Eur Arch Psychiatry Clin Neurosci (2014) 264 (Suppl 1):S45–S54 DOI 10.1007/s00406-014-0536-2

ORIGINAL PAPER

Interaction among childhood trauma and functional polymorphisms in the serotonin pathway moderate the risk of depressive disorders Sandra Van der Auwera • Deborah Janowitz • Andrea Schulz • Georg Homuth • Matthias Nauck • Henry Vo¨lzke • Matthias Rose • Henriette Meyer zu Schwabedissen Harald Ju¨rgen Freyberger • Hans Jo¨rgen Grabe

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Received: 26 June 2014 / Accepted: 3 September 2014 / Published online: 12 September 2014 Ó Springer-Verlag Berlin Heidelberg 2014

Abstract Depressive disorders are influenced by a complex interplay between genetic and environmental factors. Multiple studies support a role of serotonergic pathways in the pathophysiology of depressive disorders. As a ratelimiting enzyme of serotonin synthesis in the brain, tryptophan hydroxylase 2 (TPH2) represents a plausible candidate gene. This also applies to the serotonin reuptake transporter (5-HTTLPR) regulating the availability of serotonin in the synaptic gap. We hypothesize that functional polymorphisms (TPH2: rs7305115, 5-HTTLPR and rs25531) within both genes contribute to the risk of depressive disorders after childhood abuse in adult life. To confirm our results, we investigated two independent

Electronic supplementary material The online version of this article (doi:10.1007/s00406-014-0536-2) contains supplementary material, which is available to authorized users. S. Van der Auwera  D. Janowitz  A. Schulz  H. J. Freyberger  H. J. Grabe Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany S. Van der Auwera (&) Department of Psychiatry, University of Greifswald, Ellernholzstraße 1-2, 17475 Greifswald, Germany e-mail: [email protected] G. Homuth Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany M. Nauck Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany

samples of Caucasian subjects from the study of health in Pomerania (SHIP–LEGEND: n = 2,029 and SHIP– TREND-0: n = 2,475). Depression severity was assessed by the Beck depression inventory (BDI-II) for LEGEND and the patient health questionnaire (PHQ-9) for TREND0. Childhood abuse was assessed by the childhood trauma questionnaire. Rs7305115 (TPH2) revealed significant effects in SNP 9 abuse and SNP 9 SNP as well as in the three-way interaction. This three-way interaction among abuse, TPH2 and 5-HTTLPR showed a significant effect on depression score (p = 0.023). The SS genotype of 5-HTTLPR was associated with increased depression scores after childhood abuse only in carriers of the lowexpression TPH2 GG genotype, whereas the TPH2 AA genotype reversed this effect. Our results support the role of interaction effects of genetic variants within serotonergic pathways. Genetic variants that may decrease the M. Rose Division of Psychosomatic Medicine, Medical Department, University Medicine Berlin, Berlin, Germany H. M. zu Schwabedissen Biopharmacy, Department Pharmaceutical Sciences, University of Basel, Basel, Switzerland H. J. Freyberger  H. J. Grabe Department of Psychiatry and Psychotherapy, HELIOS Hospital Stralsund, University Medicine Greifswald, Greifswald, Germany H. J. Grabe German Center for Neurodegenerative Diseases DZNE, Site Rostock, Greifswald, Germany

