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Risk and protective genetic variants in suicidal behaviour: association with SLC1A2, SLC1A3, 5-HTR1B & NTRK2 polymorphisms

Risk and protective genetic variants in suicidal behaviour: association with SLC1A2, SLC1A3,... Background: Suicidal behaviour is known to aggregate in families. Patients with psychiatric disorders are at higher risk for suicide attempts (SA), however protective and risk genetic variants for suicide appear to be independent of underlying psychiatric disorders. Here we investigate genetic variants in genes important for neurobiological pathways linked to suicidal behaviour and/or associated endophenotypes, for association with SA among patients with co-existing psychiatric illness. Selected gene-gene and gene-environment interactions were also tested. Methods: DNA was obtained from bloods of 159 patients (76 suicide attempters and 83 non-attempters), who were profiled for DSM-IV Axis I psychiatric diagnosis. Twenty-eight single nucleotide polymorphisms (SNPs) from 18 candidate genes (COMT, 5-HT2A, 5-HT1A, 5-HTR1B, TPH1, MAO-A, TPH2, DBH, CNR1, BDNF, ABCG1, GABRA5, GABRG2, GABRB2, SLC1A2, SLC1A3, NTRK2, CRHR1) were genotyped. Genotyping was performed by KBioscience. Tests of association between genetic variants and SA were conducted using Chi squared and Armitage Trend tests. Binary logistical regression analyses were performed to evaluate the contribution of individual genetic variants to the prediction of SA, and to examine SNPs for potential gene-gene and gene-environment interactions. Results: Our analysis identified 4 SNPs (rs4755404, rs2269272, rs6296 and rs1659400), which showed evidence of association with SA compared to a non-attempter control group. We provide evidence of a 3-locus gene-gene interaction, and a putative gene-environment interaction, whereby genetic variation at the NTRK2 locus may moderate the risk associated with history of childhood abuse. Conclusion: Preliminary findings suggest that allelic variability in SLC1A2/3, 5-HTR1B and NTRK2 may be relevant to the underlying diathesis for suicidal acts. Background suicide is not exclusively determined by a psychiatric ill- Suicide represents a worldwide public health problem ness (or an alternative stressor), but rather that indivi- and is a leading cause of death among those aged 15-44 duals may have a predisposition or tendency towards years in many developed countries, representing a signif- suicidal ideation, which is aggravated further by one or icant social and economic burden http://www.who.int/ more stressors [1]. A greater understanding of clinical mental_health/prevention/suicide. According to the and biological risk factors will help us understand more stress-diathesis model of suicidal behaviour, risk of fully this model of suicidal behaviour and inform new therapies and tailored interventions. The molecular pathology of suicidal behaviour * Correspondence: murphyth@tcd.ie remains complex; epidemiological studies have demon- Department of Psychiatry & Mental Health Research, St. Vincent’s University strated familial clustering of suicide and suicidal beha- Hospital, and School of Medicine & Medical Science, University College Dublin, Elm Park, Dublin 4, Ireland viour [2]. Meta-analysis of published twin case studies Full list of author information is available at the end of the article © 2011 Murphy et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 2 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 for suicide found a higher rate of concordance for sui- Belfast, Omagh, Dublin, Portlaoise and Ballinasloe) were cide and for suicidal behaviour in monozygotic (MZ) invited to take part in a clinical and molecular genetics versus dizygotic (DZ) twins, establishing a solid genetic study of suicidal behaviour in major psychiatric disorders link [3]. Currently, risk assessment of suicidal behaviour over a year long recruitment period. In total, 159 patients relies heavily on clinical variables [4]. Indeed, patients gave written informed consent for the study. Patients with psychiatric disorders are at higher risk for suicide were interviewed for Axis I Psychiatric Disorders using attempt (SA) [5-8], however protective and risk genetic the Structured Clinical Interview for DSM-IV [24]. His- variants for suicide appear to be independent of under- tory of attempted suicide was recorded using the Colum- lying psychiatric disorders [9-11]. Identifying relevant bia University Suicide History Questionnaire [25], which genetic variants or single nucleotide polymorphisms incorporates the Scale for Suicide Ideation [26], and the (SNPs) in genes intimately linked to various neurobiolo- Suicide Intent Scale [27]. A suicide attempt was defined gical pathways, whose alteration may contribute to suici- as a completed act of self-harm with at least some dal behaviour, may provide insight into the etiological expressed intent to die (scoring at least 1 on item 10 of processes that underlie suicidal behaviour and identify Suicide Intent Scale [27]). Seventy-six (48% Male, 52% novel biological therapeutic targets. Female; Mean age: 34.7 yrs) had a history of SA and 83 Numerous neurobiological pathways have been impli- (61.4% Male, 38.6% Female; Mean age: 40.7 yrs) had not. cated in the etiology of suicide and suicidal behaviour. Childhood abuse was defined as the presence or absence Deregulation of the monoaminergic transmitter systems of a history of sexual and/or physical abuse under the age (norepinephrine, dopamine and serotonin) [12,13], of 16. Further clinical variables from clinical and demo- gamma aminobutyric acid (GABA) inhibitory neuro- graphic assessments are outlined in Table 1. All clinical transmitter system [14,15], glutamatergic excitatory neu- research interviews were performed by a trained research rotransmitter system [14,15], lipid metabolism [16,17], psychiatrist or research psychiatric nurse. Ethics approval cannabinoid system [18] and neurotrophic signalling was obtained for the study from the St Vincent’sHealth- factors [19] are linked to suicidal behaviour. Interest- care Group Ethics and Medical Research Committee. ingly, the hypothalamic-pituitary-adrenal (HPA) axis maybeinvolvedinincreased suicidal behaviourin Gene and SNP selection response to adversity during development [20], hence In this study, genes intimately linked to numerous neuro- highlighting the contribution of early environmental fac- biological pathways considered important for the patho- tors to suicide risk. genesis of suicide and/or associated disorders or Suicidal behaviour is a complex trait; therefore it is endophenotypes, were selected. Genes from the following likely to be the result of a combination of numerous pathways were considered, monoaminergic transmitter environmental and genetic factors with an added layer systems (norepinephrine, dopamine and serotonin), GABA of complexity via potential gene-gene (GxG) and gene- inhibitory neurotransmitter system, glutamatergic excita- environment (GxE) interaction effects [21]. Conse- tory neurotransmitter system, HPA axis and cannabinoid quently, investigating the relationship between genetic system. Genes important for cholesterol transport and variants and environmental factors (e.g. childhood abuse neural growth and differentiation were also selected. or alcoholism) is an important step towards elucidating Twenty-eight SNPs from the 18 selected genes (COMT, the mechanisms behind suicidal behaviour. 5-HT2A, 5-HT1A, 5-HTR1B, TPH1, MAO-A, TPH2, DBH, Here we test the hypothesis that genetic variants in CNR1, BDNF, ABCG1, GABRA5, GABRG2, GABRB2, candidate genes important for neurobiological pathways SLC1A2, SLC1A3, NTRK2, CRHR1)wereincluded inour linked to suicidal behaviour and/or associated endophe- analysis. SNPs, within these 18 genes, were screened for notypes, may confer a protective [22] or risk effect on known genetic associations with suicide, suicidal beha- SA among patients with co-existing psychiatric illness viour and/or associated endophenotypes using biomedical (suicide attempters versus non-attempter controls). In online resources PubMed http://www.ncbi.nlm.nih.gov/ addition to main genetic effects, we also tested selected pubmed and OMIM http://www.ncbi.nlm.nih.gov/omim. GxG and GxE interactions for association with SA. Priority was given to functional SNPs or SNPs within regulatory regions utilising online genetic databases Methods ensembl http://www.ensembl.org/index.html and DbSNP Clinical sample collection http://www.ncbi.nlm.nih.gov/projects/SNP/. The study consisted of 159 psychiatric patients recruited as part of the Ireland North/South Urban/Rural Epide- Genotyping miologic (INSURE) collaborative project [23]. Briefly, DNA was extracted from patient blood samples using consecutive newly referred patients to six Community standard techniques. Flanking SNP sequences were Psychiatric Clinics on the island of Ireland (Donegal, obtained from DbSNP and all genotyping assays were Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 3 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 Table 1 DSM-IV psychiatric diagnosis and clinical features of patient samples Attempter (n = 76) n (%*) Non-attempter (n = 83) n (%*) P Value Sex 0.124 Male 36(48) 51 (61.4) Female 39 (52) 32 (38.6) Mean age (years) 34.7 40.7 0.017 Positive 1st