title: Cumulative meta-analysis for genetic association: when is a new study worthwhile?
abstract: OBJECTIVE
  In this paper, we address the questions: how large a sample size would be required to show genome-wide significance between a single nucleotide polymorphism (SNP) and a genetic trait in a meta-analysis of a newly planned study together with the existing ones? Or alternatively: will a planned study of size n be able to provide evidence of a genetic association when this study is combined with a current meta-analysis?
  
  
  METHODS
  We examine the potential impact of a newly planned genetic study on an existing meta-analysis through the use of a simulation-based algorithm. The proposed approach provides an empirical estimate of the power of the updated meta-analysis to detect genome-wide significance (p<5.0×10(-8)) of a complex trait and each of a set of specific SNPs of interest or the expected p value of the updated meta-analysis including the current and proposed studies.
  
  
  RESULTS
  This technique is illustrated in the context of an updated meta-analysis of case-control studies in Paget's disease. A second example illustrates the impact of adding a newly planned study to a large meta-analysis of SNP associations with human height.
  
  
  CONCLUSIONS
  The proposed algorithm is particularly useful for the design of studies to assess a selected set of high-priority SNP associations that are 'nearly' significant in meta-analysis of existing studies. The results may help investigators decide whether an updated meta-analysis is likely to achieve genome-wide significance.
authors.affiliation: School of Kinesiology and Health Science, York University, and Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, Canada. mrotondi@yorku.ca
authors.forename: Michael A
authors.initials: MA
authors.lastname: Rotondi
authors.forename: Shelley B
authors.initials: SB
authors.lastname: Bull
mesh_terms: D000465:Algorithms; D049628:Body Size / Q000235:genetics*; D016022:Case-Control Studies; D055106:Genome-Wide Association Study; D006801:Humans; D015201:Meta-Analysis as Topic; D010001:Osteitis Deformans / Q000453:epidemiology / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D018401:Sample Size