Editors' ChoiceHuman Genetics

Rediscovering Heritability

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Science Translational Medicine  18 May 2011:
Vol. 3, Issue 83, pp. 83ec73
DOI: 10.1126/scitranslmed.3002639

In genetic epidemiology, the puzzle of missing heritability is centered on the failure of large genome-wide association studies (GWASs) to identify genetic variations (single-nucleotide polymorphisms, or SNPs) that fully explain inherited traits such as height. Height is estimated to be 80 to 90% heritable, but common SNPs discovered through GWASs seem to account for only 10% of the variance in height. GWASs focus on identifying common SNPs associated with phenotypes, and the missing heritability has been posited to reside in rare variants, epigenetic mechanisms, and gene-environment interactions. However, in a new study, Yang et al. demonstrate that common SNPs hold more explanatory power for heritability than standard GWASs have revealed so far. This news may compel those who study complex diseases that involve multiple genes—for example, cardiovascular disease and diabetes—to re-examine GWASs to gain further insights into where disease-causing mutations may lie in the human genome.

Most GWASs involve testing hundreds of thousands of SNPs across the whole genome to identify individual SNPs associated with the phenotype of interest. High thresholds for statistical significance (typically, P < 5 × 10–8) are used to avoid false positive findings. Now, Yang et al. take a different approach. They analyze the same data used to identify SNPs associated with height, body mass index (BMI), von Willebrand factor, and the QT interval (a measure of cardiac conduction) in previous GWASs, but they look within each chromosome for the collective ability of SNPs to explain variance in these traits. In a sample of 11,586 unrelated individuals, they found that the half million SNPs genotyped explained 45% of the variance in height—far more than the 10% explained by only those SNPs that were highly statistically significant. Furthermore, chromosome length and proximity to a known gene were positively correlated with the proportion of variance explained (45% in the case of height). GWASs depend on the (imperfect) ability of common SNPs to signal nearby neighboring regions that contain causal genetic mutations. Therefore, gaps in our understanding of what regulates the heritability of traits may yet be filled by research into both common and rare variants and other mechanisms of genetic control. The approach of Yang et al. can be extended to identify ever-narrower chromosomal regions that are important not only for the heritability of traits such as height and body mass index, but also for the inheritance of complex diseases such as heart disease and diabetes.

J. Yang et al., Genome partitioning of genetic variation for complex traits using common SNPs. Nat. Genet. 8 May 2011 (10.1038/ng.823). [Abstract]

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