degree family history of suicide attempt 26 (35.6) 14 (17.1) 0.014 Child abuse (Physical and/or sexual) 37 (49.3) 27 (32.5) 0.047 Axis I Diagnosis 42 (55.3) 36 (43.4) 0.18 Substance-related disorders 24 (31.6) 21 (25.3) 0.334 Substance abuse/dependence 38 (50) 29 (34.9) 0.078 Alcohol abuse/dependence 6 (8.8) 7 (8.6) 1 Schizophrenia and other psychotic disorders Bipolar disorders 5 (7.4) 4 (4.8) 0.786 Major depressive disorder 48 (63.2) 37 (44.6) 0.022 Anxiety disorders 32 (42.7) 25 (30.1) 0.14 Eating disorders 1 (1.3) 0 (0) 0.965 §P value was determined by Fishers exact or Chi squared test in all comparisons, with the exception of age, where a non-parametric Mann-Whitney test was used to determine the P Value. *Illustrated percentages of variables are calculated for valid cases/controls only. In some cases certain clinical or demographic variables could not be obtained from patients charts. designed and validated by KBioscience (Hertfordshire, four genotype models (Additive (XX = 0, XY = 1, UK). Genotyping for SNP analysis was performed by YY = 2), Dominant (XX = 0, XY & YY = 1), Over- KBioscience using the competitive allele specific PCR dominant (XX & YY = 0, XY = 1) and Recessive (XX (KASP) chemistry coupled with a FRET-based genotyp- & XY = 0, YY = 1); X = Major allele, Y = Minor ing system http://www.kbioscience.co.uk/reagents/ allele). For all models, except the additive model, KASP/KASP.html. Genotyping data was viewed using Pearson’s Chi-square test of association was used. For the additive model an exact Armitage trend test was SNPviewer (KBioscience, Hertfordshire, UK), allowing graphical viewing of the clusters that group the allele preformed. Binary logistical regression analyses were calls. performed to evaluate the contribution of the geno- SNPs in linkage disequilibrium (LD) with SNPs of type model associated with SA at each locus in the interest were identified using a combination of informa- prediction of attempted suicide, correcting for poten- tion from Ensembl http://www.ensembl.org/index.html tial confounders such as age, gender and certain psy- and Haploview http://www.broadinstitute.org/haploview/ chiatric disorders and to interrogate associated SNPs haploview. for potential GxG and GxE interactions. Analysis of potential GxE interactions were applied to SNPs with Data analysis evidence of association in at least one genetic model Deviations from Hardy Weinberg Equilibrium (HWE) (n = 3) and to one SNP which showed evidence of were calculated using the exact test implemented by association in a gender specific manner (n = 1) and SNP and Variation Suite (SVS) 7 software (Bozeman, not examined for all candidate SNPs listed in this MT 59718 USA; http://www.goldenhelix.com/SNP_Var- study. In addition, GXG interactions analysis was per- iation/svstrial.html). formed on these 4 SNPs, which showed evidence of Statistical tests of association examining the relation- association with SA and not examined for all candi- ship between patient’s alleles or genotype, at each of the date SNP listed in this study. 28 genetic loci, and suicide attempt were performed A non-parametric Mann-Whitney test was used to using Pearson’s Chi-square test or Fisher’s exact test calculate the difference in age between cases and con- (whencountsare low).Thisanalysiswas performed trols. For all other comparisons of clinical and demo- both in SPSS and SNP and Variation Suite for verifica- graphic variables a Fisher’s exact test or Chi-squared tion purposes. test of association was used. All statistical analysis was performed on SPSS (PASW statistics 18, Chicago, Illi- SNPs which showed a modest level of association in the original allelic and genotype tests of association nois, USA) and genotypic associations verified using (P < 0.1) and one SNP which showed a gender specific SNP and Variation Suite (SVS) 7 software. For all tests, association with SA, were further analysed by applying significance was ascribed at P < 0.05. Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 4 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 Table 2 Association of candidate markers Results Clinical and psychological features of study population Gene Symbol Allele RS number Significance (p) The mean age of the suicide attempter and non-attemp- Allelic Genotypic ter groups was significantly different (34.72 years versus SLC1A3 C/T rs2269272 0.562 0.075 40.67 years, respectively, (P = 0.017)). The SA group HTR1B C/G rs6296 0.895 0.047 were more likely to have a diagnosis of major depressive SLC1A2 G/C rs4755404 0.024 0.069 disorder (P = 0.022), a positive first degree family his- COMT G/A rs4680 0.123 0.205 tory of attempted suicide (P = 0.014), and a history of HTR2A G/A rs6313 0.696 0.568 child abuse (physical or sexual) (P = 0.047). No other C/T rs6311 0.628 0.307 demographic or clinical variables were statistically differ- HTR1A C/G rs6295 0.714 0.907 ent between the two groups (Table 1). TPH1 G/T rs1799913 0.136 0.192 G/T rs1800532 0.136 0.192 Candidate gene selection TPH2 A/G rs7305115 0.647 0.559 In this study, genes considered important in various DBH T/C rs2519152 0.377 0.761 neurobiological pathways associated with suicide and/or CNR1 T/G rs6454674 0.948 0.986 associated disorders or endophenotypes were chosen. T/C rs806368 0.695 0.885 Overall, 18 genes were selected for inclusion in our ana- G/A rs6801844 0.883 0.612 lysis. The majority of genes (n = 8; COMT, 5-HT2A, 5- BDNF C/T rs6265 0.422 0.650 HT1A, 5-HTR1B, TPH1, MAO-A, TPH2, DBH)are ABCG1 A/G rs1044317 0.261 0.397 important for monoaminergic transmitter systems (nore- C/G rs225374 0.631 0.823 pinephrine, dopamine and serotonin). Key genes of the C/G rs914189 0.862 0.986 GABA inhibitory neurotransmitter system (n = 3; GABRG2 C/A rs211014 0.398 0.180 GABRA5, GABRB2, GABRB2), glutamatergic excitatory GABRB2 A/G rs1816072 0.270 0.276 neurotransmitter system (n = 2; SLC1A2, SLC1A3), HPA C/T rs2491397 0.310 0.594 axis (n = 1; CRHR1), cannabinoid system (n = 1; CNR1), NTRK2 A/G rs1659400 0.453 0.474 cholesterol transport (n = 1; ABCG1), neural growth G/A rs1187272 0.137 0.388 and differentiation (n = 2; BDNF &NTRK2)werealso CRHR1 A/G rs110402 0.805 0.763 selected (see Additional File 1).Intotal,28SNPspre- T/G rs242924 0.935 0.463 sent within our 18 candidate genes were identified. The C/T rs7209436 0.852 0.872 majority of SNPs (24/28 SNPs) had previous evidence of MAOA T/G rs1799835 NA NA association with suicidal behaviour and/or associated GABRA5 A/G rs140681 NA NA disorders or endophenotypes (see Additional File 1). P value obtained from Pearson’s Chi-square test or Fisher’s exact test. NA = not applicable, as genotype are identical for case and controls. Genetic variants and suicide attempts Results of basic allelic and genotypic tests of association with SA in an over-dominant genotype model, whereby for each SNP and SA are illustrated in Table 2. Basic a heterozygote (C/G) genotype was more frequently pre- allelic and genotypic association analyses revealed two sent in patients in the SA group than non-attempter significant associations with SA; rs4755404 (Intronic group (P = 0.028). Rs2269272 variants revealed evidence region of SLC1A2; P = 0.024: Chi-square test) and of association in a recessive genotype model (P = 0.042; rs6296 (Promoter CpG island of 5-HTR1B;P=0.047: Chi-square test), with the T/T genotype more frequent Chi-square test) loci. In addition a third SNP, rs2269272 in the non-attempter group than attempter group (3’untranslated region (UTR)) in SLC1A3; P = 0.075: (Table 3). Chi-square test), with a P value < 0.1 was chosen for SNPs of interest were investigated for possible associa- further analyses. Next, four genotype models (Additive, tions with other clinical variables illustrated in Table 1. Dominant, Over-Dominant and Recessive) were tested SNP rs2269272 showed no evidence of association with for association with attempter status at each locus other clinical variables in the study. A dominant geno- (Table 3). type at the rs4755404 locus was associated with patients Rs4755404 yielded evidence of association in an addi- with a history of schizophrenia and other psychotic dis- tive and dominant genotype model (P = 0.029: Exact orders (P = 0.012; Chi-square test). A recessive genotype Armitage Trends test; P = 0.026: Chi-square test, at the rs6296 locus yielded an association with respectively), where patients with a G/C or G/G geno- individuals who abuse/depend on alcohol (p = 0.035). type were significantly morelikelytobepresent in the Binary logistical regression analyses were performed to SA group. Variation at the rs6296 locus was associated evaluate the contribution of individual risk/protective Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 5 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 Table 3 Genotype frequencies and genetic models of association Genotype Frequencies Significance (p value) Gene symbol RS number Genotype Controls SA cases Additive Dominant Over-Dominant Recessive SLC1A3 rs2269272 CC/CT/TT 0.687/0.229/0.084 0.667/0.32/0.013 0.56 0.787 0.199 0.042 HTR1B rs6296 GG/CG/CC 0.59/0.265/0.145 0.5/0.432/0.068 0.847 0.256 0.028 0.121 SLC1A2 rs4755404 CC/CG/GG 0.451/0.427/0.122 0.28/0.52/0.20 0.029 0.026 0.243 0.182 P value obtained from Pearson’s Chi-square test for all genotype tests, with the exception of the additive model, where an exact Armitage trend test was used. Numbers highlighted in bold represent genotype models that were significantly associated with Suicide attempt status (P = < 0.05). SA: Suicide Attempt. polymorphisms in the prediction of attempted suicide. significant predictor of SA in females (P = 0.048; OR = After controlling for possible confounders such as age, 2.968; 95% C.I 1.01- 8.72). gender, alcohol abuse/dependence (rs6296 only) and Finally, we investigated the effect of susceptibility loci schizophrenia (rs4755404 only), rs2269272 recessive on suicide attempts by other susceptibility loci by exam- genotype model was no longer a significant predictor of ining various two and three way G×G interactions. SA (P0.121; Odds ratio (OR) = 0.83, 95% C.I: .022- Logistic regression was used to model SA risk as a func- 1.563). Rs4755404 dominant genotype model and rs6296 tion of the genotype models associated with SA at each over-dominant genotype model were still significant pre- locus and 2-locus and 3-locus G×G interactions dictors of SA (P = 0.031; OR = 2.198; 95% CI 1.059- (Table 4). Controlling for possible confounders, age, 4.563 and P = 0.023; OR = 2.244; 95% CI 1.096-4.597, gender, alcohol abuse/dependence and schizophrenia, a respectively). 