Mol Diagn Ther DOI 10.1007/s40291-014-0110-7
ORIGINAL RESEARCH ARTICLE
Serotonin Transporter Gene: A New Polymorphism May Affect Response to Antidepressant Treatments in Major Depressive Disorder Yoshihiko Matsumoto • Chiara Fabbri • Silvia Pellegrini • Stefano Porcelli • Pierluigi Politi • Silvio Bellino • Caterina Iofrida • Veronica Mariotti • Erika Melissari • Marco Menchetti • Valentina Martinelli • Marco Cappucciati • Paola Bozzatello • Elena Brignolo • Paolo Brambilla Matteo Balestrieri • Alessandro Serretti
•
Ó Springer International Publishing Switzerland 2014
Abstract Background and Objectives Several gene variants have been related to major depressive disorder (MDD) treatment outcomes; however, few studies have investigated a possible different effect on pharmacotherapy and brief psychotherapy response. Methods A total of 137 MDD patients were randomized to either interpersonal counseling (IPC; n = 40) or antidepressant pharmacological treatment (n = 97). Outcomes were remission, response, and symptom improvement at week 8. Five genetic variants were investigated (5HTR2A rs6314, BDNF rs6265, SLC6A4 rs8076005, CREB1 rs2253206, and TPH2 rs11179023) as possible modulators of outcomes.
Results The LC6A4 rs8076005 AA genotype and A allele were associated with response rate in the antidepressant group (p = 0.015 and 0.005, respectively) and in the whole sample (p = 0.03 and 0.02, respectively). In the IPC group a non-significant trend in the same direction was observed. The TPH2 rs11179023 A allele showed a marginal association with symptom improvement in the IPC group only. Other gene variants did not impact on outcomes in any treatment group. Conclusion Our study suggests that rs8076005 in the SLC6A4 gene may be a modulator of antidepressant response, especially when pharmacological treatment is used.
Electronic supplementary material The online version of this article (doi:10.1007/s40291-014-0110-7) contains supplementary material, which is available to authorized users. Y. Matsumoto C. Fabbri S. Porcelli A. Serretti (&) Department of Biomedical and Neuromotor Sciences, University of Bologna, Viale Carlo Pepoli 5, 40123 Bologna, Italy e-mail: [email protected] Y. Matsumoto Department of Psychiatry, Yamagata University School of Medicine, Yamagata, Japan S. Pellegrini C. Iofrida V. Mariotti E. Melissari Department of Surgical, Medical, Molecular Pathology and of Critical Area, University of Pisa, Pisa, Italy P. Politi V. Martinelli M. Cappucciati Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
S. Bellino P. Bozzatello E. Brignolo Neuroscience Department, Turin University, Turin, Italy M. Menchetti Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy P. Brambilla M. Balestrieri Unit of Psychiatry, Department of Experimental and Clinical Medical Sciences (DISM), ICBN, University of Udine, Udine, Italy P. Brambilla Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, USA
Y. Matsumoto et al.
Key Points The role in treatment response of five genes involved in the modulation of the serotonergic system (HTR2A, BDNF, SLC6A4, CREB1, and TPH2) was examined in 137 major depressive disorder patients treated with interpersonal counseling (IPC) or antidepressant drugs. Our findings supported the association of SLC6A4 rs8076005 with response in both treatment groups. A marginal association between TPH2 rs11179023 and symptom improvement was observed in the IPC group only.
1 Introduction Major depressive disorder (MDD) is one of the most common psychiatric disorders (lifetime prevalence: 12.8 %) [1], and is among the major causes of worldwide disability [2]. The heavy personal and socioeconomic burden of MDD is partly due to the unsatisfactory response and remission rates (47 % and 33 %, respectively) [3]. Antidepressant drugs and psychotherapy are thought to be equally efficacious in moderate MDD [4, 5]; however, predictors of response to antidepressant treatments to guide treatment choice in the individual patient are not available. Among predictors of clinical outcomes, genetic variants are estimated to contribute substantially to the interindividual variability [6–9]. Serotonergic genes represent ideal candidates since current antidepressant drugs mainly act by the modulation of the serotonergic system. The serotonin receptor gene 2A (HTR2A) is expressed in all neocortex, hippocampus, and prefrontal cortex [10]. 5-HT-induced Ca2? response in platelets was found to be enhanced in MDD [11] after remission during treatment with imipramine [12]. The missense T allele of HTR2A rs6314 showed lower Ca2? response to 5-HT than those without the mutation [13]. Two studies found that this polymorphism may predict the efficacy of selective serotonin reuptake inhibitors (SSRIs) [14, 15]. The serotonin transporter (SLC6A4 gene) plays a pivotal role in the regulation of serotonin concentration in the synaptic cleft and extrasynaptic sites. Promoter polymorphisms (5-HTTLPR and rs25531) have been extensively investigated, leading to replicated, even if not univocal, results [16]. The intronic rs8076005 has been previously associated with interleukin (IL)-6 levels in MDD and depressive symptom severity [17], but has not been studied as a possible modulator of treatment response.
Tryptophan hydroxylase (TPH) catalyzes the rate-limiting step in the synthesis of 5-HT. TPH2 is the main isoform expressed in the CNS, but studies focused on its role in antidepressant response reported inconsistent results [18–33]. TPH2 rs1179023 variation has not been investigated in the field before, thus represents a new candidate within a gene with strong biological rationale of involvement in antidepressant action. During antidepressant treatment, the enhancement of 5-HT availability increases brain-derived neurotrophic factor (BDNF) synthesis and signaling, a major event in the stimulation of adult neurogenesis [34]. BDNF serum levels are associated with MDD and antidepressant response [35]. The rs6265 (Val66Met) was associated with BDNF secretion [36], BDNF serum levels [37], and antidepressants response [38–40]. Cyclic adenosine monophosphate response elementbinding protein 1 (CREB1) is a transcription factor activated by a number of signals, among which are neuronal growth factors and stress-induced signals [41, 42]. The CREB1 gene has been associated with recurrent early-onset MDD [43, 44]. The G allele of the promoter polymorphism rs2253206 has been associated with lower promoter activity [45] and the same single nucleotide polymorphism (SNP) may affect the risk of MDD, depression severity [46], and risk of treatment-resistant depression [47]. Given the data supporting the involvement of these genes in antidepressant action, the present paper aims to study the role of HTR2A rs6314, BDNF rs6265, SLC6A4 rs8076005, CREB1 rs2253206, and TPH2 rs11179023 in a sample 137 Italian MDD patients treated with IPC or antidepressants in a multicenter, randomized trial.
2 Methods 2.1 Sample Subjects aged 18 years or older with a diagnosis of MDD (Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision [DSM-IV TR]) were recruited. Inclusion and exclusion criteria have been detailed elsewhere [48]. Eligible patients were divided into interpersonal counseling (IPC, a type of brief psychotherapy derived from interpersonal psychotherapy [IPT] [49–51]) or pharmacological antidepressant treatment [52] groups. Subjects were collected in three centers (Neuroscience Department, Turin University; Department of Health Sciences, University of Pavia; and Institute of Psychiatry, Bologna University), as previously reported [48]. All patients recruited at Bologna University were treated with antidepressant drugs. Despite the design of the study had been planned as randomized, failure in developing a
Serotonergic Genes in Response to Antidepressants and Psychotherapy
psychotherapy arm at Bologna University (the centre that recruited the higher number of patients) resulted in different sizes between the two treatment arms. In all cases of pharmacological treatment, the antidepressant was chosen and titrated according to current guidelines up to the effective dose range within the first week of treatment. Ethical approval was obtained from the Ethic Committees of all participating centers.
electronic supplementary Table 1, together with polymorphisms in complete linkage disequilibrium (R2 [ 0.8). 2.5 Genotyping
All subjects were evaluated with both structured and unstructured interviews to obtain diagnoses assigned by two independent experienced psychiatrists. Depressive states were assessed at baseline and after 8 weeks through the Hamilton Depression Rating Scale (HDRS, 21-item version). Assessments were performed by trained psychiatrists, and inter-rater reliability was k = 0.8. A monitoring of treatment adherence through drug plasma level determination was not performed, but treatment adherence was assessed weekly by a trained psychiatrist and side effects were monitored weekly using the Dosage Record & Treatment Emergent Symptom scale (DOTES) [53]. Thus, we can suppose that non-responders at week 8 were not false non-responders due to overlooked side effects and poor treatment adherence.
