Andreas Meyer-Lindenberg’s group examine the association between a single nucleotide polymorphism (SNP), rs1344706 in gene ZNF804A, recently identified as a risk factor for schizophrenia in a genome-wide association study (GWAS) (O'Donovan et al., 2008) and functional connectivity as measured by fMRI. The attraction of this polymorphism for a study of this kind is twofold. First, statistically speaking it is the most robust SNP association with schizophrenia reported to date. Second, because a single variant shows strong evidence for association, which is not the case for other reported associations, it is possible to specify a priori for the gene in question directional hypotheses in relation to potential neurocognitive correlates. This militates against the generation of false positives through the testing of multiple SNPs and haplotypes which has rendered problematic the interpretation of at least some previous genetic imaging studies (Walters and Owen, 2007). The function of ZNF804A is unknown but the fact that it contains a zinc finger domain suggests that it may be a transcription factor. It is hoped that the characterization of the actions of SNPs identified by GWAS will identify new pathogenic mechanisms of psychosis. One way in which this can be achieved is via approaches such as that taken in this article.

Esslinger et al. report variations in functional connectivity in 115 healthy individuals according to rs1344706 risk variant status. Given the association of ZNF804A with both schizophrenia and bipolar disorder they employed two fMRI tasks thought to be sensitive to altered function in these disorders: the N Back (2back) task is sensitive to deficits of dorsolateral prefrontal cortex (DLPFC) function in schizophrenia and an emotional face-matching task is linked with amygdala function and thought to be relevant to mood disorder. They compared the activity in these regions and functional connectivity (using time-series correlation) between the three rs1344706 genotype groups.

No differences between genotype groups were found for activation, but the authors did identify altered connectivity with the most activated DLPFC locale. Risk-allele carriers were shown to exhibit a lack of uncoupling of activity (increased functional connectivity) between the right DLPFC and left hippocampus during the 2-back task as well as decreased connectivity within right DLPFC and between right and left DLPFC. Risk variant carriers also showed wide ranging increased connectivity between right amygdala and other anatomical regions. The majority of these findings showed a risk allele dose effect.

The increased DLPFC/hippocampus functional connectivity in carriers of the risk allele is potentially the most interesting finding given that Meyer-Lindenberg’s group has previously shown that those with schizophrenia show increased functional connectivity between DLPFC and hippocampus during working memory (Meyer-Lindenberg et al., 2005). Notes of caution in this regard are that 1) the biological, anatomical or functional significance of fMRI determined functional connectivity is yet to be established and 2) other functional connectivity studies in schizophrenia have produced conflicting results Lawrie et al., 2002. Nonetheless, it is interesting that rs1344706 may affect co-ordination of activity between these two brain regions given their seeming importance in psychotic conditions. The significance of these findings to cognitive deficits and other symptom domains needs further investigation particularly as others have postulated dysconnectivity has more relevance to first rank psychotic symptoms (Stephan et al., 2009).

It is likely that genome-wide association approaches will continue to identify genes with unknown neural function and so approaches such as this are likely to be a valuable way of identifying the biological/neural pathways that involve these genes. It is also imperative that as in this study methodology is employed to allow for multiple testing and also that negative findings are reported. We would also suggest caution until these findings are replicated. As well as such approaches in humans, it is also important to investigate the effects of identified variants at other levels of analysis from gene expression to behavioural genetics work. Finally we find it reassuring that GWAS approaches seem to be successful in identifying risk variants whose functions can be investigated using methods such as that taken by Esslinger et al.

References:

O'Donovan MC, Craddock N, Norton N, et al. Identification of loci associated with schizophrenia by genome-wide association and follow-up. Nature Genetics. 2008;40(9):1053-1055. Abstract

Walters JT, Owen MJ. Endophenotypes in psychiatric genetics. Mol Psychiatry. 2007;12(10):886-890. Abstract

Meyer-Lindenberg AS, Olsen RK, Kohn PD, et al. Regionally Specific Disturbance of Dorsolateral Prefrontal-Hippocampal Functional Connectivity in Schizophrenia. Archives of General Psychiatry. 2005;62(4):379-386. Abstract

Lawrie SM, Buechel C, Whalley HC, Frith CD, Friston KJ, Johnstone EC. Reduced frontotemporal functional connectivity in schizophrenia associated with auditory hallucinations. Biological Psychiatry. 2002;51(12):1008-1011. Abstract

Stephan KE, Friston KJ, Frith CD. Dysconnection in Schizophrenia: From Abnormal Synaptic Plasticity to Failures of Self-monitoring. Schizophr Bull. 2009;35(3):509-527. Abstract

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