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The Generalized Odds Ratio as a Measure of Genetic Risk Effect in the Analysis and Meta-Analysis of Association Studies

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  • Zintzaras Elias

    (University of Thessaly School of Medicine and Tufts University School of Medicine)

Abstract

The significance of risk effects in genetic association studies is assessed using the odds ratio for various genetic models (dominant, recessive and co-dominant) by merging genotypes. These models are not independent and there is no a priori biological justification for their choice. Consequently, the interpretation of their results can be problematic, especially when multiallelic variants and disease progression are investigated. The introduction of the generalized odds ratio (ORG) may be a remedy. The ORG utilizes the complete genotype distribution and it provides an estimate of the magnitude of the association, given that the mutational load and/or the phenotype are treated as a graded exposure and/or outcome. The performance of the ORG was tested in 13 meta-analyses with binary outcomes (12 with biallelic and one 3-allelic variants) and in one meta-analysis that investigated disease progression. Six biallelic meta-analyses produced a significant ORG, indicating higher risk of disease given that the diseased subjects have a higher mutational load compared to the non-diseased ones. Four of the six meta-analyses showed significance for all genetic models. The multiallelic meta-analysis produced a significant ORG, indicating that the mutational load is implicated in disease susceptibility; on the contrary, the multiple genetic models produced diverse results. In the disease progression meta-analysis, the risk of progression was related to mutational load of the variant whereas the conventional analysis did not reveal this association. Application of the ORG could overcome the shortcomings of multiple model testing or erroneous model specification and provides an alternative and robust way for genetic association testing.

Suggested Citation

  • Zintzaras Elias, 2010. "The Generalized Odds Ratio as a Measure of Genetic Risk Effect in the Analysis and Meta-Analysis of Association Studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-14, May.
    • Handle: RePEc:bpj:sagmbi:v:9:y:2010:i:1:n:21
    DOI: 10.2202/1544-6115.1542
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    Cited by:

    1. Li Liu & Qinji Su & Lixia Li & Xiaohui Lin & Yu Gan & Sidong Chen, 2014. "The Common Variant rs4444235 near BMP4 Confers Genetic Susceptibility of Colorectal Cancer: An Updated Meta-Analysis Based on a Comprehensive Statistical Strategy," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-8, June.
    2. Anyuan Zhong & Xiaolu Xiong & Huajun Xu & Minhua Shi, 2014. "An Updated Meta-Analysis of the Association between Tumor Necrosis Factor-α -308G/A Polymorphism and Obstructive Sleep Apnea-Hypopnea Syndrome," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-6, September.
    3. Jinxian Sun & Jianrong Hu & Chunlin Tu & Anyuan Zhong & Huajun Xu, 2015. "Obstructive Sleep Apnea Susceptibility Genes in Chinese Population: A Field Synopsis and Meta-Analysis of Genetic Association Studies," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-13, August.
    4. Yuhao Sun & Ye Liu & Lora Talley Watts & Qingfang Sun & Zhihong Zhong & Guo-Yuan Yang & Liuguan Bian, 2013. "Genetic Associations of Angiotensin-Converting Enzyme with Primary Intracerebral Hemorrhage: A Meta-analysis," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-8, June.

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