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Association between OPCRIT dimensions and polymorphisms of HPA axis genes in bipolar disorder
Journal of Affective Disorders 151 (2013) 744–747
Contents lists available at ScienceDirect
Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad
Research report
Association between OPCRIT dimensions and polymorphisms of HPA axis genes in bipolar disorder$ Anna Leszczyńska-Rodziewicz b,n, Małgorzata Maciukiewicz b, Aleksandra Szczepankiewicz b,c, Andrzej Pogłodziński a, Joanna Hauser b a
Department of Adult Psychiatry, Poznan University of Medical Sciences, ul. Szpitalna 27/33, 60-572 Poznan, Poland Psychiatric Genetics Unit, Poznan University of Medical Sciences, ul. Szpitalna 27/33, 60-572 Poznan, Poland c Laboratory of Molecular and Cell Biology, Department of Pulmonology, Pediatric Allergy and Clinical Immunology, Poznan University of Medical Sciences, Poland b
art ic l e i nf o
a b s t r a c t
Article history: Received 14 May 2013 Received in revised form 13 August 2013 Accepted 14 August 2013 Available online 23 August 2013
The aim of the study was to investigate the possible association between polymorphisms of HPA axis genes-CRHR1 (corticotrophin-releasing hormone receptor), NR3C1 (glucocorticoid receptor) and AVPR1B (arginine vasopressin receptor) and dimensions of bipolar disorder assessed by OPCRIT. We examined 560 patients with diagnosis of bipolar disorder (n ¼457) and unipolar disorder (n ¼103). Diagnosis was established by SCID and OPCRIT. We found association between polymorphisms of AVPR1b gene and psychotic dimension and CRHR1 polymorphisms and excitement and psychotic dimension. Our results suggest possible involvement of the AVPR1b and CRHR1 genes in the ethiology of psychotic features in the course of affective disorders, and possible involvement of CRHR1 gene in the ethiology of bipolar disorder. & 2013 Elsevier B.V. All rights reserved.
Keywords: HPA axis Genes OPCRIT dimension Bipolar disorder
1. Introduction Bipolar disorder is a severe mental disorder with episodes of depressed mood and elevated mood (mania or hypomania), in some cases also psychotic features may occur both in depressive and manic episodes. Bipolar disorder is characterized by high heredity of approximately 85% (McGuffin et al., 2003) it is also seen as stress related disorder. Since the disorder is heterogenous the search for more specific symptoms or dimension with their genetic background seems to be promising direction. The value of using dimensional approach is detecting more homogenous groups of patients according to their symptoms which may possibly be more closely linked to genetic factors. In the last few years the dimensional structure of psychoses has been investigated using the OPCRIT checklist. Factor analyses performed so far resulted in: dimensional structure of depression including two-dimensional structure of cognitive (psychic and vegetative: somatic symptoms) suggested by Suzuki et al. (1995), multidimensional model of separate depression and anxiety factors proposed by Enns et al. (1998). Delusions were described as distinct dimension from general depressive symptoms by Serretti et al. 1998. Analyses of the manic symptoms generated five independant domains: dysphoria, ☆ This study was supported by the Polish Ministry of Science and Higher Education, Grant no. N N402 243835. n Corresponding author. Tel.: þ 48 61 8491 311; fax: þ 48 61 8480 111. E-mail address: [email protected] (A. Leszczyńska-Rodziewicz).
