| Literature DB >> 32192646 |
Amaya Azqueta1, Carina Ladeira2, Lisa Giovannelli3, Elisa Boutet-Robinet4, Stefano Bonassi5, Monica Neri6, Goran Gajski7, Susan Duthie8, Cristian Del Bo'9, Patrizia Riso9, Gudrun Koppen10, Nursen Basaran11, Andrew Collins12, Peter Møller13.
Abstract
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.Entities:
Keywords: Comet assay; DNA damage; Fpg-sensitive sites; Human biomonitoring; Statistical analysis
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Year: 2019 PMID: 32192646 DOI: 10.1016/j.mrrev.2019.108288
Source DB: PubMed Journal: Mutat Res Rev Mutat Res ISSN: 1383-5742 Impact factor: 5.657