I think it would not be an exaggeration to describe these studies as a resounding disappointment. The first genome-wide association for height, published in September last year, examined 4,921 individuals and found a single significant and replicable variant associated with height (in the HMGA2 gene) that explained a meagre 0.3% of the variation in the general population. The second such scan, published in January this year, examined 6,669 individuals. This study confirmed the HMGA2 finding and identified one further significant signal, this time near the GDF5 and UQCC genes, which again explained less than 0.5% of the total variation. I saw an abstract at the American Society of Human Genetics meeting last year (as yet unpublished, as far as I can tell) in which a genome scan was reported for 10,737 individuals, which pulled out a total of 8 associated variants which together explain just 3% of the variance in height.
To summarise these results: to date genome-wide scans for height, even extremely well-powered ones with more than 10,000 participants, have identified variants responsible for less than 5% of the variation in this trait - despite height being a trait that is largely genetically determined and varies substantially between humans. What's going on?
I'm not sure if anyone really knows the answer to this question, but it's likely that there are a number of factors in play here. One possibility is that many of the genes regulating height may be acting exclusively on one of the separate body components that make up total height - say, leg length, or spine curvature. By looking at total height rather than each of these components separately researchers might be drowning out the signal from such genes, and thus missing important pieces of this curious genetic puzzle.
A new paper in PLoS ONE (open access) tests this possibility directly. The researchers used images from whole body dual energy X-ray absorptiometry (DEXA; see image on left, from here) to measure the lengths of the spine, femur (thigh), tibia (calf), humerus (upper arm) and radius (forearm) on two sets of twins: 1,157 identical and 2,594 non-identical, all of them female. For measuring genetic markers, the group used a low-density set of just 400 microsatellite markers arrayed across the genome rather than the high-density SNP chips used for most modern genome scans.Their first finding was that the different bone lengths they examined in their study were significantly correlated with one another - in other words, if you have a long thigh, it's highly likely that you also have a long forearm. However, these correlations are by no means perfect. Even the tightest association - between calf and thigh length - only had a correlation score of 0.78, meaning that knowledge of thigh length only allows you to predict around 78% of the variance in calf length. For the other bone lengths the correlations were even weaker, particularly between spine length and all of the limb bones (where the tightest correlation was still less than 0.25). That's good, because it means that these measurements are at least partially independent of one another. This is pretty important to know: if all of these components were perfectly correlated with one another, then you wouldn't capture any extra information by looking at each one separately than you would by just looking at height as a whole.
Also promising were the heritability measurements: all of the bone lengths were between 57 and 73% determined by genetic factors. That means that each of these individual components of height are each strongly regulated by genetics, just as height itself is, an important prerequisite for a genome-wide scan to have any chance of success.
After all this promising groundwork, the genome scan itself is pretty perfunctory: only two of the 400 markers they analysed showed any sign of an association with bone lengths, with one "highly suggestive" signal for spine length and one "suggestive" signal for thigh bone length, both on chromosome 5 but in different regions. To be honest, the results of this scan are neither particularly convincing nor useful, so I'm not going to dissect them any further.
The major useful findings from this study are that the independent components of height are both partially independent and highly heritable (i.e. influenced by genetics). That sets the stage for a serious genome-wide analysis of these traits. Essentially, these detailed measurements would need to be repeated in a cohort of unrelated individuals, matched as closely as possible for ancestry, age (age contributed to 11% of the variation in spine length in this study, so it's an important variable to control), and other variables, and including both males and females (as opposed to this study, which analysed only females). Then a genome scan would need to be performed using a much denser marker set: the million or more markers found in modern SNP chips rather than the paltry 400 microsatellites analysed here. Such a study would have a good shot at capturing a more impressive proportion of variation than the less than 5% harvested so far from scans for total height.
Then of course there are the inevitable follow-up studies that I keep going on about in this blog: large-scale sequencing studies to identify rare variants, targeted scans for copy-number variation not picked up by SNP chips, and analyses of heritable epigenetic modifications (chemical changes to DNA that don't affect its sequence). Given that this is a trait where common variants appear to account for only a tiny proportion of the total variation (based on the genome-wide scans decribed above) such studies assume extra importance.
Of course, one could ask why we should even care about the genetics of height - surely resources would be much better spent on disease-related traits? There's some truth to that, but I think height serves as an important model for common human phenotypic variation in general. Variation in height is common and obvious, and we know that this trait is strongly genetic. In the process of unravelling its genetic architecture we will learn important lessons that will apply to other complex traits, including those associated with health and common disease.
Subscribe to Genetic Future.Chinappen-Horsley, U., Blake, G.M., Fogelman, I., Kato, B., Ahmadi, K.R., Spector, T.D., Gibson, G. (2008). Quantitative Trait Loci for Bone Lengths on Chromosome 5 Using Dual Energy X-Ray Absorptiometry Imaging in the Twins UK Cohort. PLoS ONE, 3(3), e1752. DOI: 10.1371/journal.pone.0001752
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