genes (modules) specific to injury endpoints using the Open Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (TG-GATEs) - a toxicogenomics database containing organ-specific gene expression data matched to dose- and time-dependent chemical exposures and adverse histopathology assessments in Sprague-Dawley rats. We proposed a protocol for selecting gene modules associated with chemical-induced injuries that classify 11 liver and eight kidney histopathology endpoints based on dose-dependent activation of the identified modules. We showed that the activation of the modules for a particular chemical exposure condition, i.e., chemical-time-dose combination, correlated with the severity of histopathological damage in a dose-dependent manner. Furthermore, the modules could distinguish different types of injuries caused by chemical exposures as well as determine whether the injury module activation was specific to the tissue of origin (liver and kidney). The generated modules provide a link between toxic chemical exposures, different molecular initiating events among underlying molecular pathways and resultant organ damage. Published 2016. This article is a U.S. Government work and is in the public domain in the USA. Journal of Applied Toxicology published by John Wiley & Sons, Ltd.

"Omics" in pharmaceutical research: overview, applications, challenges, and future perspectives

In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.

Characterization of chemically induced liver injuries using gene co-expression modules

Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules) specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1) known biochemical pathways associated with liver injuries and 2) clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20%) genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.

Personalized medicine and tobacco-related health disparities: is there a role for genetics?

Genetic testing has been proposed as a means to increase smoking cessation rates and thus reduce smoking prevalence. To understand how that might be practically possible, with appreciation of the current social context of tobacco use and dependence, we performed a contextual analysis of smoking-related genetics and smoking cessation. To provide added value, genetics would need to inform and improve existing interventions for smokers (including behavioral and pharmacological treatments). Pharmacogenetics offers the most promising potential, because it may improve the efficacy of medication-based smoking cessations strategies. All proven interventions for treating tobacco dependence, however, including simple cost-effective measures, such as quit lines and physician counseling, are underutilized. As tobacco use occurs disproportionately among disadvantaged populations, efforts to improve smokers' access to health care, and to the tools that are known to help them quit, represent the most promising approaches for reducing smoking prevalence within these groups. Similar considerations apply to other chronic diseases contributing to population-level health disparities. We conclude that although genetics offers increasing opportunities to tailor drug treatment, and may in some cases provide useful risk prediction, other methods of personalizing care are likely to yield greater benefit to populations experiencing health disparities related to tobacco use.

Identification and replication of loci involved in camptothecin-induced cytotoxicity using CEPH pedigrees

To date, the Centre d'Etude Polymorphism Humain (CEPH) cell line model has only been used as a pharmacogenomic tool to evaluate which genes are responsible for the disparity in response to a single drug. The purpose of this study was demonstrate the model's ability to establish a specific pattern of quantitative trait loci (QTL) related to a shared mechanism for multiple structurally related drugs, the camptothecins, which are Topoisomerase 1 inhibitors. A simultaneous screen of six camptothecin analogues for in vitro sensitivity in the CEPH cell lines resulted in cytotoxicity profiles and orders of potency which were in agreement with the literature. For all camptothecins studied, heritability estimates for cytotoxic response averaged 23.1 ± 2.6%. Nonparametric linkage analysis was used to identify a relationship between genetic markers and response to the camptothecins. Ten QTLs on chromosomes 1, 3, 5, 6, 11, 12, 16 and 20 were identified as shared by all six camptothecin analogues. In a separate validation experiment, nine of the ten QTLs were replicated at the significant and suggestive levels using three additional camptothecin analogues. To further refine this list of QTLs, another validation study was undertaken and seven of the nine QTLs were independently replicated for all nine camptothecin analogues. This is the first study using the CEPH cell lines that demonstrates that a specific pattern of QTLs could be established for a class of drugs which share a mechanism of action. Moreover, it is the first study to report replication of linkage results for drug-induced cytotoxicity using this model. The QTLs, which have been identified as shared by all camptothecins and replicated across multiple datasets, are of considerable interest; they harbor genes related to the shared mechanism of action for the camptothecins, which are responsible for variation in response.