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Psychiatric Genetics:
doi: 10.1097/YPG.0000000000000007
Original Articles

Epistatic interaction between CRHR1 and AVPR1b variants as a predictor of major depressive disorder

Szczepankiewicz, Aleksandraa,c; Leszczyńska-Rodziewicz, Annaa,b; Pawlak, Joannaa,b; Rajewska-Rager, Aleksandrab; Wilkosc, Monikad; Zaremba, Dorotaa; Dmitrzak-Weglarz, Monikaa; Skibinska, Mariaa; Hauser, Joannaa,b

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Author Information

aDepartment of Psychiatry, Laboratory of Psychiatric Genetics

bDepartment of Adult Psychiatry

cDepartment of Pulmonology, Pediatric Allergy, and Clinical Immunology, Laboratory of Molecular and Cell Biology, Poznan University of Medical Sciences, Poznan

dDepartment of Individual Differences Psychology, Psychology Institute, Kazimierz Wielki University in Bydgoszcz, Bydgoszcz, Poland

Correspondence to Aleksandra Szczepankiewicz, PhD, Department of Pediatric Pulmonology, Allergy, and Clinical Immunology, Laboratory of Molecular and Cell Biology, Poznan University of Medical Sciences, 27/33 Szpitalna St., 60-572 Poznan, Poland Tel: +48 061 8491311; fax: +48 061 8480111; e-mail:

Received March 23, 2012

Accepted March 4, 2013

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Objective: Genes involved in the regulation of the hypothalamus–pituitary–adrenal axis are responsible for altered susceptibility to mood disorders. The aim of this study was to analyze the possible association of CRHR1 and AVPR1b gene variants with bipolar disorder and major depressive disorder (MDD).

Methods: In the study, we included 486 patients with bipolar disorder and 215 patients with MDD. Consensus diagnosis was made according to Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV) criteria, using the Structured Clinical Interview for DSM Disorders. The control group consisted of 712 healthy participants. Genotyping of CRHR1 and AVPR1b polymorphisms was performed using TaqMan single nucleotide polymorphism genotyping assays. Linkage disequilibrium analysis was carried out on Haploview. Gene–gene interactions were analyzed using the multifactor dimensionality reduction method.

Results: By single marker analysis we have found an association of rs28536160 of AVPR1b and rs4076452 and rs16940655 of CRHR1 with mood disorders (P=0.036, 0.0013, and 0.003, respectively). We observed strong linkage disequilibrium between seven CRHR1 polymorphisms grouped in two haplotype blocks; however, none of them showed an association with MDD or bipolar disorder. Similarly, no association was found for three of four strongly linked AVPR1b polymorphisms. Gene–gene interaction analysis revealed a significant epistatic interaction between AVPR1b and CRHR1 genes in susceptibility to MDD (P=0.017).

Conclusion: Polymorphisms of CRHR1 and AVPR1b may modify susceptibility to mood disorders.

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Mood disorders including bipolar disorder and major depressive disorder (MDD) are among the severe forms of mental illnesses of high socioeconomic burden. Bipolar disorder affects both sexes equally and occurs among all age groups; its worldwide prevalence is ∼3–5%. MDD affects women more often than men and its prevalence is greater than 10% recurrent depressive episodes.

Mood disorders have been characterized by dysregulation of the hypothalamus–pituitary–adrenal (HPA) axis. In bipolar disorder, several authors have reported abnormalities in urinary and cerebrospinal fluid (CSF) cortisol levels, decreased suppression in response to dexamethasone (DEX) (Zhou et al., 1987), and enhanced response to corticotropin releasing hormone (CRH) in manic patients as compared with controls; the changes in CRH secretion seemed to appear before the manic or hypomanic symptoms were clinically evident (Vieta et al., 1999). In addition, abnormal dexamethasone suppression test results (marker of HPA dysfunction) are more common during depression in the course of bipolar disorder compared with unipolar disorder (Schmider et al., 1995; Rush et al., 1997; Rybakowski and Twardowska, 1999), and HPA hyperactivity is critical for the switch from mania to depression in the rapid cyclers and ultrarapid cyclers subgroups of bipolar disorder patients (Juckel et al., 2000). In MDD, the hyperactivity of the HPA axis may be responsible for the clinical demonstration of depressive symptoms, whereas treatment with antidepressants improves HPA regulation (Holsboer, 2000).

