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Issues in the Design of Molecular and Genetic Epidemiologic Studies

  • Fowke, Jay H. (Division of Epidemiology, Vanderbilt University Medical Center)
  • Published : 2009.11.30

Abstract

The final decision of study design in molecular and genetic epidemiology is usually a compromise between the research study aims and a number of logistical and ethical barriers that may limit the feasibility of the study or the interpretation of results. Although biomarker measurements may improve exposure or disease assessments, it is necessary to address the possibility that biomarker measurement inserts additional sources of misclassification and confounding that may lead to inconsistencies across the research literature. Studies targeting multi-causal diseases and investigating gene-environment interactions must not only meet the needs of a traditional epidemiologic study but also the needs of the biomarker investigation. This paper is intended to highlight the major issues that need to be considered when developing an epidemiologic study utilizing biomarkers. These issues covers from molecular and genetic epidemiology (MGE) study designs including cross-sectional, cohort, case-control, clinical trials, nested case-control, and case-only studies to matching the study design to the MGE research goals. This review summarizes logistical barriers and the most common epidemiological study designs most relevant to MGE and describes the strengths and limitations of each approach in the context of common MGE research aims to meet specific MEG objectives.

Keywords

References

  1. Rothman N, Stewart WF, Schulte PA. Incorporating biomarkers into cancer epidemiology: A matrix of biomarker and study design categories. Cancer Epidemiol Biomarkers Prev 1995; 4(4): 301-311
  2. Shields PG. Molecular epidemiology. Prog Clin Biol Res 1996; 395: 141-157
  3. Hulka BS, Wilcosky TC, Griffith JD. Biological Markers in Epidemiology. New York: Oxford University Press; 1990
  4. Hulka BS, Margolin BH. Methodological issues in epidemiologic studies using biologic markers. Am J Epidemiol 1992; 135(2): 200-209 https://doi.org/10.1093/oxfordjournals.aje.a116272
  5. Schenk JM, Kristal AR, Neuhouser ML, Tangen CM, White E, Lin DW, et al. Serum adiponectin, C-peptide and leptin and risk of symptomatic benign prostatic hyperplasia: Results from the Prostate Cancer Prevention Trial. Prostate 2009; 69(12): 1303-1311 https://doi.org/10.1002/pros.20974
  6. Kaaks RJ. Biochemical markers as additional measurements in studies of the accuracy of dietary questionnaire measurements: Conceptual issues. Am J Clin Nutr 1997; 65(4 Suppl): 1232S-1239S https://doi.org/10.1093/ajcn/65.4.1232S
  7. Bingham SA, Day NE. Using biochemical markers to assess the validity of prospective dietary assessment methods and the effect of energy adjustment. Am J Clin Nutr 1997; 65(4 Suppl): 1130S-1137S https://doi.org/10.1093/ajcn/65.4.1130S
  8. Subar AF, Kipnis V, Troiano RP, Midthune D, Schoeller DA, Bingham S, et al. Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: The OPEN study. Am J Epidemiol 2003; 158(1): 1-13 https://doi.org/10.1093/aje/kwg092
  9. Marshall JR. High-grade prostatic intraepithelial neoplasia as an exposure biomarker for prostate cancer chemoprevention research. IARC Sci Publ 2001; 154: 191-198
  10. Owen RW. Biomarkers in colorectal cancer. IARC Sci Publ 2001; 154: 101-111

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