research article association, haplotype, and gene-gene

Hindawi Publishing CorporationThe Scientific World JournalVolume 2013 Article ID 207361 6 pageshttpdxdoiorg1011552013207361

Research ArticleAssociation Haplotype and Gene-Gene Interactions of the HPAAxis Genes with Suicidal Behaviour in Affective Disorders

Anna LeszczyNska-Rodziewicz1 Aleksandra Szczepankiewicz12 Joanna Pawlak1

Monika Dmitrzak-Weglarz1 and Joanna Hauser1

1 Department of Psychiatric Genetics Poznan University of Medical Sciences Ulica Szpitalna 2733 60-572 Poznan Poland2 Laboratory of Molecular and Cell Biology Department of Pulmonology Paediatric Allergy and Clinical ImmunologyPoznan University of Medical Sciences Ulica Szpitalna 2733 60-687 Poznan Poland

Correspondence should be addressed to Anna Leszczynska-Rodziewicz alrodziewiczumpedupl

Received 23 September 2013 Accepted 22 October 2013

Academic Editors D Ndetei and M Ota

Copyright copy 2013 Anna Leszczynska-Rodziewicz et al This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

Family twin and adoption studies have noted the heritability of specific biological factors that influence suicidal behaviour Exposureto stress is one of the factors that strongly contribute to suicide attemptsThe biological response to stress involves the hypothalamic-pituitary-adrenal axis (HPA)Therefore we found it interesting to study polymorphisms of genes involved in theHPA axis (CRHR1NR3C1 andAVPBR1)The study was performed on 597 patients 225 of whom had a history of suicide attemptsWe did not observeany significant differences in the studied polymorphisms between the group of patients with a history of suicide attempts andthe control subjects Our haplotype analysis of the AVPR1b gene revealed an association between the GCA haplotype and suicideattempts however this association was not significant after correcting formultiple testingWe did not observe any other associationin haplotype andMDR analysisWe report here a comprehensive analysis of the HPA axis genes and a lack of association for geneticvariations regarding the risk of suicide attempts in affective disorder patients Nonetheless the inconsistencies with the previouslypublished results indicate the importance of the further investigation of these polymorphisms with respect to the risk of suicideattempts

1 Introduction

According to theWHO approximately 1 million people com-mit suicide each year Therefore suicide is considered amajor public health problemThe causes of suicidal behaviourand suicide attempts are complex in that both genetic andenvironmental factors can play a role Exposure to an acuteor chronic stress accompanied by psychiatric conditionsincluding substance abuse depressedmood anxiety and alsopsychotic features can lead to suicide attempts

Family twin and adoption studies have noted the heri-tability of these features suggesting that there is a specificbiological influence on suicidal behaviour Genes containingdifferent variants interindividual differences in psychologyand related stress resilience may cause a vulnerability tosuicidal behaviour [1] as well as age sex and the history ofthe trauma A majority of the genetic studies have involved

serotonin-related genes because levels of serotonin and itsmetabolites are thought to play a role in suicidal behaviourMeta-analyses have confirmed an association between suici-dal behaviour and 5HTT (serotonin transporter) tryptophanhydroxylase (TPH1) and brain-derived neurotropic factor(BDNF) expression as well as the expression of tyrosinekinase receptor type 2 (NTRK2) [2 3]

The biological response to stress involves the hypotha-lamic-pituitary-adrenal axis (HPA) and prolonged stressmay change its function These changes can be markedby altered HPA activity (high or low cortisol levels) orreactivity (reduced or increased feedback regulation) TheseHPA disturbances are also thought to be partially predictiveof suicidal behaviour [4ndash6] and are regarded as an endophe-notype of suicidal behaviour [5] In particular AVP receptorupregulation may be critical for sustaining corticotropicresponsiveness during chronic stress or depression [7]

2 The Scientific World Journal

Jokinen et al suggested that dexamethasone suppression test(DST) nonsuppression may be a biological suicide predictorin depressed male suicide attempters [8 9] Those patientsmay be genetically predisposed to react with high levels ofHPA activity in response to a low stress andmay experience achronic state of HPA activation [10 11] This reaction occursmost likely via alteredCRHR1 (the gene controlling activationof HPA axis) expression and functionality Recently Meraliand colleagues found that CRHR1 mRNA expression waschanged in the frontal cortices of suicide victims [12] Hyper-activity of the HPA axis predicts a worse treatment outcome[13] and Binder et al suggested that dysregulation of theHPAaxis may even predict a nonresponse to antidepressant treat-ment particularly among males [14] Both low CSF5-HIAAand DST nonsuppression contribute to a fourfold increasedsuicide risk in depressed subjects in a meta-analysis per-formed byMann and Currier [5] Some studies have reportedno association between the DST test and individual suscep-tibility to suicide [15] McGowan et al observed epigeneticmodification of the glucocorticoid receptor gene as a functionof childhood abuse in the brains of suicide completers [16]Thus it is possible that HPA axis dysfunction is not linearlyrelated to suicide risk [17] Therefore it would be interestingto study the polymorphisms of genes encoding receptorsand transporters involved in the regulation of HPA axisfunction Taking into account the limited number of geneticstudies that have been published previously on the associ-ation between HPA axis genes and the history of suicideattempts we aimed in the present study to investigate thepossible association between NR3C1 CRHR1 and AVPR1bgene polymorphisms and suicidal behaviour in unipolar (UP)and bipolar (BP) patients