H. Vo¨lzke Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany

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presynaptic serotonin concentration were associated with increased adult depressive symptoms in subjects with childhood abuse. Keywords Gene–gene–environment interaction  TPH2  5-HTTLPR  Abuse  Serotonin 2. Introduction Depressive disorders belong to common causes of morbidity, disability and impaired quality of life [1]. Therefore, it is necessary to investigate the underlying etiology of depressive symptoms. Previous research revealed a robust genetic component in depressive disorders with heritability estimates between 33 and 42 % [2]. Genome-wide association studies (GWAs) and meta-analyses of genetic associations with depressive disorders and symptoms have been performed, which have not yet let to replicate findings [3, 4]. In a GWA mega-analysis of more than 9,000 MDD cases and 9,000 controls by the MDD Working Group, none of the analyzed variants reached genome-wide association. Additionally, the stratified analyses by sex, recurrent MDD, early onset or age at onset did not lead to robust or replicate findings. The serotonergic system is involved in mood regulation, appetite, sleep and sexual behaviors. The tryptophan hydroxylase 2 gene (TPH2) [5, 6] performs the rate-limiting step in the biosynthesis of serotonin in the brain [7]. As reuptake transporter, the serotonin transporter (5-HTTLPR) is a key regulator of the availability of serotonin in the synaptic gap. Both genes are of great importance in the serotonin deficiency theory postulating that the decreased serotonin levels in the brain increase the risk of depressive disorders [8]. Besides genetic factors environmental stressors seem to play a key role in the pathophysiology of psychiatric disorders. One of the best predictors of later depressive symptoms is early-life stress, especially childhood trauma [9, 10]. Many studies reported a dose–response relationship between the severity of experienced childhood trauma and depressive episodes in later life [11, 12]. To fully understand the etiology of depression, the genetic and environmental layers need to be combined [13]. In fact, empirical evidence has long suggested that the interaction between specific genetic profiles and risky environmental patterns contributes to the vulnerability of psychiatric disorders [14]. For our gene–environment (G 9 E) interaction, we focused on the variants rs7305115 of TPH2 and 5-HTTLPR and rs25531 of the serotonin transporter for several reasons: 1.

One of the most thoroughly investigated of these variants is the polymorphic region of the serotonin transporter gene, which influences the reabsorption of

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3.

4.

5.

serotonin in the synaptic gap. Specifically, the short (S)-allele proved to be a risk factor in the interaction with childhood abuse [15] and adult trauma [16] with increased depressive symptoms. Nevertheless, epidemiological studies investigating this interaction have revealed conflicting results [17]. Former research described a functional impact of rs7305115 on serotonergic function [18, 19]. Lim et al. found the A-allele to be associated with elevated TPH2 mRNA expression in the human pons. Recent findings provided evidence for the role of rs7305115 with regard to suicide attempt risk in patients with major depression [20]. They described that the G-allele frequency was significantly higher in MDD patients with attempted suicide than in MDD controls. Likewise, Xu et al. [21] demonstrated an interaction of rs7305115 and childhood trauma with regard to antidepressant response in MDD patients. They found the G-allele directly association with response to antidepressant medication. In G 9 E interaction between the SNP and childhood trauma, however, the A-allele was associated with a favorable treatment response. An additive effect of variants from both genes on neuronal activity was described by Herrmann et al. [22]. They provide evidence for 5-HTTLPR and TPH2 to be involved in the serotonergic control of emotional processing. Animal models for depression and stress revealed abnormalities in tryptophan metabolism based on metabolome analyses [23, 24].

The aim of our study was to analyze the possible two- and three-way interactions between TPH2, 5-HTTLPR and childhood abuse. We hypothesized that the interaction between childhood abuse, rs7305115 of TPH2 and/or polymorphisms within 5-HTTLPR is associated with an increased severity of depressive symptoms in carriers of the lowexpression G-allele of TPH2 and the low-reuptake S-allele of 5-HTTLPR. We investigated this hypothesis in two independent samples and additionally analyzed sex-specific differences. These have been recommended because of relevant sex differences in serotonergic pathways and behavior [25]. To our best knowledge, no previous study has investigated the interaction of rs7305115, 5-HTTLPR and rs25531 and childhood abuse with regard to depression.

Materials and methods Sample and sample recruitment The investigations in both studies were carried out in accordance with the Declaration of Helsinki, including

