| Title: | Will Big Data Close the Missing Heritability Gap? |
| Journal: | Genetics |
| Published: | 11 Sep 2017 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/28893854/ |
| DOI: | https://doi.org/10.1534/genetics.117.300271 |
| URL: | https://www.genetics.org/content/genetics/207/3/1135.full.pdf |
| Citations: | 71 (10 in last 2 years) as of 8 Aug 2024 |
Publication 8482
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Despite the important discoveries reported by genome-wide association (GWA) studies, for most traits and diseases the prediction R-squared (R-sq.) achieved with genetic scores remains considerably lower than the trait heritability. Modern biobanks will soon deliver unprecedentedly large biomedical data sets: Will the advent of big data close the gap between the trait heritability and the proportion of variance that can be explained by a genomic predictor? We addressed this question using Bayesian methods and a data analysis approach that produces a surface response relating prediction R-sq. with sample size and model complexity (e.g., number of SNPs). We applied the methodology to data from the interim release of the UK Biobank. Focusing on human height as a model trait and using 80,000 records for model training, we achieved a prediction R-sq. in testing (n = 22,221) of 0.24 (95% C.I.: 0.23-0.25). Our estimates show that prediction R-sq. increases with sample size, reaching an estimated plateau at values that ranged from 0.1 to 0.37 for models using 500 and 50,000 (GWA-selected) SNPs, respectively. Soon much larger data sets will become available. Using the estimated surface response, we forecast that larger sample sizes will lead to further improvements in prediction R-sq. We conclude that big data will lead to a substantial reduction of the gap between trait heritability and the proportion of interindividual differences that can be explained with a genomic predictor. However, even with the power of big data, for complex traits we anticipate that the gap between prediction R-sq. and trait heritability will not be fully closed.</p>
5 Authors
- Hwasoon Kim
- Alexander Grueneberg
- Ana I Vazquez
- Stephen Hsu
- Gustavo de los Campos
Enabling scientific discoveries that improve human health