NEW YORK (GenomeWeb) – The international Genetic Investigation of Anthropometric Traits Consortium has linked additional gene regions to variations in human height, bringing the total number of regions associated with the trait to more than 400.
By drawing on genome-wide data from more than a quarter of a million people, the GIANT consortium identified nearly 700 variants that reached significance, as it reported yesterday in Nature Genetics. The team further estimated that the SNPs they homed in on can explain some 36 percent of the heritability of height.
"Height is almost completely determined by genetics, but our earlier studies were only able to explain about 10 percent of this genetic influence," said the Broad Institute's Joel Hirschhorn, who led the GIANT Consortium, in a statement. "Now, by doubling the number of people in our study, we have a much more complete picture of how common genetic variants affect height — how many of them there are and how much they contribute."
Previous studies have linked 180 or so loci to height, but common variants at those loci could only explain about 12 percent of the heritability of height, or about 10 percent of the phenotypic variation, the researchers said.
To search for additional variants, Hirschhorn and the GIANT consortium performed a genome-wide association study meta-analysis that took in data from 79 studies and included 253,288 people of European descent. From this, they uncovered 697 SNPs clustered in 423 loci that reached genome-wide significance.
Though the polygenic nature of height appeared to inflate the test statistics the researchers saw, they concluded that most of the loci uncovered represent true associations.
Through a series of analyses that relied on within-family predictions and data from five additional studies, the researchers reported that the most strongly associated 2,000 SNPs could explain some 21 percent of phenotypic variation while the most strongly associated 9,500 SNPs could capture about 29 percent of phenotypic variance. Together, all common variants captured 60 percent of heritability.
"The results are consistent with a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants, located throughout the genome but clustered in both a biological and genomic manner," the researchers wrote.
The consortium turned to two gene prioritization approaches, called MAGENTA and GRAIL, and linked the SNPs they uncovered to gene regions known involved in height as well as to regions not previously associated with the trait.
By folding in results from DEPICT, a novel integrative method that not only prioritizes genes and gene sets, but also identifies tissues where those genes are highly expressed, the team confirmed and built on the MAGENTA and GRAIL findings.
Among those top prioritized genes with links to relevant pathways were GLI1 and LAMA5, which are linked to Hedgehog signaling; FRS2, which is involved in FGF signaling; and MTOR, which is involved in TGF and mTOR signaling.
Other genes highlighted by DEPICT — such as FAM101A, GLT8D2, and ARSJ — have no clear link yet to skeletal growth and may, the researchers said, represent biology left to learn.
"When you double the sample size and increase your statistical power, you can make new discoveries," Hirschhorn said. "Our results prioritize many genes and pathways as important in skeletal growth during childhood."
Indeed, they noted that CHSY1, which came in at the second spot on their list of prioritized genes, was unknown when they made their list, but mutations in it have since been linked to a syndrome marked by short stature and brachydactyly.
He and his colleagues also argued that, in light of their findings, results from large GWAS will remain relevant as sample sizes increase because they can elucidate biologically relevant information and help prioritize genes and pathways.
"As you increase the sample size, you get more biology," Hirschhorn added.