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written informed consent of all participants. The survey and study methods of both the studies were approved by the institutional review boards of the University of Greifswald. The Study of Health in Pomerania Data from the ‘‘study of health in Pomerania (SHIP)’’ were used [26]. The target population was comprised of adult German residents in northeast Germany living in 3 cities and 29 communities, with a total population of 212,157. A two-stage stratified cluster sample of adults aged 20–83 years had been drawn from local population registration files. The net sample comprised 6,267 eligible subjects, of which 4,308 Caucasian subjects participated at baseline SHIP-0 between 1997 and 2001. Follow-up examination (SHIP-1) was conducted 5 years after baseline and included 3,300 subjects. From June 2007 until August 2010, the ‘‘Life-Events and Gene-Environment Interaction in Depression (LEGEND)’’ study was carried out [27]. Among the 3,669 subjects of SHIP-0 that were invited to take part in the LEGEND study, 2,400 participated. In 2008, a new sample called SHIP–TREND-0 (n = 4,420) from the same area was drawn and similar examinations like in SHIP-0 were undertaken. The objective was to compare two samples from the same target population but from different time periods (1997 and 2008) concerning disease prevalence and risk behavior. From statistical analysis, we excluded all subjects with missing data for depression scores, (LEGEND n = 96 and TREND-0 n = 187), CTQ variables (LEGEND n = 170 and TREND-0 n = 607) and missing DNA or genotyping (TPH2: LEGEND n = 136, TREND-0 n = 1,107 and 5-HTTLPR: LEGEND n = 248, TREND-0 n = 749) (overlap exists). The final study sample for the three-way interaction included 2,029 subjects of LEGEND and 2,475 subjects of TREND-0. Phenotype measures Current depressive symptoms were assessed in LEGEND using the Beck depression inventory (BDI-II), which is a 21-item self-report questionnaire with high reliability and validity [28]. In TREND-0, we used the patient health questionnaire (PHQ-9), a 9-item self-report questionnaire also with high reliability and validity [29]. To create one common variable on depressive symptoms for both cohorts, we transformed the PHQ-9 scores (TREND-0) into BDI-II. The methodical background is described in detail by Wahl et al. [30]. Briefly, they applied item-responsetheory (IRT) methods to develop an IRT metric for eleven different depression tools including PHQ-9 and BDI-II. From that the estimated response to each of the BDI-II

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items was added to provide a sum score. Our PHQ-9 scores of TREND-0 and their transformed BDI-II values correlated with [0.9. The childhood trauma questionnaire (CTQ) was used for self-report of childhood maltreatment including emotional, physical and sexual abuse [31–33]. It has 34 items that were rated on a five-point Likert scale with higher scores indicating more self-rated exposure to traumatic events. In addition to dimensional scoring procedure, the manual provides threshold scores to determine the severity of abuse (none = 0, mild = 1, moderate = 2 and severe to extreme = 3). To investigate the role of an increasing severity of childhood abuse in G 9 E interactions, we generated a dichotomized variable of overall abuse. A subject was rated as positive for overall abuse when at least in two of the abuse sub-dimensions a severity score of C2 (at least moderate) was reported. Genotyping of TPH2 For SHIP–LEGEND, the rs7305115 genotype data were taken from our Affymetrix Human SNP Array 6.0 data set of SHIP. Hybridization of genomic DNA was done in accordance with the manufactor’s standard recommendations. The genetic data analysis workflow was created using the software InforSense. The overall genotyping efficiency of the GWA was 98.6 %. Imputation of genotypes in the SHIP cohort was performed with the software IMPUTE v0.5.0 against the HapMap II (CEU v22, Build 36) reference panel using 869,224 genotyped SNPs. In SHIP–TREND-0, genotyping of rs7305115 was performed using the pre-developed TaqManÒ SNP Genotyping Assay C_8376164_10 (Life technologies, Applied Biosystems, Darmstadt, Germany). In detail, reactions were carried out in a 10 ll volume containing 2 ll genomic DNA, 0.5 ll Primer/Probe-Mix, 5 ll Genotyping Master Mix and 2.5 ll water. Fluorescence was assessed for using the fast real-time PCR system 7900 HT (Applied Biosystems) and the Sequence Detection Software SDS 2.3. All failing samples were repeated at least twice. Genotyping of 5-HTTLPR The SLC6A4 gene harbors a VNTR (variable number tandem repeat) polymorphism in the transcription control region of the gene that is located approximately 1 kb upstream of the transcription initiation site. This area has been associated with differential expression of the transporter (rs4795541) [34]. Both variants (Short, Long) differ by a 43-bp insertion/deletion. Within the inserted fragment, an additional common single nucleotide polymorphism (SNP) occurs (rs25531) and has been reported to further affect the transcriptional activity of the SLC6A4 promoter by the genotype-dependent generation of an AP2

