Assessing and managing risk when sharing aggregate genetic variant data

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Abstract
Meta-analyses that use data from several genome-wide association studies are revealing more disease-associated genetic variants, but how can the privacy of study participants be protected when data are shared? This article considers ways to evaluate the risk of loss of privacy. Access to genetic data across studies is an important aspect of identifying new genetic associations through genome-wide association studies (GWASs). Meta-analysis across multiple GWASs with combined cohort sizes of tens of thousands of individuals often uncovers many more genome-wide associated loci than the original individual studies; this emphasizes the importance of tools and mechanisms for data sharing. However, even sharing summary-level data, such as allele frequencies, inherently carries some degree of privacy risk to study participants. Here we discuss mechanisms and resources for sharing data from GWASs, particularly focusing on approaches for assessing and quantifying the privacy risks to participants that result from the sharing of summary-level data.