title: Challenges in Translating GWAS Results to Clinical Care.
abstract: Clinical genetic testing for Mendelian disorders is standard of care in many cases; however, it is less clear to what extent and in which situations clinical genetic testing may improve preventive efforts, diagnosis and/or prognosis of complex disease. One challenge is that much of the reported research relies on tag single nucleotide polymorphisms (SNPs) to act as proxies for assumed underlying functional variants that are not yet known. Here we use coronary artery disease and melanoma as case studies to evaluate how well reported genetic risk variants tag surrounding variants across population samples in the 1000 Genomes Project Phase 3 data. We performed a simulation study where we randomly assigned a "functional" variant and evaluated how often this simulated functional variant was correctly tagged in diverse population samples. Our results indicate a relatively large error rate when generalizing increased genetic risk of complex disease across diverse population samples, even when generalizing within geographic regions. Our results further highlight the importance of including diverse populations in genome-wide association studies. Future work focused on identifying functional variants will eliminate the need for tag SNPs; however, until functional variants are known, caution should be used in the interpretation of genetic risk for complex disease using tag SNPs.
authors.affiliation: Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA 19122, USA. laura.scheinfeldt@temple.edu.|Department of Biology, Temple University, Philadelphia, PA 19122, USA. laura.scheinfeldt@temple.edu.|The Coriell Institute for Medical Research, Camden, NJ 08103, USA. laura.scheinfeldt@temple.edu.
authors.forename: Laura B
authors.initials: LB
authors.lastname: Scheinfeldt
authors.affiliation: The Coriell Institute for Medical Research, Camden, NJ 08103, USA. tschmidlen@coriell.org.
authors.forename: Tara J
authors.initials: TJ
authors.lastname: Schmidlen
authors.affiliation: The Coriell Institute for Medical Research, Camden, NJ 08103, USA. norman.gerry@abiolab.com.|Advanced BioMedical Laboratories, Cinnaminson, NJ 08007, USA. norman.gerry@abiolab.com.
authors.forename: Norman P
authors.initials: NP
authors.lastname: Gerry
authors.affiliation: The Coriell Institute for Medical Research, Camden, NJ 08103, USA. christman@coriell.org.
authors.forename: Michael F
authors.initials: MF
authors.lastname: Christman
mesh_terms: D003198:Computer Simulation; D003324:Coronary Artery Disease / Q000175:diagnosis* / Q000235:genetics; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D015438:Health Behavior; D006801:Humans; D008545:Melanoma / Q000175:diagnosis* / Q000235:genetics; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D057285:Precision Medicine / Q000379:methods*; D012307:Risk Factors
keywords: complex disease; genetic risk; precision medicine