J Bone Metab.  2014 May;21(2):99-116. 10.11005/jbm.2014.21.2.99.

Genome-wide Association Studies for Osteoporosis: A 2013 Update

• Liu YJ
• Zhang L
• Papasian C
• Deng HW

• KMID: 2241531
• DOI: http://doi.org/10.11005/jbm.2014.21.2.99

Abstract

In the past few years, the bone field has witnessed great advances in genome-wide association studies (GWASs) of osteoporosis, with a number of promising genes identified. In particular, meta-analysis of GWASs, aimed at increasing the power of studies by combining the results from different study populations, have led to the identification of novel associations that would not otherwise have been identified in individual GWASs. Recently, the first whole genome sequencing study for osteoporosis and fractures was published, reporting a novel rare nonsense mutation. This review summarizes the important and representative findings published by December 2013. Comments are made on the notable findings and representative studies for their potential influence and implications on our present understanding of the genetics of osteoporosis. Potential limitations of GWASs and their meta-analyses are evaluated, with an emphasis on understanding the reasons for inconsistent results between different studies and clarification of misinterpretation of GWAS meta-analysis results. Implications and challenges of GWAS are also discussed, including the need for multi- and inter-disciplinary studies.

Keyword

Genome-wide association study; Osteoporosis

MeSH Terms

Codon, Nonsense
Genetics
Genome
Genome-Wide Association Study*
Osteoporosis*
Codon, Nonsense

Figure

• 

  Fig. 1 Power of meta-analysis in heterogeneous populations. We simulated 17 studies (total sample size of 32,961 study subjects), 7 studies having phenotypic effects and 10 studies having no phenotypic effects. For simplicity, each sample was simulated with MAF of 0.3. Between-study variance was set at 0.6. "Subset" samples were those having effects, and "Total" were total samples. "_F" and "_R" denote "fixed-effects" and "random-effects" models for meta-analysis. Significance level of meta-analysis was set at 5×10-8. Power was estimated based on 10,000 replications.

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