Literature DB >> 14644337

The impact of new technologies on human population studies.

Michael D Waters1, James K Selkirk, Kenneth Olden.   

Abstract

Human population studies involve clinical or epidemiological observations that associate environmental exposures with health endpoints and disease. Clearly, these are the most sought after data to support assessments of human health risk from environmental exposures. However, the foundations of many health risk assessments rest on experimental studies in rodents performed at high doses that elicit adverse outcomes, such as organ toxicity or tumors. Using the results of human studies and animal data, risk assessors define the levels of environmental exposures that may lead to disease in a portion of the population. These decisions on potential health risks are frequently based on the use of default assumptions that reflect limitations in our scientific knowledge. An important immediate goal of toxicogenomics, including proteomics and metabonomics, is to offer the possibility of making decisions affecting public health and public based on detailed toxicity, mechanistic, and exposure data in which many of the uncertainties have been eliminated. Ultimately, these global technologies will dramatically impact the practice of public health and risk assessment as applied to environmental health protection. The impact is already being felt in the practice of toxicology where animal experimentation using highly controlled dose-time parameters is possible. It is also being seen in human population studies where understanding human genetic variation and genomic reactions to specific environmental exposures is enhancing our ability to uncover the causes of variations in human response to environmental exposures. These new disciplines hold the promise of reducing the costs and time lines associated with animal and human studies designed to assess both the toxicity of environmental pollutants and efficacy of therapeutic drugs. However, as with any new science, experience must be gained before the promise can be fulfilled. Given the numbers and diversity of drugs, chemicals and environmental agents; the various species in which they are studied and the time and dose factors that are critical to the induction of beneficial and adverse effects, it is only through the development of a profound knowledge base that toxicology and environmental health can rapidly advance. The National Institute of Environmental Health Sciences (NIEHS), National Center for Toxicogenomics and its university-based Toxicogenomics Research Consortium (TRC), and resource contracts, are engaged in the development, application and standardization of the science upon which to the build such a knowledge base on Chemical Effects in Biological Systems (CEBS). In addition, the NIEHS Environmental Genome Project (EGP) is working to systematically identify and characterize common sequence polymorphisms in many genes with suspected roles in determining chemical sensitivity. The rationale of the EGP is that certain genes have a greater than average influence over human susceptibility to environmental agents. If we identify and characterize the polymorphism in those genes, we will increase our understanding of human disease susceptibility. This knowledge can be used to protect susceptible individuals from disease and to reduce adverse exposure and environmentally induced disease.

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Year:  2003        PMID: 14644337     DOI: 10.1016/j.mrrev.2003.06.022

Source DB:  PubMed          Journal:  Mutat Res        ISSN: 0027-5107            Impact factor:   2.433


  4 in total

1.  Taking PROs and patient-centered care seriously: incremental and disruptive ideas for incorporating PROs in oncology practice.

Authors:  Molla Sloane Donaldson
Journal:  Qual Life Res       Date:  2008-11-09       Impact factor: 4.147

2.  Transport and dynamics of toxic pollutants in the natural environment and their effect on human health: research gaps and challenge.

Authors:  Andrew Hursthouse; George Kowalczyk
Journal:  Environ Geochem Health       Date:  2008-11-11       Impact factor: 4.609

3.  The TAO-Gen algorithm for identifying gene interaction networks with application to SOS repair in E. coli.

Authors:  Takeharu Yamanaka; Hiroyoshi Toyoshiba; Hideko Sone; Frederick M Parham; Christopher J Portier
Journal:  Environ Health Perspect       Date:  2004-11       Impact factor: 9.031

4.  Simultaneous clustering of gene expression data with clinical chemistry and pathological evaluations reveals phenotypic prototypes.

Authors:  Pierre R Bushel; Russell D Wolfinger; Greg Gibson
Journal:  BMC Syst Biol       Date:  2007-02-23
  4 in total

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