3-locus gene (G×G×G) interaction (rs6296 (C/G) × Each locus was also analysed for deviations from rs4755404 (C/G or G/G) × rs1659400 (C/C) was a sig- HWE. Deviations from HWE were observed at the nificant predictor of SA (P = 0.046). rs6296 locus in the non-attempter group (P = 0.004) To evaluate further the association between suscept- and at rs2269272 locus in the non-attempter group (P = ibility genotypes only and environmental risk factors, 0.014). logistic regression was used to model risk as a function of the genotype models associated with SA at each Genetic and environmental interaction analysis locus, environmental risk factors and their interaction. Individual SNPs were analysed for evidence of gene by Results provide evidence of a possible G (C/C genotype) sex interaction, to identify possible sex-specific associa- × E (history of childhood abuse (both physical and sex- tions with SA. Two gene-sex interactions were observed. ual)) interaction at the rs1659400 locus. Interestingly, A sex by rs2269272 interaction was found where a T/T rs1659400 was not associated with SA (p = 0.823, Chi- genotype was more frequent in non-attempter male SA square), however when all variables (including gender group. A gene by sex interaction was also observed for and age) are entered into a logistic regression analysis, an intronic SNP, rs1659400, in the NTRK2 gene. Con- the G×E interaction term is close to significance trolling for age, a C/C genotype at this locus was a (P = 0.056, Table 5). Moreover, since a C/C genotype Table 4 Final gene by gene interaction model: Logistic regression analysis 95% C.I for OR Variable B S.E Wald df P value OR Lower Upper Age -.043 .015 8.305 1 .004 .958 .930 .986 Sex -1.062 .422 6.349 1 .012 .346 .151 .790 alcohol abuse/dependence 1.164 .422 7.598 1 .006 3.204 1.400 7.333 schizophrenia and other psychotic disorders - 0.139 .810 .029 1 .864 .870 .178 4.257 rs6296 1.104 .868 1.615 1 .204 3.015 .550 16.539 rs4755404 1.291 .593 4.736 1 .030 3.636 1.137 11.628 rs1659400 .953 .934 1.041 1 .308 2.592 .416 16.159 rs6296 by rs4755404 -1.141 1.065 1.150 1 .284 .319 .040 2.573 rs6296 by rs1659400 -1.356 1.440 .887 1 .346 .258 .015 4.332 rs1659400 by rs4755404 -2.060 1.139 3.275 1 .070 .127 .014 1.187 rs6296 by rs4755404 by rs1659400 3.613 1.811 3.982 1 .046 37.087 1.067 1289.592 Constant .592 .778 .579 1 .447 1.808 B, unstandardised logistic regression coefficient; S.E, Standard error; Wald, Wald statistic; df, Degrees of freedom; OR, Odds ratio; C.I., Confidence interval Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 6 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 Table 5 Gene by environment interaction: Logistic transporters could impair reuptake of glutamate, hence regression analysis prolong synaptic activation and potentially lead to cyto- 95% C.I for OR toxic damage to neurons and glia [15]. SLC1A2 and SLC1A3 are downregulated in the brains of MDD Variable B S.E Wald df P OR Lower Upper value patients compared to controls [28]. Moreover, decreased Sex -.384 .358 1.152 1 .283 .681 .338 1.373 SLC1A3 expression has been observed in suicide brains Age -.035 .013 7.669 1 .006 .965 .941 .990 [29]. rs1659400 -.038 .426 .008 1 .928 .962 .417 2.219 In this study, the SLC1A2 gene variant, rs4755404, was abuse -.508 .469 1.175 1 .278 .602 .240 1.508 associated with SA and schizophrenia and other psycho- rs1659400 by 1.518 .795 3.641 1 .056 4.562 .960 21.684 tic disorders. Consistent with these findings, rs4755404 abuse was previously associated with schizophrenia in a Japa- Constant 1.406 .627 5.035 1 .025 4.079 nese patient cohort [30]. In contrast, the SLC1A3 gene Females variant, rs2269272, was significantly associated with Only male non-attempters, where a gene-sex interaction was Age -.025 .018 1.911 1 .167 .975 .941 1.010 observed. The T/T genotype is absent from the attemp- rs1659400 .166 .634 .068 1 .794 1.181 .341 4.093 ter group and over-represented in the male non-attemp- abuse .003 .774 .000 1 .997 1.003 .220 4.571 ter group, suggesting a T/T genotype may confer a rs1659400 by 2.653 1.378 3.707 1 .054 14.202 .953 211.572 protective effect on risk of SA, particularly in males abuse with underlying psychiatric disorders. HWE analysis Constant .633 .848 .556 1 .456 1.883 revealed that the control groupwasnotinequilibrium B, unstandardised logistic regression coefficient; S.E, Standard Error; Wald, for the rs2269272 locus, which is likely due to the fact Wald statistic; df, degrees of freedom; OR, Odds ratio; C.I., Confidence interval that our control group is not “disease-free” but rather consists of individuals with underlying psychiatric condi- was associated with female SA, a G×E interaction was tions. However, the possibility that some other factor examined in females only. A G×E interaction contribu- may be influencing the over-representation of T allele ted to the predictive ability of the model (P = 0.054, homozygotes in the non-attempter group cannot be Table 5), a trend which did not reach statistical signifi- ruled out. Therefore, further investigation in a larger cance. Taken together our results suggest that indivi- cohort of patients is warranted. Taken together, our duals who experienced childhood abuse (physical or findings support the glial hypothesis of mood abnormal- sexual) and have a C/C genotype at the rs1659400 locus ities [28] and concur with the literature on a putative role of glutamate dysregulation in suicidal behaviour. may be more susceptible to SA. The serotonin (5-HT) system is the most widely stu- died area of neurobiological suicide research [21]. Aber- Discussion rant 5-HT receptor binding has been implicated in We have identified 4 SNPs (rs4755404, rs2269272, suicide and SA [12]. 5-HTR1B binding is decreased in rs6296 and rs1659400) in genes SLC1A2, SLC1A3, 5- the prefrontal cortex of suicide brains [31]. Previously a HTR1B and NTRK2, respectively, which showed evi- 5-HTR1B promoter CpG island genetic variant, rs6296, dence of association with SA compared to a non- was associated with SA [32]. However, findings are attempter psychiatric control group. At present, there inconsistent and a number of studies have found no evi- is no published data on 3/4 of the genetic variants dence of association [33,34]. Rs6296 has also been asso- (rs4755404, rs2269272 and rs1659400) reported here ciated with substance use disorders, major depression and their association with suicide or SA. In addition, and inconsistently with alcohol abuse [33,35]. Here we we identified a 3-locus (rs6296 (C/G) × rs4755404 (C/ G or G/G) × rs1659400 (C/C)) G×G interaction, which report a significant association between the rs6296 locus was a significant predictor of SA, suggesting that varia- and SA. In addition, persons with a C/G genotype and a tion in SLC1A2, 5-HTR1B and NTRK2 genes may con- history of abuse or dependence on alcohol were signifi- tribute to the risk of SA independently, and in an cantly associated with SA, but a gene × alcohol interac- interactive manner. This paper provides evidence for tion was not evident, suggesting that they represent the first time of a putative G×E interaction, where additive risk factors. These findings provide the impetus genetic variation at the rs1659400 locus may moderate for future studies in a cohort of alcohol abuse/depen- the risk associated with history of childhood abuse and dence patients to further understand the relevance of subsequent suicidal acts. rs6296 genetic variants and SA in patients with a history of alcohol abuse/dependence. SLC1A2 and SLC1A3 are glial high-affinity transporter NTRK2 (TRKB) encodes the receptor for BDNF. Aber- molecules that regulate glutamate concentrations at rant neurotrophic signalling has been implicated in synapses [15]. Aberrant expression of these key Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 7 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 suicide risk by various studies [36,37]. BDNF and genetic and environmental risk factors. In this study, NTRK2 mRNA and protein expression are reported multiple testing correction, such as Bonferroni correc- downregulated