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transcription factor binding site in the rs25531 G-allele [35]. Together, this leads to the thought that 5-HTTLPR is triallelic with S, LA and LG—alleles. We developed a restriction fragment length polymorphism (RFLP) method that allows for determination of both variants (S/L; rs25531) within one assay. The 5-HTTLPR region was PCR amplified using the oligonucleotide primers SLC6A4_SE (50 -CTCCTAGGATCGCT CCTGCATC-30 ) and SLC6A4_AS (50 -GGACCGCAAG GTGG-GCGGGAGGCTTGGAG-30 ), resulting in amplicons of 294 bp (S-variant) and 337 bp (L-variant). The restriction enzyme BcnI (Fermentas) digested the rs25531 variant differentially, in addition to two constitutive restriction sites in the amplicon. This resulted in the following fragments: S-allele, 200, 61, 33 bp; LA-allele, 243, 61, 33 bp; and LG-allele, 70, 173, 61, 33 bp. The detection of fragments of 173, 200 or 243 bp in 4 % agarose gels allowed for allocation to the respective alleles. Representative samples of different genotypes were further verified by sequencing of the amplicons. Based on previous reports on gene expression, we classified the genotypes into three functional ‘‘triallelic’’ genotypes: LALA = LL; LGLA or SLA = SL; LGLG or LGS or SS = SS [35]. However recently, the functional relevance of rs25531 has been call into question [36]. Still, we also report the results of the three-way interaction for this triallelic 5-HTTLPR. For that task, the genotypes LGLG/LGS/SS will be referred to as SS, the genotypes LGLA/SLA as SL and the genotype LALA as LL.

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20.3 % in LEGEND had a BDI-II score of zero and 14.1 % in TREND-0 had a score of 2.5, which represents the smallest value in the transformed variable. Therefore, we used Tobit regression, a method designed to deal with censored distribution [40]. Statistical analyses were performed using STATA/MP software, version 13 (StataCorp LP, College Station, TX).

Results The sample characteristic including the subjects of the three-way interaction analysis is given in Table 1. TPH2 and the triallelic 5-HTTLPR genotypes were in accordance with the Hardy–Weinberg equilibrium for LEGEND (p = 0.16 and p = 0.46) as well as for TREND-0 (p = 0.44 and p = 0.59), respectively. There were significant differences between the subjects of LEGEND and TREND-0 regarding age (p \ 0.001) and depression score (p \ 0.001). The age difference was caused by the different survey waves of LEGEND and TREND-0, whereas the higher BDI score was an effect of the transformation of PHQ-9 into BDI-II. The PHQ-9 has a ground effect that results in higher BDI-II scores. Both samples also revealed sex differences. Female subjects had a significantly higher load of childhood abuse, as well as higher depression scores compared to males who were significantly older. Main effects

Statistical analysis Linear regression analyses with robust estimates were applied to investigate the association between the genotypes of TPH2 and 5-HTTLPR and childhood trauma with regard to depression scores in LEGEND and TREND-0. In explorative analyses, we examined the direct effects of the genetic variants and childhood trauma on depression scores in LEGEND and TREND-0, respectively. Furthermore, two-way interactions were performed between the genotypes (G 9 G) and childhood abuse (G 9 E) with BDI-II scores as dependent variable. As a final step, we calculated the three-way interaction with TPH2, 5-HTTLPR and childhood abuse (G 9 G 9 E). All analyses were adjusted for age, sex and study population (in the combined sample analyses). We combined both studies in case the effects showed the same direction. We choose restricted cubic splines [37] to ensure an adequate model fit [38] because age was not linearly related to depression severity (neither in LEGEND nor in TREND-0). Restricted cubic splines have been considered to be superior to categorized age groups [39]. Explorative analysis of the continuous BDI-II scores revealed a censored distribution among the samples:

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We found no direct effect of TPH2 and the triallelic 5-HTTLPR genotypes on the BDI-II score and also no association between the genotypes and abuse (Fisher’s exact test with p value corrected for two comparisons; p \ 0.025). Expectedly, childhood abuse demonstrated significant main effects with more self-reported childhood abuse indicating higher depression scores. Two-way interactions In LEGEND alone, no significant G 9 E interaction between TPH2 and childhood abuse was found although the interaction pointed to G as the susceptible allele (b = 1.01 and p = 0.40). For TREND-0, this interaction was supported (b = 1.70 and p = 0.047). Carriers of the GG genotype of rs7305115 who were exposed to childhood abuse had higher mean BDI-II scores compared to those carrying no G-allele. Given the higher statistical power, the G 9 E interaction was supported at p \ 0.1 level in the combined sample (b = 1.36 and p = 0.063) (Table 2, supplement Figure S1). Because the regression coefficients indicated a distinct role of GG compared to AA and AG, we repeated the analyses combining AA and AG. This

