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International Journal of Genomics
Volume 2018, Article ID 5121540, 7 pages
https://doi.org/10.1155/2018/5121540
Research Article

Common DNA Variants Accurately Rank an Individual of Extreme Height

1Department of Biology, Brigham Young University, Provo, UT 84602, USA
2Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
3Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
4Department of Psychology, Utah State University, Logan, UT, USA
5Center for Epidemiologic Studies, Utah State University, Logan, UT, USA
6Department of Mathematics and Statistics, Utah State University, Logan, UT, USA
7Alzheimer’s Disease Neuroimaging Initiative, University of Southern California, Los Angeles, CA 90089, USA

Correspondence should be addressed to John S. K. Kauwe; ude.uyb@ewuak

Received 28 February 2018; Accepted 6 June 2018; Published 4 September 2018

Academic Editor: Monika Dmitrzak-Weglarz

Copyright © 2018 Corinne E. Sexton et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. M. Purcell, N. R. Wray, J. L. Stone et al., “Common polygenic variation contributes to risk of schizophrenia and bipolar disorder,” Nature, vol. 460, pp. 748–752, 2009. View at Publisher · View at Google Scholar · View at Scopus
  2. The International Multiple Sclerosis Genetics Consortium (IMSGC), “Evidence for polygenic susceptibility to multiple sclerosis—the shape of things to come,” The American Journal of Human Genetics, vol. 86, no. 4, pp. 621–625, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. E. A. Stahl, D. Wegmann, G. Trynka et al., “Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis,” Nature Genetics, vol. 44, no. 5, pp. 483–489, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. M. A. Simonson, A. G. Wills, M. C. Keller, and M. B. McQueen, “Recent methods for polygenic analysis of genome-wide data implicate an important effect of common variants on cardiovascular disease risk,” BMC Medical Genetics, vol. 12, no. 1, p. 146, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. M. J. Machiela, C. Y. Chen, C. Chen, S. J. Chanock, D. J. Hunter, and P. Kraft, “Evaluation of polygenic risk scores for predicting breast and prostate cancer risk,” Genetic Epidemiology, vol. 35, no. 6, pp. 506–514, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. D. M. Evans, P. M. Visscher, and N. R. Wray, “Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk,” Human Molecular Genetics, vol. 18, no. 18, pp. 3525–3531, 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. R. A. Fisher, “XV.—The correlation between relatives on the supposition of Mendelian inheritance,” Earth and Environmental Science Transactions of the Royal Society of Edinburgh, vol. 52, no. 2, pp. 399–433, 1919. View at Publisher · View at Google Scholar · View at Scopus
  8. K. Silventoinen, S. Sammalisto, M. Perola et al., “Heritability of adult body height: a comparative study of twin cohorts in eight countries,” Twin Research and Human Genetics, vol. 6, no. 5, pp. 399–408, 2003. View at Publisher · View at Google Scholar · View at Scopus
  9. P. M. Visscher, S. E. Medland, M. A. R. Ferreira et al., “Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings,” PLoS Genetics, vol. 2, no. 3, article e41, 2006. View at Publisher · View at Google Scholar · View at Scopus
  10. A. R. Wood, T. Esko, J. Yang et al., “Defining the role of common variation in the genomic and biological architecture of adult human height,” Nature Genetics, vol. 46, no. 11, pp. 1173–1186, 2014. View at Publisher · View at Google Scholar · View at Scopus
  11. J. Yang, B. Benyamin, B. P. McEvoy et al., “Common SNPs explain a large proportion of the heritability for human height,” Nature Genetics, vol. 42, no. 7, pp. 565–569, 2010. View at Publisher · View at Google Scholar · View at Scopus