in the prefrontal cortex and hippocam- tion, was not applied. Bonferroni correction can be pus of suicide victims compared to controls [36,37]. The regarded as ultraconservative [50] and ignores the func- majority of studies have focused on functional BDNF tional candidate gene study design utilised, which is variant, rs6265, which has been inconsistently implicated likely to increase the prior probability of detecting an association. In addition, given our modest sample size, in suicide and MDD [38,39]. In this study, we found no Bonferroni correction is likely to result in large type II evidence of association between rs6265 and SA, consis- error rates. Arguably the best solution to type I error is tent with a previous report [40]. Previously, a number of genetic variants within the NTRK2 gene have been asso- replication [50]. ciated with SA among depressed patients [41]. We observed a significant association with NTRK2 intronic Conclusion genetic variant, rs1659404, and SA in females. In conclusion,wehaveidentified statistically as well as Rs1659400 is in strong LD with several other SNPs biologically significant genetic polymorphisms that may within the NTRK1 gene, some of which have been be relevant to the underlying diathesis for suicidal acts implicated in alcohol dependence and depression [1]. An understanding of the functional consequence of [42,43]. these SNPs from a neuropathological standpoint would To date a number of gene × childhood adversity inter- be advantageous to advance our understanding of their actions have been reported in psychiatric patients role in SA. The SNP associations identified in this [44-46]. Childhood trauma (including abuse) has been study, although modest, merit further investigation in a reported to interact with low expressing 5-HTTLPR gen- larger cohort of suicide attempters and may contribute otypes and moderate the risk of suicidal behaviour [47]. to future meta-analysis of suicidal behaviour susceptibil- Recently, an interaction between child maltreatment and ity loci. Moreover, follow-up research of the genetic sus- 5-HTT polymorphisms and suicidal ideation among chil- ceptibly polymorphisms identified in this study may dren was described [48]. Here we report, for the first increase our understanding of the complex relationship time, a possible moderation effect of a NTRK2 poly- of genetic and environmental factors in suicidal beha- morphism on childhood abuse and risk for future suici- viour in major psychiatric disorders. dal acts. It is important to note that a history of childhood abuse was assessed in this study by a trained Contributions of Authors clinician as opposed to self-report questionnaires. TMM performed genetic and statistical analysis, inter- Recent research has demonstrated that clinician ratings pretation of the data and drafted the manuscript. MR of developmental histories, such as childhood sexual and carried out blood collection and Clinical rating and physical abuse, are in agreement with patient’sself- contributed to study design. TF participated in the reports and thus supports the validity of clinician design of the study and helped to draft the manuscript. reports for numerous clinical variables, including child- CK participated in the design of the study. RM partici- hood abuse assessment [49]. Future studies could inves- pated in the design of the study. JO’G carried out tigate the putative interaction of this genetic variant blood collection and Clinical rating. EC participated in with childhood trauma score, which would include sex- the design of the study. JB carried out blood collection ual, physical and emotional abuse and neglect. Such a and Clinical rating. MR carried out blood collection studywould provideamorecomprehensiveassessment and Clinical rating. AJ participated in the design of the of gene × childhood adversity interaction and risk for study. AM carried out blood collection and Clinical SA at this locus. rating. NB carried out blood collection and Clinical A number of limitations are apparent in the current rating. AC carried out blood collection and Clinical study. Firstly, case/control samples were not age- rating DL carried out Clinical rating. SB carried out matched, with the SA group having a significantly Clinical rating. PT participated in statistical and younger mean age. The SA group also contained a genetic analysis and helped to draft the manuscript. greater number of individuals with a family history of AB extracted DNA and prepared sample for storage SA and a history of childhood abuse. In addition, rates and genotyping. LQ participated in statistical analysis. of MDD diagnoses were different in SA and non- LD participated in statistical and genetic analysis and attempter psychiatric controls. However, the genetic var- helped to draft the manuscript. CK participated in the iants identified in this study were not associated with design of the study and help to draft the manuscript. either MDD, a family history of SA or abuse. Moreover, KMM participated in the design of the study and help our sample size may have reduced power to detect small to draft the manuscript. All authors have read and genetic effects, or alternative interactions between approved the final manuscript. Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 8 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 8. Winokur G, Tsuang M: The Iowa 500: suicide in mania, depression, and Additional material schizophrenia. Am J Psychiatry 1975, 132:650-651. 9. Henriksson MM, Aro HM, Marttunen MJ, Heikkinen ME, Isometsa ET, Additional file 1: Summary of candidate genes. A comprehensive list Kuoppasalmi KI, Lonnqvist JK: Mental disorders and comorbidity in of all gene names, symbols and SNPs studied in the current report suicide. Am J Psychiatry 1993, 150:935-940. 10. Vijayakumar L, Rajkumar S: Are risk factors for suicide universal? A case- control study in India. Acta Psychiatr Scand 1999, 99:407-411. 11. Brent DA, Bridge J, Johnson BA, Connolly J: Suicidal behavior runs in families. A controlled family study of adolescent suicide victims. Arch List of abbreviations Gen Psychiatry 1996, 53:1145-1152. DZ: Dizygotic; GxG: Gene-Gene; GABA: Gamma Aminobutyric Acid; GxE: 12. Stockmeier CA, Shapiro LA, Dilley GE, Kolli TN, Friedman L, Rajkowska G: Gene-Environment; HPA: Hypothalamic-Pituitary-Adrenal; HWE: Hardy Increase in serotonin-1A autoreceptors in the midbrain of suicide Weinberg Equilibrium; INSURE: Ireland North/South Urban/Rural victims with major depression-postmortem evidence for decreased Epidemiologic; LD: Linkage Disequilibrium; MZ: Monozygotic; OR: Odds Ratio; serotonin activity. J Neurosci 1998, 18:7394-7401. SA: Suicide Attempts; SNPs: Single Nucleotide Polymorphisms; SVS: SNP and 13. Bach-Mizrachi H, Underwood MD, Tin A, Ellis SP, Mann JJ, Arango V: Variation Suite; UTR: Untranslated Region Elevated expression of tryptophan hydroxylase-2 mRNA at the neuronal level in the dorsal and median raphe nuclei of depressed suicides. Mol Acknowledgements Psychiatry 2008, 13(507-513):465. We acknowledge funding from the Craig-Dobbin Newman Fellowship in 14. Sequeira A, Mamdani F, Ernst C, Vawter MP, Bunney WE, Lebel V, Rehal S, Mental Health Research and the Programme for Research in Third-Level Klempan T, Gratton A, Benkelfat C, Rouleau GA, Mechawar N, Turecki G: Institutions (PRTCI) and statistical advice from the Centre for Support and Global brain gene expression analysis links glutamatergic and Training in Analysis and Research (CSTAR), University College Dublin. We GABAergic alterations to suicide and major depression. PLoS One 2009, 4: would like to acknowledge assistance from Aggie Boylan, Hammad Khan e6585. and Sharyn Carley. 15. Choudary PV, Molnar M, Evans SJ, Tomita H, Li JZ, Vawter MP, Myers RM, Bunney WE Jr, Akil H, Watson SJ, Jones EG: Altered cortical glutamatergic Author details and GABAergic signal transmission with glial involvement in depression. Department of Psychiatry & Mental Health Research, St. Vincent’s University Proc Natl Acad Sci USA 2005, 102:15653-15658. 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Caspi A, Sugden K, Moffitt TE, Taylor A, Craig IW, Harrington H, McClay J, Mill J, Martin J, Braithwaite A, Poulton R: Influence of life stress on • Thorough peer review depression: moderation by a polymorphism in the 5-HTT gene. Science • No space constraints or color figure charges 2003, 301:386-389. • Immediate publication on acceptance 46. Prathikanti S, Weinberger DR: Psychiatric genetics–the new era: genetic research and some clinical implications. Br Med Bull 2005, 73-74:107-122. • Inclusion in PubMed, CAS, Scopus and Google Scholar 47. Roy A, Hu XZ, Janal MN, Goldman D: Interaction between childhood • Research which is freely available for redistribution trauma and serotonin transporter gene variation in suicide. Neuropsychopharmacology 2007, 32:2046-2052. Submit your manuscript at www.biomedcentral.com/submit http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Behavioral and Brain Functions Springer Journals

Risk and protective genetic variants in suicidal behaviour: association with SLC1A2, SLC1A3, 5-HTR1B & NTRK2 polymorphisms

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Springer Journals
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Copyright © 2011 by Murphy et al; licensee BioMed Central Ltd.
