I've discussed why this kind of thing is problematic in a previous blogpost, but perhaps a figure will help. The point is that in a large sample you can have a statistically strong association between a condition such as dyslexia and a genetic variant, but this does not mean that you can predict who will be dyslexic from their genes.
Proportions with risk variants estimated from Scerri et al (2011) |
In this example, based on one of the best-replicated associations in the literature, you can see that most people with dyslexia don't have the risk version of the gene, and most people with the risk version of the gene don't have dyslexia. The effect sizes of individual genetic variants can be very small even when the strength of genetic association is large.
So what about the results from the latest Yale press release? Do they allow for more accurate identification of dyslexia on the basis of genes? In a word, no. I was pleased to see that the authors reported the effect sizes associated with the key genetic variants, which makes it relatively easy to estimate their usefulness in screening. In addition to identifying two sequences in DCDC2 associated with risk of language or reading problems, the authors noted an interaction with a risk version of another gene, KIAA0319, such that children with risk versions in both genes were particularly likely to have problems. The relevant figure is shown here.
Fig 3A from Powers et al (2013) |
There are several points to note from this plot, bearing in mind that dyslexia or SLI would normally only be diagnosed if a child's reading or language scores were at least 1.0 SD below average.
- For children who have either KIAA0319 or DCDC2 risk variants, but not both, the average score on reading and language measures is at most 0.1 SD below average.
- For those who have both risk factors together, some tests give scores that are 0.3 SD below average, but this is only a subset of the reading/language measures. On nonword reading, often used as a diagnostic test for dyslexia, there is no evidence of any deficit in those with both risk versions of the genes. On the two language measures, the deficit hovers around 0.15 SD below the mean.
- The tests that show the largest deficits in those with two risk factors are measures of IQ rather than reading or language. Even here, the degree of impairment in those with two risk factors together indicates that the majority of children with this genotype would not fall in the impaired range.
- The number of children with the two risk factors together is very small, around 1% of the population.
In sum, I think this is an interesting paper that might help us discover more about how genetic variation works to influence cognitive development by affecting brain function. The authors present the data in a way that allows us to appraise the clinical significance of the findings quite easily. However, the results indicate that, far from indicating translational potential for diagnosis and treatment, genetic effects are subtle and unlikely to be useful for this purpose.
*It is unclear to me whether the Yale University Press Office are actively involved in gatecrashing Research Blogging, or whether this is just an independent 'blogger' who is recycling press releases as if they are blogposts.
Reference
Powers, N., Eicher, J., Butter, F., Kong, Y., Miller, L., Ring, S., Mann, M., & Gruen, J. (2013). Alleles of a Polymorphic ETV6 Binding Site in DCDC2 Confer Risk of Reading and Language Impairment The American Journal of Human Genetics DOI: 10.1016/j.ajhg.2013.05.008
Scerri, T. S., Morris, A. P., Buckingham, L. L., Newbury, D. F., Miller, L. L., Monaco, A. P., . . . Paracchini, S. (2011). DCDC2, KIAA0319 and CMIP are associated with reading-related traits. Biological Psychiatry, 70, 237-245. doi: 10.1016/j.biopsych.2011.02.005
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