0165-0327/$ - see front matter & 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jad.2013.08.012
irritable mood, psychomotor acceleration, psychosis and increased hedonic functions (Cassidy, 2010; Serretti et al., 1999). McIntosh et al. obtained a solution for mania, depression, disorganization and reality distortion domains, similar to those identified previously (Serretti et al., 2001; McIntosh et al., 2001). A number of studies have examined the association between the dimensions with various clinically significant characteristics (Allardyce et al., 2007). The most consistent finding is a strong association between the negative dimension and poor outcome (Dikeos et al., 2006), the associations of other dimensions are inconsistent. Factor analysis is very helpful tool for investigation of less heterogeneous clinical sub-phenotype. Results may be further used in association analyses on the population level as well as genome-wide association studies (Belmonte Mahon et al., 2011). Involvement of the hypothalamic–pituitary–adrenal (HPA) axis disturbances in the ethiology of psychiatric disorders is one of the most consistent findings in psychiatry (Pariante, 2009). The patients with acute phase of psychotic symptoms, healthy first degree relatives of patients with major depression have been described to show HPA axis hyperactivity (Pariante, 2009). One of the repeatedly reported biological abnormalities in depression is the alteration in the HPA axis function (Kunugi et al., 2010; Hori et al., 2013) also persons with risk for developing depression because of personality traits have shown HPA axis hyperactivity. Our goal was to examine association with previously detected factor structure of bipolar disorder and possible association with the polymorphisms of HPA axis genes-NR3C1 (glucocorticoid
A. Leszczyńska-Rodziewicz et al. / Journal of Affective Disorders 151 (2013) 744–747
receptor gene), CRHR1(corticotrophin-releasing hormone receptor gene) and AVPR1b (arginine vasopressin receptor gene).
2. Methods 2.1. Method of genotyping We draw venous blood after receiving written consent from each individual. The DNA was extracted from 10 ml of EDTA anticoagulated whole blood using the salting out method proposed by (Miller et al., 1988). We applied following criteria to select SNP set to be genotyped: functionality (in experimental functional studies), high frequency (MAF40.05), indication as tag SNP in HapMap (HapMap Genome Browser release♯24) (Phase 1 and 2 – full dataset) or previously reported associations for psychiatric disorders (both positive and negative findings). Chosen SNPs set covers whole gene region including coding regions of known functionality and non-coding regions (introns, UTRs) possible to affect gene regulation. The polymorphisms from NR3C1, AVPR1b and CRHR1 genes were genotyped using TaqMan Genotyping Master Mix and TaqMan SNP Genotyping assays (Applied Biosystems). Detailed list of SNPs analyzed together with ID numbers of TaqMan assays are available in Table 1. All the assays were validated and predesigned except for three polymorphisms (rs6195, rs41423247 and rs28632197) for which custom assays were designed. Reaction components and amplification parameters were based on manufacturer's instructions. The amplification for TaqMan SNP genotyping assay plates was done in ABI PRISMs 7900HT Sequence Detection System. Data acquisition and analysis was performed using the allelic discrimination analysis module in SDS v2.1 software (Applied Biosystems). For each reaction plate we included genomic control DNA samples and non-template controls (water). We also performed control of TaqMan SNP genotyping assay (25% of randomly chosen samples from both groups) in order to check for genotyping accuracy and to detect identical genotypes in all repeated samples. We performed genotyping without prior knowledge about clinical status of the subjects. 2.2. Statistical analysis All computations were done using R environment (R Development Core Team, 2012) for statistical computing and graphics We used previously discovered dimensions as a
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quantitive trait in association studies. By Shapiro–Wilk test of normality was performed. As trait of interest turned out to be highly non-normal we used non parametric one-way analysis of variance (Kruskal–Wallis test). To state which genotype change provided significant result and to perform post-hoc test we performed used Mann–Whitney U test with Holm adjustment for multiple testing. Quantitive trait was defined as a sum of appropriate OPCRIT ratings. 2.3. Sample characteristics We studied inpatients only, recruited at the psychiatric hospital of the Poznan University of Medical Sciences in Poznan, Poland. Diagnosis was made according to DSM-IV criteria, using Structured Clinical Interview for DSM-IV (SCID). Confirmation by two experienced psychiatrists was essential for making final diagnosis. Local Bioethics Committee approved the study. We excluded patients with severe neurological and/or somatic diseases and comorbidity with psychiatric disorders. Into final association studies 560 patients with diagnosis of bipolar disorder (n¼ 457) and unipolar disorder (n¼103) were included. After filtering (taking only the patients with full OPCRIT measures) we took 208 men and 352 women of mean age 45 (SD¼15) into further analysis. The structure of the symptom dimensions was obtained using OPCRIT test results. OPCRIT is composed of 90 items covering symptoms of major psychoses (McGuffin et al., 1991) Craddock et al. validated OPCRIT as a convenient reliable tool for assessing diagnosis (Craddock et al., 1996). We applied a lifetime perspective for screening symptoms, as suggested by Farmer et al., 1992. 2.4. Quantitative train definition We used clinical dimension as a quantitative trait for association analyses. In our previous paper we computed factor structure of bipolar affective (Maciukiewicz et al., 2012). Receiving information about item composition of all dimensions and sub-dimensions, we defined trait of interest as a sum of appropriate OPCRIT ratings. Trait represented then continuum of symptoms dimensions strength. Fig. 1 presents list of dimensions/sub-dimensions used. Detailed description of dimensions and approached used for theirs detection are present in our previous work (Maciukiewicz et al., 2012).