2 Materials and Methods

21 Patients We included 597 patients (367 female 230male) aged 18ndash84 (mean = 47 SD = 14) who met DSM-IVcriteria for bipolar disorder (391 BPI 104 BPII) or recurrentdepression (119899 = 102) and were living in the Wielkopolskaregion of Poland The diagnosis was established using theStructured Clinical Interview for DSM-IV Axis I Disorders(SCID-I) [18] Among patients with BP disorder 197 peoplehad a history of suicide attempt(s) among the UP patients28 people had a history of suicide attempt(s) The range ofduration for disease in our group was 1ndash54 years (mean 15years SD = 11) Informed consent was obtained from eachpatient after the nature of the procedure had been fullyexplained to them

22 Control Group The control group consisted of 712 sub-jects Control subjects were recruited from a group of healthyvolunteers blood donors and hospital staff and students ofthe University of Medical Sciences in Poznan and the Clini-cal Neuropsychology Unit Collegium Medicum BydgoszczOnly 40 of the control group were psychiatrically screenedusing the Polish version of the MINI Plus scale to excludeindividuals with any serious mental health problems Themean age was 377 SD = 125 The control group was matchedwith age and sex The study was approved by our local ethicscommittee

23 Genotyping DNA was extracted from using the saltingout method [19] SNP selection was carried out under thefollowing criteria functionality (in experimental functionalstudies) high frequency (MAF gt 005) indication as a tagSNP in HapMap or previously reported associations withpsychiatric disorders (both positive and negative findings)The SNPs chosen included both coding regions of knownfunctionality and noncoding regions (introns UTRs) thatcould affect gene regulationTheNR3C1CRHR1 andAVPR1bpolymorphisms were genotyped using TaqMan SNP Geno-typing assays (Applied Biosystems) and TaqMan GenotypingMaster Mix The list of SNPs analysed and the ID numbersof the TaqMan assays were used according to previouslydescribed findings [20] For each reaction plate nontemplatecontrols (water) and genomic control DNA samples wereincluded To check for genotyping accuracy control TaqManSNP genotyping assay was performed 15 of randomly cho-sen samples from both groups and identical genotypes wereidentified in all repeated samples The clinical status of thesubjects was not known during genotyping The genotypingsuccess rates were between 9603 and 9897 The totalnumber of genotyped patients differs on the different SNPsdue to genotyping errors and therefore exclusions fromfurther studies

24 Statistical Analysis Two-tailed Pearsonrsquos chi-squared(1205942) test and Fisherrsquos exact test were respectively used to testdifferences in the genotypic and allelic distribution betweenthe groups of patients and the control subjects Two-tailedpower analysis was also performed Calculations were per-formed using Statistica version 90 Odds ratios were calcu-lated using 2times 2 contingency tables by using Fisherrsquos exact testin a demo version of GraphPad InStat 3 software Linkage dis-equilibrium (LD) between the CRHR1 AVPR1b and NR3C1polymorphisms was examined by pairwise comparisons of 1199032and 1198631015840 using Haploview version 41 [21] Corrections formultiple testing were performed for multiple comparisonsin the haplotype analysis and were completed for 10000permutations

Higher-order gene-gene interactions among the testedSNPs were analysed using the nonparametric and geneticmodel-free multifactor dimensionality reduction (MDR)approach (v20 beta 83) All interactions were tested using10-fold cross-validation in an exhaustive search consideringall possible SNP combinations The model with the highesttesting balance accuracy and cross-validation consistency ofgt5 out of 10 was selected as the ldquobest modelrdquo Statistical sig-nificance was determined using a 1000-fold permutation test(MDRpermutation testingmodule v10 beta 2)The softwareis available online (httpwwwepistasisorg)

The power to detect an association for an odds ratio of 15for our sample was about 80 for each SNP

3 Results

31 HWE Analysis The genotype distributions were inHardy-Weinberg equilibrium except the following polymor-phisms rs16940655 of CRHR1 rs10052957 and rs258813 ofNR3C1 and rs28632197 ofAVPBR1 in the group of the patients

The Scientific World Journal 3

Rs61

98

Rs6191

Rs6196

Rs258813

Rs33388

rs41

4232

47

rs61

95

Rs10

0529

57

Block 1 (39 kb)1 2 3 4 5 6 7 8

98 95 959599

9999

99

9994

98

96

9819 20

97

Figure 1 Relative positions and LD estimates between NR3C1polymorphisms in the analyzed population Coloured squares cor-respond to 1198631015840 values with numerical estimates given within thesquares

and the control group We did not include those polymor-phisms into the further analysis

32 Association Analysis We did not observe any significantdifferences in the studied polymorphisms between the groupof patients with a history of suicide attempts and the controlsubjects or in genotype distribution (results shown in Tables1 2 and 3 0 = controls 1 = suicidal patients) or allelefrequencies (data not shown) Analysis stratified by genderalso did not reveal any statistically significant differencesbetween patients with suicide attempts and the control group(data not shown)We also compared the bipolar patients withthe history of suicide attempts versus bipolar patients withoutsuicide attempts in the past but no significance was foundbetween the two groups (data not shown)