DNA was purified from whole blood using the QIAamp DNA Blood Kit (Qiagen, Valencia, CA, USA), according to the manufacturer’s protocol. rs6314 (HTR2A, Chr 13q14–q21), rs6265 (BDNF, Chr 11p13), rs8076005 (SLC6A4, Chr 17q11.2), rs2253206 (CREB1, Chr 2q34),and rs11179023 (TPH2, Chr 12q21.1) were genotyped by high-resolution melting polymerase chain reaction (HRM PCR). All experiments were performed by the Rotor Gene Q instrument (Qiagen), using the Type-it HRM PCR kit (Qiagen). All primers were designed by Beacon Designer v. 7.9 (PREMIER Biosoft, Palo Alto, CA, USA). After an initial step of enzyme activation at 95 °C for 5 min, PCRs were carried out for 40 cycles as follows: denaturation at 95 °C for 10 s and annealing at 60 °C for 30 s. HRM analysis was performed with a temperature resolution of 0.1 °C and a temperature range between 70 and 85 °C. Data collection and genotype calls were obtained by the Rotor-Gene 6000 series software v. 1.7 (Qiagen) using as reference genotypes DNA samples sequenced by ABI PrismÒ 310 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA).
2.3 Outcomes
2.6 Statistical Analysis
The primary outcome was remission at week 8, defined according to standard criteria (HDRS score B7), and the secondary outcomes were response (at least 50 % reduction in HDRS score) and HDRS percentage improvement at week 8.
The effect of genotypes and alleles on response and remission was tested by Pearson’s Chi-squared tests. A multivariate analysis of variance (MANOVA) was used to study the effect of genotypes and alleles on improvement at week 8, adjusting for center, sex, age, and baseline severity. Analyses were carried out only in completers, in the two individual treatment groups and in the whole sample. Despite the selected candidate genes showing a strong biological rationale for involvement in antidepressant mechanisms of action and the pre-test probability of association being favorable, Bonferroni correction was applied to reduce the risk of false positives. Thus, the alpha value was set to 0.005 considering five independent polymorphisms that were tested in two independent groups of patients (IPC- and antidepressant-treated). The whole sample was not considered as an independent group. In addition, the three analyzed phenotypes (response, remission, and symptom improvement) were considered as highly related to each other. Furthermore, we stated only remission as a primary outcome (see Sect. 2.3.). Our whole sample setting alpha value to 0.005 two-tailed provides a power of 0.80 to detect a risk allele (for nonremission) with odds ratio (OR) C4.0 (Gpower 3.1 software).
2.2 Evaluations
2.4 Polymorphism Selection The genotyped SNPs were selected according to the following criteria: (1) tagging approach (R2 = 0.08); (2) reported prevalence of at least 5 % for the minor allele among Caucasians (data from http://hapmap.ncbi.nlm.nih. gov/); (3) availability of a validated assay in our laboratory; and (4) previous literature findings. In detail, the Tagger software was used to test SNPs downloaded from HapMap (Rel 28 Phase II ? III, August 2010, NCBI B36 assembly, dbSNP b126) and that satisfied some quality criteria (maximum number of Mendel errors = 1; p-value for the Hardy–Weinberg equilibrium (HWE) [0.001, minor allele frequency [MAF] [5 %). The Tagger program was used to identify SNPs that tagged at least two other SNPs with r2 and logarithm of the odds (LOD) thresholds of 0.8 and 3, respectively. The selected polymorphisms are shown in the
Y. Matsumoto et al.
3 Results SCL6A4 rs8076005 slightly deviated from the HWE (p = 0.03), while the other polymorphisms satisfied HWE (HT2A rs6314: p = 0.61; BDNF rs6265: p = 0.34; CREB1 rs2253206: p = 0.52; TPH2 rs11179023: p = 0.45). For one subject in the IPC group and two in the antidepressant group, genotyping was not successful and they were thus excluded from the analysis. Clinical-demographic characteristics of the sample are reported in Table 1. The majority of patients were treated with SSRIs (80.4 %), and further clinical data have been reported in a previous paper [48]. Non-completers (12.74 %) did not show any difference in age, sex, and baseline severity when compared with the 8-week completers [48]. As previously reported [48], no difference was observed in clinical outcomes between the two treatment groups (Table 1). In the IPC group, the number of remitters was slightly higher than that of responders because the IPC group had lower baseline severity than the antidepressant group. Nevertheless, the difference was not so pronounced to be clinically relevant, and analyses were adjusted for baseline severity. 3.1 Effect of Polymorphisms on Outcomes The SLC6A4 rs8076005 A allele reached the significance threshold for association with better response in the
antidepressant group (p = 0.005) and showed a consistent trend in the whole sample (p = 0.02) [Tables 2 and 3]. Furthermore, rs8076005 A allele carriers showed a trend of higher symptom improvement at week 8 in the whole sample (F = 3.29; df = 2; p = 0.04). The association between the rs8076005 AA genotype A allele and response was more evident after correction for age, sex, baseline severity, and center in the antidepressant group (Z = 2.81, p = 0.005; Z = 3.10, p = 0.002, respectively), while trends were found in the whole group (Z = 2.51, p = 0.012; Z = 2.54, p = 0.011, respectively). The TPH2 rs11179023 A allele showed a mild trend of selective association with symptom improvement in the IPC group (F = 4.29; df = 1; p = 0.042), but no effect was found on response and remission. The other investigated polymorphisms did not show evidence or trends of impact on clinical outcomes in none of the analyzed groups (Tables 2 and 3; data pertaining to percentage improvement not shown).
