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Data-dredging gene-dose analyses in association studies: biases and their corrections
Wen-Chung Lee1, Hsiao-Yuan Huang
1Graduate Institute of Epidemiology, College of Public Health, National Taiwan University, No. 1 Jen-Ai Road, 1st Section, Taipei, Taiwan. wenchung@ha.mc.ntu.edu.tw
Summary
Gene-dose analyses in disease risk studies can be biased if "high-risk" genotypes are defined by case-control frequency differences. This study demonstrates that such data-dredging leads to false positives, but a permutation correction method effectively resolves these biases.
Area of Science:
- Genetics
- Biostatistics
- Epidemiology
Background:
- Case-control association studies frequently employ gene-dose analyses to assess the combined effect of multiple genetic loci on disease risk.
- A common methodological pitfall involves defining high-risk genotypes or alleles based on their higher frequency within the case group compared to the control group.
Purpose of the Study:
- To investigate the potential for bias introduced by a specific definition of "high-risk" genotypes in gene-dose analyses.
- To evaluate the impact of this "data-dredging" approach on the accuracy of genetic association studies.
- To propose and validate a statistical method for correcting identified biases.
Main Methods:
- Utilized Monte Carlo simulations to model the "data-dredging" gene-dose analysis under various scenarios, including null hypotheses where no true association exists.
- Developed and implemented a permutation correction method designed to mitigate the identified biases.
- Compared the results of the biased analysis with the corrected analysis.
Main Results:
- Monte Carlo simulations confirmed that the "data-dredging" approach can produce significantly biased results, leading to an overestimation of risk even without a true genetic association.
- The proposed permutation correction method demonstrated a high degree of effectiveness in correcting these biases.
- The corrected analyses yielded more accurate estimates of the joint effect of multiple loci on disease risk.
Conclusions:
- The definition of "high-risk" genotypes based on case-control frequency differences in gene-dose analyses is inherently flawed and can lead to spurious findings.
- A permutation correction method offers a robust solution for rectifying biases in gene-dose analyses.
- Accurate genetic association studies require careful methodological considerations to avoid "data-dredging" and ensure reliable results.
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