33 Haplotype Analysis Linkage disequilibrium analysis ofthe three analysed genes revealed strong linkage between thepolymorphisms For theNR3C1 gene we observed linkage for5 out of 8 studied polymorphisms grouped in one haplotypeblock (1198631015840 = 10 LOD = 3911 1199032 = 0162) (Figure 1)

However none of the haplotypes were significantly morefrequent in the group of patients with suicide attemptscompared to the control group (Table 4)

For the CRHR1 gene we observed linkage in 6 out of 7polymorphisms grouped in two haplotype blocks rs4076452rs4792887 are rs110402 in one block (1198631015840 = 10 LOD = 37661199032 = 0216) and rs173365 rs242950 and rs878886 in the otherblock (1198631015840 = 10 LOD = 549 1199032 = 0285) (Figure 2)

Our haplotype analysis did not reveal any significantdifferences in the haplotype frequencies of the two blocksbetween patients with suicide attempts and control subjects(Table 5)

For theAVPR1b gene we observed linkage disequilibriumfor 3 out of 4 analysed polymorphisms grouped in one hap-lotype block (1198631015840 = 098 LOD = 4556 1199032 = 0302) (Figure 3)

In our haplotype analysis we observed an associationbetween the GCA haplotype and suicide attempts however

Table 1 Polymorphisms in GR (NR3C1) gene (genotypes)

rs41423247 CC CG GG119875

119899 119899 119899 0 65 1303 239 479 195 398 0551 27 135 87 435 86 43

rs6195 CC CT TT119875

119899 119899 119899 0 450 8893 56 1107 0 0 0281 177 885 22 110 1 05

rs6198 CC CT TT119875

119899 119899 119899 0 14 28 116 232 370 74 0331 3 153 54 2755 139 7092

rs6191 AA AC CC119875

119899 119899 119899 0 136 2715 244 487 121 2415 0721 57 2938 88 4536 49 2526

rs6196 AA AG GG119875

119899 119899 119899 0 366 7205 129 2539 13 256 021 146 73 53 265 1 05

rs33388 AA AT TT119875

119899 119899 119899 0 138 2727 245 4842 123 2431 0841 58 2915 92 4623 49 24620 control 1 suicidal patients

Table 2 Polymorphisms in AVPR1b gene (genotypes)

rs28536160 CC CT TT119875

119899 119899 119899 0 2 04 73 1448 429 85121 0 0 22 11 178 89 031

rs28373064 AA AG GG119875

119899 119899 119899 0 349 6884 139 2742 19 3751 133 665 60 30 7 35 078

rs35369693 CC CG GG119875


this association was not significant after correction for mul-tiple testing (119875 value of 0130 after 10000 permutations)(Table 6)

34 Gene times Gene Interaction Analysis The results of ourexhaustive MDR analysis evaluating combinations of alltested SNPs are summarised in Table 7

The best combination of possibly interactive polymor-phisms in predicting suicidal attempts was observed in the4-locus model However no significance was observed for


Table 3 Polymorphisms of CRHR1 gene (genotypes)

rs4076452 CC CG GG119875

119899 119899 119899 0 11 254 142 3279 280 6467 0481 5 309 45 2778 112 6914

rs12936511 CC CT TT119875

119899 119899 119899 0 394 918 34 793 1 0231 149 9198 12 741 1 062 075

rs4792887 CC CT TT119875

119899 119899 119899 0 332 772 94 2186 4 0931 130 7975 32 1963 1 061 077

rs242950 CC CT TT119875

119899 119899 119899 0 325 754 99 2297 7 162 0811 126 7778 34 2099 2 123

rs878886 CC CG GG119875

119899 119899 119899 0 304 702 118 2725 11 25 051 106 654 51 3148 5 309

rs173365 AA AG GG119875

119899 119899 119899 0 78 1801 206 4758 149 3441 091 28 1718 77 4724 58 3558

rs110402 AA AG GG119875


Table 4 Comparison of haplotype frequencies for the analysedNR3C1 polymorphisms between patients with suicide attempts andthe control group

Haplotype Haplotypefrequency

Case controlratio 120594

2119875

Block 1TCAGT 0478 0475 0479 0015 0901TAAGA 0222 0218 0224 0072 0788CAAAA 0150 0170 0142 1711 0190TAGAA 0144 0135 0147 0332 0564

this combination (the testing balanced accuracy for this 4-locus model was 90 cross-validation consistency was 510(50) and an empiric 119875 value of 0589 is based on 1000-foldpermutations) Similarly other combinations of the analysedpolymorphisms also did not reach statistical significancein predicting susceptibility to an increased risk of suicideattempts

Table 5 Comparison of haplotype frequencies for the analysedCRHR1 polymorphisms between patients with suicide attempts andthe control group



2119875

Block 1GCA 0489 0510 0481 0755 0385GCG 0323 0321 0323 00050 0943CTG 0110 0104 0112 0166 0683CCG 0074 0065 0077 0487 0485

Block 2GCC 0584 0592 0581 0118 0731ACG 0169 0187 0162 1061 0303ATC 0127 0118 0130 0312 0576ACC 0120 0103 0127 129 0256