3. Results Table 1 Description of polymorphisms analyzed in this study. Gene
SNP ID
Substitution
Custom name
TaqMan assay ID
NR3C1
rs10052957 rs6196 rs6198 rs6191 rs258813 rs33388 rs6195 rs41423247 rs28536160 rs28373064 rs35369693 rs28632197 rs878886 rs173365 rs242950 rs242937 rs110402 rs12936511 rs4792887 rs4076452 rs16940655
A/G A/G C/T A/C A/G A/T A/G C/G C/T A/G C/G A/G C/G A/G C/T A/G A/G C/T C/T C/G C/T
Tth111I Asn766Asn GR9β – – – N363S BclI – – – 364Arg 4His – – – – – – – – Val66Ala
C__30158011_10 C__1046361_10 C__8951023_10 C__3234245_20 C__1046357 C__1046426_10 Custom assay Custom assay C__64453209_10 C__64453210_10 C__64453216_10 Custom assay C___7450783_10 C___2544830_10 C___2257678_10 C_2544832_10 C_2544843_10 C__25957478_10 C__27895630_10 C__26012398_10 C_11935968_10
AVPR1b
CRHR1
Aassociation between rs28536160 genotype TT and CT of the AVPR1B gene and psychotic dimension both in bipolar disorder and bipolar type 1 disorder was found. Association between the rs4076452 genotype CG and CC of CRHR1 gene and excitement dimension, and rs242937 genotype AG and GG of CRHR1 gene and psychotic dimension. The results are shown in Table 2. For other polymorphisms and dimensions we did not found any associations (data not shown).
4. Discussion Our results suggest the involvement of the polymorphisms of the genes of HPA axis in the occurrence of psychotic and excitement dimensions of bipolar disorder. In study performed by Maciukiewicz et al., 2012 the presence of psychotic dimension in bipolar disorder was proved and the structure of psychotic dimension resembled the one described by Serretti and Olgiati (2004). In our previous paper we found association between polymorphism rs28536160 of the AVPR1b gene and psychotic features in bipolar patients (LeszczyńskaRodziewicz et al., 2012). Current results replicated previous one,
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A. Leszczyńska-Rodziewicz et al. / Journal of Affective Disorders 151 (2013) 744–747
Fig. 1.