  12. J. Yang, T. A. Manolio, L. R. Pasquale et al., “Genome-partitioning of genetic variation for complex traits using common SNPs,” Nature Genetics, vol. 43, no. 6, pp. 519–525, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. Y. Chan, O. L. Holmen, A. Dauber et al., “Common variants show predicted polygenic effects on height in the tails of the distribution, except in extremely short individuals,” PLoS Genetics, vol. 7, no. 12, article e1002439, 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. F. Liu, A. E. J. Hendriks, A. Ralf et al., “Common DNA variants predict tall stature in Europeans,” Human Genetics, vol. 133, no. 5, pp. 587–597, 2014. View at Publisher · View at Google Scholar · View at Scopus
  15. C. D. Fryar, Q. Gu, C. L. Ogden, and K. M. Flegal, “Anthropometric reference data for children and adults; United States, 2011-2014,” Vital and Health Statistics, vol. 3, no. 392016, 2016. View at Google Scholar
  16. J. C. S. Breitner, B. W. Wyse, J. C. Anthony et al., “APOE-ε4 count predicts age when prevalence of AD increases, then declines the Cache County study,” Neurology, vol. 53, no. 2, pp. 321–331, 1999. View at Publisher · View at Google Scholar
  17. M. T. W. Ebbert, P. G. Ridge, A. R. Wilson et al., “Population-based analysis of Alzheimer’s disease risk alleles implicates genetic interactions,” Biological Psychiatry, vol. 75, no. 9, pp. 732–737, 2014. View at Publisher · View at Google Scholar · View at Scopus
  18. H. Li, “Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM,” 2013, http://arxiv.org/abs/1303.3997.
  19. B. N. Howie, P. Donnelly, and J. Marchini, “A flexible and accurate genotype imputation method for the next generation of genome-wide association studies,” PLoS Genetics, vol. 5, no. 6, article e1000529, 2009. View at Publisher · View at Google Scholar · View at Scopus
  20. The 1000 Genomes Project Consortium, “A global reference for human genetic variation,” Nature, vol. 526, pp. 68–74, 2015. View at Google Scholar
  21. A. R. Sharp, P. G. Ridge, M. H. Bailey et al., “Population substructure in Cache County, Utah: the Cache County study,” BMC Bioinformatics, vol. 15, Supplement 7, pp. S8–S8, 2014. View at Publisher · View at Google Scholar · View at Scopus
  22. A. C. Naj, G. Jun, G. W. Beecham et al., “Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease,” Nature Genetics, vol. 43, no. 5, pp. 436–441, 2011. View at Publisher · View at Google Scholar · View at Scopus
  23. K. L. Boehme, S. Mukherjee, P. K. Crane, and J. S. Kauwe, “ADGC 1000 Genomes combined data workflow,” October 2015, http://kauwelab.byu.edu/Portals/22/adgc_combined_1000G_09192014.pdf.
  24. J. C. Barrett, B. Fry, J. Maller, and M. J. Daly, “Haploview: analysis and visualization of LD and haplotype maps,” Bioinformatics, vol. 21, no. 2, pp. 263–265, 2005. View at Publisher · View at Google Scholar · View at Scopus
  25. F. Dudbridge, “Power and predictive accuracy of polygenic risk scores,” PLoS Genetics, vol. 9, no. 3, article e1003348, 2013. View at Publisher · View at Google Scholar · View at Scopus
  26. R Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, 2018, http://www.R-project.org/.
  27. B. Bogin and L. Rios, “Rapid morphological change in living humans: implications for modern human origins,” Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, vol. 136, no. 1, pp. 71–84, 2003. View at Publisher · View at Google Scholar · View at Scopus
  28. G. Su, O. F. Christensen, T. Ostersen, M. Henryon, and M. S. Lund, “Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers,” PLoS One, vol. 7, no. 9, article e45293, 2012. View at Publisher · View at Google Scholar · View at Scopus
  29. P. M. Visscher, J. Yang, and M. E. Goddard, “A commentary on ‘Common SNPs explain a large proportion of the heritability for human height’ by Yang et al. (2010),” Twin Research and Human Genetics, vol. 13, no. 06, pp. 517–524, 2010. View at Publisher · View at Google Scholar · View at Scopus
  30. T. A. Manolio, F. S. Collins, N. J. Cox et al., “Finding the missing heritability of complex diseases,” Nature, vol. 461, no. 7265, pp. 747–753, 2009. View at Publisher · View at Google Scholar · View at Scopus
  31. J. Yang, J. Zeng, M. E. Goddard, N. R. Wray, and P. M. Visscher, “Concepts, estimation and interpretation of SNP-based heritability,” Nature Genetics, vol. 49, no. 9, pp. 1304–1310, 2017. View at Publisher · View at Google Scholar · View at Scopus