In response to stress, CRH is released from the hypothalamus and binds to the corticotropin releasing hormone receptor (CRHR1) in the pituitary gland, which further stimulates adrenocorticotropic hormone (ACTH) production in the anterior pituitary (Bittencourt and Sawchenko, 2000). ACTH, after binding to its receptor, mediates glucocorticoid release from the adrenal gland. The crucial role of CRHR1 in activating the HPA axis was demonstrated by Timpl et al. (1998), who by using the CRHR1-knockout model showed that stress response cannot be compensated for by any other system or by the highly homologous CRHR2 receptor.

The potential role of arginine vasopressin (AVP) and the vasopressinergic system in mood disorders was described by Gold et al. (1978), who postulated that AVP deficiency in animal models is involved in a number of behavioral changes (memory processes, pain sensitivity, synchronization of biological rhythms) that are observed in affective disorders. These changes are reversible when the peptide is replaced. The involvement of AVP was also confirmed by the results of the DEX/CRH test in depressive patients, who showed an enhanced ACTH response to CRH, possibly due to AVP-mediated ACTH release (Lim et al., 2000). AVP mRNA levels have been shown to be increased in the hypothalamus of depressed patients (Meynen et al., 2006), which is supported by an increase in AVP-positive neurons in the same region in depressed patients (Purba et al., 1996). AVP exerts its effects through specific membrane receptors, of which several subtypes have been identified (Jard et al., 1986; Barberis et al., 1992; Birnbaumer, 2000). The AVPR1b (V3) receptor subtype possesses ACTH-releasing properties. AVPR1b receptor levels and corticotropin responsiveness were shown to change under chronic stress (Aguilera et al., 1994), and upregulation of the AVPR1b receptor levels, underlying the shift in the hypothalamic drive from CRH to AVP, was suggested to play a role in depression (Scott and Dinan, 2002).

The natural candidates responsible for HPA axis dysfunction and altered susceptibility to mood disorders are therefore genes involved in the physiological response to stress in the HPA axis, thus regulating the action of the CRH system (including the CRHR1 gene) and the AVP system (including the AVPR1b gene). The CRHR1 gene is located on chromosome 17q12-q22, which is reported in several linkage studies on bipolar disorder (Dick et al., 2003; Ewald et al., 2005; Fullerton et al., 2010). The gene encoding AVPR1b is located on the human chromosome 1q32, a region implicated by a genome scan for bipolar disorder (Detera-Wadleigh et al., 1999) and a continuous measure of depression and anxiety (Nash et al., 2004).

On the basis of the above data, we hypothesized that genetic variation within two receptor genes, CRHR1 and AVPR1b, that regulate the function of the CRH and AVP systems is involved in the disturbed HPA axis response, thus altering the risk for bipolar disorder and MDD. As there have been only a few studies on the association between these two genetic variants and mood disorders, we aimed to analyze the polymorphisms of CRHR1 and AVPR1b genes in a large group of patients diagnosed with bipolar disorder and MDD, as well as in controls. Moreover, taking into account the possible interactions between these two systems, we aimed to analyze whether any combination of the variants of two analyzed genes can be used as a marker for predisposition to either bipolar disorder or MDD.

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Materials and methods

Study design

This study was a case–control association study that compared a group of bipolar patients and a group of patients with MDD with controls.

The project was approved by the local ethics committee. After the participants were provided a complete description of the study, written informed consent was obtained. The study was carried out in compliance with the Code of Ethics of the World Medical Association (Declaration of Helsinki).

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The study included 701 patients with affective disorders: 486 patients with bipolar disorder and 215 patients with MDD. Patients were recruited from among inpatients from the Wielkopolska region, considered as ethnically homogenous (Cavalli-Sforza, 1994), treated at the Department of Psychiatry, University of Medical Sciences, Poznan. Consensus lifetime diagnosis for each patient was made by two experienced psychiatrists. Phenotyping was based on clinical interviews, medical records, and family history, and consensus diagnosis was made according to Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV) criteria, using the Structured Clinical Interview for DSM Disorders (First et al., 1996). All relevant clinical information on the course of both disorders was obtained from the Structured Clinical Interview for DSM Disorders. The description of the patients is presented in Table 1.

Table 1
Table 1
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Control group

The control group consisted of 712 participants from the same geographical region of Poland. Control participants were recruited from a group of healthy volunteers, blood donors, and hospital staff and students of the University of Medical Sciences, Poznan, and the Clinical Neuropsychology Unit, Collegium Medicum, Bydgoszcz. Only 40% of the control group was psychiatrically screened using the Polish version of the Mini-International Neuropsychiatric Interview Plus scale (Lecrubier et al., 1997) to exclude the presence of any serious mental health problem. For the remaining 60% of the control group, participants with any chronic diseases (including psychiatric disorders) were excluded. The description of the control group is shown in Table 1.

