Beyond missing heritability: Prediction of complex traits

Robert Makowsky, Nicholas M. Pajewski, Yann C. Klimentidis, Ana I. Vazquez, Christine W. Duarte, David B. Allison, Gustavo de los Campos

Research output: Contribution to journalArticle

166 Scopus citations

Abstract

Despite rapid advances in genomic technology, our ability to account for phenotypic variation using genetic information remains limited for many traits. This has unfortunately resulted in limited application of genetic data towards preventive and personalized medicine, one of the primary impetuses of genome-wide association studies. Recently, a large proportion of the "missing heritability" for human height was statistically explained by modeling thousands of single nucleotide polymorphisms concurrently. However, it is currently unclear how gains in explained genetic variance will translate to the prediction of yet-to-be observed phenotypes. Using data from the Framingham Heart Study, we explore the genomic prediction of human height in training and validation samples while varying the statistical approach used, the number of SNPs included in the model, the validation scheme, and the number of subjects used to train the model. In our training datasets, we are able to explain a large proportion of the variation in height (h2 up to 0.83, R2 up to 0.96). However, the proportion of variance accounted for in validation samples is much smaller (ranging from 0.15 to 0.36 depending on the degree of familial information used in the training dataset). While such R2 values vastly exceed what has been previously reported using a reduced number of pre-selected markers (<0.10), given the heritability of the trait (~0.80), substantial room for improvement remains.

Original languageEnglish (US)
Article numbere1002051
JournalPLoS genetics
Volume7
Issue number4
DOIs
StatePublished - Apr 2011

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics
  • Genetics(clinical)
  • Cancer Research

Fingerprint Dive into the research topics of 'Beyond missing heritability: Prediction of complex traits'. Together they form a unique fingerprint.

  • Cite this

    Makowsky, R., Pajewski, N. M., Klimentidis, Y. C., Vazquez, A. I., Duarte, C. W., Allison, D. B., & de los Campos, G. (2011). Beyond missing heritability: Prediction of complex traits. PLoS genetics, 7(4), [e1002051]. https://doi.org/10.1371/journal.pgen.1002051