In humans, height is a trait that varies across a huge range of values that can all be considered normal. Even if you exclude those individuals with genetic changes that ensure they will be excessively tall or short, people can undergo normal patterns of growth and still wind up separated by two feet of height when they're done growing. Studies that rely on twins suggest that 90 percent or more of human height is controlled by our genes but, to date, not a single gene had been identified that was actually associated with this trait. An advance release of a Nature Genetics study suggests there is a very good reason for that: individual genes have too small an effect to allow their easy detection.
The study used a population of nearly 5,000 individuals, and scanned their genomes for individual base changes (single nucleotide polymorphisms, or SNPs) that were associated with their height. Very few changes looked even remotely interesting from a statistical perspective. After verification on a different population, only two SNPs in a single gene came through. The gene, HMGA2, turned out to be an excellent candidate for regulating height. Changes in the gene alter body size in animals as diverse as mice and chickens, and a mutation in the gene in a human was identified due to the fact that the child was about 170 cm tall at eight years of age.
Exceptional mutations aside, the real message of the paper is just how mild the typical effect of height variation factors is. Even though this variation in HMGA2 was the strongest factor identified, the authors estimate that it accounts for far less than one percent of typical human variations. Even two copies of the "tall" allele of the gene are estimated to add only 8 mm to a typical person's height.
This, to me, raises some serious questions about how important it is to pursue further studies in this area. This study managed to get its data from an ongoing survey of type 2 diabetics, but still wound up with 21 authors plus two consortia credited. Given that any further work would need even larger study populations to identify other statistically significant SNPs, it's not clear whether performing the statistical analysis of other studies and following up on interesting looking areas will really be worth the effort.
Nature Genetics, 2007. DOI: 10.1038/ng2121