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DNA was extracted from 10 ml of EDTA-anticoagulated whole blood using the salting out method (Miller et al., 1988). Single nucleotide polymorphisms (SNPs) were selected on the basis of the following criteria: functionality (in experimental functional studies), high frequency (minor allele frequency>0.05), indication of being a tag SNP in HapMap [HapMap Genome Browser release #24 (phase 1 and 2 – full dataset)], or previously reported associations with psychiatric disorders (both positive and negative findings). SNPs chosen include both coding regions of known functionality and noncoding regions (introns, untranslated repeats) capable of affecting gene regulation.

The nine polymorphisms of CRHR1 and four polymorphisms of AVPR1b were genotyped using TaqMan SNP genotyping assays (Applied Biosystems, Bleiswijk, the Netherlands) and TaqMan genotyping Master Mix. The list of SNPs analyzed and the identification numbers of TaqMan assays are shown in Table 2.

Table 2
Table 2
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All the assays were validated and predesigned, except for one, which was a custom-designed assay for the polymorphism in AVPR1b (rs28632197). Reaction components and amplification parameters were based on the manufacturer’s instructions. The TaqMan SNP genotyping assay plates were amplified using the ABI PRISM 7900HT Sequence Detection System. Data acquisition and analysis was carried out using the allelic discrimination analysis module in SDS v2.4 software (Applied Biosystems).

On each reaction plate, control genomic DNA samples and nontemplate controls (water) were included. Quality control of the reaction was also performed (15% of randomly chosen samples from both groups) to check for genotyping accuracy, and identical genotypes were identified in all repeated samples. Genotyping was performed without the knowledge of the clinical status of the participants.

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Statistical analysis

The two-tailed Pearson’s χ2-test and Fisher’s exact test were used to test differences in the genotypic and allelic distributions, respectively, between the groups of patients and controls. In addition, two-tailed power analysis was carried out using Quanto software, which includes minor allele frequency as well as prevalence of disease in its calculations. Calculations were carried out using the computer program Statistica, version 9.0 (StatSoft Poland, Cracow, Poland). Odds ratios were calculated with 2×2 contingency tables using Fisher’s exact test on a demo version of GraphPad InStat 3 software (GraphPad Software, San Diego, California, USA). Linkage disequilibrium in SNPs within CRHR1 and AVPR1b genes was examined by pairwise comparisons of r2 and D′ using Haploview, version 4.1 (Barrett et al., 2005). Correction for multiple testing was performed for multiple comparisons in haplotype analysis, by 10 000 permutations.

Higher-order gene–gene interactions among tested SNPs were analyzed using the nonparametric and genetic model-free multifactor dimensionality reduction (MDR) approach (v.2.0 beta 8.3). A detailed description of the methodology can be found in the study by Ritchie et al. (2001). All interactions were tested using 10-fold cross-validations in an exhaustive search considering all possible SNP combinations. The model with the highest testing balance accuracy and a cross-validation consistency of greater than 5 of 10 was selected as the ‘best model’. Statistical significance was determined using a 1000-fold permutation test (MDR permutation testing module, v.1.0 beta 2). The software is available online (

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Hardy–Weinberg equilibrium test

All the studied polymorphisms were tested for accordance with Hardy–Weinberg equilibrium (HWE). One of the SNPs, rs242937, in the CRHR1 gene showed significant deviation from HWE in both controls and patients (P<0.000); therefore, we excluded the results from further analysis and interpretation. Among other SNPs, deviation was also observed for rs28632197 in the AVPR1b gene and rs16940655 in the CRHR1 gene in a group of patients (Table 3).

Table 3
Table 3
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Single marker association analysis

Genotyping success rates for the studied polymorphisms were between 96.66 and 99.58%. Genotyping error rates for all the polymorphisms were less than 1%.

In the single marker association analysis of AVPR1b gene we observed an association of rs28536160 with mood disorders (P=0.036); this was not observed in the bipolar disorder and MDD patients separately. The results of single marker association analysis are shown in Table 3.

For the CRHR1 gene, we observed an association of rs4076452 and rs16940655 with mood disorders (P=0.013 and 0.003, respectively). Moreover, the association of rs16940655 was also observed in patients with bipolar disorder (P=0.007). We found that rs4076452 was significantly associated with an increased risk for MDD in our group.