4 Discussion This study investigated the effect of five serotonergic polymorphisms on clinical outcomes of IPC, a type of brief psychotherapy, versus antidepressant pharmacotherapy. As previously reported in this sample [48], IPC, as well as
Table 1 Clinical characteristics and outcomes at week 8 according to treatment group. Chi-squared and Fisher’s exact tests were used as appropriate to test differences between the two treatment groups Whole sample (N = 137)
IPC (N = 40)
Antidepressants (N = 97)
Statistics
88 (64.23)
25 (62.50)
63 (64.95)
49 (35.77)
15 (37.50)
34 (35.05)
Yes
87 (63.50)
28 (70.00)
59 (60.82)
No
50 (36.50)
12 (30.00)
38 (39.18)
V2 = 0.671, df = 1, p = 0.41
Improvement (%)
54.66 ± 28.77
52.09 ± 19.86
55.72 ± 31.76
t = -0.67, CI -0.144 to 0.071, p = 0.50
HDRS missing at week 8
20
1
19
OR 0.13, CI 0.003–0.865, p = 0.03
Baseline severity (HDRS)
17.97 ± 5.24
16.24 ± 4.01
18.58 ± 5.50
t = -2.49, CI -4.18 to -0.48, p = 0.014
Age, years (mean ± SD)
51.02 ± 17.98
44.10 ± 16.19
53.51 ± 18.00
t = -2.95, CI -15.72 to -3.10, p = 0.004
Gender (F/M)
91/46
24/16
67/30
V2 = 1.05, df = 1, p = 0.31
Pharmacological treatment [n (%)]
–
None
78 (80.4): SSRIs
–
Response [n (%)] Yes No Remission [n (%)]
V2 = 0.006, df = 1, p = 0.94
15 (15.5): SNRIs 4 (4.1): other antidepressants
CI 95 % confidence interval, IPC interpersonal counselling, OR odds ratio, HDRS Hamilton Depression Rating Scale, SD standard deviation, F female, M male, SSRIs selective serotonin reuptake inhibitors, SNRIs serotonin norepinephrine reuptake inhibitors
8 (66.67)
0 (0)
No
10 (83.33)
2 (13.33)
Yes
Yes
Response
1 (4.17)
5 (20.83)
6 (50.00)
2 (16.67)
No
TPH2 rs11179023
13 (48.15)
5 (18.52)
5 (33.33)
14 (58.33)
Yes
Remission
No
5 (20.83)
Response
2 (16.67)
4 (14.81)
2 (13.33)
13 (86.67)
23 (85.19)
4 (16.67)
20 (83.33)
CREB1 rs2253206
No
Yes
Remission
No
Yes
Response
SLC6A4 rs8076005
11 (40.74)
9 (60.00)
0 (0)
3 (11.11)
10 (41.67)
3 (12.50)
Yes
Remission
No
Yes
Response
BDNF rs6265
18 (75.00)
4 (33.33)
9 (33.33)
8 (53.33)
5 (20.83)
0 (0)
0 (0)
0 (0)
0 (0)
4 (33.33)
13 (48.15)
6 (40.00)
11 (45.83)
31 (83.78)
v2 = 2.207, df = 2
p = 0.99
v2 = 0.022, df = 2
p = 0.11
v2 = 4.398, df = 2
3 (4.84)
7 (18.92)
8 (13.79)
5 (15.15)
10 (16.13)
20 (54.05)
32 (55.17)
p = 0.88
14 (42.42)
p = 0.78
38 (61.29)
1 (2.70)
3 (5.17)
1 (3.03)
3 (4.84)
v2 = 0.022, df = l
v2 = 0.079, df = 1
p = 0.24
v2 = 2.898, df = 2
p = 0.28
v2 = 2.584, df = 2
Statistics
p = 0.64
5 (13.51)
14 (24.14)
6 (18.18)
13 (20.97)
17 (27.42)
17 (49.95)
33 (56.90)
16 (48.48)
34 (54.84)
10 (27.03)
22 (37.93)
11 (33.33)
21 (33.87)
14 (37.84)
23 (39.66)
13 (39.39)
24 (38.71)
AG
42 (67.74)
13 (35.14)
17 (29.31)
12 (36.36)
18 (29.03)
7 (18.92)
4 (6.90)
8 (24.24)
3 (4.84)
22 (59.46)
32 (55.17)
19 (57.58)
v2 = 3.449, df = 2
p = 0.57
v2 = 1.133, df = 2
p = 0.76
v2 = 0.545, df = 2
p = 0.16
v2 = 3.622, df = 2
p = 0.015
v2 = 8.405, df = 2
p = 0.81
v2 = 0.419, df = 2
p = 0.92
v2 = 0.175, df = 2
Statistics
p = 0.22
v2 = 3.022, df = 2
p = 0.72
v2=0.669, df = 2
Statistics
35 (56.45)
GG
1 (2.70)
0 (0)
0 (0)
1 (1.61)
AA
AG
GG
0 (0)
44 (75.86)
27 (81.82)
48 (77.42)
AA
3 (25.00)
v2 = 0.214, df = l
p = 0.45
v2 = 0.566, df = l
TT
Antidepressants (N = 95)
9 (75.00)
No
0 (0)
0 (0)
0 (0)
CT
IPC (N = 39)
22 (81.48)
Yes
5 (15.52)
4 (26.67)
11 (73.33)
No
Remission
4 (16.67)
20 (83.33)
Yes
Response
HTR2A rs6314
Statistics
CC
TT
CC
CT
Antidepressants (N = 95)
IPC (N = 39)
Table 2 Response and remission at week 8 for each genotype and treatment group
8 (16.33)
19 (22.35)
10 (20.83)
17 (19.77)
CT
4 (4.66)
9 (18.37)
13 (15.29)
7 (14.58)
15 (17.44)
30 (61.22
55 (64.71)
27 (56.25)
58 (67.44)
1 (2.04)
6 (7.06)
1 (2.08)
6 (6.98)
AA
22 (25.58)
23 (46.94)
46 (54.12)
21 (43.75)
48 (55.81)
12 (24.49)
26 (30.59)
13 (27.08)
25 (29.07)
22 (44.90)
34 (40.00)
22 (45.83)
34 (39.53)
AG
Whole sample (N = 134)
40 (81.63)
66 (77.65)
38 (79.17)
68 (79.07)
CC
Whole sample (N = 134)
60 (69.77)
17 (34.69)
26 (30.59)
20 (41.67)
23 (26.74)
7 (14.29)
4 (4.71)
8 (16.67)
3 (3.49)
26 (53.06)
45 (52.94)
25 (52.08)
46 (53.49)
GG
1 (2.04)
0 (0)
0 (0)
1 (1.16)
TT
v2 = 0.911, df = 2
p = 0.72
v2 = 0.653, df = 2
p = 0.21
v2 = 3.162, df = 2
p = 0.14
v2 = 3.942, df = 2
p = 0.03
v2 = 7.168, df = 2
p = 0.43
v2 = 1.677, df = 2
p = 0.42
v2 = 1.716, df = 2
Statistics
p = 0.31
v2 = 2.357, df = 2
p = 0.75
v2 = 0.576, df = 2
Statistics
Serotonergic Genes in Response to Antidepressants and Psychotherapy
p = 0.90 32 (65.31) 15 (30.61) 2 (4.08)
IPC interpersonal counseling
0 (0) No
Values reported in parentheses represent percentage values corresponding to the reported numeric values
p = 0.97 22 (59.46) 13 (35.14) 2 (5.41) p = 0.79 10 (83.33)
23 (27.06) 4 (4.71) v2 = 0.065, df = 2 36 (62.07) 19 (32.76) 3 (5.17) v2 = 0.466, df = 2 22 (81.48) 4 (14.81) 1 (3.70) Yes
2 (16.67)
v2 = 0.205, df = 2 58 (68.24)
p = 0.63 30 (62.50) 16 (33.33) 2 (4.17) p = 0.18 16 (48.48) 15 (45.45) 2 (6.06) p = 0.33 14 (93.33) 1 (6.67) 0 (0) No
Statistics AG
GG
Table 2 continued
Remission
AG AA AA AA
AG
Antidepressants (N = 95) IPC (N = 39)
GG
Statistics
Whole sample (N = 134)