Table 2 Associations of SNP of CRHR1 and AVPR1b genes. SNP
Localization
BP
BP I
rs242937 rs4076452 rs28536160
CRHR1 CRHR1 AVPR1B promoter
psych(p ¼0.005) exc1(p ¼ 0.016) psych(p ¼0.0250)
none none psych(p ¼0.05)
strongly suggesting involvement of polymorphism mentioned in the ethiology of psychotic features. Arginine vasopressin is regarded as a minor ACTH secretagogue in rodents, but evidences suggest it has a role in mediating the neuroendocrine response to some acute and chronic stressors (Stewart et al., 2008). AVP is considered as weak stimulant of the HPA axis on its own, it also potentiates the stimulatory effect of CRH (Young et al., 2007). Under the chronic stress AVP expression in the paraventricular nucleus is enhanced and AVP becomes the first activator of corticotropin (Dempster et al., 2007). Studies of affected sibling pairs which had a history of psychotic, manic or depressive symptoms in the course of illness have found modest aggregation for each symptom dimension (Niehaus et al., 2005). Some studies have found scores on negative or disorganized dimension to be associated with elevated risk of psychosis in relatives (Peralta and Cuesta, 2009). In the study performed by Cardno et al. none of the dimensions were significant predictor of psychosis risk in co-twins (Cardno et al., 2008). Dempster et al. found evidence for association between the AVPR1b polymorphisms (rs35369693 and rs33985287) and childhood onset of depression, especially in women. Some studies on the other hand showed polymorphisms of both AVPR1b (rs28632197) and CRHR1 (rs878886) genes altered susceptibility to panic disorder (Keck et al., 2008). The current findings indicate that variants of CRHR1 marker (rs12938031) may promote the development of anhedonia in the face of stress. In the study performed by Utge (Utge et al., 2010) the association between rs173365 (located in CRHR1) and early morning awakening was found in female cases of depression. The polymorphism of CRHR1 marker (rs4076452) appeared to be associated with early-onset depression. In our study we detected association between rs242937 and excitement dimension. Excitement dimension consist of the OPCRIT points fulfilling the criteria for mania, this association is interesting since the majority of the studies suggest involvement of the polymorphisms in the CRHR1 gene in the ethiology of depression or the response to antidepressant treatment (Papiol et al., 2007; Ishitobi et al., 2012; Liu et al., 2007; Licinio et al., 2004). CRH acts as a neurotransmitter via CRHR1 eliciting the anxiety related behavior, and influencing arousal and attention (Polanczyk et al., 2009). We also found the association between psychotic dimension and rs242937 CRHR1 gene, since the psychotic feature may occur
as a reaction to stress and in the reaction to stress HPA activation cause release of CRH hormone acting at CRHR1 receptor to stimulate adrenocorticotropic hormone release this might be the reason why this association was found. There is also the possibility that those SNP's are in linkage disequilibrium with a sequence variant in the 5′ regulatory region that influences expression of the CRHR1 gene. For NR3C1 gene polymorphisms we have not detected any associations. It has been reported that rs6191 variant is associated with depressive symptoms in the elderly in co-existence with childhood adversity (Sinclair et al., 2012). In our previous study association between the three polymorphisms of NR3C1 gene (rs6198, rs6191 and rs33388) with the MDD disorder and predominance of depressive symptoms in the course of bipolar disorder was shown (Szczepankiewicz et al., 2011). The strength of our paper is using new approach-dimensional structure of bipolar disorder, which seems to be promising tool for investigation of more homogenous groups, thus allowing to identify genes involved in the ethiology of the symptoms rather than the disease itself. Taking into consideration the limitations, which include: (1) the exact definition of the optimal dimension to be used as a phenotype for molecular studies is not clear, also it is not known to which extent variation in symptom dimensions are influenced by genetic factors, and (2) total number of the patients included in the study, results should be interpreted very carefully. Functionality of the SNP's with which we found association is not yet fully understood, although the polymorphism rs4076452 of CRHR1 gene is located in the promoter region probably influencing transcription process, the polymorphism rs28536160 is located upstream also influencing functionality. There is also possibility that these SNPs are in strong linkage disequilibrium with other, functionally relevant variants that are causative for BP development. This may be also the reason why we identified association.
Role of funding source This study was supported by the Polish Ministry of Science and Higher Education, Grant no. N N402 243835; the Polish Ministry of Science and Higher Education had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
Conflict of interest Nothing to declare
References Allardyce, J., Suppes, T., Van Os, J., 2007. Dimensions and the psychosis phenotype. International Journal of Methods in Psychiatric Research 16 (Suppl. 1), S34–S40.
