Deterministic identification of specific individuals from GWAS results

Ruichu Cai, Zhifeng Hao, Marianne Winslett, Xiaokui Xiao, Yin Yang, Zhenjie Zhang, Shuigeng Zhou

Research output: Contribution to journalArticle

15 Citations (Scopus)


Motivation: Genome-wide association studies (GWASs) are commonly applied on human genomic data to understand the causal gene combinations statistically connected to certain diseases. Patients involved in these GWASs could be re-identified when the studies release statistical information on a large number of single-nucleotide polymorphisms. Subsequent work, however, found that such privacy attacks are theoretically possible but unsuccessful and unconvincing in real settings. Results: We derive the first practical privacy attack that can successfully identify specific individuals from limited published associations from the Wellcome Trust Case Control Consortium (WTCCC) dataset. For GWAS results computed over 25 randomly selected loci, our algorithm always pinpoints at least one patient from the WTCCC dataset. Moreover, the number of re-identified patients grows rapidly with the number of published genotypes. Finally, we discuss prevention methods to disable the attack, thus providing a solution for enhancing patient privacy. Availability and implementation: Proofs of the theorems and additional experimental results are available in the support online documents. The attack algorithm codes are publicly available at The genomic dataset used in the experiments is available at on request.

Original languageEnglish
Pages (from-to)1701-1707
Number of pages7
Issue number11
Publication statusPublished - 2015
Externally publishedYes


ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

Cai, R., Hao, Z., Winslett, M., Xiao, X., Yang, Y., Zhang, Z., & Zhou, S. (2015). Deterministic identification of specific individuals from GWAS results. Bioinformatics, 31(11), 1701-1707.