Application of the comet assay in human biomonitoring: An hCOMET perspective
Research output: Contribution to journal › Review › peer-review
Accepted author manuscript, 1.04 MB, PDF document
The comet assay is a well-accepted biomonitoring tool to examine the effect of dietary, lifestyle, environmental and occupational exposure on levels of DNA damage in human cells. With such a wide range of determinants for DNA damage levels, it becomes challenging to deal with confounding and certain factors are inter-related (e.g. poor nutritional intake may correlate with smoking status). This review describes the effect of intrinsic (i.e. sex, age, tobacco smoking, occupational exposure and obesity) and extrinsic (season, environmental exposures, diet, physical activity and alcohol consumption) factors on the level of DNA damage measured by the standard or enzyme-modified comet assay. Although each factor influences at least one comet assay endpoint, the collective evidence does not indicate single factors have a large impact. Thus, controlling for confounding may be necessary in a biomonitoring study, but none of the factors is strong enough to be regarded a priori as a confounder. Controlling for confounding in the comet assay requires a case-by-case approach. Inter-laboratory variation in levels of DNA damage and to some extent also reproducibility in biomonitoring studies are issues that have haunted the users of the comet assay for years. Procedures to collect specimens, and their storage, are not standardized. Likewise, statistical issues related to both sample-size calculation (before sampling of specimens) and statistical analysis of the results vary between studies. This review gives guidance to statistical analysis of the typically complex exposure, co-variate, and effect relationships in human biomonitoring studies.
|Journal||Mutation Research - Reviews in Mutation Research|
|Number of pages||20|
|Publication status||Published - 2020|
- Comet assay, DNA damage, Fpg-sensitive sites, Human biomonitoring, Statistical analysis