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Contents lists available at ScienceDirect
Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad
Research report
Association between OPCRIT dimensions and polymorphisms of HPA axis genes in bipolar disorder$ Anna Leszczyńska-Rodziewicz b,n, Małgorzata Maciukiewicz b, Aleksandra Szczepankiewicz b,c, Andrzej Pogłodziński a, Joanna Hauser b a
Department of Adult Psychiatry, Poznan University of Medical Sciences, ul. Szpitalna 27/33, 60-572 Poznan, Poland Psychiatric Genetics Unit, Poznan University of Medical Sciences, ul. Szpitalna 27/33, 60-572 Poznan, Poland c Laboratory of Molecular and Cell Biology, Department of Pulmonology, Pediatric Allergy and Clinical Immunology, Poznan University of Medical Sciences, Poland b
art ic l e i nf o
a b s t r a c t
Article history: Received 14 May 2013 Received in revised form 13 August 2013 Accepted 14 August 2013 Available online 23 August 2013
The aim of the study was to investigate the possible association between polymorphisms of HPA axis genes-CRHR1 (corticotrophin-releasing hormone receptor), NR3C1 (glucocorticoid receptor) and AVPR1B (arginine vasopressin receptor) and dimensions of bipolar disorder assessed by OPCRIT. We examined 560 patients with diagnosis of bipolar disorder (n ¼457) and unipolar disorder (n ¼103). Diagnosis was established by SCID and OPCRIT. We found association between polymorphisms of AVPR1b gene and psychotic dimension and CRHR1 polymorphisms and excitement and psychotic dimension. Our results suggest possible involvement of the AVPR1b and CRHR1 genes in the ethiology of psychotic features in the course of affective disorders, and possible involvement of CRHR1 gene in the ethiology of bipolar disorder. & 2013 Elsevier B.V. All rights reserved.
Keywords: HPA axis Genes OPCRIT dimension Bipolar disorder
1. Introduction Bipolar disorder is a severe mental disorder with episodes of depressed mood and elevated mood (mania or hypomania), in some cases also psychotic features may occur both in depressive and manic episodes. Bipolar disorder is characterized by high heredity of approximately 85% (McGuffin et al., 2003) it is also seen as stress related disorder. Since the disorder is heterogenous the search for more specific symptoms or dimension with their genetic background seems to be promising direction. The value of using dimensional approach is detecting more homogenous groups of patients according to their symptoms which may possibly be more closely linked to genetic factors. In the last few years the dimensional structure of psychoses has been investigated using the OPCRIT checklist. Factor analyses performed so far resulted in: dimensional structure of depression including two-dimensional structure of cognitive (psychic and vegetative: somatic symptoms) suggested by Suzuki et al. (1995), multidimensional model of separate depression and anxiety factors proposed by Enns et al. (1998). Delusions were described as distinct dimension from general depressive symptoms by Serretti et al. 1998. Analyses of the manic symptoms generated five independant domains: dysphoria, ☆ This study was supported by the Polish Ministry of Science and Higher Education, Grant no. N N402 243835. n Corresponding author. Tel.: þ 48 61 8491 311; fax: þ 48 61 8480 111. E-mail address: [email protected] (A. Leszczyńska-Rodziewicz).