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Table 1 Descriptive characteristics of participants in SHIP–Trend-0 and SHIP–LEGENDE by sex, N(%) or mean ± SD Characteristic

LEGEND (n = 2,029)

p*

Male (n = 968)

Female (n = 1,061)

56.9 (±14.2)

54.2 (±13.4)

AA Both

149 (15.4) 485 (50.1)

GG

334 (34.5)

Age

Trend-0 (n = 2,475)

p*

Male (n = 1,207)

Female (n = 1,268)

52.6 (±15.2)

50.9 (±14.7)

172 (16.2) 526 (49.6)

185 (15.3) 611 (50.6)

197 (15.5 %) 592 (46.7 %)

363 (34.2)

411 (34.1)

479 (37.8 %)

\0.001

0.005

LEGEND versus Trend-0 p* \0.001

TPH2

5-HTTLPR LGLG/LGS/SS

195 (20.1)

218 (20.5)

240 (19.9)

264 (20.8)

LGLA/SLA

487 (50.3)

546 (51.5)

602 (49.9)

653 (51.5)

LALA

286 (29.5)

297 (28.0)

365 (30.2)

351 (27.7)

Abuse

72 (7.4)

113 (10.7)

0.013

63 (5.2)

129 (10.2)

\0.001

BDI-II

5.8 (±6.6)

7.2 (±8.0)

\0.001

7.4 (±5.5)

8.5 (±5.6)

\0.001

\0.001

* Fisher test for count data and t test for metric data

Table 2 Two-way interactions (Tobit regression with robust estimates adjusted for age, sex and study) with BDI-II as dependent variable in the combined sample LEGEND b TPH2*abuse

Trend-0 p

b

LEGEND ? Trend-0 p

1.01

0.40

1.70

5-HTTLPR*abuse

1.27

0.28

0.34

TPH2*5-HTTLPR

-0.18

0.68

-0.55

0.047* 0.70 0.042*

b

p 1.36

0.063?

0.69

0.35

-0.46

0.071?

Coding variants: TPH2 (G-allele), 5-HTTLPR (L-allele) ?

\0.1, * \0.05

further supported the interaction in the combined sample on a significant level (b = 2.10 and p = 0.042). People who experienced childhood abuse had mean BDI-II scores of 12.1 (95 % CI 10.5–13.7) when carrying also the GG genotype of TPH2 compared to mean BDI-II scores of 9.9 (95 % CI 7.5–12.3) when carrying the AA type (Table 3, supplement Figure S1). Contrary to TPH2, the triallelic genotypes of 5-HTTLPR demonstrated no significant effect on BDI-II score in interaction with abuse neither in LEGEND nor in TREND-0. However, in the combined sample, the effects remained stable in the same direction (Table 2, supplement Figure S2). In the G 9 G interaction combining both samples, subjects carrying the GG type of TPH2 and the SS genotype of the triallelic 5-HTTLPR showed higher mean depression scores than controls. In LEGEND, this effect was relatively small, whereas in TREND-0, this interaction reached significance (b = -0.55 and p = 0.042). The combined sample revealed a substantial interaction (b = -0.46. p = 0.071) (Table 2), but mainly driven by TREND-0. Carriers of the SS genotype of 5-HTTLPR had mean BDI-II scores of 7.2 (95 % CI 6.3–8.2) when

carrying also the GG genotype of TPH2 compared to mean BDI-II scores of 5.9 (95 % CI 4.6–7.3) when carrying the AA type (Table 3, supplement Figure S3). All two-way interactions for the combined sample are given in detail in Table 3. Three-way interaction (TPH2–5-HTTLPR–childhood abuse) To ensure an adequate power, we only analyzed the threeway interaction in the combined sample. A significant interaction between the triallelic 5-HTTLPR, TPH2 and abuse was not found on a global level but for single categories of the interaction term (p = 0.025, supplement Table S1). Carriers of the SS genotype of 5-HTTLPR had mean BDI-II scores of 15.0 (95 % CI 11.0–19.0) when carrying also the GG genotype of TPH2 compared to mean BDI-II scores of 6.8 (95 % CI 2.1–11.4) when carrying the AA type (supplement Table S1, Fig. 1). Because an interacting effect was only visible in carriers of the SS genotype of the triallelic 5-HTTLPR, which represented the reference category, we repeated the two-way analyses between

