Molecular epidemiology: A better approach for the early detection of pathophysiologic response to environmental toxicants and disease

  • JI Anetor
  • FAA Adeniyi
  • SB Olaleye

Abstract

Our environment is becoming increasingly contaminated by a profusion of substances in the form of industrial and Municipal Waste, air and water pollutants; by heavy metals (such as lead) herbicides,
pesticides, cosmetics and so on. The number of chemicals that affect man increases at alarming rates. These agents may be dangerous because they produce biochemical, genetic, structural or physiological
lesions in a significant segment of the population. The importance of elucidating the nature and the mechanisms of physiological and toxicological reactions has been emphasized in the investigations of
occupational and environmental diseases, such investigations have revealed that the clinical manifestations of intoxication may have their origin in injurious effects of subcellular or biochemical types. Slight to
moderate derangements in metabolism may impair the functional activity of organs and lead to subclinical or overt clinical effects. These may elude detection or recognition of their health implications unless
biomarkers, the functional components of molecular epidemiology are employed. Molecular epidemiology is an approach which aims to examine aetiology of disease in a more precise way by focusing on biomarkers of disease risk rather than relying on the actual occurrence of disease. Such studies can be carried out in a short time and with relatively small numbers of subjects compared with conventional epidemiology, which though currently more popular merely reveals association, and causal links often remain obscure. Detection
of early biochemical lesions that are related to subsequent changes in structure and physiology would be useful as early indicators of environmental hazards that produce disease in humans, that is by employing molecular epidemiology. This will be greatly enhanced by newer tools, such as toxicogenomics and metabonomics.
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eISSN: 1119-5096