Choosing blindly but wisely: Differentially private solicitation of DNA datasets for disease marker discovery

Journal of the American Medical Informatics Association

Volumn 22, Issue 1, 2015, Pages 100-108

  Zhao, Yongan ^a   Wang, Xiaofeng ^a   Jiang, Xiaoqian ^b   Ohno Machado, Lucila ^b   Tang, Haixu ^a  

^a INDIANA UNIVERSITY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Differential privacy; Genome wide association studies; Haplotype blocks; Privacy preserving techniques; Single nucleotide polymorphisms (SNPs); Test statistics

Indexed keywords

ACCESS TO INFORMATION; ALGORITHM; ARTICLE; DISEASE MARKER; GENE LINKAGE DISEQUILIBRIUM; GENETIC ASSOCIATION; GENETIC DATABASE; GENETIC PRIVACY; HUMAN GENOME; INFORMATION PROCESSING; PRIVACY PRESERVING TECHNIQUE; SINGLE NUCLEOTIDE POLYMORPHISM; CONFIDENTIALITY; GENETIC MARKER; GENOME-WIDE ASSOCIATION STUDY; HUMAN;

DNA; GENETIC MARKER;

CONFIDENTIALITY; DATASETS AS TOPIC; DNA; GENETIC MARKERS; GENOME, HUMAN; GENOME-WIDE ASSOCIATION STUDY; HUMANS; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84938572122     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2014-003043     Document Type: Article

References (26)

1. Hardy J, Singleton A. Genomewide association studies and human disease. N Engl J Med 2009;360:1759-68.
2. Cooper RS, Kaufman JS, Ward R. Race and genomics. N Engl J Med 2003;348:1166-70.
3. Paw B, Tieu P, Kaback M, et al. Frequency of three Hex A mutant alleles among Jewish and non-Jewish carriers identified in a Tay-Sachs screening program. Am J Hum Genet 1990;47:698.
4. Tsui LC. Mutations and sequence variations detected in the cystic fibrosis transmembrane conductance regulator (CFTR) gene: a report from the Cystic Fibrosis Genetic Analysis Consortium. Hum Mutat 1992;1:197-203.
5. Thein SL. Genetic insights into the clinical diversity of b thalassaemia. Br J Haematol 2004;124:264-74.
6. Homer N, Szelinger S, Redman M, et al. Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet 2008;4:e1000167.
7. Sankararaman S, Obozinski G, Jordan MI, et al. Genomic privacy and limits of individual detection in a pool. Nat Genet 2009;41:965-7.
8. Policy for Sharing of Data Obtained in NIH Supported or Conducted Genome-Wide Association Studies (GWAS). http://grants.nih.gov/grants/guide/notice-files/NOT-OD-07-088.html
9. Wang R, Fuga Li Y, Wang XF, et al. Learning your identity and disease from research papers: information leaks in genome wide association study. Proceedings of the 16th ACM Conference on Computer and Communications Security. 2009. ACM.
10. Bush WS, Moore JH. Genome-wide association studies. PLoS Comput Biol 2012;8:e1002822.
11. Price AL, Zaitlen NA, Reich D, et al. New approaches to population stratification in genome-wide association studies. Nat Rev Genet 2010;11:459-63.
12. Irit D, Nissim K. Revealing information while preserving privacy. Proceedings of the Twenty-second ACM SIGMODSIGACT-SIGART Symposium on Principles of Database Systems. 2003. ACM.
13. Dwork C, McSherry F, Nissim K, et al. Calibrating noise to sensitivity in private data analysis. Theory of Cryptography Conference (TCC). Springer, 2006:265-84.
14. Privacy preserving GWAS data sharing. Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on. 2011. IEEE.
15. Craig DW, Goor RM, Wang Z, et al. Assessing and managing risk when sharing aggregate genetic variant data. Nat Rev Genet 2011;12:730-6.
16. Kaye J, Heeney C, Hawkins N, et al. Data sharing in genomics-re-shaping scientific practice. Nat Rev Genet 2009; 10:331-5.
17. Wang S, Sparks L, Xie H, et al. Subtyping obesity with microarrays: implications for the diagnosis and treatment of obesity. Int J Obes 2009;33:481-9.
18. Dwork C. Differential privacy. In: Automata, languages and programming. Burkhard M, auf der Heide FM, eds. Springer, 2006:1-12.
19. Gabriel SB, Schaffner SF, Nguyen H, et al. The structure of haplotype blocks in the human genome. Science 2002;296: 2225-9.
20. Zhang K, Qin ZS, Liu JS, et al. Haplotype block partitioning and tag SNP selection using genotype data and their applications to association studies. Genome Res 2004;14: 908-16.
21. Gupta V, Khadgawat R, Ng HKT, et al. A Validation Study of Type 2 Diabetes-related Variants of the TCF7L2, HHEX, KCNJ11, and ADIPOQ Genes in one Endogamous Ethnic Group of North India. Ann Hum Genet 2010;74:361-8.
22. Barnett GC, Coles CE, Elliott RM, et al. Independent validation of genes and polymorphisms reported to be associated with radiation toxicity: a prospective analysis study. Lancet Oncol 2012;13:65-77.
23. Burton PR, Clayton DG, Cardon LR, et al. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007;447:661-78.
24. Shimizu C, Jain S, Davila S, et al. Transforming growth factor-b signaling pathway in patients with Kawasaki disease. Circulation 2011;4:16-25.
25. Burns JC, GlodéMP. Kawasaki syndrome. Lancet 2004; 364:533-44.
26. Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc B 1996;58:267-88.