Table 6 Comparison of haplotype frequencies for the analysedAVPR1b polymorphisms between patients with suicide attempts andthe control group



2119875

Block 1AGG 0823 0814 0826 0291 0589GGG 0076 0068 0079 0547 0459GCA 0060 0081 0052 4087 0043lowast

GGA 0041 0037 0042 0162 0687lowastNot significant after correction for multiple test using 10000 permutations(119875 = 0130)

4 Discussion

The results of our study suggested a possible associationbetween the haplotype of the AVPR1b gene and suicideattempts which did not reach significance after multiple test-ing correctionWe did not find any interactions for genotypesor for the alleles of the studied polymorphisms in the group ofsuicidal patients Also Dempster et al suggested the involve-ment of the AVPR1b gene polymorphisms in the etiology ofchildhood onset mood disorders particularly in females [22]Ben-Efraim et al found association between the high Beckscale results in patients with suicide attempts and rs33990840and a major 6-SNP haplotype of AVPR1b gene [23] Previ-ously we reported the association between the rs28536160polymorphism of the AVPR1b gene and rs1293651 of theCRHR1 gene and bipolar patients with psychotic features[20] In this study we did not find association between poly-morphisms of CRHR1 gene and suicidal patients althoughWasserman et al identified a CRHR1 SNP that showed anassociation in the suicide attempters exposed to low-mediumstress and a relationship between neurotic personality traitsand suicidality The genetic variation in the TBX19 gene (aregulator of the HPA axis) was observed by Wasserman et al[24 25] In suicidal males they found an association betweenthe T and A alleles of SNPs rs4792287 and rs110402 and theT allele of rs12936511 of the CRHR1 gene Polymorphisms in


Table 7 Multilocus interaction model for the risk of suicide attempts with the NR3C1 AVPR1b and CRHR1 genes by the MDR method

Model Loci combination Testing balancedaccuracy ()

Cross-validationconsistency () 119875 value

2-locus Rs258813 of NR3C1 and rs110402 of CRHR1 47 30 0989

3-locus Rs41423247 and rs258813 of NR3C1 and rs110402of CRHR1 52 50 0760

4-locus Rs41423247 and rs258813 of NR3C1 rs28373064 ofAVPR1b and rs110402 of CRHR1 50 90 0589

1 2 3 4 6 7 8Block 1 (24 kb) Block 2 (11 kb)

95

81

98

24 69

60

40

71 76

Rs40

7645

2

Rs4792887

Rs110402

Rs12

9365

11

Rs173365

Rs242950

Rs878886

Figure 2 Relative positions and LD estimates between AVPR1bpolymorphisms in the analyzed population Coloured squares cor-respond to 1198631015840 values with numerical estimates given within thesquares

the CRHR1 gene have also been associated with depressionand the treatment efficiency of depression [26ndash29] Papiol etal showed associations of the A allele of the CRHR1 rs110402SNP with hte age of onset and with seasonal pattern of majordepression [29] Bradley et al reported that theT andGallelesof the rs4792887 and rs110402 CRHR1 SNPs were linked withdepression [26] In the study performed by De Luca et al anassociation between haplotype variation at the CRHR2 locusand suicidal behaviour was observed [30] Interestingly theyalso found interactions between polymorphisms of CRHR1gene in suicidal schizophrenic patients [31] We did not findan association between the polymorphisms of the NR3C1CRHR1 and AVPBR1 genes and the whole group of affectivedisorder patients (data not published) However in the studyperformed by Szczepankiewicz et al [32] an associationbetween NR3C1 polymorphisms and depression was found

Themain limitations of our study that might have yieldedfalse-positive or- negative results include the following thelimited sample size of the patient group (119899 = 225) the factthat only 40 of the control group had been screened forpsychiatric disorders and the lack of Hardy-Weinberg equi-librium for the four analysed SNPsHowever taking into con-sideration the lifetime prevalence of psychiatric disorders andthe power of the studied polymorphisms (gt80) it seemsunlikely that these factors affected our results

Rs28

5361

60

Rs28373064

Rs35369693

Rs28632197

Block 1 (7 kb)

2

88 98 98

99

97

1 3 4

Figure 3 Relative positions and LD estimates between CRHR1polymorphisms in the analyzed population Coloured squares cor-respond to 1198631015840 values with numerical estimates given within thesquares

5 Conclusions

We report here a comprehensive analysis of HPA axis genesand a lack of association of genetic variation with the risk ofsuicide attempts in affective disorder patients Nonethelessthe inconsistencieswith the previously published associationsindicate the importance of further investigation of thosepolymorphisms with respect to the risk of suicide attempts

Conflict of Interests

The authors report no potential conflict of interests

Acknowledgment

This study was supported by the Ministry of Science andHigher Education Grants nos IP 2011053771 and 201101BNZ502795

References

[1] D Wasserman J Wasserman and M Sokolowski ldquoGenetics ofHPA-axis depression and suicidalityrdquo European Psychiatry vol25 no 5 pp 278ndash280 2010


[2] PMcGuffinN Perroud RUher et al ldquoThe genetics of affectivedisorder and suiciderdquo European Psychiatry vol 25 no 5 pp275ndash277 2010