GG
Statistics
Y. Matsumoto et al.
antidepressants, are effective in the treatment of mild to moderate MDD. The SLC6A4 rs8076005 AA genotype and A allele were associated with response in the antidepressant group, with consistent trends in the whole sample (Tables 2 and 3). Rs8076005 has been previously suggested as a risk factor for MDD through the neural–immune interaction [17], even if this does not necessarily imply an impact of the SNP on antidepressant response. In detail, rs8076005 G allele carriers showed higher depressive symptom severity and higher IL-6 levels, as well as the same was demonstrated for the minor allele of SNPs that are in linkage disequilibrium with rs8076005 (rs12150214, rs11080122, rs8071667, rs2020936, rs25528, and rs6354). Interestingly, IL-6 levels were previously demonstrated to negatively affect antidepressant response [54–56]. Two SNPs in linkage disequilibrium with rs8076005 (rs6354 and rs2020936) were associated with anxiety, MDD, and neuroticism [57]. On the other hand, the rs8076005 A allele did not affect clinical outcomes in the IPC group, which instead may be influenced by TPH2 rs11179023. Inconsistent results were found about the role of TPH2 variants in antidepressant response [14, 20, 29, 31, 32, 58], but rs11179023 has not been investigated previously. In this study, the rs11179023 A allele showed a trend of higher symptom improvement at week 8 only in the IPC group, while the genotypic analysis could not be performed since only one subject carried the AA genotype. Clearly, the present result did not allow the tracing of any statement, but suggested a new polymorphism within a known candidate gene for further investigation. In the present study, HTR2A rs6314 was not associated with antidepressants or IPC outcomes. Despite some inconsistent results, previous studies suggested that this polymorphism may be associated with SSRI response [14, 15, 59]. Thus, the use of different treatments in our study or the small sample size may partly explain the reported negative findings. In this study, BDNF rs6265 did also not affect treatment outcomes. Recent meta-analyses reported that the heterozygous genotype may be a predictor of better antidepressant response [38–40], but negative findings have also been reported [60–71]. The inconsistency in previous results may be at least partly due to different rs6265 allele and genotype distribution across populations. Indeed, the frequency of the Met allele is higher in the Asian population than in the Caucasian population, and the Met allele may be protective against MDD and may be associated with better antidepressant response only in Asian subjects [38, 40, 72]. Phosphorylation of CREB is related to cellular resilience and neuroplasticity [73]. Phosphorylated CREB (pCREB) is positively correlated with antidepressant and IPT
Yes
7 (14.58)
41 (85.42)
14 (58.33)
10 (41.67)
No
TPH2 rs11179023 Response
31 (57.41)
21 (70.00)
9 (30.00)
23 (42.59)
24 (50.00)
24 (50.00)
2 (8.33)
Yes
Remission
No
Yes
Response
CREB1 rs2253206
22 (91.67)
No
4 (7.41)
2 (6.67)
28 (93.33)
50 (92.59)
4 (8.33)
44 (91.67)
Yes
Remission
No
Yes
Response
16 (66.67)
No 8 (33.33) SLC6A4 rs8076005
21 (70.00)
9 (30.00)
37 (68.52)
32 (66.67)
16 (33.33)
17 (31.48)
Yes
Remission
No
Yes
Response
BDNF rs6265
v2 = 2.538, df = 1
p = 0.94
v2 = 0.006, df = 1
p = 0.08
v2 = 3.025, df = 1
p = 0.89
v2 = 0.020, df = 1
p = 0.79
v2 = 0.072, df = 1
p = 0.87
v2 = 0.026, df = 1
p = 0.76
v2 = 0.094, df = 1
Statistics
7 (9.46)
23 (18.55)
31 (41.89)
49 (42.24)
26 (39.39)
54 (43.55)
50 (67.57)
86 (74.14)
39 (59.09)
97 (78.23)
16 (21.62)
29 (25.00)
15 (22.73)
30 (24.19)
101 (81.45)
43 (58.11)
67 (57.76)
40 (60.61)
70 (56.45)
24 (32.43)
30 (25.86)
27 (40.91)
27 (21.77)
58 (78.38)
87 (75.00)
51 (77.27)
94 (75.81)
G
A
G
67 (90.54)
14 (12.07)
6 (0.09)
15 (12.10)
A
p = 0.66
102 (87.93)
60 (90.91)
109 (87.90)
Antidepressants (N = 95)
3 (12.50)
v2 = 0.190, df = 1
p = 0.48
v2 = 0.501, df = 1
IPC (N = 39)
21 (87.50)
No
5 (9.26)
4 (13.33)
26 (86.67)
49 (90.74)
4 (8.33)
44 (91.67)
Yes
Remission
No
Yes
Response
HTR2Ars6314
T
C
Statistics
C
T
Antidepressants (N = 95)
IPC (N = 39)
Table 3 Response and remission at week 8 for each allele and treatment group
v2 = 2.623, df = 1
p = 0.96
v2 = 0.002, df = 1
p = 0.58
v2 = 0.305, df = 1
p = 0.33
v2 = 0.959, df = 1
p = 0.005
v2 = 7.752, df = 1
p = 0.59
v2 = 0.285, df = 1
p = 0.82
v2 = 0.051, df = 1
Statistics
p = 0.58
v2 = 0.313, df = 1
p = 0.53
v2 = 0.396, df = 1
Statistics
10 (10.20)
19 (11.18)
10 (10.42)
19 (11.05)
T
30 (17.44)
41 (41.84)
72 (42.35)
35 (36.46)
78 (45.35)
72 (73.47)
136 (80.00)
67 (69.79)
141 (81.98)
24 (24.49)
46 (27.06)
24 (25.00)
46 (26.74)
A
142 (82.56)
57 (58.16)
98 (57.65)
61 (63.54)
94 (54.65)
26 (26.53)
34 (20.00)
29 (30.21)
31 (18.02)
74 (75.51)
124 (72.94)
72 (75.00)
126 (73.26)
G
Whole sample (N = 134)
88 (89.80)
151 (88.82)
86 (89.58)
153 (88.95)
C
Whole sample (N = 134)
v2 = 0.467, df = 1
p = 0.93
v2 =0.007, df = 1
p = 0.16
v2 = 1.997, df = 1
p = 0.22
v2 = 1.526, df = 1
p = 0.02
v2 = 5.265, df = 1
p = 0.65
v2 = 0.213, df = 1
p = 0.76
v2 = 0.097, df = 1
Statistics
p = 0.81
v2 = 0.061, df = 1
p = 0.87
v2 = 0.025, df = 1
Statistics
Serotonergic Genes in Response to Antidepressants and Psychotherapy
19 (19.39)
79 (80.61)
p = 0.82
response in MDD [73, 74]. Previous association studies suggested that the CREB1 gene may show a selective effect on the risk of treatment resistance in MDD [47] and paroxetine response [71]. Our negative results are line with other studies focused on response to mixed antidepressant treatments [61, 75]. Among the limitations of the present study, the first is the limited statistical power compared with current pharmacogenetic studies, particularly in the IPC group. Thus, the present findings should be cautiously considered. However, the low sample size mainly affects the risk of false negative findings given the lack of power to find small effect sizes. Furthermore, the choice of candidate genes with strong biological plausibility for involvement in antidepressant mechanisms of action contributes to reducing the risk of false positives. Other limitations are represented by the use of the present sample in a previous pharmacogenetic study [48] and the recruitment of patients in different centers (even if the center of recruitment was used as covariate and inter-rater reliability was good). Another issue is the deviation of SLC6A4 rs8076005 from HWE, despite that the MAF was in line with that reported in the HapMap database for the CEU population (0.22 in our study and 0.18 according to HapMap phase III release on NCBI B36 assembly, dbSNP b126). The availability of more evaluation time points could have provided information about response timing in the two treatment groups. Finally, the use of a naturalistic setting in the pharmacological arm of the study could be seen as a limitation, but also provided a perspective that is more near to real clinical practice, and the major part of patients were treated with SSRIs. Despite these limitations, the present study is among the few that have investigated the impact of genetic variants on brief psychotherapy response. Previous studies were mainly focused on the effect of genetic variants on personality characteristics that may in turn affect psychotherapy outcome. Further genetic studies directly focused on the efficacy of psychological interventions in MDD are clearly needed. Personality features should be considered as modulators. However, in the present sample the comorbidity with personality disorders did not affect IPC outcomes [48], as found by an independent study [76]. IPC interpersonal counseling
p = 0.709 22 (91.67) 2 (8.33) No
Values reported in parentheses represent percentage values corresponding to the reported numeric values
p = 0.82 57 (77.03)
31 (18.24) v2 = 0.053, df = 1 91 (78.45) 25 (21.55) v2 = 0.139, df = 1 6 (11.11) Yes
48 (88.89)
17 (22.97)
v2 = 0.054, df = 1 139 (81.76)
p = 0.49 76 (79.17) 20 (20.83) p = 0.11 19 (28.79) p = 0.11 No
Remission
1 (3.33)
29 (96.67)
47 (71.21)
G A G A Statistics G A
IPC (N = 39)
Table 3 continued
Antidepressants (N = 95)
Statistics
Whole sample (N = 134)
Statistics
Y. Matsumoto et al.
5 Conclusions Our study suggests that SLC6A4 rs8076005 may impact on antidepressant response at week 8, especially in patients treated with antidepressant drugs. TPH2 may be a selective modulator of IPC response, even if this result is even more preliminary given the limited size of the IPC-treated group and the non-significance of the finding after Bonferroni
Serotonergic Genes in Response to Antidepressants and Psychotherapy
correction. IPC, an effective treatment in mild to moderate MDD, is worthy of further investigation in genetic studies. Acknowledgments (2008XWR4SB).
