The liver toxicity biomarker study phase I: markers for the effects of tolcapone or entacapone

The Liver Toxicity Biomarker Study is a systems toxicology approach to discover biomarkers that are indicative of a drug's potential to cause human idiosyncratic drug-induced liver injury. In phase I, the molecular effects in rat liver and blood plasma induced by tolcapone (a "toxic" drug) were compared with the molecular effects in the same tissues by dosing with entacapone (a "clean" drug, similar to tolcapone in chemical structure and primary pharmacological mechanism). Two durations of drug exposure, 3 and 28 days, were employed. Comprehensive molecular analysis of rat liver and plasma samples yielded marker analytes for various drug-vehicle or drug-drug comparisons. An important finding was that the marker analytes associated with tolcapone only partially overlapped with marker analytes associated with entacapone, despite the fact that both drugs have similar chemical structures and the same primary pharmacological mechanism of action. This result indicates that the molecular analyses employed in the study are detecting substantial "off-target" markers for the two drugs. An additional interesting finding was the modest overlap of the marker data sets for 3-day exposure and 28-day exposure, indicating that the molecular changes in liver and plasma caused by short- and long-term drug treatments do not share common characteristics.

The Liver Toxicity Biomarker Study: Phase I Design and Preliminary Results

Drug-induced liver injury (DILI) is the primary adverse event that results in withdrawal of drugs from the market and a frequent reason for the failure of drug candidates in development. The Liver Toxicity Biomarker Study (LTBS) is an innovative approach to investigate DILI because it compares molecular events produced in vivo by compound pairs that (a) are similar in structure and mechanism of action, (b) are associated with few or no signs of liver toxicity in preclinical studies, and (c) show marked differences in hepatotoxic potential. The LTBS is a collaborative preclinical research effort in molecular systems toxicology between the National Center for Toxicological Research and BG Medicine, Inc., and is supported by seven pharmaceutical companies and three technology providers. In phase I of the LTBS, entacapone and tolcapone were studied in rats to provide results and information that will form the foundation for the design and implementation of phase II. Molecular analysis of the rat liver and plasma samples combined with statistical analyses of the resulting datasets yielded marker analytes, illustrating the value of the broad-spectrum, molecular systems analysis approach to studying pharmacological or toxicological effects.

Correlation network analysis for data integration and biomarker selection

High-throughput biomolecular profiling techniques such as transcriptomics, proteomics and metabolomics are increasingly being used in in vivo studies to recognize and characterize effects of xenobiotics on organs and systems. Of particular interest are biomarkers of treatment-related effects which are detectable in easily accessible biological fluids such as blood. A fundamental challenge in such biomarker studies is selecting among the plethora of biomolecular changes induced by a compound and revealed by molecular profiling, to identify biomarkers which are exclusively or predominantly due to specific processes. In this work we present a cross-compartment correlation network approach, involving no a priori supervision or design, to integrate proteomic, metabolomic and transcriptomic data for selecting circulating biomarkers. The case study we present is the identification of biomarkers of drug-induced hepatic toxicity effects in a rodent model. Biomolecular profiling of both blood plasma and liver tissue from Wistar Hannover rats administered a toxic compound yielded many hundreds of statistically significant molecular changes. We exploited drug-induced correlations between blood plasma analytes and liver tissue molecules across study animals in order to nominate selected plasma molecules as biomarkers of drug-induced hepatic alterations of lipid metabolism and urea cycle processes.

Methods for the differential integrative omic analysis of plasma from a transgenic disease animal model

Multitiered quantitative analysis of biological systems is rapidly becoming the desired approach to study hierarchical functional interactions between proteins and metabolites. We describe here a novel systematic approach to analyze organisms with complex metabolic regulatory networks. By using precise analytical methods to measure biochemical constituents and their relative abundance in whole plasma of transgenic ApoE*3-Leiden mice and an isogenic wild-type control group, simultaneous snapshots of metabolic and protein states were obtained. Novel data processing and multivariate analysis tools such as Impurity Resolution Software (IMPRESS) and Windows-based linear fit program (WINLIN) were used to compare protein and metabolic profiles in parallel. Canonical correlations of the resulting data show quantitative relationships between heterogeneous components in the TG animals. These results, obtained solely from whole plasma analysis allowed us, in a rapid manner, to corroborate previous findings as well as find new events pertaining to dominant and peripheral events in lipoprotein metabolism of a genetically modified mammalian organism in relation to ApoE3, a key mediator of lipoprotein metabolism.