[3] J Pawlak M Dmitrzak-Węglarz M Skibinska et al ldquoAssocia-tion between suicidal behavior and genes of serotonergic systemin affective disordersrdquo in press Nowiny Lekarskie 2013

[4] W Coryell E Young and B Carroll ldquoHyperactivity of thehypothalamic-pituitary-adrenal axis and mortality in majordepressive disorderrdquo Psychiatry Research vol 142 no 1 pp 99ndash104 2006

[5] J J Mann and D Currier ldquoA review of prospective studiesof biologic predictors of suicidal behavior in mood disordersrdquoArchives of Suicide Research vol 11 no 1 pp 3ndash16 2007

[6] A Pfennig H E Kunzel N Kern et al ldquoHypothalamus-pituitary-adrenal system regulation and suicidal behavior indepressionrdquo Biological Psychiatry vol 57 no 4 pp 336ndash3422005

[7] M Pompili G Serafini M Innamorati et al ldquoThe hypotha-lamic-pituitary-adrenal axis and serotonin abnormalities aselective overview for the implications of suicide preventionrdquoEuropean Archives of Psychiatry and Clinical Neuroscience vol260 no 8 pp 583ndash600 2010

[8] J Jokinen B Martensson A L Nordstrom and P Nord-strom ldquoCSF 5-HIAA and DST non-suppression-independentbiomarkers in suicide attemptersrdquo Journal of Affective Disor-ders vol 105 no 1ndash3 pp 241ndash245 2008

[9] J Jokinen and P Nordstrom ldquoHPA axis hyperactivity andattempted suicide in young adult mood disorder inpatientsrdquoJournal of Affective Disorders vol 116 no 1-2 pp 117ndash120 2009

[10] J Jokinen A-L Nordstrom and P Nordstrom ldquoCSF 5-HIAAand DST non-suppression orthogonal biologic risk factors forsuicide in male mood disorder inpatientsrdquo Psychiatry Researchvol 165 no 1-2 pp 96ndash102 2009

[11] J Jokinen and P Nordstrom ldquoHPA axis hyperactivity as suicidepredictor in elderly mood disorder inpatientsrdquo Psychoneuroen-docrinology vol 33 no 10 pp 1387ndash1393 2008

[12] Z Merali L Du P Hrdina et al ldquoDysregulation in the suicidebrain mRNA expression of corticotropin-releasing hormonereceptors and GABAA receptor subunits in frontal corticalbrain regionrdquo Journal of Neuroscience vol 24 no 6 pp 1478ndash1485 2004

[13] J P Brouwer B C Appelhof E F C van Rossum et al ldquoPre-diction of treatment response by HPA-axis and glucocorticoidreceptor polymorphisms in major depressionrdquo Psychoneuroen-docrinology vol 31 no 10 pp 1154ndash1163 2006

[14] E B Binder H E Kunzel T Nickel et al ldquoHPA-axis regula-tion at in-patient admission is associated with antidepressanttherapy outcome in male but not in female depressed patientsrdquoPsychoneuroendocrinology vol 34 no 1 pp 99ndash109 2009

[15] W Pitchot G Scantamburlo E Pinto et al ldquoVasopressin-neurophysin and DST in major depression relationship withsuicidal behaviorrdquo Journal of Psychiatric Research vol 42 no8 pp 684ndash688 2008

[16] P O McGowan A Sasaki A C DrsquoAlessio et al ldquoEpigeneticregulation of the glucocorticoid receptor in human brainassociates with childhood abuserdquo Nature Neuroscience vol 12no 3 pp 342ndash348 2009

[17] A McGirr G Diaconu M T Berlim and G Turecki ldquoPersonaland family history of suicidal behaviour is associated with lowerperipheral cortisol in depressed outpatientsrdquo Journal of AffectiveDisorders vol 131 no 1ndash3 pp 368ndash373 2011

[18] M B First R L Spitzer M Gibbon and J Williams StructuredClinical Interview for DSM-IV Axis I Disorders Clinician Ver-sion (SCID-CV) American Psychiatric Press Washington DCUSA 1996

[19] S A Miller D D Dykes and H F Polesky ldquoA simple saltingout procedure for extracting DNA from human nucleated cellsrdquoNucleic Acids Research vol 16 no 3 article 1215 1988

[20] A Leszczynska-Rodziewicz A SzczepankiewiczMDmitrzak-Weglarz M Skibinska and J Hauser ldquoAssociation betweenfunctional polymorphism of the AVPR1b gene and polymor-phism rs1293651 of the CRHR1 gene and bipolar disorder withpsychotic featuresrdquo Journal of Affective Disorders vol 138 no 3pp 490ndash493 2012

[21] J C Barrett B Fry J Maller andM J Daly ldquoHaploview analy-sis and visualization of LD and haplotypemapsrdquo Bioinformaticsvol 21 no 2 pp 263ndash265 2005

[22] E L Dempster I Burcescu K Wigg et al ldquoEvidence ofan association between the vasopressin V1b receptor gene(AVPR1B) and childhood-onset mood disordersrdquo Archives ofGeneral Psychiatry vol 64 no 10 pp 1189ndash1195 2007

