Our analysis has found that RGS4
variants exhibit some tentative signals for association with endophenotypes that might be relevant to the pathogenesis of schizophrenia. Common 'risk' alleles of SNP4 and SNP18, the SNPs that have been previously related also to reduced prefrontal cortex volume and function, were associated in the current study with an increase in negative schizotypal personality traits amongst a large population of apparently healthy young male conscripts. Haplotype analysis generally supported this association. An isolated model-specific effect of risk allele A (SNP18) on antisaccade error rate was noted. The SNPs 1 and 7 that were not associated with reduced brain volumes in a previous study [16
] had no effect on cognitive or schizotypy endophenotypes.
Negative schizotypy personality traits in the general population similarly to their illness counterpart (negative symptoms in schizophrenia), are considered to be associated mostly with subtle deficits of prefrontal brain function. This is indicated by the modest but persistent correlation of this schizotypy factor to executive dysfunction and working memory deficits [38
]. If RGS4
variants truly contribute to structural and functional alterations of the prefrontal cortex [16
], the observed association of RGS4
risk variants with negative schizotypy may reflect such an impact on prefrontal function. Furthermore, the dose effect of risk allele A of SNP18 on negative schizotypy and simultaneously on antisaccade error rate (arguably a good index of Dorsolateral Prefrontal Cortex integrity) provides some further support to the notion that RGS4
risk variants are associated with subtle deficits at the information processing level surveyed by the prefrontal cortex. A similar pleiotropic effect of SNP4 on negative psychotic symptoms and tasks dependant on the integrity of prefrontal function (verbal fluency) was also noted in a recent association study [9
] although these associations did not survive multiple comparison testing. On the other hand, we observed no clear effect of RGS4
polymorphisms on 2- Back working memory indices of performance as in a recent study [17
], but nevertheless haplotype analyses offered a soft signal of association with spatial working memory.
variation was associated with negative rather than positive schizotypy. These two factors may have relatively independent neurocognitive [40
] neurochemical [41
] and genetic [42
] underpinnings. Negative symptoms in schizophrenia lay in an etiological continuum with their personality counterpart [44
] and may have greater familiar, neurodevelopmental and possibly genetic basis than positive ones. Interestingly the first emerging association studies which include clinical and neurocognitive outcomes, also suggest associations of SNP4 or SNP18 with PANSS global psychopathology scores [9
], negative PANSS symptoms and simultaneous association with tasks dependent of prefrontal brain function (verbal fluency) and impaired neurodevelopment (premorbid verbal IQ) [9
If RGS4 variation has only modest effects on negative schizotypy endophenotypes, as observed in our study, this may explain the inconsistency of the previous association studies and the lack of a demonstrable strong association with schizophrenia per se, when these studies have been combined in meta-analyses [14
]. Depending on the population mix and the importance that these endophenotypes may play in the disease process, some case-control studies of schizophrenia may show subtle effects with RGS4
variants, while others may show none. Genetic effects on schizophrenia risk may be very small on average and may require thousands of several tens of thousands of subjects to document or refute convincingly [46
]. Conversely, quantitative traits such as these endophenotypes would be possible to study efficiently with relatively smaller sample sizes. Still, the importance of replicating our results in other cohorts cannot be over-emphasize [47
]. Conclusive results are likely to require considerable sample sizes even for these endophenotypes, and in the presence of population or other heterogeneity, consistent replication may be difficult [49
Along these lines, we acknowledge that, several, if not all, of the identified signals in our study might be false positives [50
]. With 4 SNPs and 10 outcome variables, there are 40 sets of analyses performed, even without consideration of haplotypes. However, 2 SNPs were in almost perfect linkage disequilibrium and many of the outcomes also show high correlation with each other. Therefore, the multiplicity of comparisons is far less than implied at first sight. Moreover, our approach was to target variants of a gene that already had some indirect or direct support for involvement in the pathogenesis of schizophrenia and therefore the pre-study probability of significant associations was not negligible as in a hypothesis-free, discovery-oriented approach. Regardless, the interpretation of the modestly significant associations should be conservative. In addition, the Bayes factors obtained for the nominally significant associations are not very strong, but they should not be disregarded, given the prior evidence on potential implication of this genes and variants in related phenotypes.
We should also acknowledge that observed associations may exist due to hitherto unidentified risk variants at RGS4 that are in strong linkage disequilibrium with these four SNPs. All four SNPs in the associated haplotype are non-coding SNPs, but SNPs 1, 4 and 7 are located in a 5' region of the gene that may play a role in transcription regulation.
Another limitation of our study was the considerable rate of non-responders for some items, especially the Schizotypal Personality Questionnaire and the loss of some information due to failure of genotyping in some mouthwash samples. These missing data may have eroded some of the power of the study to detect statistically significant genetic effects. However, there is no reason why genotypes would be missed preferentially in participants with specific phenotypes and indeed we found no hint of such association. Similarly, we found no evidence that phenotype data were missing based on phenotype. Therefore, missing data is unlikely to have generated false-positives.