Developing sustainable studies on environmental health

被引:12
作者
Albertini, RJ [1 ]
机构
[1] Univ Vermont, Genet Toxicol Lab, Burlington, VT 05401 USA
关键词
biomarkers; molecular epidemiology; environmental carcinogenesis; cancer risk assessment; transitional epidemiology;
D O I
10.1016/S0027-5107(01)00191-9
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Toxicogenetics, toxicogenomics and proteomics are providing new biomarkers for use in human studies. These, coupled with the more traditional biological responses currently in use, provide a vast armamentarium for assessing exposures, effects and susceptibility factors relating to environmental pollutants. Biomarker availability, however, does not automatically translate to usefulness for studies directed at human health improvement. Transitional studies bridging the gap between laboratory and field, with the biomarker as dependent variable, are required for validation for intended applications. Prospective or cross-sectional studies are usually optimal for validating biomarkers of exposure, where the biomarker response follows the event (exposure) and the entire study population is affected. Biomarkers of effect, where the event (outcome) follows the biomarker response and may be infrequent in the study population, present more complex problems. Identification of genotypes as susceptibility factors requires that additional issues be addressed. Despite these difficulties, new data are emerging from transitional investigations that are providing validated biomarkers for sustainable human studies. It is now possible to envision schemes for integrating the results of molecular epidemiological investigations into the general toxicological evaluations of environmental agents. These will allow intermediate endpoints to be used for making realistic human health assessments and for elucidating pathogenic mechanisms that identify targets for intervention, all with the goal of preventing environmentally mediated human disease. Finally, select biomarker responses that predict the likelihood of disease occurrence will find application in the interpretation of individual medical diagnostic tests, with the goal of improving cancer detection and management. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:317 / 331
页数:15
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