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abuse and TPH2 stratified by 5-HTTLPR genotype (SS vs. SL vs. LL). This analysis revealed a significant global interaction between abuse and TPH2 only in carriers of the SS genotype of 5-HTTLPR (b = 3.75 and p = 0.023; Table 4). Table 3 Two-way interactions for abuse, TPH2 and the triallelic 5-HTTLPR (Tobit regression with robust estimates adjusted for age, sex and study) with BDI-II as dependent variable (separate analyses each in the combined sample) Abuse

5-HTTLPR

TPH2

n

BDI-II

No

AA

709

6.1 (5.6–6.7)

No

AG

2,224

6.1 (5.8–6.4)

No

GG

1,570

6.0 (5.6–6.3)

Yes

AA

64

9.9 (7.5–12.3

Yes

AG

181

10.2 (9.0–11.4)

Yes

GG

167

12.1 (10.5–13.7)

No

LGLG/LGS/SS

1,010

6.2 (5.7–6.6) 6.3 (6.0–6.6)

No

LGLA/SLA

2,410

No

LALA

1,379

Yes Yes

LGLG/LGS/SS LGLA/SLA

93 213

12.0 (9.9–14.1) 10.0 (8.9–11.2)

Yes

LALA

120

12.6 (10.8–14.5)

LGLG/LGS/SS

AA

147

5.9 (4.6–7.3)

AG

486

6.3 (5.5–7.0)

LGLG/LGS/SS

GG

311

7.2 (6.3–8.2)

LGLA/SLA

AA

371

6.5 (5.7–7.3)

LGLA/SLA

AG

1,110

6.6 (6.1–7.0)

LGLA/SLA

GG

863

6.6 (6.1–7.1)

LALA

AA

205

6.5 (5.4–7.6)

LALA

AG

677

6.3 (5.7–6.8)

LALA

GG

455

6.0 (5.3–6.7)

123

0.063

0.35

5.8 (5.4–6.1)

LGLG/LGS/SS

Fig. 1 Marginsplot of threeway interaction of abuse, triallelic 5-HTTLPR genotypes (SS, SL, LL) and TPH2 genotypes (AA, AG, GG) in the combined sample (mean and 95 % CI)

Global p value

0.071

Sensitivity analysis We further checked for putative sex differences and the effect of the biallelic version of the serotonin transporter polymorphism with regard to the interaction. There were no sex-specific effects either in the two-way or in the threeway analyses. The biallelic version of the 5-HTTLPR showed the same direction of the effects as the triallelic version but largely missed significance. To acknowledge the impact of the two different BDI distributions in LEGEND and TREND-0 (after transformation from PHQ-9), we additionally transformed them into z-scores and repeated the analyses. All results could be confirmed, partially with stronger effects. Because of the recent discussions on confounder–environment interaction in G 9 E studies [41], we checked the influence of additional C 9 E (confounder–environment) and C 9 G (confounder–gene) terms on the G 9 E effect. We added the abuse 9 sex and SNP 9 sex interaction term to both two-way interactions (TPH2 9 abuse, 5-HTTLPR 9 abuse). For TPH2 9 abuse, the effect size changed from b = 1.36 (p = 0.063) to b = 1.42 (p = 0.051), and similarly for 5-HTTLPR 9 abuse, the values changed from b = 0.69 (p = 0.35) to b = 0.71 (p = 0.34), which are changes of \3 % each. This indicates that the C 9 E and C 9 G interaction has no substantial effect on our G 9 E interaction. Explorative analysis of individual BDI-II and PHQ-9 items As depression is defined by a variety of different symptoms, we analyzed which items of the two depression questionnaires show an association with TPH2 and

Eur Arch Psychiatry Clin Neurosci (2014) 264 (Suppl 1):S45–S54 Table 4 Two-way interactions between abuse and TPH2 stratified by 5-HTTLPR genotype (Tobit regression with robust estimates adjusted for age, sex and study) with BDI-II as dependent variable (combined sample n = 4,504) Abuse

TPH2

n

BDI-II

on cognitive items as well (worthlessness, suicidal thoughts and concentration) but not after correcting for multiple testing.

