Background: Much of what we thought we knew about genetics needs to be modified in light of recent discoveries. What are the implications of these advances for identifying genes responsible for the high heritability of many behavioural disorders and dimensions in childhood?
Methods: Although quantitative genetics such as twin studies will continue to yield important findings, nothing will advance the field as much as identifying the specific genes responsible for heritability. Advances in molecular genetics have been driven by technology, especially DNA microarrays the size of a postage stamp that can genotype a million DNA markers simultaneously. DNA microarrays have led to a dramatic shift in research towards genome-wide association (GWA) studies. The ultimate goal of GWA is to sequence each individual's entire genome, which has begun to happen.
Results: GWA studies suggest that for most complex traits and common disorders genetic effects are much smaller than previously considered: The largest effects account for only 1% of the variance of quantitative traits. This finding implies that hundreds of genes are responsible for the heritability of behavioural problems in childhood, and that it will be difficult to identify reliably these genes of small effect. Another discovery with far-reaching implications for future genetic research is the importance of non-coding RNA (DNA transcribed into RNA but not translated into amino acid sequences), which redefines what the word gene means. Non-coding RNA underlines the need for a genome-wide approach that is not limited to the 2% of DNA responsible for specifying the amino acid sequences of proteins.
Conclusions: The only safe prediction is that the fast pace of genetic discoveries will continue and will increasingly affect research in child psychology and psychiatry. DNA microarrays will make it possible to use hundreds of genes to predict genetic risk and to use these sets of genes in top-down behavioural genomic research that explores developmental change and continuity, multivariate heterogeneity and co-morbidity, and gene-environment interaction and correlation. A crucial question is whether the prediction of genetic risk will be sufficiently robust to translate into genetically based diagnoses, personalized treatments, and prevention programmes.