Cognitive function is highly heritable (Devlin et al., 1997), yet we have relatively little understanding of which genes regulate either general intelligence or specific cognitive functions. A long list of mutations can cause the large cognitive impairments that we class as learning disability—including many of the same CNVs associated with cognitive disorders such as autism and schizophrenia (Guilmatre et al., 2009). Prior to the GWAS era, it was generally assumed that normal variation—outside of the range of learning disability—would be regulated by common variants of small effect. Yet GWAS, a technology well suited to detecting common variants of small effect, has not massively increased our understanding of the genetic basis of cognition.

One explanation for this relative lack of success is that, compared with quantitative phenotypes such as height or BMI, the measurement of cognition can be time consuming and therefore costly, so really large-scale studies are rare. Moreover, any two studies are very unlikely to use identical cognitive tests, introducing error to the phenotypic measurement and making it difficult to combine datasets. In this context, the Nithianantharajah paper is a beautiful example of how translational research using relatively simple but neuroscience-led assays can increase our understanding of the genetics of cognition, while avoiding the need for the ever-increasing sample sizes.

In particular, I was impressed by the building up of related but increasingly complex forms of cognition across the rodent tasks, and the use of the closest possible analogues between mouse and human assays. (Disclosure: I am employed by Cambridge Cognition, the suppliers of the CANTAB tests used in the human phenotyping.) Adding to these very careful phenotyping methodologies, the parallel experiment across both mouse and human "knockouts" is a really elegant piece of translational neuroscience.

Like many traits underlying brain function, it is inherently easy to believe that variants that have large effects on cognition would create strong evolutionary advantages or disadvantages. The authors here demonstrate not only that a related family of genes affects multiple aspects of cognitive function, but also that variation in these genes produces different cognitive tendencies in the mouse, including reciprocal effects of variants of Dlg2 and Dlg3, which seem, at least at first pass, to be conserved in human behavior.

There is a lot to digest in this and the companion paper by Ryan et al., but the methodology appears to have been very useful here in understanding cognition, and may provide useful insights for researchers trying to decipher other aspects of the schizophrenia phenotype.

References:

Devlin B, Daniels M, Roeder K (1997). The heritability of IQ. Nature.388(6641):468-71. Abstract

Guilmatre A, Dubourg C, Mosca AL, Legallic S, Goldenberg A, Drouin-Garraud V, Layet V, Rosier A, Briault S, Bonnet-Brilhault F, Laumonnier F, Odent S, Le Vacon G, Joly-Helas G, David V, Bendavid C, Pinoit JM, Henry C, Impallomeni C, Germano E, Tortorella G, Di Rosa G, Barthelemy C, Andres C, Faivre L, Frébourg T, Saugier Veber P, Campion D. (2009). Recurrent rearrangements in synaptic and neurodevelopmental genes and shared biologic pathways in schizophrenia, autism, and mental retardation. Arch Gen Psychiatry;66(9):947-56. Abstract

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