Global p value

Discussion

5-HTTLPR: LGLG/LGS/SS No

AA

122

5.6 (4.2–7.0)

No

AG

438

5.8 (5.1–6.5)

No

GG

261

6.2 (5.3–7.2)

Yes

AA

14

5.8 (5.1–6.5)

Yes

AG

30

11.8 (7.9–15.6)

Yes

GG

31

14.6 (10.6–18.6)

0.023

5-HTTLPR: LGLA/SLA No

AA

327

6.1 (5.3–6.9)

No

AG

974

6.4 (5.9–6.8)

No

GG

755

6.2 (5.7–6.8)

Yes

AA

28

10.9 (7.6–14.3)

Yes

AG

85

9.2 (7.5–10.8)

73

10.2 (8.1–12.2)

Yes GG 5-HTTLPR: LALA

S51

No

AA

183

6.1 (5.1–7.2)

No

AG

601

5.8 (5.2–6.3)

No

GG

393

5.4 (4.8–6.1)

Yes

AA

15

11.4 (5.6–17.3)

Yes

AG

49

11.4 (9.3–13.4)

Yes

GG

43

13.1 (9.4–16.8)

0.92

0.40

5-HTTLPR or an effect in the two-way interactions. To overcome the problem of different scales in BDI-II and PHQ-9, we generated dichotomized variables with 0 for ‘‘absent’’ (lowest category without the specific symptom) and 1 ‘‘present’’ (other grading). The logistic regressions for LEGEND (BDI-II) and TREND-0 (PHQ-9) revealed patterns of item groups that contributed more to the G 9 E interactions. In LEGEND, the items related to the cognitive dimension of depression (worthlessness, guilty feelings and punishment feelings) as proposed by Beck and Steer [28] were significantly (p \ 0.05 %) associated with 5-HTTLPR but not after correction for multiple testing. The same applied to G 9 E two-way interactions with TPH2 and 5-HTTLPR (supplement Table S2). Significant effects were observed for worthlessness, punishment feelings and irritability. Interestingly, items concerning the somatic affective symptoms such as changes in sleeping patterns, appetite or loss of energy were not affected by both genetic variations. In TREND-0, a similar pattern could be observed although only the nine PHQ items were available. No direct associations between PHQ-9 items and serotonergic SNPs could be observed in TREND-0. Nevertheless, the G 9 G interaction seemed to have an effect

We confirmed our hypothesis of an interaction among childhood abuse and genetic variants of TPH2 and 5-HTTLPR. This could be seen in the two-way as well as in the three-way interactions. The GG genotype of rs7305115 (TPH2) was associated with higher depression scores in interaction with abuse which strongly supported the role of serotonin availability in susceptibility for depressive symptoms and disorders. This susceptibility can be explained on the molecular level of serotonin synthesis. Rs7305115 is located on exon 7 and is suggested to have an effect on mRNA transcription and processing. Lim et al. [18] proved that homozygote carriers of the A-allele contained significantly higher levels on TPH2 mRNA than G-allele carriers. In this regard, it was proposed that nonsense-associated altered splicing results in modified transcripts of TPH2 [42]. They assumed that the A-allele generates an efficient protein-binding site for splicing factors, whereas the G-allele leads to a nonfunctional site and more frequently degradation of the transcript. The result is a truncated protein with reduced efficacy and lower serotonin levels in the synapse and synaptic gap. This effect may be too small to have a direct impact on the phenotype level of depressive symptoms in subjects without childhood abuse. However, under the pressure of childhood abuse, the serotonergic system is probably not able to compensate this shortcoming in serotonin synthesis as indicated by the increased risk of adult depressive symptoms associated with the GG genotype. In contrast, unlike other studies in which a G 9 E interaction between the SS genotype of 5-HTTLPR and childhood abuse could be observed, our results do not support this interaction [43]. In fact, we provide evidence for a G 9 G interaction between our analyzed variants. Carriers of the GG genotype of TPH2 and the SS genotype of the triallelic 5-HTTLPR showed significantly higher BDI-II scores. Although the genotypes revealed no main effect on depression score, the biological interaction of both risk variants was sufficient to show an effect on depressive symptoms. Such an additive interaction between two variants of TPH2 (rs4570625) and the triallelic 5-HTTLPR has been reported previously [22]. In our analyses, this effect was even higher in the three-way interaction with childhood abuse. Our results pointed to a risk-enhancing effect of the GG genotype of TPH2 when carriers of the SS genotype of the triallelic 5-HTTLPR

