Conference highlights toxicogenomics, bioinformatics and computational biology
The third international Toxicogenomics Integrated with Environmental Sciences (TIES) conference was held Sept. 15-16 in Chapel Hill, N.C. The conference was webcast in two-way transmission to researchers at the U.S. Environmental Protection Agency’s National Center for Environmental Assessment in Washington, D.C. and Health Canada, and in one-way video transmission to other sites worldwide.
Nearly 200 specialists in biology, toxicology, statistics, and bioinformatics gathered at the William and Ida Friday Center for Continuing Education. They explored issues surrounding the use of increasingly complicated and promising platforms that generate rapidly expanding volumes of data on gene, protein, and metabolic patterns of expression as well as emerging technologies such as cellular imaging, epigenetics and predictive modeling. The goal of this kind of research is to characterize and predict molecular responses to environmental exposures on a global scale, to advance both biomedical research and regulatory science.
Sponsors of the conference included NIEHS, the University of North Carolina at Chapel Hill (UNC-CH), the Society of Toxicology, Health Canada, the U.S. Food and Drug Administration (FDA), and the SAS Institute.
One important theme of the meeting might be expressed this way — Be careful when you wish for more data, because you might end up facing more difficulty than you ever imagined managing and interpreting all that new information.
Shaking the pillars of the paradigm of average
As the first speaker in session one “Bioinformatics — Revealing pathways and biological systems underlying biological conditions,” Harvard University computational biologist John Quackenbush, Ph.D., set the tone for his talk and, arguably, the entire conference by quoting mathematician Samuel Karlin. “The purpose of models,” Quackenbush told the audience, “is not to fit the data but to sharpen the questions.”
As biomedical research segues from a laboratory science to an informational science, Quackenbush argued, it becomes important to pay attention to the phenomenology of variance, as well as to the averages typically imposed upon biological data. A holistic approach using rank-ordered-based analysis of gene expression outliers, he said, may offer scientists insight into how the degree of variance influences the phenotype and progression of disease through epigenomic alterations, and provides the spark for evolutionary development.
The data speak, but we must invent their language
One of a host of biostatisticians speaking at the meeting wasFred Wright, Ph.D. , of UNC-CH, who spoke on expression quantitative trait locus (eQTL) analysis and variation in RNA expression.
As Wright explained, the new FastMAP eQTL analysis is several orders of magnitude faster than previous methods. However, he cautioned, it is still up to biostatisticians to develop the model for identifying the most informative single nucleotide polymorphisms (SNPs) and significant combinations for statistical analysis.
In addition to determining which candidates and combinations of SNPs are causal, Wright explained, researchers have to consider several other issues, such as the most informative tissue types for eQTL analysis, whether DNA and RNA are from the same patient, and the possibility that specific DNA sequences used as probes themselves contain SNPs that may affect outcomes.
Grounding toxigenomics in the realm of public health
Two talks, by NIEHS grantees Rebecca Fry, Ph.D. , of UNC-CH, and David Threadgill, Ph.D. , of North Carolina State University, brought the potential of integrated toxicogenomics home for listeners — both in terms of human health and in terms of environmental exposures in North Carolina.
Fry reported on her work using gene-expression analysis in human subjects to explore the two faces of arsenic, as a chemical that triggers gene expression pathways, which promote oncogenesis and tumor progression, and as a chemotherapeutic agent in the form of arsenic trioxide, which can target some forms of cancer in patients with certain gene expression patterns (see related story).
Threadgill reported on research inspired by epidemiological studies of exposure to trichloroethylene (TCE) in the water supply at Camp Lejeune, N.C. , and the presence of arsenic in the slate belt of North Carolina. He set up experiments, using ten groups of genetically diverse mice exposed to various combinations of TCE and arsenic, to look at the pathology of exposed animals, gene expression patterns, and the potential synergy of the chemicals in mixture.