The discipline of epidemiology studies the determinants of diseases in human populations, identifies causes, determines outcomes and develops prevention strategies. Traditional epidemiology is most useful for studies of acute, relatively common diseases with short incubation periods but less so for studies of chronic low incidence diseases with long incubation periods. Molecular epidemiology, which employs biological responses or biomarkers as surrogates of exposures or effects, can help with the latter. For this reason, there is a great interest in developing and validating biomarkers. DNA damage underlies an important group of chronic diseases with long incubation periods, i.e., cancer. Biomarkers may measure the exposures that induce the DNA damage, the damage itself, or individual susceptibility to damage. Before they can be used for human population research, however, these measures must be validated. Biomarker validation critically depends on field studies. This is accomplished through transitional epidemiological studies that 'bridge the gap' between laboratory and field. Transitional epidemiological studies are of three varieties: (i) Developmental, (ii) Characterization, and (iii) Applied. Biomarkers are the dependent variables in transitional studies. An international network of laboratories for human population monitoring requires yet another dimension for validation, i.e., the comparability of results among laboratories must be determined. This will be achieved by sample sharing projects, with workshops to compare results. Only then can results in one population be compared with results in another. Interlaboratory standardization of assays for biomarkers validated by transitional studies will have far-reaching benefits. It will allow development of worldwide databases of background values for the various biomarkers-or biomarker maps. This, in turn, will facilitate problem identification and eventually constitute the baselines for area-specific population monitoring. Biomarker databases so developed can be compared with worldwide databases for cancer and heritable diseases, validating the former as statistical surrogates of the latter. (C) 1999 Elsevier Science B.V. All rights reserved.
