Variation in regulator of G-protein signaling 17 gene (RGS17) is associated with multiple substance dependence diagnoses

Substance (alcohol or drug) dependence (SD) is a set of complex disorders influenced by gene-gene and gene-environment interactions. Genes involved in dopaminergic, serotonergic, GABAergic, glutamatergic, cannabinoid, and opioidergic systems have been implicated in SD risk. Mounting evidence suggests that variation in genes coding for dopamine, serotonin, GABA, glutamate, cannabinoid, and opioid receptors may increase vulnerability to SD and related phenotypes [1–4]. The function of these receptors, which belong to a large G protein-coupled receptor (GPCR) family, is regulated by regulators of G-protein signaling proteins (RGSs) [5, 6].

Members of the RGS family are functionally related to selective GPCR signal transduction pathways [7]. For example, they participate in opioid receptor desensitization, internalization, recycling and degradation [8, 9]. In analyzing the function of RGS17 in mouse brain, Garzon et al.[10] found that, when RGS17 expression was reduced, the μ-opioid receptor (MOR)-mediated antinociceptive response to morphine and d-Ala²N-MePhe⁴, Gly-ol⁵-enkephalin (DAMGO) was increased. Ajit et al.[11] demonstrated that RGS17 interacted with protein kinase C interacting protein (PKCI-1) and modulated the signaling pathway of the MOR. Moreover, in membranes from periaqueductal gray matter (PAG), both RGS17 and RGS20 co-precipitated with the MOR [10]. By use of intraventricular administration of antisense oligonucleotides, Garzon et al.[12] demonstrated that a suppression of RGS20 expression in mouse brain greatly increased the supraspinal antinociceptive effect of the MOR agonists. Together, these findings indicate that GPCRs (e.g., MOR) are functionally linked to RGS proteins (e.g., RGS17 and RGS20).

RGS 17 and RGS20 are two members of the RGS-Rz subfamily. They are closely related to opioid receptors in both chromosomal location and cellular function. The RGS17 gene (RGS17) is linked to the μ-opioid receptor (MOR) gene (OPRM1) on chromosome 6 (distance: about 0.9 Mb), and the RGS20 gene (RGS20) is linked to the κ-opioid receptor (KOR) gene (OPRK1) on chromosome 8 (distance: about 0.6 Mb) [6]. Close genomic proximity may reflect a coordinated transcription of the linked genes or a shared regulatory mechanism for their expression [9]. In other words, the transcription of RSG 17 (or RGS20) may influence the transcription of OPRM1 (or OPRK1) and vice versa. Genomic proximity may also reflect a functional relationship between the RGS-Rz proteins (RGS17 and RGS20) and opioid receptors.

Several studies, including ours, have shown a positive association between variation at OPRM1[13–17] and OPRK1[18, 19] and alcohol or drug dependence, although negative results have been reported [20]. Additionally, mouse genome scans have mapped a quantitative trait locus (QTL) for morphine preference to the μ-opioid receptor gene region (where RGS17 is located) [21] and a QTL for alcohol consumption to the κ-opioid receptor gene region (where RGS20 is located) [22]. Considering the close relationship between the RGS-Rz proteins and opioid receptors, and the association between opioid receptor genes and alcohol or drug dependence, we hypothesized that variation in RGS17 and RGS20 could affect vulnerability to various SD types. To date, no published studies have examined the association between RGS17 and RGS20 polymorphisms and SD or other psychiatric disorders, although associations between RGS2 variants and anxiety [23, 24] and between RGS4 variants and schizophrenia [25, 26] have been reported. We used a case–control association study approach to analyze the association of RGS17 and RGS20 variants and risk for four different SD diagnoses. We also examined the correlation between genotypes of SD-associated variants and gene expression levels.

RGS17 (RGS-Z2) and RGS20 (RGS-Z1) are two members of the RGS-Rz subfamily of GTPase-activating proteins (GAP) that efficiently deactivate GalphazGTP subunits, and thereby turn off the signaling pathway of G protein-coupled receptors (GPCRs), including opioid receptors. Considering their intimate interactions with opioid receptors (mainly the mu-receptor) and their gene locations (RGS17 is in the vicinity of OPRM1 and RGS20 is in the vicinity of OPRK1), the two genes (RGS17 and RGS20) encoding them are both positional and functional susceptibility candidate loci for SD. We found that multiple RGS17 SNPs were associated with multiple SD phenotypes in both AAs and EAs. However, none of the eight RGS20 SNPs were associated with any of the four dependence traits.

Although variation in RGS17 influences susceptibility to multiple dependence traits in both AAs and EAs, our results suggest that different mechanisms may be operative in some cases. SNPs rs596359 (in the promoter region) and rs6931160 (in intron 1) were associated with at least one of the four dependence traits in both populations. SNPs rs9397585, rs1933258 and rs9371276, which are all located in intron 1 and the same haplotype block (Block II) (Figure 2), were associated with one of the four dependence traits only in EAs. SNPs rs516557 (in intron 2) and rs545323 (in intron 4) were associated with one of the four dependence traits in only AAs (Table 3). Analyses of haplotypes harboring these SNPs supported the individual SNP findings. Haplotypes GATTC and GTTCT, containing alleles (underlined) of SNP rs545323 (Figure 2, haplotype Block I) were associated with OD and MjD, respectively, only in AAs, after permutation tests to correct for multiple comparisons. Haplotype CCC C, containing alleles (underlined) of the three SNPs (rs9397585, rs1933258 and rs9371276) located in intron 1 and haplotype Block II (Figure 2) was associated with OD only in EAs, after permutation tests to correct for multiple comparisons. These findings suggest that the population-specific associations were dependent on the location of variants in RGS17.