[23] Y J Ben-Efraim D Wasserman J Wasserman and MSokolowski ldquoFamily-based study of AVPR1B association andinteraction with stressful life events on depression and anxietyin suicide attemptsrdquo Neuropsychopharmacology vol 38 no 8pp 1504ndash1511 2013

[24] D Wasserman M Sokolowski V Rozanov and J WassermanldquoThe CRHR1 gene a marker for suicidality in depressed malesexposed to low stressrdquo Genes Brain and Behavior vol 7 no 1pp 14ndash19 2008

[25] D Wasserman J Wasserman V Rozanov and M SokolowskildquoDepression in suicidal males genetic risk variants in theCRHR1 generdquoGenes Brain and Behavior vol 8 no 1 pp 72ndash792009

[26] R G Bradley E B Binder M P Epstein et al ldquoInfluenceof child abuse on adult depression moderation by the corti-cotropin-releasing hormone receptor generdquo Archives of GeneralPsychiatry vol 65 no 2 pp 190ndash200 2008

[27] J Licinio F OrsquoKirwan K Irizarry et al ldquoAssociation ofa corticotropin-releasing hormone receptor 1 haplotype andantidepressant treatment response in Mexican-AmericansrdquoMolecular Psychiatry vol 9 no 12 pp 1075ndash1082 2004

[28] Z Liu F Zhu G Wang et al ldquoAssociation study of corti-cotropin-releasing hormone receptor1 gene polymorphismsand antidepressant response in major depressive disordersrdquoNeuroscience Letters vol 414 no 2 pp 155ndash158 2007

[29] S Papiol B Arias C Gasto B Gutierrez R Catalan and LFananas ldquoGenetic variability at HPA axis in major depressionand clinical response to antidepressant treatmentrdquo Journal ofAffective Disorders vol 104 no 1ndash3 pp 83ndash90 2007

[30] V De Luca S Tharmalingam and J L Kennedy ldquoAssociationstudy between the corticotropin-releasing hormone receptor 2gene and suicidality in bipolar disorderrdquo European Psychiatryvol 22 no 5 pp 282ndash287 2007

[31] V De Luca S Tharmalingam C Zai et al ldquoAssociation of HPAaxis genes with suicidal behaviour in schizophreniardquo Journal ofPsychopharmacology vol 24 no 5 pp 677ndash682 2010

[32] A Szczepankiewicz A Leszczynska-Rodziewicz J Pawlak etal ldquoGlucocorticoid receptor polymorphism is associated withmajor depression and predominance of depression in the courseof bipolar disorderrdquo Journal of Affective Disorders vol 134 no1ndash3 pp 138ndash144 2011

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Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom


Jokinen et al suggested that dexamethasone suppression test(DST) nonsuppression may be a biological suicide predictorin depressed male suicide attempters [8 9] Those patientsmay be genetically predisposed to react with high levels ofHPA activity in response to a low stress andmay experience achronic state of HPA activation [10 11] This reaction occursmost likely via alteredCRHR1 (the gene controlling activationof HPA axis) expression and functionality Recently Meraliand colleagues found that CRHR1 mRNA expression waschanged in the frontal cortices of suicide victims [12] Hyper-activity of the HPA axis predicts a worse treatment outcome[13] and Binder et al suggested that dysregulation of theHPAaxis may even predict a nonresponse to antidepressant treat-ment particularly among males [14] Both low CSF5-HIAAand DST nonsuppression contribute to a fourfold increasedsuicide risk in depressed subjects in a meta-analysis per-formed byMann and Currier [5] Some studies have reportedno association between the DST test and individual suscep-tibility to suicide [15] McGowan et al observed epigeneticmodification of the glucocorticoid receptor gene as a functionof childhood abuse in the brains of suicide completers [16]Thus it is possible that HPA axis dysfunction is not linearlyrelated to suicide risk [17] Therefore it would be interestingto study the polymorphisms of genes encoding receptorsand transporters involved in the regulation of HPA axisfunction Taking into account the limited number of geneticstudies that have been published previously on the associ-ation between HPA axis genes and the history of suicideattempts we aimed in the present study to investigate thepossible association between NR3C1 CRHR1 and AVPR1bgene polymorphisms and suicidal behaviour in unipolar (UP)and bipolar (BP) patients

2 Materials and Methods

21 Patients We included 597 patients (367 female 230male) aged 18ndash84 (mean = 47 SD = 14) who met DSM-IVcriteria for bipolar disorder (391 BPI 104 BPII) or recurrentdepression (119899 = 102) and were living in the Wielkopolskaregion of Poland The diagnosis was established using theStructured Clinical Interview for DSM-IV Axis I Disorders(SCID-I) [18] Among patients with BP disorder 197 peoplehad a history of suicide attempt(s) among the UP patients28 people had a history of suicide attempt(s) The range ofduration for disease in our group was 1ndash54 years (mean 15years SD = 11) Informed consent was obtained from eachpatient after the nature of the procedure had been fullyexplained to them