The
study
was
funded
by
14.
MIUR
Disclosure statement Dr Serretti is, or has been, a consultant/ speaker for Abbott, Astra Zeneca, Clinical Data, Boheringer, Bristol Myers Squibb, Eli Lily, GlaxoSmithkline, Janssen, Lundbeck, Pfizer, Sanofi, and Servier. Yoshihiko Matsumoto, Chiara Fabbri, Silvia Pellegrini, Stefano Porcelli, Pierluigi Politi, Silvio Bellino, Caterina Iofrida, Veronica Mariotti, Erika Melissari, Marco Menchetti, Valentina Martinelli, MarcoCappucciati, Paola Bozzatello, Elena Brignolo, Paolo Brambilla, and Matteo Balestrieri have no conflicts of interest.
15.
16.
17.
18.
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ORIGINAL RESEARCH ARTICLE
Serotonin Transporter Gene: A New Polymorphism May Affect Response to Antidepressant Treatments in Major Depressive Disorder Yoshihiko Matsumoto • Chiara Fabbri • Silvia Pellegrini • Stefano Porcelli • Pierluigi Politi • Silvio Bellino • Caterina Iofrida • Veronica Mariotti • Erika Melissari • Marco Menchetti • Valentina Martinelli • Marco Cappucciati • Paola Bozzatello • Elena Brignolo • Paolo Brambilla Matteo Balestrieri • Alessandro Serretti
•
Ó Springer International Publishing Switzerland 2014
Abstract Background and Objectives Several gene variants have been related to major depressive disorder (MDD) treatment outcomes; however, few studies have investigated a possible different effect on pharmacotherapy and brief psychotherapy response. Methods A total of 137 MDD patients were randomized to either interpersonal counseling (IPC; n = 40) or antidepressant pharmacological treatment (n = 97). Outcomes were remission, response, and symptom improvement at week 8. Five genetic variants were investigated (5HTR2A rs6314, BDNF rs6265, SLC6A4 rs8076005, CREB1 rs2253206, and TPH2 rs11179023) as possible modulators of outcomes.
Results The LC6A4 rs8076005 AA genotype and A allele were associated with response rate in the antidepressant group (p = 0.015 and 0.005, respectively) and in the whole sample (p = 0.03 and 0.02, respectively). In the IPC group a non-significant trend in the same direction was observed. The TPH2 rs11179023 A allele showed a marginal association with symptom improvement in the IPC group only. Other gene variants did not impact on outcomes in any treatment group. Conclusion Our study suggests that rs8076005 in the SLC6A4 gene may be a modulator of antidepressant response, especially when pharmacological treatment is used.
Electronic supplementary material The online version of this article (doi:10.1007/s40291-014-0110-7) contains supplementary material, which is available to authorized users. Y. Matsumoto C. Fabbri S. Porcelli A. Serretti (&) Department of Biomedical and Neuromotor Sciences, University of Bologna, Viale Carlo Pepoli 5, 40123 Bologna, Italy e-mail: [email protected] Y. Matsumoto Department of Psychiatry, Yamagata University School of Medicine, Yamagata, Japan S. Pellegrini C. Iofrida V. Mariotti E. Melissari Department of Surgical, Medical, Molecular Pathology and of Critical Area, University of Pisa, Pisa, Italy P. Politi V. Martinelli M. Cappucciati Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
S. Bellino P. Bozzatello E. Brignolo Neuroscience Department, Turin University, Turin, Italy M. Menchetti Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy P. Brambilla M. Balestrieri Unit of Psychiatry, Department of Experimental and Clinical Medical Sciences (DISM), ICBN, University of Udine, Udine, Italy P. Brambilla Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, USA
Y. Matsumoto et al.
Key Points The role in treatment response of five genes involved in the modulation of the serotonergic system (HTR2A, BDNF, SLC6A4, CREB1, and TPH2) was examined in 137 major depressive disorder patients treated with interpersonal counseling (IPC) or antidepressant drugs. Our findings supported the association of SLC6A4 rs8076005 with response in both treatment groups. A marginal association between TPH2 rs11179023 and symptom improvement was observed in the IPC group only.
1 Introduction Major depressive disorder (MDD) is one of the most common psychiatric disorders (lifetime prevalence: 12.8 %) [1], and is among the major causes of worldwide disability [2]. The heavy personal and socioeconomic burden of MDD is partly due to the unsatisfactory response and remission rates (47 % and 33 %, respectively) [3]. Antidepressant drugs and psychotherapy are thought to be equally efficacious in moderate MDD [4, 5]; however, predictors of response to antidepressant treatments to guide treatment choice in the individual patient are not available. Among predictors of clinical outcomes, genetic variants are estimated to contribute substantially to the interindividual variability [6–9]. Serotonergic genes represent ideal candidates since current antidepressant drugs mainly act by the modulation of the serotonergic system. The serotonin receptor gene 2A (HTR2A) is expressed in all neocortex, hippocampus, and prefrontal cortex [10]. 5-HT-induced Ca2? response in platelets was found to be enhanced in MDD [11] after remission during treatment with imipramine [12]. The missense T allele of HTR2A rs6314 showed lower Ca2? response to 5-HT than those without the mutation [13]. Two studies found that this polymorphism may predict the efficacy of selective serotonin reuptake inhibitors (SSRIs) [14, 15]. The serotonin transporter (SLC6A4 gene) plays a pivotal role in the regulation of serotonin concentration in the synaptic cleft and extrasynaptic sites. Promoter polymorphisms (5-HTTLPR and rs25531) have been extensively investigated, leading to replicated, even if not univocal, results [16]. The intronic rs8076005 has been previously associated with interleukin (IL)-6 levels in MDD and depressive symptom severity [17], but has not been studied as a possible modulator of treatment response.
Tryptophan hydroxylase (TPH) catalyzes the rate-limiting step in the synthesis of 5-HT. TPH2 is the main isoform expressed in the CNS, but studies focused on its role in antidepressant response reported inconsistent results [18–33]. TPH2 rs1179023 variation has not been investigated in the field before, thus represents a new candidate within a gene with strong biological rationale of involvement in antidepressant action. During antidepressant treatment, the enhancement of 5-HT availability increases brain-derived neurotrophic factor (BDNF) synthesis and signaling, a major event in the stimulation of adult neurogenesis [34]. BDNF serum levels are associated with MDD and antidepressant response [35]. The rs6265 (Val66Met) was associated with BDNF secretion [36], BDNF serum levels [37], and antidepressants response [38–40]. Cyclic adenosine monophosphate response elementbinding protein 1 (CREB1) is a transcription factor activated by a number of signals, among which are neuronal growth factors and stress-induced signals [41, 42]. The CREB1 gene has been associated with recurrent early-onset MDD [43, 44]. The G allele of the promoter polymorphism rs2253206 has been associated with lower promoter activity [45] and the same single nucleotide polymorphism (SNP) may affect the risk of MDD, depression severity [46], and risk of treatment-resistant depression [47]. Given the data supporting the involvement of these genes in antidepressant action, the present paper aims to study the role of HTR2A rs6314, BDNF rs6265, SLC6A4 rs8076005, CREB1 rs2253206, and TPH2 rs11179023 in a sample 137 Italian MDD patients treated with IPC or antidepressants in a multicenter, randomized trial.
