Over 400 Gene Regions Influence Height: Study
After looking at about two million common genetic variants, scientists have roughly doubled the number of known gene regions influencing height to more than 400, according to a new study.
Involving more than 300 institutions and more than 250,000 subjects, the study, published in the journal Nature Genetics, not only provides insight into the biology behind height, but also offers a model for investigating traits and diseases caused by many common gene changes at once.
"Height is almost completely determined by genetics, but our earlier studies were only able to explain about 10 percent of this genetic influence," Joel Hirschhorn, co-senior investigator on the study, said 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."
According to researchers from the international Genetic Investigation of Anthropometric Traits (GIANT) Consortium, 697 gene variants (in 424 gene regions) are reportedly related to height - the largest number to date associated with any trait or disease. This allows scientists to explain about 20 percent of the heritability of height, whereas before it was only 12 percent, says co-first author Tonu Esko.
"Many of the genes we identified are likely to be important regulators of skeletal growth, but were not known to be involved until now. Some may also be responsible for unexplained syndromes of abnormal skeletal growth in children. As you increase the sample size, you get more biology," Hirschhorn explained.
Since height is easy to measure, and an estimated 80 percent of variation in height is genetic, it is considered a model trait for understanding how human genetics works.
Previous studies have shown that a large number of genes influence height, particularly ones from common genetic variants and not rare ones. But this new study is the first to draw definitive conclusions, given that greater sample size equals greater statistical power.
Among GIANT's future goals is to look at variants that occur at lower than five percent frequency, and to look for variants in the non-protein-coding portions of genes.