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Biomedicine; Neurosciences; Neurology; Behavioral Therapy; Psychiatry
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21711518
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Abstract

Background: Suicidal behaviour is known to aggregate in families. Patients with psychiatric disorders are at higher risk for suicide attempts (SA), however protective and risk genetic variants for suicide appear to be independent of underlying psychiatric disorders. Here we investigate genetic variants in genes important for neurobiological pathways linked to suicidal behaviour and/or associated endophenotypes, for association with SA among patients with co-existing psychiatric illness. Selected gene-gene and gene-environment interactions were also tested. Methods: DNA was obtained from bloods of 159 patients (76 suicide attempters and 83 non-attempters), who were profiled for DSM-IV Axis I psychiatric diagnosis. Twenty-eight single nucleotide polymorphisms (SNPs) from 18 candidate genes (COMT, 5-HT2A, 5-HT1A, 5-HTR1B, TPH1, MAO-A, TPH2, DBH, CNR1, BDNF, ABCG1, GABRA5, GABRG2, GABRB2, SLC1A2, SLC1A3, NTRK2, CRHR1) were genotyped. Genotyping was performed by KBioscience. Tests of association between genetic variants and SA were conducted using Chi squared and Armitage Trend tests. Binary logistical regression analyses were performed to evaluate the contribution of individual genetic variants to the prediction of SA, and to examine SNPs for potential gene-gene and gene-environment interactions. Results: Our analysis identified 4 SNPs (rs4755404, rs2269272, rs6296 and rs1659400), which showed evidence of association with SA compared to a non-attempter control group. We provide evidence of a 3-locus gene-gene interaction, and a putative gene-environment interaction, whereby genetic variation at the NTRK2 locus may moderate the risk associated with history of childhood abuse. Conclusion: Preliminary findings suggest that allelic variability in SLC1A2/3, 5-HTR1B and NTRK2 may be relevant to the underlying diathesis for suicidal acts. Background suicide is not exclusively determined by a psychiatric ill- Suicide represents a worldwide public health problem ness (or an alternative stressor), but rather that indivi- and is a leading cause of death among those aged 15-44 duals may have a predisposition or tendency towards years in many developed countries, representing a signif- suicidal ideation, which is aggravated further by one or icant social and economic burden http://www.who.int/ more stressors [1]. A greater understanding of clinical mental_health/prevention/suicide. According to the and biological risk factors will help us understand more stress-diathesis model of suicidal behaviour, risk of fully this model of suicidal behaviour and inform new therapies and tailored interventions. The molecular pathology of suicidal behaviour * Correspondence: murphyth@tcd.ie remains complex; epidemiological studies have demon- Department of Psychiatry & Mental Health Research, St. Vincent’s University strated familial clustering of suicide and suicidal beha- Hospital, and School of Medicine & Medical Science, University College Dublin, Elm Park, Dublin 4, Ireland viour [2]. Meta-analysis of published twin case studies Full list of author information is available at the end of the article © 2011 Murphy et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 2 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 for suicide found a higher rate of concordance for sui- Belfast, Omagh, Dublin, Portlaoise and Ballinasloe) were cide and for suicidal behaviour in monozygotic (MZ) invited to take part in a clinical and molecular genetics versus dizygotic (DZ) twins, establishing a solid genetic study of suicidal behaviour in major psychiatric disorders link [3]. Currently, risk assessment of suicidal behaviour over a year long recruitment period. In total, 159 patients relies heavily on clinical variables [4]. Indeed, patients gave written informed consent for the study. Patients with psychiatric disorders are at higher risk for suicide were interviewed for Axis I Psychiatric Disorders using attempt (SA) [5-8], however protective and risk genetic the Structured Clinical Interview for DSM-IV [24]. His- variants for suicide appear to be independent of under- tory of attempted suicide was recorded using the Colum- lying psychiatric disorders [9-11]. Identifying relevant bia University Suicide History Questionnaire [25], which genetic variants or single nucleotide polymorphisms incorporates the Scale for Suicide Ideation [26], and the (SNPs) in genes intimately linked to various neurobiolo- Suicide Intent Scale [27]. A suicide attempt was defined gical pathways, whose alteration may contribute to suici- as a completed act of self-harm with at least some dal behaviour, may provide insight into the etiological expressed intent to die (scoring at least 1 on item 10 of processes that underlie suicidal behaviour and identify Suicide Intent Scale [27]). Seventy-six (48% Male, 52% novel biological therapeutic targets. Female; Mean age: 34.7 yrs) had a history of SA and 83 Numerous neurobiological pathways have been impli- (61.4% Male, 38.6% Female; Mean age: 40.7 yrs) had not. cated in the etiology of suicide and suicidal behaviour. Childhood abuse was defined as the presence or absence Deregulation of the monoaminergic transmitter systems of a history of sexual and/or physical abuse under the age (norepinephrine, dopamine and serotonin) [12,13], of 16. Further clinical variables from clinical and demo- gamma aminobutyric acid (GABA) inhibitory neuro- graphic assessments are outlined in Table 1. All clinical transmitter system [14,15], glutamatergic excitatory neu- research interviews were performed by a trained research rotransmitter system [14,15], lipid metabolism [16,17], psychiatrist or research psychiatric nurse. Ethics approval cannabinoid system [18] and neurotrophic signalling was obtained for the study from the St Vincent’sHealth- factors [19] are linked to suicidal behaviour. Interest- care Group Ethics and Medical Research Committee. ingly, the hypothalamic-pituitary-adrenal (HPA) axis maybeinvolvedinincreased suicidal behaviourin Gene and SNP selection response to adversity during development [20], hence In this study, genes intimately linked to numerous neuro- highlighting the contribution of early environmental fac- biological pathways considered important for the patho- tors to suicide risk. genesis of suicide and/or associated disorders or Suicidal behaviour is a complex trait; therefore it is endophenotypes, were selected. Genes from the following likely to be the result of a combination of numerous pathways were considered, monoaminergic transmitter environmental and genetic factors with an added layer systems (norepinephrine, dopamine and serotonin), GABA of complexity via potential gene-gene (GxG) and gene- inhibitory neurotransmitter system, glutamatergic excita- environment (GxE) interaction effects [21]. Conse- tory neurotransmitter system, HPA axis and cannabinoid quently, investigating the relationship between genetic system. Genes important for cholesterol transport and variants and environmental factors (e.g. childhood abuse neural growth and differentiation were also selected. or alcoholism) is an important step towards elucidating Twenty-eight SNPs from the 18 selected genes (COMT, the mechanisms behind suicidal behaviour. 