2 Methods 2.1 Sample Subjects aged 18 years or older with a diagnosis of MDD (Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision [DSM-IV TR]) were recruited. Inclusion and exclusion criteria have been detailed elsewhere [48]. Eligible patients were divided into interpersonal counseling (IPC, a type of brief psychotherapy derived from interpersonal psychotherapy [IPT] [49–51]) or pharmacological antidepressant treatment [52] groups. Subjects were collected in three centers (Neuroscience Department, Turin University; Department of Health Sciences, University of Pavia; and Institute of Psychiatry, Bologna University), as previously reported [48]. All patients recruited at Bologna University were treated with antidepressant drugs. Despite the design of the study had been planned as randomized, failure in developing a
Serotonergic Genes in Response to Antidepressants and Psychotherapy
psychotherapy arm at Bologna University (the centre that recruited the higher number of patients) resulted in different sizes between the two treatment arms. In all cases of pharmacological treatment, the antidepressant was chosen and titrated according to current guidelines up to the effective dose range within the first week of treatment. Ethical approval was obtained from the Ethic Committees of all participating centers.
electronic supplementary Table 1, together with polymorphisms in complete linkage disequilibrium (R2 [ 0.8). 2.5 Genotyping
All subjects were evaluated with both structured and unstructured interviews to obtain diagnoses assigned by two independent experienced psychiatrists. Depressive states were assessed at baseline and after 8 weeks through the Hamilton Depression Rating Scale (HDRS, 21-item version). Assessments were performed by trained psychiatrists, and inter-rater reliability was k = 0.8. A monitoring of treatment adherence through drug plasma level determination was not performed, but treatment adherence was assessed weekly by a trained psychiatrist and side effects were monitored weekly using the Dosage Record & Treatment Emergent Symptom scale (DOTES) [53]. Thus, we can suppose that non-responders at week 8 were not false non-responders due to overlooked side effects and poor treatment adherence.
DNA was purified from whole blood using the QIAamp DNA Blood Kit (Qiagen, Valencia, CA, USA), according to the manufacturer’s protocol. rs6314 (HTR2A, Chr 13q14–q21), rs6265 (BDNF, Chr 11p13), rs8076005 (SLC6A4, Chr 17q11.2), rs2253206 (CREB1, Chr 2q34),and rs11179023 (TPH2, Chr 12q21.1) were genotyped by high-resolution melting polymerase chain reaction (HRM PCR). All experiments were performed by the Rotor Gene Q instrument (Qiagen), using the Type-it HRM PCR kit (Qiagen). All primers were designed by Beacon Designer v. 7.9 (PREMIER Biosoft, Palo Alto, CA, USA). After an initial step of enzyme activation at 95 °C for 5 min, PCRs were carried out for 40 cycles as follows: denaturation at 95 °C for 10 s and annealing at 60 °C for 30 s. HRM analysis was performed with a temperature resolution of 0.1 °C and a temperature range between 70 and 85 °C. Data collection and genotype calls were obtained by the Rotor-Gene 6000 series software v. 1.7 (Qiagen) using as reference genotypes DNA samples sequenced by ABI PrismÒ 310 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA).
2.3 Outcomes
2.6 Statistical Analysis
The primary outcome was remission at week 8, defined according to standard criteria (HDRS score B7), and the secondary outcomes were response (at least 50 % reduction in HDRS score) and HDRS percentage improvement at week 8.
The effect of genotypes and alleles on response and remission was tested by Pearson’s Chi-squared tests. A multivariate analysis of variance (MANOVA) was used to study the effect of genotypes and alleles on improvement at week 8, adjusting for center, sex, age, and baseline severity. Analyses were carried out only in completers, in the two individual treatment groups and in the whole sample. Despite the selected candidate genes showing a strong biological rationale for involvement in antidepressant mechanisms of action and the pre-test probability of association being favorable, Bonferroni correction was applied to reduce the risk of false positives. Thus, the alpha value was set to 0.005 considering five independent polymorphisms that were tested in two independent groups of patients (IPC- and antidepressant-treated). The whole sample was not considered as an independent group. In addition, the three analyzed phenotypes (response, remission, and symptom improvement) were considered as highly related to each other. Furthermore, we stated only remission as a primary outcome (see Sect. 2.3.). Our whole sample setting alpha value to 0.005 two-tailed provides a power of 0.80 to detect a risk allele (for nonremission) with odds ratio (OR) C4.0 (Gpower 3.1 software).
2.2 Evaluations
2.4 Polymorphism Selection The genotyped SNPs were selected according to the following criteria: (1) tagging approach (R2 = 0.08); (2) reported prevalence of at least 5 % for the minor allele among Caucasians (data from http://hapmap.ncbi.nlm.nih. gov/); (3) availability of a validated assay in our laboratory; and (4) previous literature findings. In detail, the Tagger software was used to test SNPs downloaded from HapMap (Rel 28 Phase II ? III, August 2010, NCBI B36 assembly, dbSNP b126) and that satisfied some quality criteria (maximum number of Mendel errors = 1; p-value for the Hardy–Weinberg equilibrium (HWE) [0.001, minor allele frequency [MAF] [5 %). The Tagger program was used to identify SNPs that tagged at least two other SNPs with r2 and logarithm of the odds (LOD) thresholds of 0.8 and 3, respectively. The selected polymorphisms are shown in the
Y. Matsumoto et al.
3 Results SCL6A4 rs8076005 slightly deviated from the HWE (p = 0.03), while the other polymorphisms satisfied HWE (HT2A rs6314: p = 0.61; BDNF rs6265: p = 0.34; CREB1 rs2253206: p = 0.52; TPH2 rs11179023: p = 0.45). For one subject in the IPC group and two in the antidepressant group, genotyping was not successful and they were thus excluded from the analysis. Clinical-demographic characteristics of the sample are reported in Table 1. The majority of patients were treated with SSRIs (80.4 %), and further clinical data have been reported in a previous paper [48]. Non-completers (12.74 %) did not show any difference in age, sex, and baseline severity when compared with the 8-week completers [48]. As previously reported [48], no difference was observed in clinical outcomes between the two treatment groups (Table 1). In the IPC group, the number of remitters was slightly higher than that of responders because the IPC group had lower baseline severity than the antidepressant group. Nevertheless, the difference was not so pronounced to be clinically relevant, and analyses were adjusted for baseline severity. 3.1 Effect of Polymorphisms on Outcomes The SLC6A4 rs8076005 A allele reached the significance threshold for association with better response in the
antidepressant group (p = 0.005) and showed a consistent trend in the whole sample (p = 0.02) [Tables 2 and 3]. Furthermore, rs8076005 A allele carriers showed a trend of higher symptom improvement at week 8 in the whole sample (F = 3.29; df = 2; p = 0.04). The association between the rs8076005 AA genotype A allele and response was more evident after correction for age, sex, baseline severity, and center in the antidepressant group (Z = 2.81, p = 0.005; Z = 3.10, p = 0.002, respectively), while trends were found in the whole group (Z = 2.51, p = 0.012; Z = 2.54, p = 0.011, respectively). The TPH2 rs11179023 A allele showed a mild trend of selective association with symptom improvement in the IPC group (F = 4.29; df = 1; p = 0.042), but no effect was found on response and remission. The other investigated polymorphisms did not show evidence or trends of impact on clinical outcomes in none of the analyzed groups (Tables 2 and 3; data pertaining to percentage improvement not shown).