22 Control Group The control group consisted of 712 sub-jects Control subjects were recruited from a group of healthyvolunteers blood donors and hospital staff and students ofthe University of Medical Sciences in Poznan and the Clini-cal Neuropsychology Unit Collegium Medicum BydgoszczOnly 40 of the control group were psychiatrically screenedusing the Polish version of the MINI Plus scale to excludeindividuals with any serious mental health problems Themean age was 377 SD = 125 The control group was matchedwith age and sex The study was approved by our local ethicscommittee

23 Genotyping DNA was extracted from using the saltingout method [19] SNP selection was carried out under thefollowing criteria functionality (in experimental functionalstudies) high frequency (MAF gt 005) indication as a tagSNP in HapMap or previously reported associations withpsychiatric disorders (both positive and negative findings)The SNPs chosen included both coding regions of knownfunctionality and noncoding regions (introns UTRs) thatcould affect gene regulationTheNR3C1CRHR1 andAVPR1bpolymorphisms were genotyped using TaqMan SNP Geno-typing assays (Applied Biosystems) and TaqMan GenotypingMaster Mix The list of SNPs analysed and the ID numbersof the TaqMan assays were used according to previouslydescribed findings [20] For each reaction plate nontemplatecontrols (water) and genomic control DNA samples wereincluded To check for genotyping accuracy control TaqManSNP genotyping assay was performed 15 of randomly cho-sen samples from both groups and identical genotypes wereidentified in all repeated samples The clinical status of thesubjects was not known during genotyping The genotypingsuccess rates were between 9603 and 9897 The totalnumber of genotyped patients differs on the different SNPsdue to genotyping errors and therefore exclusions fromfurther studies

24 Statistical Analysis Two-tailed Pearsonrsquos chi-squared(1205942) test and Fisherrsquos exact test were respectively used to testdifferences in the genotypic and allelic distribution betweenthe groups of patients and the control subjects Two-tailedpower analysis was also performed Calculations were per-formed using Statistica version 90 Odds ratios were calcu-lated using 2times 2 contingency tables by using Fisherrsquos exact testin a demo version of GraphPad InStat 3 software Linkage dis-equilibrium (LD) between the CRHR1 AVPR1b and NR3C1polymorphisms was examined by pairwise comparisons of 1199032and 1198631015840 using Haploview version 41 [21] Corrections formultiple testing were performed for multiple comparisonsin the haplotype analysis and were completed for 10000permutations

Higher-order gene-gene interactions among the testedSNPs were analysed using the nonparametric and geneticmodel-free multifactor dimensionality reduction (MDR)approach (v20 beta 83) All interactions were tested using10-fold cross-validation in an exhaustive search consideringall possible SNP combinations The model with the highesttesting balance accuracy and cross-validation consistency ofgt5 out of 10 was selected as the ldquobest modelrdquo Statistical sig-nificance was determined using a 1000-fold permutation test(MDRpermutation testingmodule v10 beta 2)The softwareis available online (httpwwwepistasisorg)

The power to detect an association for an odds ratio of 15for our sample was about 80 for each SNP

3 Results

31 HWE Analysis The genotype distributions were inHardy-Weinberg equilibrium except the following polymor-phisms rs16940655 of CRHR1 rs10052957 and rs258813 ofNR3C1 and rs28632197 ofAVPBR1 in the group of the patients


Rs61

98

Rs6191

Rs6196

Rs258813

Rs33388

rs41

4232

47

rs61

95

Rs10

0529

57

Block 1 (39 kb)1 2 3 4 5 6 7 8

98 95 959599

9999

99

9994

98

96

9819 20

97











rs41423247 CC CG GG119875

119899 119899 119899 0 65 1303 239 479 195 398 0551 27 135 87 435 86 43

rs6195 CC CT TT119875

119899 119899 119899 0 450 8893 56 1107 0 0 0281 177 885 22 110 1 05

rs6198 CC CT TT119875

119899 119899 119899 0 14 28 116 232 370 74 0331 3 153 54 2755 139 7092

rs6191 AA AC CC119875

119899 119899 119899 0 136 2715 244 487 121 2415 0721 57 2938 88 4536 49 2526

rs6196 AA AG GG119875

119899 119899 119899 0 366 7205 129 2539 13 256 021 146 73 53 265 1 05

rs33388 AA AT TT119875



rs28536160 CC CT TT119875

119899 119899 119899 0 2 04 73 1448 429 85121 0 0 22 11 178 89 031

rs28373064 AA AG GG119875

119899 119899 119899 0 349 6884 139 2742 19 3751 133 665 60 30 7 35 078

rs35369693 CC CG GG119875







rs4076452 CC CG GG119875

119899 119899 119899 0 11 254 142 3279 280 6467 0481 5 309 45 2778 112 6914

rs12936511 CC CT TT119875

119899 119899 119899 0 394 918 34 793 1 0231 149 9198 12 741 1 062 075

rs4792887 CC CT TT119875

119899 119899 119899 0 332 772 94 2186 4 0931 130 7975 32 1963 1 061 077

rs242950 CC CT TT119875

119899 119899 119899 0 325 754 99 2297 7 162 0811 126 7778 34 2099 2 123

rs878886 CC CG GG119875

119899 119899 119899 0 304 702 118 2725 11 25 051 106 654 51 3148 5 309

rs173365 AA AG GG119875

119899 119899 119899 0 78 1801 206 4758 149 3441 091 28 1718 77 4724 58 3558

rs110402 AA AG GG119875





2119875






2119875






2119875



4 Discussion









1 2 3 4 6 7 8Block 1 (24 kb) Block 2 (11 kb)

