Smoking and Selected DNA Repair Gene Polymorphisms in Controls: Systematic Review and Meta-Analysis

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Citation

Hodgson, M. Elizabeth; Poole, Charles L.; Olshan, Andrew F.; North, Kari E.; Zeng, Donglin; & Millikan, Robert C. (2010). Smoking and Selected DNA Repair Gene Polymorphisms in Controls: Systematic Review and Meta-Analysis. Cancer Epidemiology, Biomarkers & Prevention, 19(12), 3055-3086. PMCID: PMC3108462

Abstract

Background: When the case-only study design is used to estimate statistical interaction between genetic (G) and environmental (E) exposures, G and E must be independent in the underlying population, or the case-only estimate of interaction (COR) will be biased. Few studies have examined the occurrence of G-E association in published control group data.
Methods: To examine the assumption of G-E independence in empirical data, we conducted a systematic review and meta-analysis of G-E associations in controls for frequently investigated DNA repair genes (XRCC1 Arg399Gln, Arg194Trp, or Arg280His, XPD Lys751Gln, and Asp312Asn, and XRCC3 Thr241Met) and smoking (ever/never smoking, current/not current smoker, smoking duration, smoking intensity and pack-years).
Results: Across the 55 included studies, SNP-smoking associations in controls (ORz) were not reliably at the null value of 1.0 for any SNP-smoking combinations. Two G-E combinations were too heterogeneous for summary estimates: XRCC1 399 and ever-never smoking (N=21), and XPD 751 and pack-years (N=12). ORz ranges for these combinations were: [ORz (95% confidence interval (CI)] 0.7 (0.4, 1.2) - 1.9 (1.2, 2.8) and 0.8 (0.5, 1.3) - 2.3 (0.8, 6.1), respectively). Estimates for studies considered homogeneous (Cochran's Q p-value <0.10) varied 2- to 5-fold. No study characteristics were identified that could explain heterogeneity.
Conclusions: We recommend the independence assumption be evaluated in the population underlying any potential case-only study, rather than in a proxy control group(s) or pooled controls. Impact: These results suggest that G-E association in controls may be population-specific. Increased access to control data would improve evaluation of the independence assumption.

URL

http://dx.doi.org/10.1158/1055-9965.EPI-10-0877

Reference Type

Journal Article

Year Published

2010

Journal Title

Cancer Epidemiology, Biomarkers & Prevention

Author(s)

Hodgson, M. Elizabeth
Poole, Charles L.
Olshan, Andrew F.
North, Kari E.
Zeng, Donglin
Millikan, Robert C.

PMCID

PMC3108462

ORCiD

Olshan - 0000-0001-9115-5128