0165-0327/$ - see front matter & 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jad.2013.08.012
irritable mood, psychomotor acceleration, psychosis and increased hedonic functions (Cassidy, 2010; Serretti et al., 1999). McIntosh et al. obtained a solution for mania, depression, disorganization and reality distortion domains, similar to those identified previously (Serretti et al., 2001; McIntosh et al., 2001). A number of studies have examined the association between the dimensions with various clinically significant characteristics (Allardyce et al., 2007). The most consistent finding is a strong association between the negative dimension and poor outcome (Dikeos et al., 2006), the associations of other dimensions are inconsistent. Factor analysis is very helpful tool for investigation of less heterogeneous clinical sub-phenotype. Results may be further used in association analyses on the population level as well as genome-wide association studies (Belmonte Mahon et al., 2011). Involvement of the hypothalamic–pituitary–adrenal (HPA) axis disturbances in the ethiology of psychiatric disorders is one of the most consistent findings in psychiatry (Pariante, 2009). The patients with acute phase of psychotic symptoms, healthy first degree relatives of patients with major depression have been described to show HPA axis hyperactivity (Pariante, 2009). One of the repeatedly reported biological abnormalities in depression is the alteration in the HPA axis function (Kunugi et al., 2010; Hori et al., 2013) also persons with risk for developing depression because of personality traits have shown HPA axis hyperactivity. Our goal was to examine association with previously detected factor structure of bipolar disorder and possible association with the polymorphisms of HPA axis genes-NR3C1 (glucocorticoid
A. Leszczyńska-Rodziewicz et al. / Journal of Affective Disorders 151 (2013) 744–747
receptor gene), CRHR1(corticotrophin-releasing hormone receptor gene) and AVPR1b (arginine vasopressin receptor gene).
2. Methods 2.1. Method of genotyping We draw venous blood after receiving written consent from each individual. The DNA was extracted from 10 ml of EDTA anticoagulated whole blood using the salting out method proposed by (Miller et al., 1988). We applied following criteria to select SNP set to be genotyped: functionality (in experimental functional studies), high frequency (MAF40.05), indication as tag SNP in HapMap (HapMap Genome Browser release♯24) (Phase 1 and 2 – full dataset) or previously reported associations for psychiatric disorders (both positive and negative findings). Chosen SNPs set covers whole gene region including coding regions of known functionality and non-coding regions (introns, UTRs) possible to affect gene regulation. The polymorphisms from NR3C1, AVPR1b and CRHR1 genes were genotyped using TaqMan Genotyping Master Mix and TaqMan SNP Genotyping assays (Applied Biosystems). Detailed list of SNPs analyzed together with ID numbers of TaqMan assays are available in Table 1. All the assays were validated and predesigned except for three polymorphisms (rs6195, rs41423247 and rs28632197) for which custom assays were designed. Reaction components and amplification parameters were based on manufacturer's instructions. The amplification for TaqMan SNP genotyping assay plates was done in ABI PRISMs 7900HT Sequence Detection System. Data acquisition and analysis was performed using the allelic discrimination analysis module in SDS v2.1 software (Applied Biosystems). For each reaction plate we included genomic control DNA samples and non-template controls (water). We also performed control of TaqMan SNP genotyping assay (25% of randomly chosen samples from both groups) in order to check for genotyping accuracy and to detect identical genotypes in all repeated samples. We performed genotyping without prior knowledge about clinical status of the subjects. 2.2. Statistical analysis All computations were done using R environment (R Development Core Team, 2012) for statistical computing and graphics We used previously discovered dimensions as a
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quantitive trait in association studies. By Shapiro–Wilk test of normality was performed. As trait of interest turned out to be highly non-normal we used non parametric one-way analysis of variance (Kruskal–Wallis test). To state which genotype change provided significant result and to perform post-hoc test we performed used Mann–Whitney U test with Holm adjustment for multiple testing. Quantitive trait was defined as a sum of appropriate OPCRIT ratings. 2.3. Sample characteristics We studied inpatients only, recruited at the psychiatric hospital of the Poznan University of Medical Sciences in Poznan, Poland. Diagnosis was made according to DSM-IV criteria, using Structured Clinical Interview for DSM-IV (SCID). Confirmation by two experienced psychiatrists was essential for making final diagnosis. Local Bioethics Committee approved the study. We excluded patients with severe neurological and/or somatic diseases and comorbidity with psychiatric disorders. Into final association studies 560 patients with diagnosis of bipolar disorder (n¼ 457) and unipolar disorder (n¼103) were included. After filtering (taking only the patients with full OPCRIT measures) we took 208 men and 352 women of mean age 45 (SD¼15) into further analysis. The structure of the symptom dimensions was obtained using OPCRIT test results. OPCRIT is composed of 90 items covering symptoms of major psychoses (McGuffin et al., 1991) Craddock et al. validated OPCRIT as a convenient reliable tool for assessing diagnosis (Craddock et al., 1996). We applied a lifetime perspective for screening symptoms, as suggested by Farmer et al., 1992. 2.4. Quantitative train definition We used clinical dimension as a quantitative trait for association analyses. In our previous paper we computed factor structure of bipolar affective (Maciukiewicz et al., 2012). Receiving information about item composition of all dimensions and sub-dimensions, we defined trait of interest as a sum of appropriate OPCRIT ratings. Trait represented then continuum of symptoms dimensions strength. Fig. 1 presents list of dimensions/sub-dimensions used. Detailed description of dimensions and approached used for theirs detection are present in our previous work (Maciukiewicz et al., 2012).