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Linkage disequilibrium and haplotype analysis

Strong linkage disequilibrium was found for three of four analyzed polymorphisms of the AVPR1b gene (Fig. 1), and these were grouped into one haplotype block. Haplotype analysis for relationship with disease status using Haploview did not show significant association of any haplotype with either bipolar disorder or MDD (Table 4).

Fig. 1
Fig. 1
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Table 4
Table 4
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For the CRHR1 gene, strong linkage disequilibrium was observed in eight of nine polymorphisms analyzed. Haploview analysis defined two haplotype blocks: block 1 containing rs4792887 and rs110402 and block 2 with rs12936511, rs16940655, rs173365, rs242950, and rs878886 (Fig. 2). We observed that the CCACG haplotype in the second haplotype block was significantly more frequent in the patients with mood disorders than in healthy individuals (P=0.031); however, the difference was not observed after multiple testing correction (after 10 000 permutations, P=0.208). For the MDD and bipolar disorder patients, we have not observed any significant differences in haplotype frequencies (Table 4).

Fig. 2
Fig. 2
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Multifactor dimensionality reduction analysis

Results of exhaustive MDR analysis evaluating combinations of all tested SNPs for each comparison are summarized in Table 5. The best combination of possibly interactive polymorphisms in predicting bipolar disorder was that of rs878886 and rs110402 of the CRHR1 gene. The testing balanced accuracy for this two-locus model was 54% and cross-validation consistency was 8/10 (80%); an empiric P-value of 0.395 based on 1000-fold permutations was obtained. For MDD prediction, we observed that the best model of interactive variants was the four-locus model (rs28536160 and rs28373064 of AVPR1b and rs4076452 and rs110402 of CRHR1), with a testing balance accuracy of 58% and cross-validation consistency of 9/10 (90%); an empiric P-value of 0.017 based on 1000-fold permutations was obtained.

Table 5
Table 5
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Power analysis

The power to detect an association for odds ratio, which in our sample was evaluated as 1.4, was above 80% for each SNP.

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The main finding of this study is an association of the AVPR1b and CRHR1 polymorphisms with mood disorders in the entire group of patients, as well as in bipolar and MDD patients separately. Moreover, we found that gene–gene interactions between CRHR1 and AVPR1b variants are important predictors of MDD susceptibility.

Previous studies on genetic variants and the regulation of CRH and AVP systems in mood disorders, in particular bipolar disorder, are limited. The involvement of the CRHR1 polymorphism in regulation of the HPA axis and cortisol response to the DEX/CRH test in the patients with childhood maltreatment was reported by Tyrka et al. (2009), indicating the importance of interactions between candidate genes for regulation of the HPA axis and early-life stress in the development of mood disorders. Several association studies showed the lack of a relationship between MDD and CRHR1 variants (Papiol et al., 2007; Dong et al., 2009). However, in their study on gene–environment interactions, Bradley et al. (2008) reported that the CRHR1 TAT haplotype formed by the three most significant SNPs investigated (rs7209436, rs110402, and rs242924) was protective in terms of reducing depression symptoms among patients subjected to childhood abuse. This effect was also observed for the TCA haplotype (rs7209436, rs4792887, rs110402). This finding was further confirmed by Ressler et al. (2010) in a sample of 1059 individuals, although the finding of an interaction between the TAT haplotype and childhood abuse was not replicated in another study including 1638 individuals (Grabe et al., 2010). However, the latter analysis reported a gene–environment interaction between the CRHR1 polymorphism (with rs17689882 reaching gene-wide significance when adjusting for 28 SNPs) and physical neglect in the analyzed population.

In our study, we found rs4076452 and rs16940655 polymorphisms of the CRHR1 gene to be significantly associated with mood disorders, and we also observed an association of the rs4076452 variant with MDD and the rs16940655 polymorphism with bipolar disorder. These SNPs were not analyzed previously in mood disorders; however, their locations (5′UTR and exon 3, respectively) suggest potential functionality, possibly by increasing neuroendocrine sensitivity to stress. Such an enhanced sensitivity of the CRHR1 receptor or altered receptor feedback regulation could account for increased cortisol responsivity in the DEX/CRH test, as in the case of rs110402 (Tyrka et al., 2009).