5-HT2A, 5-HT1A, 5-HTR1B, TPH1, MAO-A, TPH2, DBH, Here we test the hypothesis that genetic variants in CNR1, BDNF, ABCG1, GABRA5, GABRG2, GABRB2, candidate genes important for neurobiological pathways SLC1A2, SLC1A3, NTRK2, CRHR1)wereincluded inour linked to suicidal behaviour and/or associated endophe- analysis. SNPs, within these 18 genes, were screened for notypes, may confer a protective [22] or risk effect on known genetic associations with suicide, suicidal beha- SA among patients with co-existing psychiatric illness viour and/or associated endophenotypes using biomedical (suicide attempters versus non-attempter controls). In online resources PubMed http://www.ncbi.nlm.nih.gov/ addition to main genetic effects, we also tested selected pubmed and OMIM http://www.ncbi.nlm.nih.gov/omim. GxG and GxE interactions for association with SA. Priority was given to functional SNPs or SNPs within regulatory regions utilising online genetic databases Methods ensembl http://www.ensembl.org/index.html and DbSNP Clinical sample collection http://www.ncbi.nlm.nih.gov/projects/SNP/. The study consisted of 159 psychiatric patients recruited as part of the Ireland North/South Urban/Rural Epide- Genotyping miologic (INSURE) collaborative project [23]. Briefly, DNA was extracted from patient blood samples using consecutive newly referred patients to six Community standard techniques. Flanking SNP sequences were Psychiatric Clinics on the island of Ireland (Donegal, obtained from DbSNP and all genotyping assays were Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 3 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 Table 1 DSM-IV psychiatric diagnosis and clinical features of patient samples Attempter (n = 76) n (%*) Non-attempter (n = 83) n (%*) P Value Sex 0.124 Male 36(48) 51 (61.4) Female 39 (52) 32 (38.6) Mean age (years) 34.7 40.7 0.017 Positive 1st degree family history of suicide attempt 26 (35.6) 14 (17.1) 0.014 Child abuse (Physical and/or sexual) 37 (49.3) 27 (32.5) 0.047 Axis I Diagnosis 42 (55.3) 36 (43.4) 0.18 Substance-related disorders 24 (31.6) 21 (25.3) 0.334 Substance abuse/dependence 38 (50) 29 (34.9) 0.078 Alcohol abuse/dependence 6 (8.8) 7 (8.6) 1 Schizophrenia and other psychotic disorders Bipolar disorders 5 (7.4) 4 (4.8) 0.786 Major depressive disorder 48 (63.2) 37 (44.6) 0.022 Anxiety disorders 32 (42.7) 25 (30.1) 0.14 Eating disorders 1 (1.3) 0 (0) 0.965 §P value was determined by Fishers exact or Chi squared test in all comparisons, with the exception of age, where a non-parametric Mann-Whitney test was used to determine the P Value. *Illustrated percentages of variables are calculated for valid cases/controls only. In some cases certain clinical or demographic variables could not be obtained from patients charts. designed and validated by KBioscience (Hertfordshire, four genotype models (Additive (XX = 0, XY = 1, UK). Genotyping for SNP analysis was performed by YY = 2), Dominant (XX = 0, XY & YY = 1), Over- KBioscience using the competitive allele specific PCR dominant (XX & YY = 0, XY = 1) and Recessive (XX (KASP) chemistry coupled with a FRET-based genotyp- & XY = 0, YY = 1); X = Major allele, Y = Minor ing system http://www.kbioscience.co.uk/reagents/ allele). For all models, except the additive model, KASP/KASP.html. Genotyping data was viewed using Pearson’s Chi-square test of association was used. For the additive model an exact Armitage trend test was SNPviewer (KBioscience, Hertfordshire, UK), allowing graphical viewing of the clusters that group the allele preformed. Binary logistical regression analyses were calls. performed to evaluate the contribution of the geno- SNPs in linkage disequilibrium (LD) with SNPs of type model associated with SA at each locus in the interest were identified using a combination of informa- prediction of attempted suicide, correcting for poten- tion from Ensembl http://www.ensembl.org/index.html tial confounders such as age, gender and certain psy- and Haploview http://www.broadinstitute.org/haploview/ chiatric disorders and to interrogate associated SNPs haploview. for potential GxG and GxE interactions. Analysis of potential GxE interactions were applied to SNPs with Data analysis evidence of association in at least one genetic model Deviations from Hardy Weinberg Equilibrium (HWE) (n = 3) and to one SNP which showed evidence of were calculated using the exact test implemented by association in a gender specific manner (n = 1) and SNP and Variation Suite (SVS) 7 software (Bozeman, not examined for all candidate SNPs listed in this MT 59718 USA; http://www.goldenhelix.com/SNP_Var- study. In addition, GXG interactions analysis was per- iation/svstrial.html). formed on these 4 SNPs, which showed evidence of Statistical tests of association examining the relation- association with SA and not examined for all candi- ship between patient’s alleles or genotype, at each of the date SNP listed in this study. 28 genetic loci, and suicide attempt were performed A non-parametric Mann-Whitney test was used to using Pearson’s Chi-square test or Fisher’s exact test calculate the difference in age between cases and con- (whencountsare low).Thisanalysiswas performed trols. For all other comparisons of clinical and demo- both in SPSS and SNP and Variation Suite for verifica- graphic variables a Fisher’s exact test or Chi-squared tion purposes. test of association was used. All statistical analysis was performed on SPSS (PASW statistics 18, Chicago, Illi- SNPs which showed a modest level of association in the original allelic and genotype tests of association nois, USA) and genotypic associations verified using (P < 0.1) and one SNP which showed a gender specific SNP and Variation Suite (SVS) 7 software. For all tests, association with SA, were further analysed by applying significance was ascribed at P < 0.05. Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 4 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 Table 2 Association of candidate markers Results Clinical and psychological features of study population Gene Symbol Allele RS number Significance (p) The mean age of the suicide attempter and non-attemp- Allelic Genotypic ter groups was significantly different (34.72 years versus SLC1A3 C/T rs2269272 0.562 0.075 40.67 years, respectively, (P = 0.017)). The SA group HTR1B C/G rs6296 0.895 0.047 were more likely to have a diagnosis of major depressive SLC1A2 G/C rs4755404 0.024 0.069 disorder (P = 0.022), a positive first degree family his- COMT G/A rs4680 0.123 0.205 tory of attempted suicide (P = 0.014), and a history of HTR2A G/A rs6313 0.696 0.568 child abuse (physical or sexual) (P = 0.047). No other C/T rs6311 0.628 0.307 demographic or clinical variables were statistically differ- HTR1A C/G rs6295 0.714 0.907 ent between the two groups (Table 1). TPH1 G/T rs1799913 0.136 0.192 G/T rs1800532 0.136 0.192 Candidate gene selection TPH2 A/G rs7305115 0.647 0.559 In this study, genes considered important in various DBH T/C rs2519152 0.377 0.761 neurobiological pathways associated with suicide and/or CNR1 T/G rs6454674 0.948 0.986 associated disorders or endophenotypes were chosen. T/C rs806368 0.695 0.885 Overall, 18 genes were selected for inclusion in our ana- G/A rs6801844 0.883 0.612 lysis. The majority of genes (n = 8; COMT, 5-HT2A, 5- BDNF C/T rs6265 0.422 0.650 HT1A, 5-HTR1B, TPH1, MAO-A, TPH2, DBH)are ABCG1 A/G rs1044317 0.261 0.397 important for monoaminergic transmitter systems (nore- C/G rs225374 0.631 0.823 pinephrine, dopamine and serotonin). Key genes of the C/G rs914189 0.862 0.986 GABA inhibitory neurotransmitter system (n = 3; GABRG2 C/A rs211014 0.398 0.180 GABRA5, GABRB2, GABRB2), glutamatergic excitatory GABRB2 A/G rs1816072 0.270 0.276 neurotransmitter system (n = 2; SLC1A2, SLC1A3), HPA C/T rs2491397 0.310 0.594 axis (n = 1; CRHR1), cannabinoid system (n = 1; CNR1), NTRK2 A/G rs1659400 0.453 0.474 cholesterol transport (n = 1; ABCG1), neural growth G/A rs1187272 0.137 0.388 and differentiation (n = 2; BDNF &NTRK2)werealso CRHR1 A/G rs110402 0.805 0.763 selected (see Additional File 1).Intotal,28SNPspre- T/G rs242924 0.935 0.463 sent within our 18 candidate genes were identified. The C/T rs7209436 0.852 0.872 majority of SNPs (24/28 SNPs) had previous evidence of MAOA T/G rs1799835 NA NA association with suicidal behaviour and/or associated GABRA5 A/G rs140681 NA NA disorders or endophenotypes (see Additional File 1). P value obtained from Pearson’s Chi-square test or Fisher’s exact test. NA = not applicable, as genotype are identical for case and controls. Genetic variants and suicide attempts Results of basic allelic and genotypic tests of association with SA in an over-dominant genotype model, whereby for each SNP and SA are illustrated in Table 2. Basic a heterozygote (C/G) genotype was more frequently pre- allelic and genotypic association analyses revealed two sent in patients in the SA group than non-attempter significant associations with SA; rs4755404 (Intronic group (P = 0.028). Rs2269272 variants revealed evidence region of SLC1A2; P = 0.024: Chi-square test) and of association in a recessive genotype model (P = 0.042; rs6296 (Promoter CpG island of 5-HTR1B;P=0.047: Chi-square test), with the T/T genotype more