4 Discussion This study investigated the effect of five serotonergic polymorphisms on clinical outcomes of IPC, a type of brief psychotherapy, versus antidepressant pharmacotherapy. As previously reported in this sample [48], IPC, as well as
Table 1 Clinical characteristics and outcomes at week 8 according to treatment group. Chi-squared and Fisher’s exact tests were used as appropriate to test differences between the two treatment groups Whole sample (N = 137)
IPC (N = 40)
Antidepressants (N = 97)
Statistics
88 (64.23)
25 (62.50)
63 (64.95)
49 (35.77)
15 (37.50)
34 (35.05)
Yes
87 (63.50)
28 (70.00)
59 (60.82)
No
50 (36.50)
12 (30.00)
38 (39.18)
V2 = 0.671, df = 1, p = 0.41
Improvement (%)
54.66 ± 28.77
52.09 ± 19.86
55.72 ± 31.76
t = -0.67, CI -0.144 to 0.071, p = 0.50
HDRS missing at week 8
20
1
19
OR 0.13, CI 0.003–0.865, p = 0.03
Baseline severity (HDRS)
17.97 ± 5.24
16.24 ± 4.01
18.58 ± 5.50
t = -2.49, CI -4.18 to -0.48, p = 0.014
Age, years (mean ± SD)
51.02 ± 17.98
44.10 ± 16.19
53.51 ± 18.00
t = -2.95, CI -15.72 to -3.10, p = 0.004
Gender (F/M)
91/46
24/16
67/30
V2 = 1.05, df = 1, p = 0.31
Pharmacological treatment [n (%)]
–
None
78 (80.4): SSRIs
–
Response [n (%)] Yes No Remission [n (%)]
V2 = 0.006, df = 1, p = 0.94
15 (15.5): SNRIs 4 (4.1): other antidepressants
CI 95 % confidence interval, IPC interpersonal counselling, OR odds ratio, HDRS Hamilton Depression Rating Scale, SD standard deviation, F female, M male, SSRIs selective serotonin reuptake inhibitors, SNRIs serotonin norepinephrine reuptake inhibitors
8 (66.67)
0 (0)
No
10 (83.33)
2 (13.33)
Yes
Yes
Response
1 (4.17)
5 (20.83)
6 (50.00)
2 (16.67)
No
TPH2 rs11179023
13 (48.15)
5 (18.52)
5 (33.33)
14 (58.33)
Yes
Remission
No
5 (20.83)
Response
2 (16.67)
4 (14.81)
2 (13.33)
13 (86.67)
23 (85.19)
4 (16.67)
20 (83.33)
CREB1 rs2253206
No
Yes
Remission
No
Yes
Response
SLC6A4 rs8076005
11 (40.74)
9 (60.00)
0 (0)
3 (11.11)
10 (41.67)
3 (12.50)
Yes
Remission
No
Yes
Response
BDNF rs6265
18 (75.00)
4 (33.33)
9 (33.33)
8 (53.33)
5 (20.83)
0 (0)
0 (0)
0 (0)
0 (0)
4 (33.33)
13 (48.15)
6 (40.00)
11 (45.83)
31 (83.78)
v2 = 2.207, df = 2
p = 0.99
v2 = 0.022, df = 2
p = 0.11
v2 = 4.398, df = 2
3 (4.84)
7 (18.92)
8 (13.79)
5 (15.15)
10 (16.13)
20 (54.05)
32 (55.17)
p = 0.88
14 (42.42)
p = 0.78
38 (61.29)
1 (2.70)
3 (5.17)
1 (3.03)
3 (4.84)
v2 = 0.022, df = l
v2 = 0.079, df = 1
p = 0.24
v2 = 2.898, df = 2
p = 0.28
v2 = 2.584, df = 2
Statistics
p = 0.64
5 (13.51)
14 (24.14)
6 (18.18)
13 (20.97)
17 (27.42)
17 (49.95)
33 (56.90)
16 (48.48)
34 (54.84)
10 (27.03)
22 (37.93)
11 (33.33)
21 (33.87)
14 (37.84)
23 (39.66)
13 (39.39)
24 (38.71)
AG
42 (67.74)
13 (35.14)
17 (29.31)
12 (36.36)
18 (29.03)
7 (18.92)
4 (6.90)
8 (24.24)
3 (4.84)
22 (59.46)
32 (55.17)
19 (57.58)
v2 = 3.449, df = 2
p = 0.57
v2 = 1.133, df = 2
p = 0.76
v2 = 0.545, df = 2
p = 0.16
v2 = 3.622, df = 2
p = 0.015
v2 = 8.405, df = 2
p = 0.81
v2 = 0.419, df = 2
p = 0.92
v2 = 0.175, df = 2
Statistics
p = 0.22
v2 = 3.022, df = 2
p = 0.72
v2=0.669, df = 2
Statistics
35 (56.45)
GG
1 (2.70)
0 (0)
0 (0)
1 (1.61)
AA
AG
GG
0 (0)
44 (75.86)
27 (81.82)
48 (77.42)
AA
3 (25.00)
v2 = 0.214, df = l
p = 0.45
v2 = 0.566, df = l
TT
Antidepressants (N = 95)
9 (75.00)
No
0 (0)
0 (0)
0 (0)
CT
IPC (N = 39)
22 (81.48)
Yes
5 (15.52)
4 (26.67)
11 (73.33)
No
Remission
4 (16.67)
20 (83.33)
Yes
Response
HTR2A rs6314
Statistics
CC
TT
CC
CT
Antidepressants (N = 95)
IPC (N = 39)
Table 2 Response and remission at week 8 for each genotype and treatment group
8 (16.33)
19 (22.35)
10 (20.83)
17 (19.77)
CT
4 (4.66)
9 (18.37)
13 (15.29)
7 (14.58)
15 (17.44)
30 (61.22
55 (64.71)
27 (56.25)
58 (67.44)
1 (2.04)
6 (7.06)
1 (2.08)
6 (6.98)
AA
22 (25.58)
23 (46.94)
46 (54.12)
21 (43.75)
48 (55.81)
12 (24.49)
26 (30.59)
13 (27.08)
25 (29.07)
22 (44.90)
34 (40.00)
22 (45.83)
34 (39.53)
AG
Whole sample (N = 134)
40 (81.63)
66 (77.65)
38 (79.17)
68 (79.07)
CC
Whole sample (N = 134)
60 (69.77)
17 (34.69)
26 (30.59)
20 (41.67)
23 (26.74)
7 (14.29)
4 (4.71)
8 (16.67)
3 (3.49)
26 (53.06)
45 (52.94)
25 (52.08)
46 (53.49)
GG
1 (2.04)
0 (0)
0 (0)
1 (1.16)
TT
v2 = 0.911, df = 2
p = 0.72
v2 = 0.653, df = 2
p = 0.21
v2 = 3.162, df = 2
p = 0.14
v2 = 3.942, df = 2
p = 0.03
v2 = 7.168, df = 2
p = 0.43
v2 = 1.677, df = 2
p = 0.42
v2 = 1.716, df = 2
Statistics
p = 0.31
v2 = 2.357, df = 2
p = 0.75
v2 = 0.576, df = 2
Statistics
Serotonergic Genes in Response to Antidepressants and Psychotherapy
p = 0.90 32 (65.31) 15 (30.61) 2 (4.08)
IPC interpersonal counseling
0 (0) No
Values reported in parentheses represent percentage values corresponding to the reported numeric values
p = 0.97 22 (59.46) 13 (35.14) 2 (5.41) p = 0.79 10 (83.33)
23 (27.06) 4 (4.71) v2 = 0.065, df = 2 36 (62.07) 19 (32.76) 3 (5.17) v2 = 0.466, df = 2 22 (81.48) 4 (14.81) 1 (3.70) Yes
2 (16.67)
v2 = 0.205, df = 2 58 (68.24)
p = 0.63 30 (62.50) 16 (33.33) 2 (4.17) p = 0.18 16 (48.48) 15 (45.45) 2 (6.06) p = 0.33 14 (93.33) 1 (6.67) 0 (0) No
Statistics AG
GG
Table 2 continued
Remission
AG AA AA AA
AG
Antidepressants (N = 95) IPC (N = 39)
GG
Statistics
Whole sample (N = 134)