Integrative Biological Analysis of the APOE*3-Leiden Transgenic Mouse

Integrative (or systems biology) is a new approach to analyzing biological entities as integrated systems of genetic, genomic, protein, metabolite, cellular, and pathway events that are in flux and interdependent. Here, we demonstrate the application of intregrative biological analysis to a mammalian disease model, the apolipoprotein E3-Leiden (APO*E3) transgenic mouse. Mice selected for the study were fed a normal chow diet and sacrificed at 9 weeks of age-conditions under which they develop only mild type I and II atherosclerotic lesions. Hepatic mRNA expression analysis showed a 25% decrease in APO A1 and a 43% increase in liver fatty acid binding protein expression between transgenic and wild type control mice, while there was no change in PPAR-alpha expression. On-line high performance liquid chromatography-mass spectrometry quantitative profiling of tryptic digests of soluble liver proteins and liver lipids, coupled with principle component analysis, enabled rapid identification of early protein and metabolite markers of disease pathology. These included a 44% increase in L-FABP in transgenic animals compared to controls, as well as an increase in triglycerides and select bioactive lysophosphatidylcholine species. A correlation analysis of identified genes, proteins, and lipids was used to construct an interaction network. Taken together, these results indicate that integrative biology is a powerful tool for rapid identification of early markers and key components of pathophysiologic processes, and constitute the first application of this approach to a mammalian system.

Survey of human mitochondrial diseases using new genomic/proteomic tools

BACKGROUND

We have constructed Bayesian prior-based, amino-acid sequence profiles for the complete yeast mitochondrial proteome and used them to develop methods for identifying and characterizing the context of protein mutations that give rise to human mitochondrial diseases. (Bayesian priors are conditional probabilities that allow the estimation of the likelihood of an event - such as an amino-acid substitution - on the basis of prior occurrences of similar events.) Because these profiles can assemble sets of taxonomically very diverse homologs, they enable identification of the structurally and/or functionally most critical sites in the proteins on the basis of the degree of sequence conservation. These profiles can also find distant homologs with determined three-dimensional structures that aid in the interpretation of effects of missense mutations.

RESULTS

This survey reports such an analysis for 15 missense mutations, one insertion and three deletions involved in Leber's hereditary optic neuropathy, Leigh syndrome, mitochondrial neurogastrointestinal encephalomyopathy, Mohr-Tranebjaerg syndrome, iron-storage disorders related to Friedreich's ataxia, and hereditary spastic paraplegia. We present structural correlations for seven of the mutations.

CONCLUSIONS

Of the 19 mutations analyzed, 14 involved changes in very highly conserved parts of the affected proteins. Five out of seven structural correlations provided reasonable explanations for the malfunctions. As additional genetic and structural data become available, this methodology can be extended. It has the potential for assisting in identifying new disease-related genes. Furthermore, profiles with structural homologs can generate mechanistic hypotheses concerning the underlying biochemical processes - and why they break down as a result of the mutations.

PROTEAN. Protein sequence analysis and prediction

The archaeal, bacterial, andeukaryotic genome projects have overwhelmed our ability to experimentally elucidate the function of each novel gene and gene product. To a certain extent, protein functional assignments can be derived via sequence similarity measures and direct primary sequence analysis using methods to predict hydropathy, secondary structure, amphilicity, and antigenicity. Function can also be inferred on the basis of sequence motifs, such as phosphorylation and lipid binding signatures. These methods, provided in DNASTAR's PROTEAN module, can be used to putatively assign roles for novel proteins from the genome explosion as well as clarify function for better known proteins.