frequent Chi-square test) loci. In addition a third SNP, rs2269272 in the non-attempter group than attempter group (3’untranslated region (UTR)) in SLC1A3; P = 0.075: (Table 3). Chi-square test), with a P value < 0.1 was chosen for SNPs of interest were investigated for possible associa- further analyses. Next, four genotype models (Additive, tions with other clinical variables illustrated in Table 1. Dominant, Over-Dominant and Recessive) were tested SNP rs2269272 showed no evidence of association with for association with attempter status at each locus other clinical variables in the study. A dominant geno- (Table 3). type at the rs4755404 locus was associated with patients Rs4755404 yielded evidence of association in an addi- with a history of schizophrenia and other psychotic dis- tive and dominant genotype model (P = 0.029: Exact orders (P = 0.012; Chi-square test). A recessive genotype Armitage Trends test; P = 0.026: Chi-square test, at the rs6296 locus yielded an association with respectively), where patients with a G/C or G/G geno- individuals who abuse/depend on alcohol (p = 0.035). type were significantly morelikelytobepresent in the Binary logistical regression analyses were performed to SA group. Variation at the rs6296 locus was associated evaluate the contribution of individual risk/protective Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 5 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 Table 3 Genotype frequencies and genetic models of association Genotype Frequencies Significance (p value) Gene symbol RS number Genotype Controls SA cases Additive Dominant Over-Dominant Recessive SLC1A3 rs2269272 CC/CT/TT 0.687/0.229/0.084 0.667/0.32/0.013 0.56 0.787 0.199 0.042 HTR1B rs6296 GG/CG/CC 0.59/0.265/0.145 0.5/0.432/0.068 0.847 0.256 0.028 0.121 SLC1A2 rs4755404 CC/CG/GG 0.451/0.427/0.122 0.28/0.52/0.20 0.029 0.026 0.243 0.182 P value obtained from Pearson’s Chi-square test for all genotype tests, with the exception of the additive model, where an exact Armitage trend test was used. Numbers highlighted in bold represent genotype models that were significantly associated with Suicide attempt status (P = < 0.05). SA: Suicide Attempt. polymorphisms in the prediction of attempted suicide. significant predictor of SA in females (P = 0.048; OR = After controlling for possible confounders such as age, 2.968; 95% C.I 1.01- 8.72). gender, alcohol abuse/dependence (rs6296 only) and Finally, we investigated the effect of susceptibility loci schizophrenia (rs4755404 only), rs2269272 recessive on suicide attempts by other susceptibility loci by exam- genotype model was no longer a significant predictor of ining various two and three way G×G interactions. SA (P0.121; Odds ratio (OR) = 0.83, 95% C.I: .022- Logistic regression was used to model SA risk as a func- 1.563). Rs4755404 dominant genotype model and rs6296 tion of the genotype models associated with SA at each over-dominant genotype model were still significant pre- locus and 2-locus and 3-locus G×G interactions dictors of SA (P = 0.031; OR = 2.198; 95% CI 1.059- (Table 4). Controlling for possible confounders, age, 4.563 and P = 0.023; OR = 2.244; 95% CI 1.096-4.597, gender, alcohol abuse/dependence and schizophrenia, a respectively). 3-locus gene (G×G×G) interaction (rs6296 (C/G) × Each locus was also analysed for deviations from rs4755404 (C/G or G/G) × rs1659400 (C/C) was a sig- HWE. Deviations from HWE were observed at the nificant predictor of SA (P = 0.046). rs6296 locus in the non-attempter group (P = 0.004) To evaluate further the association between suscept- and at rs2269272 locus in the non-attempter group (P = ibility genotypes only and environmental risk factors, 0.014). logistic regression was used to model risk as a function of the genotype models associated with SA at each Genetic and environmental interaction analysis locus, environmental risk factors and their interaction. Individual SNPs were analysed for evidence of gene by Results provide evidence of a possible G (C/C genotype) sex interaction, to identify possible sex-specific associa- × E (history of childhood abuse (both physical and sex- tions with SA. Two gene-sex interactions were observed. ual)) interaction at the rs1659400 locus. Interestingly, A sex by rs2269272 interaction was found where a T/T rs1659400 was not associated with SA (p = 0.823, Chi- genotype was more frequent in non-attempter male SA square), however when all variables (including gender group. A gene by sex interaction was also observed for and age) are entered into a logistic regression analysis, an intronic SNP, rs1659400, in the NTRK2 gene. Con- the G×E interaction term is close to significance trolling for age, a C/C genotype at this locus was a (P = 0.056, Table 5). Moreover, since a C/C genotype Table 4 Final gene by gene interaction model: Logistic regression analysis 95% C.I for OR Variable B S.E Wald df P value OR Lower Upper Age -.043 .015 8.305 1 .004 .958 .930 .986 Sex -1.062 .422 6.349 1 .012 .346 .151 .790 alcohol abuse/dependence 1.164 .422 7.598 1 .006 3.204 1.400 7.333 schizophrenia and other psychotic disorders - 0.139 .810 .029 1 .864 .870 .178 4.257 rs6296 1.104 .868 1.615 1 .204 3.015 .550 16.539 rs4755404 1.291 .593 4.736 1 .030 3.636 1.137 11.628 rs1659400 .953 .934 1.041 1 .308 2.592 .416 16.159 rs6296 by rs4755404 -1.141 1.065 1.150 1 .284 .319 .040 2.573 rs6296 by rs1659400 -1.356 1.440 .887 1 .346 .258 .015 4.332 rs1659400 by rs4755404 -2.060 1.139 3.275 1 .070 .127 .014 1.187 rs6296 by rs4755404 by rs1659400 3.613 1.811 3.982 1 .046 37.087 1.067 1289.592 Constant .592 .778 .579 1 .447 1.808 B, unstandardised logistic regression coefficient; S.E, Standard error; Wald, Wald statistic; df, Degrees of freedom; OR, Odds ratio; C.I., Confidence interval Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 6 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 Table 5 Gene by environment interaction: Logistic transporters could impair reuptake of glutamate, hence regression analysis prolong synaptic activation and potentially lead to cyto- 95% C.I for OR toxic damage to neurons and glia [15]. SLC1A2 and SLC1A3 are downregulated in the brains of MDD Variable B S.E Wald df P OR Lower Upper value patients compared to controls [28]. Moreover, decreased Sex -.384 .358 1.152 1 .283 .681 .338 1.373 SLC1A3 expression has been observed in suicide brains Age -.035 .013 7.669 1 .006 .965 .941 .990 [29]. rs1659400 -.038 .426 .008 1 .928 .962 .417 2.219 In this study, the SLC1A2 gene variant, rs4755404, was abuse -.508 .469 1.175 1 .278 .602 .240 1.508 associated with SA and schizophrenia and other psycho- rs1659400 by 1.518 .795 3.641 1 .056 4.562 .960 21.684 tic disorders. Consistent with these findings, rs4755404 abuse was previously associated with schizophrenia in a Japa- Constant 1.406 .627 5.035 1 .025 4.079 nese patient cohort [30]. In contrast, the SLC1A3 gene Females variant, rs2269272, was significantly associated with Only male non-attempters, where a gene-sex interaction was Age -.025 .018 1.911 1 .167 .975 .941 1.010 observed. The T/T genotype is absent from the attemp- rs1659400 .166 .634 .068 1 .794 1.181 .341 4.093 ter group and over-represented in the male non-attemp- abuse .003 .774 .000 1 .997 1.003 .220 4.571 ter group, suggesting a T/T genotype may confer a rs1659400 by 2.653 1.378 3.707 1 .054 14.202 .953 211.572 protective effect on risk of SA, particularly in males abuse with underlying psychiatric disorders. HWE analysis Constant .633 .848 .556 1 .456 1.883 revealed that the control groupwasnotinequilibrium B, unstandardised logistic regression coefficient; S.E, Standard Error; Wald, for the rs2269272 locus, which is likely due to the fact Wald statistic; df, degrees of freedom; OR, Odds ratio; C.I., Confidence interval that our control group is not “disease-free” but rather consists of individuals with underlying psychiatric condi- was associated with female SA, a G×E interaction was tions. However, the possibility that some other factor examined in females only. A G×E interaction contribu- may be influencing the over-representation of T allele ted to the predictive ability of the model (P = 0.054, homozygotes in the non-attempter group cannot be Table 5), a trend which did not reach statistical signifi- ruled out. Therefore, further investigation in a larger cance. Taken together our results suggest that indivi- cohort of patients is warranted. Taken together, our duals who experienced childhood abuse (physical or findings support the glial hypothesis of mood abnormal- sexual) and have a C/C genotype at the rs1659400 locus ities [28] and concur with the literature on a putative role of glutamate dysregulation in suicidal behaviour. may be more susceptible to SA. The serotonin (5-HT) system is the most widely stu- died area of neurobiological suicide research [21]. Aber- Discussion rant 5-HT receptor binding has been implicated in We have identified 4 SNPs (rs4755404, rs2269272, suicide and SA [12]. 