3. Results Table 1 Description of polymorphisms analyzed in this study. Gene
SNP ID
Substitution
Custom name
TaqMan assay ID
NR3C1
rs10052957 rs6196 rs6198 rs6191 rs258813 rs33388 rs6195 rs41423247 rs28536160 rs28373064 rs35369693 rs28632197 rs878886 rs173365 rs242950 rs242937 rs110402 rs12936511 rs4792887 rs4076452 rs16940655
A/G A/G C/T A/C A/G A/T A/G C/G C/T A/G C/G A/G C/G A/G C/T A/G A/G C/T C/T C/G C/T
Tth111I Asn766Asn GR9β – – – N363S BclI – – – 364Arg 4His – – – – – – – – Val66Ala
C__30158011_10 C__1046361_10 C__8951023_10 C__3234245_20 C__1046357 C__1046426_10 Custom assay Custom assay C__64453209_10 C__64453210_10 C__64453216_10 Custom assay C___7450783_10 C___2544830_10 C___2257678_10 C_2544832_10 C_2544843_10 C__25957478_10 C__27895630_10 C__26012398_10 C_11935968_10
AVPR1b
CRHR1
Aassociation between rs28536160 genotype TT and CT of the AVPR1B gene and psychotic dimension both in bipolar disorder and bipolar type 1 disorder was found. Association between the rs4076452 genotype CG and CC of CRHR1 gene and excitement dimension, and rs242937 genotype AG and GG of CRHR1 gene and psychotic dimension. The results are shown in Table 2. For other polymorphisms and dimensions we did not found any associations (data not shown).
4. Discussion Our results suggest the involvement of the polymorphisms of the genes of HPA axis in the occurrence of psychotic and excitement dimensions of bipolar disorder. In study performed by Maciukiewicz et al., 2012 the presence of psychotic dimension in bipolar disorder was proved and the structure of psychotic dimension resembled the one described by Serretti and Olgiati (2004). In our previous paper we found association between polymorphism rs28536160 of the AVPR1b gene and psychotic features in bipolar patients (LeszczyńskaRodziewicz et al., 2012). Current results replicated previous one,
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Fig. 1.
