The bipolar disorder risk allele at CACNA1C also confers risk of recurrent major depression and of schizophrenia View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-10

AUTHORS

E K Green, D Grozeva, I Jones, L Jones, G Kirov, S Caesar, K Gordon-Smith, C Fraser, L Forty, E Russell, M L Hamshere, V Moskvina, I Nikolov, A Farmer, P McGuffin, , P A Holmans, M J Owen, M C O'Donovan, N Craddock

ABSTRACT

Molecular genetic analysis offers opportunities to advance our understanding of the nosological relationship between psychiatric diagnostic categories in general, and the mood and psychotic disorders in particular. Strong evidence (P=7.0 × 10(-7)) of association at the polymorphism rs1006737 (within CACNA1C, the gene encoding the α-1C subunit of the L-type voltage-gated calcium channel) with the risk of bipolar disorder (BD) has recently been reported in a meta-analysis of three genome-wide association studies of BD, including our BD sample (N=1868) studied within the Wellcome Trust Case Control Consortium. Here, we have used our UK case samples of recurrent major depression (N=1196) and schizophrenia (N=479) and UK non-psychiatric comparison groups (N=15316) to examine the spectrum of phenotypic effect of the bipolar risk allele at rs1006737. We found that the risk allele conferred increased risk for schizophrenia (P=0.034) and recurrent major depression (P=0.013) with similar effect sizes to those previously observed in BD (allelic odds ratio ∼1.15). Our findings are evidence of some degree of overlap in the biological underpinnings of susceptibility to mental illness across the clinical spectrum of mood and psychotic disorders, and show that at least some loci can have a relatively general effect on susceptibility to diagnostic categories, as currently defined. Our findings will contribute to a better understanding of the pathogenesis of major psychiatric illness, and such knowledge should be useful in providing an etiological rationale for shaping psychiatric nosology, which is currently reliant entirely on descriptive clinical data. More... »

PAGES

1016

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/mp.2009.49

DOI

http://dx.doi.org/10.1038/mp.2009.49

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1043020826

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/19621016


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