5-HTR1B binding is decreased in rs6296 and rs1659400) in genes SLC1A2, SLC1A3, 5- the prefrontal cortex of suicide brains [31]. Previously a HTR1B and NTRK2, respectively, which showed evi- 5-HTR1B promoter CpG island genetic variant, rs6296, dence of association with SA compared to a non- was associated with SA [32]. However, findings are attempter psychiatric control group. At present, there inconsistent and a number of studies have found no evi- is no published data on 3/4 of the genetic variants dence of association [33,34]. Rs6296 has also been asso- (rs4755404, rs2269272 and rs1659400) reported here ciated with substance use disorders, major depression and their association with suicide or SA. In addition, and inconsistently with alcohol abuse [33,35]. Here we we identified a 3-locus (rs6296 (C/G) × rs4755404 (C/ G or G/G) × rs1659400 (C/C)) G×G interaction, which report a significant association between the rs6296 locus was a significant predictor of SA, suggesting that varia- and SA. In addition, persons with a C/G genotype and a tion in SLC1A2, 5-HTR1B and NTRK2 genes may con- history of abuse or dependence on alcohol were signifi- tribute to the risk of SA independently, and in an cantly associated with SA, but a gene × alcohol interac- interactive manner. This paper provides evidence for tion was not evident, suggesting that they represent the first time of a putative G×E interaction, where additive risk factors. These findings provide the impetus genetic variation at the rs1659400 locus may moderate for future studies in a cohort of alcohol abuse/depen- the risk associated with history of childhood abuse and dence patients to further understand the relevance of subsequent suicidal acts. rs6296 genetic variants and SA in patients with a history of alcohol abuse/dependence. SLC1A2 and SLC1A3 are glial high-affinity transporter NTRK2 (TRKB) encodes the receptor for BDNF. Aber- molecules that regulate glutamate concentrations at rant neurotrophic signalling has been implicated in synapses [15]. Aberrant expression of these key Murphy et al. Behavioral and Brain Functions 2011, 7:22 Page 7 of 9 http://www.behavioralandbrainfunctions.com/content/7/1/22 suicide risk by various studies [36,37]. BDNF and genetic and environmental risk factors. In this study, NTRK2 mRNA and protein expression are reported multiple testing correction, such as Bonferroni correc- downregulated in the prefrontal cortex and hippocam- tion, was not applied. Bonferroni correction can be pus of suicide victims compared to controls [36,37]. The regarded as ultraconservative [50] and ignores the func- majority of studies have focused on functional BDNF tional candidate gene study design utilised, which is variant, rs6265, which has been inconsistently implicated likely to increase the prior probability of detecting an association. In addition, given our modest sample size, in suicide and MDD [38,39]. In this study, we found no Bonferroni correction is likely to result in large type II evidence of association between rs6265 and SA, consis- error rates. Arguably the best solution to type I error is tent with a previous report [40]. Previously, a number of genetic variants within the NTRK2 gene have been asso- replication [50]. ciated with SA among depressed patients [41]. We observed a significant association with NTRK2 intronic Conclusion genetic variant, rs1659404, and SA in females. In conclusion,wehaveidentified statistically as well as Rs1659400 is in strong LD with several other SNPs biologically significant genetic polymorphisms that may within the NTRK1 gene, some of which have been be relevant to the underlying diathesis for suicidal acts implicated in alcohol dependence and depression [1]. An understanding of the functional consequence of [42,43]. these SNPs from a neuropathological standpoint would To date a number of gene × childhood adversity inter- be advantageous to advance our understanding of their actions have been reported in psychiatric patients role in SA. The SNP associations identified in this [44-46]. Childhood trauma (including abuse) has been study, although modest, merit further investigation in a reported to interact with low expressing 5-HTTLPR gen- larger cohort of suicide attempters and may contribute otypes and moderate the risk of suicidal behaviour [47]. to future meta-analysis of suicidal behaviour susceptibil- Recently, an interaction between child maltreatment and ity loci. Moreover, follow-up research of the genetic sus- 5-HTT polymorphisms and suicidal ideation among chil- ceptibly polymorphisms identified in this study may dren was described [48]. Here we report, for the first increase our understanding of the complex relationship time, a possible moderation effect of a NTRK2 poly- of genetic and environmental factors in suicidal beha- morphism on childhood abuse and risk for future suici- viour in major psychiatric disorders. dal acts. It is important to note that a history of childhood abuse was assessed in this study by a trained Contributions of Authors clinician as opposed to self-report questionnaires. TMM performed genetic and statistical analysis, inter- Recent research has demonstrated that clinician ratings pretation of the data and drafted the manuscript. MR of developmental histories, such as childhood sexual and carried out blood collection and Clinical rating and physical abuse, are in agreement with patient’sself- contributed to study design. TF participated in the reports and thus supports the validity of clinician design of the study and helped to draft the manuscript. reports for numerous clinical variables, including child- CK participated in the design of the study. RM partici- hood abuse assessment [49]. Future studies could inves- pated in the design of the study. JO’G carried out tigate the putative interaction of this genetic variant blood collection and Clinical rating. EC participated in with childhood trauma score, which would include sex- the design of the study. JB carried out blood collection ual, physical and emotional abuse and neglect. Such a and Clinical rating. MR carried out blood collection studywould provideamorecomprehensiveassessment and Clinical rating. AJ participated in the design of the of gene × childhood adversity interaction and risk for study. AM carried out blood collection and Clinical SA at this locus. rating. NB carried out blood collection and Clinical A number of limitations are apparent in the current rating. AC carried out blood collection and Clinical study. Firstly, case/control samples were not age- rating DL carried out Clinical rating. SB carried out matched, with the SA group having a significantly Clinical rating. PT participated in statistical and younger mean age. The SA group also contained a genetic analysis and helped to draft the manuscript. greater number of individuals with a family history of AB extracted DNA and prepared sample for storage SA and a history of childhood abuse. In addition, rates and genotyping. LQ participated in statistical analysis. of MDD diagnoses were different in SA and non- LD participated in statistical and genetic analysis and attempter psychiatric controls. However, the genetic var- helped to draft the manuscript. CK participated in the iants identified in this study were not associated with design of the study and help to draft the manuscript. either MDD, a family history of SA or abuse. Moreover, KMM participated in the design of the study and help our sample size may have reduced power to detect small to draft the manuscript. All authors have read and genetic effects, or alternative interactions between approved the final manuscript. Murphy et al. 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