Genes for optimism, dyslexia and obesity and other mythical beasts

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I recently received an email from a company called mygeneprofile: “By discovering your child's inborn talents & personality traits, it can surely provide a great head start to groom your child in the right way… our Inborn Talent Genetic Test has 99.8% accuracy.” I’d registered to receive information from the company having heard they were offering a genetic test for such diverse traits as optimism, composure, intelligence, and dancing (link).

Despite all the efforts of the Human Genome Project, I was not aware of any genetic test that could reliably predict a child’s personality or ability. I was not therefore surprised when my emails asking for evidence went unanswered, though I continue to receive messages that oscillate between carrots (free gifts! discounts!!) and sticks (without this test “your child will have MISERABLE life (sic))”.

The test company relies on a widespread assumption that people’s psychological attributes are predictable from their genes. So where does this belief come from, and why is it wrong? 

People’s understanding of genetic effects is heavily influenced by the way genetics is taught in schools. Mendel and his wrinkly and smooth peas make a nice introduction to genetic transmission, but the downside is that we go away with the idea that genes have an all-or-none effect on a binary trait.  Some characteristics are inherited this way (more or less), and they tend to be the ones that textbooks focus on: e.g., eye colour, colour-blindness, Huntington’s disease. But most genetic effects are far more subtle and complex than this. Take height, for instance. Genes are important in determining how tall you are, but this is not down to one gene: instead, there is a whole host of genes, each of which nudges height up or down by a small amount (see link).

The expression of a gene may also depend crucially on the environment; for instance, obesity relates both to calorie intake and genetic predisposition, but the effects are not just additive: some people can eat a great deal without gaining weight, whereas in others, body mass depends substantially on food intake (see link). Furthermore, a genetic predisposition to obesity can be counteracted by exercise (see link).Furthermore, genetic influences may interact in complicated ways.  For instance, coat colour in mice is affected by combinations of genes, so that one cannot predict whether a mouse is black, white or agouti (mouse coloured!) just by knowledge of status of one gene.

This means that we get a very different impression of strength of genetic influences on a trait if we look at the impact of a person’s whole genome, compared to looking at individual genes in isolation. The twin study was the traditional method for estimating genetic influences before we had the technology to study genes directly, and it compares how far people’s similarity on a trait depends on their genetic relationship. Researchers measure a trait, such as sensation-seeking, in identical and fraternal twin pairs growing up in the same environment and consider whether the two twin types are equally similar. If both sets of twins resemble each other equally strongly, this indicates that the environment, rather than genes, is critical. And if twins don’t resemble one another at all, this could mean either that the trait is influenced by child-specific experiences, not shared by the co-twin, or that our measure of sensation-seeking is unreliable.  But if identical twins are more similar than fraternal twins, this means genes affect the trait, i.e. it is heritable. There are several niggly criticisms of the twin method; for instance, it can give misleading estimates if identical twins are treated more similarly than fraternal twins, or if twinning itself influences the trait in question. For most traits, however, these don’t seem sufficient to explain away the substantial heritability estimates that are found for traits such as height, reading ability, and sensation-seeking.  But these estimates don’t tell us about the individual genes that influence a trait – they rather indicate how important genes are relative to non-genetic influences.

Interactive effects, either between multiple genes or between genes and environments, will not be detected in a conventional twin study analysis. If a gene is expressed only in a particular environment, twins who have the same version of the gene will usually also have the same environment, and so the expression of the gene will be the same for both. And for an effect that depends on having a particular combination of genes, identical twins will have the same constellation of genetic variants, whereas the likelihood of fraternal twins having an identical gene profile decreases with the number of genes involved.  Heritability estimates depend on comparing similarity of a trait for identical vs fraternal twins, and will be increased if gene-gene interactions are involved.