With regard to comorbidities of bipolar disorder and MDD, an association of CRHR1 variants with the specific patterns of alcohol dependence was reported (Treutlein et al., 2006). In the pharmacogenetic study by Liu et al. (2007), it was found that the rs242941 CRHR1 polymorphism was associated with the antidepressant response to fluoxetine in depressed patients. Moreover, Keck et al. (2008) in their study showed the relevance of the combined effect of CRHR1 and AVPR1b polymorphisms in the susceptibility to panic disorder.

For the AVP system, a study by Van West et al. (2004) showed that a major haplotype (ATCAG) of the five SNPs of the AVPR1b gene (rs28536160, rs28373064, rs33976516, rs33985287, rs33933482) is protective against recurrent major depression in Belgian and Swedish samples of unipolar patients. Moreover, the involvement of the AVPR1b gene polymorphism in the pathogenesis of mood disorders was confirmed by the association study of AVPR1b SNPs with childhood-onset mood disorders (bipolar disorder and MDD; Dempster et al., 2007; Dempster et al., 2009) and attention deficit hyperactivity disorder (Van West et al., 2009). However, in their recent study, Van West et al. (2010) reported that none of the five AVPR1b polymorphisms analyzed in their previous study (Van West et al., 2004) influenced cortisol levels after a psychosocial stress response in a child psychiatric population (patients diagnosed with attention deficit hyperactivity disorder and social phobia).

In our analysis we observed that the rs28536160 polymorphism, one of the SNPs previously associated with recurrent major depression (Van West et al., 2004), was also associated with mood disorder in our population, but not in subgroups of bipolar and MDD patients analyzed separately or in haplotype blocks (data not shown) for single polymorphism association. The inconsistency with the previous findings of a positive association with MDD may result from the differences in sample sizes of patient groups (n=89 in the Belgian and Swedish samples of the study by Van West and colleagues and n=215 in the present study).

In this study, we applied MDR to identify gene–gene interactions that are significant in predicting increased susceptibility to mood disorders. The use of this method facilitates the detection of combinations of multiple genes that modify disease susceptibility. Essentially, MDR pools multilocus genotypes into high-risk and low-risk groups. MDR includes no assumption as regards the mode of inheritance and minimizes false-positive results due to multiple testing. MDR has been shown to have reasonable power in identifying multilocus interactions in case–control studies with relatively small sample sizes (Dai et al., 2009) and has been applied so far for gene–gene interactions in complex disorders such as hypertension (Williams et al., 2004), type 2 diabetes mellitus (Cho et al., 2004), myocardial infarction (Coffey et al., 2004), asthma (Chan et al., 2006; Leung et al., 2007), and atopy (Park et al., 2007). In our study, we found a significant gene–gene interaction between AVPR1b (rs28536160 and rs28373064) and CRHR1 (rs4076452 and rs110402) in the four-locus model predicting MDD. Such an interaction has not been reported previously. Our finding may support the importance of the interaction between the CRH and AVP systems in the development of MDD. Increasing evidence indicates that interactions between the two regulators (CRHR1 and AVPR1b) play an important role in modulating pituitary ACTH responsiveness according to the physiological requirement. Young et al. (2007) in their study demonstrated that AVPR1b and CRHR1 receptors can form homodimers and heterodimers in a ligand-independent manner, possibly influencing CRH and AVP signaling. This further supports the role of intergenic interactions between AVPR1b and CRHR1 in the alteration of HPA axis function and susceptibility to MDD.

Among the limitations of the present study, we should mention the lack of careful psychiatric screening in the majority of the control group, which might have yielded false-negative or false-positive results. Another limitation is the sample size of the MDD patient group (n=215), although, at least with regard to interaction analysis, previous studies have successfully used the MDR method to identify gene–gene interactions for complex traits with a total sample size between 177 and 686 (Ritchie et al., 2001; Cho et al., 2004; Coffey et al., 2004; Williams et al., 2004) and sufficient power to detect gene–gene interactions in the presence of 5% genotyping error, 5% missing data, or a combination of both (Ritchie et al., 2001; Ritchie et al., 2003).

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We demonstrate here for the first time that epistatic interactions between CRHR1 and AVPR1b genetic variants may be important predictors of altered HPA axis function and, therefore, increased MDD susceptibility. Further, our results support the involvement of the CRHR1 and AVPR1b genetic variants in the development of mood disorders.

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The authors thank Agata Groszewska and Dominika Oles for technical support.

This study was supported by the Ministry of Science and Higher Education (grant no. IP 2011 053771).

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Conflicts of interest

There are no conflicts of interest.

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association; bipolar disorder; gene; major depressive disorder; polymorphism

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