Genetic analyses of complex diseases are fraught with challenges because we often know so little about how to control for the genetic and environmental sources of heterogeneity. For this reason, when studies attempting to replicate initial associations of complex disorders produce different results, it is difficult to interpret their significance. Recently, a number of candidates for schizophrenia susceptibility genes have emerged from the analyses of linkage-defined positional candidates, some of which have been motivated by other biological information such as gene expression. In addition, there have been studies replicating these initial findings, in a sense, but the interpretation of these results is often obscure. In fact, most often neither the associated alleles nor the associated haplotypes are consistent across these studies (Shirts and Nimgaonkar 2004
). Here, we investigate the results for one of the genes recently described as a positional and functional SCZ susceptibility candidate, RGS4
. Unlike many of the other candidates, RGS4
is a relatively small gene in which patterns of LD have been investigated and associations reported for a limited number of SNPs. Yet, like the other candidates, studies of the association between SCZ and RGS4
alleles and haplotypes have been plagued by inconsistency. In this report, we performed meta-analysis in an attempt to understand these inconsistencies.
Our goal was to elicit greater evidence for, or against, RGS4 as a gene containing variations affecting susceptibility to SCZ. Moreover, if the evidence was positive, then we hoped the analyses would elucidate exactly what factors generate susceptibility. Our results are compatible with at least two risk variants conferring susceptibility to SCZ, specifically both the common haplotypes of the four alleles in which associations have been previously reported at this gene.
Our family-based analyses detected significant transmission distortion incorporating all haplotypes. These observations were made using two different software programs, making it unlikely that they are due to idiosyncrasies in analytic software. The results could also not be attributed to deviations from Hardy-Weinberg Equilibrium in the parent population. We scrutinized these results and conducted additional analyses, all of which suggest that overtransmission of both of the two most common haplotypes appears to be the most parsimonious explanation for the results of the global tests.
Evaluation of the distribution of test statistics from individual samples also supported family-based associations, even after the most significant sample was excluded. These analyses would be particularly persuasive if consistent deviations from expected distributions were detected across multiple studies, rather than being attributable to few studies with large effect sizes. Indeed, inspection of transmission distortions at each sample revealed modest deviations from expectations in the global tests for most samples ().
Case-control analyses appear to support this conclusion. No individual risk haplotype was detected in cladistic analyses or assessment of the pooled Caucasian sample. Instead, the distribution of test statistics suggested associations with global haplotype tests across samples. If transmission to affected offspring was biased toward the two most common haplotypes, one would expect to detect this effect in a sufficiently powered case-control sample. We investigated this hypothesis in the Caucasian sample. Our results showed nonsignificant patterns similar to those of the family-based analyses of association with both common haplotypes compared with all other haplotypes. However, the differences between case and control haplotype frequencies were relatively small (<2%).
Collectively, our analyses point toward a modest association resulting from overtransmission of both of the common haplotypes to SCZ cases at the expense of other haplotypes. There are a number of possible explanations for the observed results, including biological, statistical, molecular, and population phenomena.
Is there a biologically plausible explanation why two common haplotypes, accounting for greater than 80% of all haplotypes, are overtransmitted to individuals with SCZ? Arguably, the simplest explanation is that the liability locus or loci remain undetected and are found more commonly (or exclusively) on these two haplotypes. Certainly recurrent mutations or recombinations that transfer liability alleles between haplotypes are likely to involve these common haplotypes. Our results could account for at least two different possibilities in such a scenario: allelic (intragenic) heterogeneity or the contribution of multiple individual loci to susceptibility. Similar results could also be obtained by the presence of a single, rare susceptibility variant occurring against the background of both common haplotypes. Evaluation of these explanations would require comprehensive sequencing through RGS4
and its surrounding regions in many individuals. The nebulous nature of what constitute the important elements for expression of RGS4
complicates this analysis. On the other hand, expression assays using RGS4
alleles and haplotypes are reasonably straightforward and of interest in light of past analyses (Mirnics et al 2001
; Erdely et al 2004
It is also possible, although more difficult to defend, that the haplotypes themselves have an impact on SCZ susceptibility. Notably, SNPs 1, 4, and 7 lay within the 5′ upstream region of the gene, and the haplotypes investigated here span the first exon of RGS4. The potential effect of these, or unknown variants as discussed above, on promoter activity and/or transcription is intriguing, given our results. The significance of our findings could also be rooted in phenotypic subgroups for which RGS4 may modulate expression of the disease phenotype. Seeking clinical subfeatures that may be significantly impacted by functional changes related to RGS4 could provide insight into the biological role of this gene on SCZ susceptibility.
Statistical phenomena may also contribute to our findings. One of the curious observations from the past studies of RGS4
is that one common haplotype would appear to be overtransmitted in one sample and yet the other common haplotype would appear to be overtransmitted in the next sample tested. Is this phenomenon compatible with our results, which suggest that both common haplotypes are overtransmitted? Recent simulation studies suggest that even when the liability locus is amongst the loci tested within a gene, the liability locus often does not produce the maximum test statistic (Roeder et al 2005
). Instead, other loci in substantial LD with the liability locus yield the maximum test statistic. Moreover, haplotype analyses carry similar challenges, as simulations have shown that in the presence of a liability haplotype, multiple patterns of haplotype associations can be found (Seltman et al 2001
). Seltman et al (2001)
concluded that in many instances, cladograms and measured haplotype analyses, such as those conducted herein, can provide greater insight into what haplotype bears risk alleles. However, if the scenario revealed by our analyses is, in fact, true, then cladistic analyses are unlikely to yield much insight.
By our analysis plan, we first performed global tests of association using bootstrap testing and permutation tests; if these tests were significant, we then would explore the data to determine what was generating the significant findings. In fact, our global tests were significant, and our conclusions are based on our subsequent exploratory analyses. It is noteworthy, however, that even if we were to correct for our exploratory analyses by a conservative Bonferroni-type correction for the number of SNPs (4), common haplotypes (6), and study designs tested (2, family-based and case-control), our results would still exceed the significance threshold (p < .001) for significant transmission distortion.
It is possible that the overtransmission of the two common haplotypes results from technical issues of little interest to the genetics of SCZ, such as population heterogeneity or molecular analysis. Due to the use of transmission tests, confounding due to population heterogeneity is of little concern. We conducted analyses to assess population heterogeneity in our case-control sample, and our results suggest heterogeneity is relatively minor across samples of European ancestry. However, technical molecular issues could explain the result. Due to the retrospective nature of the analyses, uniform quality control in genotyping measures could not be imposed. Notably, we scrutinized quality control and found that rigorous checks were used in genotyping assays. Still, it is well known that genotyping errors can mimic biased transmissions (see Gordon et al 1999
; Mitchell et al 2003
for review), and that bias is most likely to present itself as the overtransmission of common alleles/haplotypes. Countering this concern, somewhat, are shared observations: case-control analyses suggest similar overrepresentation of common haplotypes in SCZ cases, and rarer haplotypes showed similar frequencies in the singleton cases that could not be evaluated for Mendelian transmission (or in the control samples) than in the family-based probands that did have Mendelian checks. Still, potential confounds due to assay variation could impact on our results and warrant consideration.
In summary, we report a meta-analysis of RGS4 polymorphisms with schizophrenia. Genotype data from 13,807 individuals were analyzed collaboratively by 13 independent groups. To our knowledge, this is the largest such study to date in SCZ research. Future studies may require sequencing across the risk haplotypes in a large number of patients. Similar methodology to that presented here may help resolve some of the other controversial associations reported for psychiatric and nonpsychiatric genetically complex disorders.