Table 2 Associations of SNP of CRHR1 and AVPR1b genes. SNP
Localization
BP
BP I
rs242937 rs4076452 rs28536160
CRHR1 CRHR1 AVPR1B promoter
psych(p ¼0.005) exc1(p ¼ 0.016) psych(p ¼0.0250)
none none psych(p ¼0.05)
strongly suggesting involvement of polymorphism mentioned in the ethiology of psychotic features. Arginine vasopressin is regarded as a minor ACTH secretagogue in rodents, but evidences suggest it has a role in mediating the neuroendocrine response to some acute and chronic stressors (Stewart et al., 2008). AVP is considered as weak stimulant of the HPA axis on its own, it also potentiates the stimulatory effect of CRH (Young et al., 2007). Under the chronic stress AVP expression in the paraventricular nucleus is enhanced and AVP becomes the first activator of corticotropin (Dempster et al., 2007). Studies of affected sibling pairs which had a history of psychotic, manic or depressive symptoms in the course of illness have found modest aggregation for each symptom dimension (Niehaus et al., 2005). Some studies have found scores on negative or disorganized dimension to be associated with elevated risk of psychosis in relatives (Peralta and Cuesta, 2009). In the study performed by Cardno et al. none of the dimensions were significant predictor of psychosis risk in co-twins (Cardno et al., 2008). Dempster et al. found evidence for association between the AVPR1b polymorphisms (rs35369693 and rs33985287) and childhood onset of depression, especially in women. Some studies on the other hand showed polymorphisms of both AVPR1b (rs28632197) and CRHR1 (rs878886) genes altered susceptibility to panic disorder (Keck et al., 2008). The current findings indicate that variants of CRHR1 marker (rs12938031) may promote the development of anhedonia in the face of stress. In the study performed by Utge (Utge et al., 2010) the association between rs173365 (located in CRHR1) and early morning awakening was found in female cases of depression. The polymorphism of CRHR1 marker (rs4076452) appeared to be associated with early-onset depression. In our study we detected association between rs242937 and excitement dimension. Excitement dimension consist of the OPCRIT points fulfilling the criteria for mania, this association is interesting since the majority of the studies suggest involvement of the polymorphisms in the CRHR1 gene in the ethiology of depression or the response to antidepressant treatment (Papiol et al., 2007; Ishitobi et al., 2012; Liu et al., 2007; Licinio et al., 2004). CRH acts as a neurotransmitter via CRHR1 eliciting the anxiety related behavior, and influencing arousal and attention (Polanczyk et al., 2009). We also found the association between psychotic dimension and rs242937 CRHR1 gene, since the psychotic feature may occur
as a reaction to stress and in the reaction to stress HPA activation cause release of CRH hormone acting at CRHR1 receptor to stimulate adrenocorticotropic hormone release this might be the reason why this association was found. There is also the possibility that those SNP's are in linkage disequilibrium with a sequence variant in the 5′ regulatory region that influences expression of the CRHR1 gene. For NR3C1 gene polymorphisms we have not detected any associations. It has been reported that rs6191 variant is associated with depressive symptoms in the elderly in co-existence with childhood adversity (Sinclair et al., 2012). In our previous study association between the three polymorphisms of NR3C1 gene (rs6198, rs6191 and rs33388) with the MDD disorder and predominance of depressive symptoms in the course of bipolar disorder was shown (Szczepankiewicz et al., 2011). The strength of our paper is using new approach-dimensional structure of bipolar disorder, which seems to be promising tool for investigation of more homogenous groups, thus allowing to identify genes involved in the ethiology of the symptoms rather than the disease itself. Taking into consideration the limitations, which include: (1) the exact definition of the optimal dimension to be used as a phenotype for molecular studies is not clear, also it is not known to which extent variation in symptom dimensions are influenced by genetic factors, and (2) total number of the patients included in the study, results should be interpreted very carefully. Functionality of the SNP's with which we found association is not yet fully understood, although the polymorphism rs4076452 of CRHR1 gene is located in the promoter region probably influencing transcription process, the polymorphism rs28536160 is located upstream also influencing functionality. There is also possibility that these SNPs are in strong linkage disequilibrium with other, functionally relevant variants that are causative for BP development. This may be also the reason why we identified association.
Role of funding source This study was supported by the Polish Ministry of Science and Higher Education, Grant no. N N402 243835; the Polish Ministry of Science and Higher Education had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
Conflict of interest Nothing to declare
References Allardyce, J., Suppes, T., Van Os, J., 2007. Dimensions and the psychosis phenotype. International Journal of Methods in Psychiatric Research 16 (Suppl. 1), S34–S40.
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