Nonreplication in Genetic Studies of Complex Diseases—Lessons Learned From Studies of Osteoporosis and Tentative Remedies

Authors

  • Hui Shen,

    1. The Key Laboratory of Biomedical Information Engineering of Ministry of Education and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
    2. Osteoporosis Research Center, Creighton University Medical Center, Omaha, Nebraska, USA
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  • Yongjun Liu,

    1. Osteoporosis Research Center, Creighton University Medical Center, Omaha, Nebraska, USA
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  • Pengyuan Liu,

    1. Osteoporosis Research Center, Creighton University Medical Center, Omaha, Nebraska, USA
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  • Robert R Recker,

    1. Osteoporosis Research Center, Creighton University Medical Center, Omaha, Nebraska, USA
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  • Hong-Wen Deng PhD

    Corresponding author
    1. The Key Laboratory of Biomedical Information Engineering of Ministry of Education and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
    2. Osteoporosis Research Center, Creighton University Medical Center, Omaha, Nebraska, USA
    3. Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, ChangSha, Hunan, China
    • Osteoporosis Research Center, Creighton University Medical Center, 601 N. 30th Street, Suite 6787, Omaha, NE 68131, USA
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  • The authors have no conflict of interest.

Abstract

Inconsistent results have accumulated in genetic studies of complex diseases/traits over the past decade. Using osteoporosis as an example, we address major potential factors for the nonreplication results and propose some potential remedies.

Over the past decade, numerous linkage and association studies have been performed to search for genes predisposing to complex human diseases. However, relatively little success has been achieved, and inconsistent results have accumulated. We argue that those nonreplication results are not unexpected, given the complicated nature of complex diseases and a number of confounding factors. In this article, based on our experience in genetic studies of osteoporosis, we discuss major potential factors for the inconsistent results and propose some potential remedies. We believe that one of the main reasons for this lack of reproducibility is overinterpretation of nominally significant results from studies with insufficient statistical power. We indicate that the power of a study is not only influenced by the sample size, but also by genetic heterogeneity, the extent and degree of linkage disequilibrium (LD) between the markers tested and the causal variants, and the allele frequency differences between them. We also discuss the effects of other confounding factors, including population stratification, phenotype difference, genotype and phenotype quality control, multiple testing, and genuine biological differences. In addition, we note that with low statistical power, even a “replicated” finding is still likely to be a false positive. We believe that with rigorous control of study design and interpretation of different outcomes, inconsistency will be largely reduced, and the chances of successfully revealing genetic components of complex diseases will be greatly improved.

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