An international team of researchers, including a number from the University of North Carolina at Chapel Hill schools of medicine and public health, have discovered hundreds of genes that influence human height.
Their findings confirm that the combination of a large number of genes in any given individual, rather than a simple "tall" gene or "short" gene, helps to determine a person's stature. It also points the way to future studies exploring how these genes combine into biological pathways to impact human growth.
"While we haven't explained all of the heritability of height with this study, we have confidence that these genes play a role in height and now can begin to learn about the pathways in which these genes play a role," said study coauthor Karen L. Mohlke, PhD, associate professor of genetics in the UNC School of Medicine.
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"These investigators had once been competing with each other to find height genes, but then realized that the next step was to combine their samples and see what else could be found," said Mohlke. "The competitors became collaborators to achieve a common scientific goal."
Large-scale collaborations like this are awesome: people get less credit in a paper with hundreds of co-authors, but they are part of something worthwhile. Plus, it's nice to see a table of authors' different contributions listed in the supplementary material :)
Nature doi:10.1038/nature09410
Hundreds of variants clustered in genomic loci and biological pathways affect human height
Hana Lango Allen et al.
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2, 3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P less than 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
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