title: Anonymization of electronic medical records for validating genome-wide association studies.
abstract: Genome-wide association studies (GWAS) facilitate the discovery of genotype-phenotype relations from population-based sequence databases, which is an integral facet of personalized medicine. The increasing adoption of electronic medical records allows large amounts of patients' standardized clinical features to be combined with the genomic sequences of these patients and shared to support validation of GWAS findings and to enable novel discoveries. However, disseminating these data "as is" may lead to patient reidentification when genomic sequences are linked to resources that contain the corresponding patients' identity information based on standardized clinical features. This work proposes an approach that provably prevents this type of data linkage and furnishes a result that helps support GWAS. Our approach automatically extracts potentially linkable clinical features and modifies them in a way that they can no longer be used to link a genomic sequence to a small number of patients, while preserving the associations between genomic sequences and specific sets of clinical features corresponding to GWAS-related diseases. Extensive experiments with real patient data derived from the Vanderbilt's University Medical Center verify that our approach generates data that eliminate the threat of individual reidentification, while supporting GWAS validation and clinical case analysis tasks.
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37203, USA. grigorios.loukides@vanderbilt.edu
authors.forename: Grigorios
authors.initials: G
authors.lastname: Loukides
authors.forename: Aris
authors.initials: A
authors.lastname: Gkoulalas-Divanis
authors.forename: Bradley
authors.initials: B
authors.lastname: Malin
mesh_terms: D000465:Algorithms; D035041:Anonymous Testing / Q000379:methods*; D003625:Data Collection / Q000379:methods*; D057286:Electronic Health Records; D030661:Genetic Privacy; D055106:Genome-Wide Association Study / Q000379:methods*; D057285:Precision Medicine / Q000379:methods*
references.citation: Nat Rev Drug Discov. 2006 Jan;5(1):23-6
references.pmid: 16374513
references.citation: Nat Genet. 2007 Oct;39(10):1181-6
references.pmid: 17898773
references.citation: Science. 2007 Jun 1;316(5829):1341-5
references.pmid: 17463248
references.citation: Methods Inf Med. 2006;45(3):267-74
references.pmid: 16685334
references.citation: Nature. 2008 Dec 11;456(7223):728-31
references.pmid: 19079049
references.citation: Clin Pharmacol Ther. 2008 Sep;84(3):362-9
references.pmid: 18500243
references.citation: J Clin Invest. 2008 May;118(5):1590-605
references.pmid: 18451988
references.citation: J Am Med Inform Assoc. 2010 May-Jun;17(3):322-7
references.pmid: 20442151
references.citation: Fed Regist. 2002 Aug 14;67(157):53181-273
references.pmid: 12180470
references.citation: PLoS Genet. 2008 Aug 29;4(8):e1000167
references.pmid: 18769715