The most statistically significant result was obtained for SNP rs596359, which is located in the promoter region of RGS17. Chi-square tests, logistic regression analyses, and permutation tests all showed a positive association between SNP rs596359 and all four SD phenotypes in both populations (Table 3). Further, meta-analyses that combined data from both AAs and EAs showed that SNP rs596359 yielded an odds ratio from 1.28 to 1.33 for risk of all four SD traits (data not shown). Specifically, the G allele of SNP rs596359 was significantly more frequent in cases than in controls in both populations (Additional file 1: Tables S1 and S2). Thus, this promoter variant may increase the risk for SD by influencing RGS17 transcription. To validate the functional effect of this promoter variant on RGS17 transcription, we analyzed the correlation of rs596359 genotypes and RGS17 mRNA expression levels in lymphoblastoid cell lines from both CEU and YRI subjects recruited for the HapMap project (http://hapmap.ncbi.nlm.nih.gov/). The G allele of SNP rs596359 showed a dose-related decrease in RGS17 transcription by decreasing mRNA expression levels (Figure 3). Moreover, bioinformatic analyses indicated that substitution of the A allele for the G allele at rs596359 site generated a transcription binding site in the promoter region of RGS17 for transcription factor AML1a. This transcription factor has a higher affinity for DNA-binding than AML1b, but lacks the putative transcriptional activation domain that is possessed by AML1b. Thus, AML1a dominantly suppresses the transcriptional activity exerted by AML1b [36]. Several other studies have demonstrated that AML1a inhibited erythroid or granulocytic differentiation [37, 38]. Based on these findings, we would speculate that rs596359 G allele carriers have lower RGS17 activity and thus greater synaptic neurotransmission and rewarding function mediated by GPCRs such as opioid receptors. To test this hypothesis, the influence of SNP rs596359 on RGS17 promoter activity should be measured using other approaches (e.g., luciferase reporter gene assays).

None of the eight RGS20 SNPs showed significant association with any of the four SD phenotypes in either AAs or EAs. There are three possible explanations for this lack of association. First, the RGS20 SNPs selected for this study may have a minor or undetectable effect on SD. Fine-mapping of this gene could identify variants showing a stronger association with SD traits. Second, RGS20 may have a weak effect on susceptibility to SD due to its being physically linked to OPRK1, which has a less important role than OPRM1 (which is physically linked to RGS17) in mediating the rewarding effects of alcohol or drugs [17, 19]. Third, similar to OPRK1, which mediates the psychotomimetic effects of some drugs [39], RGS20 may mainly regulate other biological activities than SD. Further studies are warranted to determine whether RGS20 is a susceptibility gene for SD.

The present study has several limitations. First, our finding is limited by the relatively small size of the control sample. Moreover, we did not control for prior genotyping performed on this sample in multiple testing corrections because we were concerned that overly conservative results might be obtained. Second, SD frequently co-occurs with Axis I disorders (e.g., depression and anxiety disorders) and Axis II disorders (i.e., personality disorders). Thus, our findings of an association between RGS17 variants and SD may be cofounded by comorbid disorders. Third, given the close relationship between the RGS-Rz (RGS17 and RGS20) and opioid receptor (OPRM1 and OPRK1, respectively) genes, gene-gene interaction analyses should be conducted. We would speculate that strong gene-gene interaction effects (e.g., of OPRM1 and RGS17) on SD would be detectable. Even though variation at RGS20 did not show significant association with SD in individual gene analysis, interaction effects of that gene with OPRM1 or OPRK1 on SD risk may exist. Fourth, in this study, we ignored polymorphisms in exonic regions because they are rare in the genes examined. There is only one known SNP rs2295230 (synonymous) in RGS17 exon 2 that had a minor allele frequency greater than 5% in AA and EA populations. Exonic SNP rs2295230 is in tight LD with intronic SNP rs9371276 (which was included in this study) (CEU: D’ = 0.96, r² =0.92; YRI: D’ = 0.86, r² = 0.54, using genotyping data from the 1000 Genomes Project). It is also situated close to SNP rs2295230. Thus, exonic SNP rs2295230 was not considered in the present study. As we know, rare variants in coding regions may have a larger impact on disease risk (in the few individuals who carry them) than common non-coding variants (which may have a greater impact at the population level). Recent genome-wide association studies using common genetic variants have identified specific loci and/or genomic regions that contribute to the etiology of certain disorders. However, only a small proportion of the heritability of complex disorders, such as SD, can be accounted for by common variants [40, 41]. Therefore, it is necessary to sequence exons of target genes (such as RGS17 and RGS20) or perform exomic sequencing using next-generation sequencing technology to identify new rare variants and analyze their association with SD. Fifth, given the incomplete penetrance of susceptibility genes for alcohol or drug dependence in monozygotic twins [42], epigenetic mechanisms should be studied to determine their contribution to SD risk. Altered DNA methylation levels in a number of genes (e.g., OPRM1) have been found in patients with alcohol or opioid dependence [43, 44]. Altered methylation of RGS17 and RGS20 (especially in their promoter regions) could increase the risk for SD. Therefore, epigenetic studies may provide further evidence about the role of RGS17 and RGS20 in the etiology of SD.

In summary, we found that RGS17 polymorphisms were associated with multiple SD phenotypes in both AA and EA populations. Our findings suggest that lower transcription levels of RSG17 due to certain genetic variants (e.g., the promoter SNP rs596356) may modulate the reinforcing effects of alcohol or drugs that are mediated by GPCRs such as opioid receptors and thus influence the vulnerability to SD. Given the fact that RGS17 is significantly expressed in striatal regions including the nucleus accumbens and putamen [45], if our findings are validated, RGS17 and its protein product could be good targets for medications to treat SD.