Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology, Boston, MA, USA. cassa@mit.edu
BACKGROUND: Genomic sequencing of SNPs is increasingly prevalent, though the amount of familial information these data contain has not been quantified. METHODS: We provide a framework for measuring the risk to siblings of a patient's SNP genotype disclosure, and demonstrate that sibling SNP genotypes can be inferred with substantial accuracy. RESULTS: Extending this inference technique, we determine that a very low number of matches at commonly varying SNPs is sufficient to confirm sib-ship, demonstrating that published sequence data can reliably be used to derive sibling identities. Using HapMap trio data, at SNPs where one child is homozygotic major, with a minor allele frequency </= 0.20, (N = 452684, 65.1%) we achieve 91.9% inference accuracy for sibling genotypes. CONCLUSION: These findings demonstrate that substantial discrimination and privacy risks arise from use of inferred familial genomic data.