In contrast,  genome-wide association studies are designed to find individual genes that influence specific traits. They adopt the strategy of looking for associations between DNA variants (alleles) and the trait, either by categorising people, e.g. as dyslexic or not, and comparing the proportions with different alleles, or by seeing whether people who have zero, one or two copies of an allele differ in their average score on a trait such as reading ability.  When these studies started out, many people assumed we would find gene variants that exerted a big effect, and so might reasonably be termed ‘the gene for” dyslexia, optimism, and so on.  However, this has not been the case.

Take personality, for instance, one of the domains that mygeneprofile claims to test for. A few weeks ago, a major study was reported in which  the genes of over 5000 people were investigated but no significant associations were found. Commentators on the research argued that the measurement of personality – typically on the basis of self-report questionnaires - may be the problem.  But the self-same measures yield high estimates of heritability when used in twin studies.  And a similar pattern has been found for other traits: including height, intelligence and obesity, i.e., a mismatch in evidence of genetic influence from twin studies (typically moderate to strong for these traits) and findings of individual genes associated with the trait (with effects that are very small at best). 

This account may surprise readers who have read of recent discoveries of genes for conditions such as dyslexia, where the impression is sometimes given that there are strong effects.  The reason is that reports of molecular genetic studies usually emphasise the p-value, a measure of how probable it is that a result could have arisen by chance. A low p-value indicates that a result is reliable, but it does not mean the effect is large. These studies typically use very large samples precisely because this allows them detect even small effects.  Consider one of the more reliable associations between genes and behaviour: a gene known as KIAA0319 which has been found to relate to reading ability in several different samples. In one study, an overall association was reported with p = .0001, indicating that the likelihood of the association being a fluke is 1 in 10,000. However, this reflected the fact that one gene variant was found in 39% of normal readers and only 25% of dyslexics, with a different variant being seen in 30% of controls and 35% of dyslexics. Some commentators have argued that such small effects are uninteresting.  I disagree: findings like this can pave the way for studies into the neurobiological effects of the gene on brain development (see link), and for studies of gene-gene and gene-environment interactions.  But it does mean that talk of a ‘gene for dyslexia’, or genetic screening for personality or ability are seriously misguided.

The small effect size of individual genes, and interactions with environment or other genes,  are not the only explanations for “missing heritability”. A trait may be influenced by genetic variants that have a large effect but which are individually very rare in the population. These would be very hard to detect using current methods. The role of so-called copy number variants is also a focus of current interest: these are large chunks of DNA which are replicated or deleted and which are surprisingly common in all of us.  These lead to an increase or decrease in gene product, but won’t be found with standard methods that focus just on identifying the DNA sequence. Both mechanisms are thought to be important in the genetics of autism, which is increasingly looking like a highly heterogeneous condition – i.e. there are multiple genetic risk factors and different ones are important in different people. 

What are the implications of all of this for the stories we hear in the media about new genetic discoveries?  The main message is we need to be aware of the small effect of most individual genes on human traits. The idea that we can test for a single gene that causes musical talent, optimism or intelligence is just plain wrong. Even where reliable associations are found, they don’t correspond to the kind of major influences that we learned about in school biology. And we need to realise that twin studies, which consider the total effect of a person’s genetic makeup on a trait, can give different results from molecular studies of individual genes. What makes us individual can’t be reduced to the net effect of a few individual genes.

Background reading

Bishop, D. V. M. (2009). Genes, cognition and communication: insights from neurodevelopmental disorders. The Year in Cognitive Neuroscience: Annals of the New York Academy of Sciences, 1156, 1-18.

Maher, B. (2008). Personal genomes: The case of the missing heritability. Nature, 456, 18-21 doi:10.1038/456018a.

Plomin, R., DeFries, J. C., McClearn, G. E.,  McGuffin, P. (2008). Behavioral Genetics. (5th Edition). New York: Worth Publishers.

Rutter, M. (2006). Genes and Behavior: Nature-Nurture Interplay Explained. Oxford: Blackwell.

Note: this is a slightly extended version of a blog on Guardian Science Blog, 9/9/10