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were exposed to childhood abuse, whereas the AA genotype seemed to have a protective effect (mean BDI-II scores 15.0 vs. 6.8). Thus, possible negative effects of the SS genotype could be buffered by the high expressing AA genotype of TPH2. Our study supports the hypothesis that TPH2 and the serotonin transporter, two key regulators of the serotonin pathway, are involved in G 9 E interactions in the face of adverse childhood experience. The results also clearly support the assumption of the serotonin deficit hypothesis [8] linking the occurrence of depressive symptoms to lack of serotonin in the synaptic gap. This is in line with findings from Neumeister et al. investigating the clinical effects of tryptophan depletion, the precursor molecule of serotonin [44]. They reported that the genotype of 5-HTTLPR moderated behavioral response to tryptophan depletion in patients with recurrent MDD. Carriers of at least one L-allele showed higher depression scores than the SS genotype. Although our study showed the impact of TPH2, 5-HTTLPR and childhood abuse on depression, several limitations need discussion: 1.

2.

3.

4.

It has been pointed out previously that individual SNPs, although functional, convey a relatively small effect. Therefore, in future studies, one should consider also polygenic risk scores where the information on many risk variants can be accumulated [45]. Studies on G 9 E interactions revealed a number of different environmental factors that might interact with genes. This includes early-life stress like childhood trauma as well as positive or negative life events [10]. Thus, a combination of individual polygenic as well as poly-environmental risk scores could be important to get more comprehensive insights into the individual risk of disease. Although the genome is a stable construct, the regulation of gene expression can be altered by epigenetic changes. One of these mechanisms is DNA-methylation with varying patterns over lifetime, especially after environmental stress [46]. A number of studies found associations between early trauma and alterations in methylation patterns of candidate genes like 5-HTTLPR [47]. Therefore, it seems conceivable that some effects of genetic variation may be masked by methylation or that the observed interactions are also driven by them. According to DSM-IV, depression is defined by several symptoms affecting mood and energy, experience of enjoyment, eating and sleeping patterns, feelings of guilt and worthlessness and suicidal thoughts. The heterogeneity of these symptoms has been widely

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5.

6.

reported [48]. Some studies made proposed to distinguish between subtypes, such as melancholic or atypical depression [49] based on metabolic status or HPA-axis reactivity [50]. Our analysis of the individual depression items also supported this distinction between depression subtypes. Mainly items concerning the cognitive dimension of depression were affected by the G 9 E and G 9 G interactions, but no item concerning somatic factors. In their initial study, Beck and Steer proposed this distinction between a somatic affective and a cognitive dimension in the BDI-II items [28]. Thus, it might be important to stratify cases with depressive disorders according to their metabolic status, depression subtypes (somatic, cognitive) or environmental factors like age at onset or exposure to childhood and adult trauma. We investigated BDI-II sum scores as a measure for depressive symptoms by a self-rating questionnaire. A structured interview with professional raters could provide a more precise insight into different symptoms, especially when searching for depression subtypes. Although the overall sample size of our study was large, the number of subjects in subgroups of the interaction analyses dropped to 14 cases at minimum, especially in combination with abuse and the minor alleles.

In the next step, we will analyze additional variants within the serotonin pathway to get a more comprehensive view of interacting genes and environmental factors regarding depressive symptoms. This includes serotonin receptors (HTR) as well as further genes impacting on presynaptic processes such as monoamine oxidase (MAOA/B) or dopa decarboxylase (DDC). In conclusion, we demonstrated the role of the low-expression G-allele of TPH2 and the S-allele of the triallelic 5-HTTLPR in the susceptibility for depressive disorders in subjects who have experienced childhood abuse. Acknowledgments SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (Grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of MecklenburgWest Pomerania. Genome-wide data have been supported by the Federal Ministry of Education and Research (Grant no. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. This work was also funded by Federal Ministry of Education and Research (GANI_MED; Grant no. 03IS2061A) and the German Research Foundation (DFG: GR 1912/5-1). Conflict of interest The authors have declared that no conflicts of interest exist.

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