95

81

98

24 69

60

40

71 76

Rs40

7645

2

Rs4792887

Rs110402

Rs12

9365

11

Rs173365

Rs242950

Rs878886




Rs28

5361

60

Rs28373064

Rs35369693

Rs28632197

Block 1 (7 kb)

2

88 98 98

99

97

1 3 4


5 Conclusions




Acknowledgment


References







































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















Rs61

98

Rs6191

Rs6196

Rs258813

Rs33388

rs41

4232

47

rs61

95

Rs10

0529

57

Block 1 (39 kb)1 2 3 4 5 6 7 8

98 95 959599

9999

99

9994

98

96

9819 20

97











rs41423247 CC CG GG119875

119899 119899 119899 0 65 1303 239 479 195 398 0551 27 135 87 435 86 43

rs6195 CC CT TT119875

119899 119899 119899 0 450 8893 56 1107 0 0 0281 177 885 22 110 1 05

rs6198 CC CT TT119875

119899 119899 119899 0 14 28 116 232 370 74 0331 3 153 54 2755 139 7092

rs6191 AA AC CC119875

119899 119899 119899 0 136 2715 244 487 121 2415 0721 57 2938 88 4536 49 2526

rs6196 AA AG GG119875

119899 119899 119899 0 366 7205 129 2539 13 256 021 146 73 53 265 1 05

rs33388 AA AT TT119875



rs28536160 CC CT TT119875

119899 119899 119899 0 2 04 73 1448 429 85121 0 0 22 11 178 89 031

rs28373064 AA AG GG119875

119899 119899 119899 0 349 6884 139 2742 19 3751 133 665 60 30 7 35 078

rs35369693 CC CG GG119875







rs4076452 CC CG GG119875

119899 119899 119899 0 11 254 142 3279 280 6467 0481 5 309 45 2778 112 6914

rs12936511 CC CT TT119875

119899 119899 119899 0 394 918 34 793 1 0231 149 9198 12 741 1 062 075

rs4792887 CC CT TT119875

119899 119899 119899 0 332 772 94 2186 4 0931 130 7975 32 1963 1 061 077

rs242950 CC CT TT119875

119899 119899 119899 0 325 754 99 2297 7 162 0811 126 7778 34 2099 2 123

rs878886 CC CG GG119875

119899 119899 119899 0 304 702 118 2725 11 25 051 106 654 51 3148 5 309

rs173365 AA AG GG119875

119899 119899 119899 0 78 1801 206 4758 149 3441 091 28 1718 77 4724 58 3558

rs110402 AA AG GG119875





2119875






2119875






2119875



4 Discussion









1 2 3 4 6 7 8Block 1 (24 kb) Block 2 (11 kb)

95

81

98

24 69

60

40

71 76

Rs40

7645

2

Rs4792887

Rs110402

Rs12

9365

11

Rs173365

Rs242950

Rs878886




Rs28

5361

60

Rs28373064

Rs35369693

Rs28632197

Block 1 (7 kb)

2

88 98 98

99

97

1 3 4


5 Conclusions




Acknowledgment


References







































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of


















rs4076452 CC CG GG119875

119899 119899 119899 0 11 254 142 3279 280 6467 0481 5 309 45 2778 112 6914

rs12936511 CC CT TT119875

119899 119899 119899 0 394 918 34 793 1 0231 149 9198 12 741 1 062 075

rs4792887 CC CT TT119875

119899 119899 119899 0 332 772 94 2186 4 0931 130 7975 32 1963 1 061 077

rs242950 CC CT TT119875

119899 119899 119899 0 325 754 99 2297 7 162 0811 126 7778 34 2099 2 123

rs878886 CC CG GG119875

119899 119899 119899 0 304 702 118 2725 11 25 051 106 654 51 3148 5 309

rs173365 AA AG GG119875

119899 119899 119899 0 78 1801 206 4758 149 3441 091 28 1718 77 4724 58 3558

rs110402 AA AG GG119875





2119875






2119875






2119875



4 Discussion









1 2 3 4 6 7 8Block 1 (24 kb) Block 2 (11 kb)

95

81

98

24 69

60

40

71 76

Rs40

7645

2

Rs4792887

Rs110402

Rs12

9365

11

Rs173365

Rs242950

Rs878886




Rs28

5361

60

Rs28373064

Rs35369693

Rs28632197

Block 1 (7 kb)

2

88 98 98

99

97

1 3 4


5 Conclusions




Acknowledgment


References







































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of























1 2 3 4 6 7 8Block 1 (24 kb) Block 2 (11 kb)

95

81

98

24 69

60

40

71 76

Rs40

7645

2

Rs4792887

Rs110402

Rs12

9365

11

Rs173365

Rs242950

Rs878886




Rs28

5361

60

Rs28373064

Rs35369693

Rs28632197

Block 1 (7 kb)

2

88 98 98

99

97

1 3 4


5 Conclusions




Acknowledgment


References







































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of





















































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















research article association, haplotype, and gene-gene

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