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Article
Common DNA Variants Accurately Rank an Individual of Extreme Height
International Journal of Genomics
  • Corinne E. Sexton, Brigham Young University
  • Mark T. W. Ebbert, Mayo Clinic
  • Ryan H. Miller, University of Utah
  • Meganne Ferrel, Brigham Young University
  • JoAnn T. Tschanz, Utah State University
  • Chris D. Corcoran, Utah State University
  • Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Neuroimaging Initiative
  • Perry G. Ridge, Brigham Young University
  • John S. K. Kauwe, Brigham Young University
Document Type
Article
Publisher
Hindawi
Publication Date
9-4-2018
Creative Commons License
Creative Commons Attribution 4.0
Disciplines
Abstract

Polygenic scores (or genetic risk scores) quantify the aggregate of small effects from many common genetic loci that have been associated with a trait through genome-wide association. Polygenic scores were first used successfully in schizophrenia and have since been applied to multiple phenotypes including multiple sclerosis, rheumatoid arthritis, and height. Because human height is an easily-measured and complex polygenic trait, polygenic height scores provide exciting insights into the predictability of aggregate common variant effect on the phenotype. Shawn Bradley is an extremely tall former professional basketball player from Brigham Young University and the National Basketball Association (NBA), measuring 2.29 meters (7′6″, 99.99999th percentile for height) tall, with no known medical conditions. Here, we present a case where a rare combination of common SNPs in one individual results in an extremely high polygenic height score that is correlated with an extreme phenotype. While polygenic scores are not clinically significant in the average case, our findings suggest that for extreme phenotypes, polygenic scores may be more successful for the prediction of individuals.

Citation Information
Corinne E. Sexton, Mark T. W. Ebbert, Ryan H. Miller, et al., “Common DNA Variants Accurately Rank an Individual of Extreme Height,” International Journal of Genomics, vol. 2018, Article ID 5121540, 7 pages, 2018. https://doi.org/10.1155/2018/5121540.