Abstract:
:In this article, we review some of the data that contribute to our understanding of the genetic architecture of psychiatric disorders. These include results from evolutionary modelling (hence no data), the observed recurrence risk to relatives and data from molecular markers. We briefly discuss the common-disease common-variant hypothesis, the success (or otherwise) of genome-wide association studies, the evidence for polygenic variance and the likely success of exome and whole-genome sequencing studies. We conclude that the perceived dichotomy between 'common' and 'rare' variants is not only false, but unhelpful in making progress towards increasing our understanding of the genetic basis of psychiatric disorders. Strong evidence has been accumulated that is consistent with the contribution of many genes to risk of disease, across a wide range of allele frequencies and with a substantial proportion of genetic variation in the population in linkage disequilibrium with single-nucleotide polymorphisms (SNPs) on commercial genotyping arrays. At the same time, most causal variants that segregate in the population are likely to be rare and in total these variants also explain a significant proportion of genetic variation. It is the combination of allele frequency, effect size and functional characteristics that will determine the success of new experimental paradigms such as whole exome/genome sequencing to detect such loci. Empirical results suggest that roughly half the genetic variance is tagged by SNPs on commercial genome-wide chips, but that individual causal variants have a small effect size, on average. We conclude that larger experimental sample sizes are essential to further our understanding of the biology underlying psychiatric disorders.
journal_name
Mol Psychiatryjournal_title
Molecular psychiatryauthors
Visscher PM,Goddard ME,Derks EM,Wray NRdoi
10.1038/mp.2011.65subject
Has Abstractpub_date
2012-05-01 00:00:00pages
474-85issue
5eissn
1359-4184issn
1476-5578pii
mp201165journal_volume
17pub_type
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