Year: 2022
Type: preprint
Abstract: Introduction Privacy protection is a core principle of genomic research but needs further refinement for high-throughput proteomic platforms. Methods We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS) and then calculated genotype probabilities by protein level for each protein-genotype combination (training). Using the most significant 100 proteins, we applied a naïve Bayesian approach to match proteomes to genomes for 2,812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA) with SomaScan 1.3K proteomes and also 2,646 COPDGene subjects with SomaScan 5K proteomes (testing). We tested whether subtracting mean genotype effect for each pQTL SNP would obscure genetic identity. Results In the four testing cohorts, we were able to correctly match 90%-95% their proteomes to their correct genome and for 95%-99% we could match the proteome to the 1% most likely genome. With larger profiling (SomaScan 5K), correct identification was > 99%. The accuracy of matching in subjects with African ancestry was lower (∼60%) unless training included diverse subjects. Mean genotype effect adjustment reduced identification accuracy nearly to random guess. Conclusion Large proteomic datasets (> 1,000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered deidentified. These findings suggest that large scale proteomic data be given privacy protections of genomic data, or that bioinformatic transformations (such as adjustment for genotype effect) should be applied to obfuscate identity.
Source: medRxiv
Authors: Andrew C. Hill, Elizabeth M. Litkowski, Ani Manichaikul, Leslie Lange, Katherine A. Pratte, Katerina J. Kechris, Matthew DeCamp, Marilyn Coors, Victor E. Ortega, Stephen S. Rich, Jerome I. Rotter, Robert E. Gerzsten, Clary B. Clish, Jeffery Curtis, Xiaowei Hu, Debby Ngo, Wanda K O’Neal, Deborah Meyers, Eugene Bleecker, Brian D. Hobbs, Michael H. Cho, Farnoush Banaeikashani, Russell P. Bowler
Institutions: National Jewish Health, Colorado School of Public Health, University of Virginia, Mayo Clinic, The Lundquist Institute, Harbor–UCLA Medical Center, Beth Israel Deaconess Medical Center, Broad Institute, University of Michigan, Novartis (Switzerland), University of North Carolina at Chapel Hill, Brigham and Women's Hospital, University of Arizona, Harvard University, University of Colorado Denver
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Funders: Foundation for the National Institutes of Health, AstraZeneca, GlaxoSmithKline, Sanofi, Ikaria, Jackson State University, Chiesi Farmaceutici, COPD Foundation, Novartis Pharmaceuticals Corporation, Sunovion, Regeneron Pharmaceuticals, Mylan, Forest Research Institute, Mississippi State Department of Health, Grifols, National Institutes of Health, Gillings School of Public Health, University of North Carolina at Chapel Hill, National Heart, Lung, and Blood Institute
Awards: G2099663897, G2212190077, G3027037974, G3868091120, G3999916299, G4578545918, G4749522346, G4975107759, G5195001291, G5434367891, G5510456481, G5878489336, SPIROMICS GIC Support, G6112557991, G7206313631, SPIROMICS II: Biological underpinnings of COPD heterogeneity and progression, G87279447, G8837091488, G8957911378
OpenAlex ID: W4223589462