GG
Statistics
Y. Matsumoto et al.
antidepressants, are effective in the treatment of mild to moderate MDD. The SLC6A4 rs8076005 AA genotype and A allele were associated with response in the antidepressant group, with consistent trends in the whole sample (Tables 2 and 3). Rs8076005 has been previously suggested as a risk factor for MDD through the neural–immune interaction [17], even if this does not necessarily imply an impact of the SNP on antidepressant response. In detail, rs8076005 G allele carriers showed higher depressive symptom severity and higher IL-6 levels, as well as the same was demonstrated for the minor allele of SNPs that are in linkage disequilibrium with rs8076005 (rs12150214, rs11080122, rs8071667, rs2020936, rs25528, and rs6354). Interestingly, IL-6 levels were previously demonstrated to negatively affect antidepressant response [54–56]. Two SNPs in linkage disequilibrium with rs8076005 (rs6354 and rs2020936) were associated with anxiety, MDD, and neuroticism [57]. On the other hand, the rs8076005 A allele did not affect clinical outcomes in the IPC group, which instead may be influenced by TPH2 rs11179023. Inconsistent results were found about the role of TPH2 variants in antidepressant response [14, 20, 29, 31, 32, 58], but rs11179023 has not been investigated previously. In this study, the rs11179023 A allele showed a trend of higher symptom improvement at week 8 only in the IPC group, while the genotypic analysis could not be performed since only one subject carried the AA genotype. Clearly, the present result did not allow the tracing of any statement, but suggested a new polymorphism within a known candidate gene for further investigation. In the present study, HTR2A rs6314 was not associated with antidepressants or IPC outcomes. Despite some inconsistent results, previous studies suggested that this polymorphism may be associated with SSRI response [14, 15, 59]. Thus, the use of different treatments in our study or the small sample size may partly explain the reported negative findings. In this study, BDNF rs6265 did also not affect treatment outcomes. Recent meta-analyses reported that the heterozygous genotype may be a predictor of better antidepressant response [38–40], but negative findings have also been reported [60–71]. The inconsistency in previous results may be at least partly due to different rs6265 allele and genotype distribution across populations. Indeed, the frequency of the Met allele is higher in the Asian population than in the Caucasian population, and the Met allele may be protective against MDD and may be associated with better antidepressant response only in Asian subjects [38, 40, 72]. Phosphorylation of CREB is related to cellular resilience and neuroplasticity [73]. Phosphorylated CREB (pCREB) is positively correlated with antidepressant and IPT
Yes
7 (14.58)
41 (85.42)
14 (58.33)
10 (41.67)
No
TPH2 rs11179023 Response
31 (57.41)
21 (70.00)
9 (30.00)
23 (42.59)
24 (50.00)
24 (50.00)
2 (8.33)
Yes
Remission
No
Yes
Response
CREB1 rs2253206
22 (91.67)
No
4 (7.41)
2 (6.67)
28 (93.33)
50 (92.59)
4 (8.33)
44 (91.67)
Yes
Remission
No
Yes
Response
16 (66.67)
No 8 (33.33) SLC6A4 rs8076005
21 (70.00)
9 (30.00)
37 (68.52)
32 (66.67)
16 (33.33)
17 (31.48)
Yes
Remission
No
Yes
Response
BDNF rs6265
v2 = 2.538, df = 1
p = 0.94
v2 = 0.006, df = 1
p = 0.08
v2 = 3.025, df = 1
p = 0.89
v2 = 0.020, df = 1
p = 0.79
v2 = 0.072, df = 1
p = 0.87
v2 = 0.026, df = 1
p = 0.76
v2 = 0.094, df = 1
Statistics
7 (9.46)
23 (18.55)
31 (41.89)
49 (42.24)
26 (39.39)
54 (43.55)
50 (67.57)
86 (74.14)
39 (59.09)
97 (78.23)
16 (21.62)
29 (25.00)
15 (22.73)
30 (24.19)
101 (81.45)
43 (58.11)
67 (57.76)
40 (60.61)
70 (56.45)
24 (32.43)
30 (25.86)
27 (40.91)
27 (21.77)
58 (78.38)
87 (75.00)
51 (77.27)
94 (75.81)
G
A
G
67 (90.54)
14 (12.07)
6 (0.09)
15 (12.10)
A
p = 0.66
102 (87.93)
60 (90.91)
109 (87.90)
Antidepressants (N = 95)
3 (12.50)
v2 = 0.190, df = 1
p = 0.48
v2 = 0.501, df = 1
IPC (N = 39)
21 (87.50)
No
5 (9.26)
4 (13.33)
26 (86.67)
49 (90.74)
4 (8.33)
44 (91.67)
Yes
Remission
No
Yes
Response
HTR2Ars6314
T
C
Statistics
C
T
Antidepressants (N = 95)
IPC (N = 39)
Table 3 Response and remission at week 8 for each allele and treatment group
v2 = 2.623, df = 1
p = 0.96
v2 = 0.002, df = 1
p = 0.58
v2 = 0.305, df = 1
p = 0.33
v2 = 0.959, df = 1
p = 0.005
v2 = 7.752, df = 1
p = 0.59
v2 = 0.285, df = 1
p = 0.82
v2 = 0.051, df = 1
Statistics
p = 0.58
v2 = 0.313, df = 1
p = 0.53
v2 = 0.396, df = 1
Statistics
10 (10.20)
19 (11.18)
10 (10.42)
19 (11.05)
T
30 (17.44)
41 (41.84)
72 (42.35)
35 (36.46)
78 (45.35)
72 (73.47)
136 (80.00)
67 (69.79)
141 (81.98)
24 (24.49)
46 (27.06)
24 (25.00)
46 (26.74)
A
142 (82.56)
57 (58.16)
98 (57.65)
61 (63.54)
94 (54.65)
26 (26.53)
34 (20.00)
29 (30.21)
31 (18.02)
74 (75.51)
124 (72.94)
72 (75.00)
126 (73.26)
G
Whole sample (N = 134)
88 (89.80)
151 (88.82)
86 (89.58)
153 (88.95)
C
Whole sample (N = 134)
v2 = 0.467, df = 1
p = 0.93
v2 =0.007, df = 1
p = 0.16
v2 = 1.997, df = 1
p = 0.22
v2 = 1.526, df = 1
p = 0.02
v2 = 5.265, df = 1
p = 0.65
v2 = 0.213, df = 1
p = 0.76
v2 = 0.097, df = 1
Statistics
p = 0.81
v2 = 0.061, df = 1
p = 0.87
v2 = 0.025, df = 1
Statistics
Serotonergic Genes in Response to Antidepressants and Psychotherapy
19 (19.39)
79 (80.61)
p = 0.82
response in MDD [73, 74]. Previous association studies suggested that the CREB1 gene may show a selective effect on the risk of treatment resistance in MDD [47] and paroxetine response [71]. Our negative results are line with other studies focused on response to mixed antidepressant treatments [61, 75]. Among the limitations of the present study, the first is the limited statistical power compared with current pharmacogenetic studies, particularly in the IPC group. Thus, the present findings should be cautiously considered. However, the low sample size mainly affects the risk of false negative findings given the lack of power to find small effect sizes. Furthermore, the choice of candidate genes with strong biological plausibility for involvement in antidepressant mechanisms of action contributes to reducing the risk of false positives. Other limitations are represented by the use of the present sample in a previous pharmacogenetic study [48] and the recruitment of patients in different centers (even if the center of recruitment was used as covariate and inter-rater reliability was good). Another issue is the deviation of SLC6A4 rs8076005 from HWE, despite that the MAF was in line with that reported in the HapMap database for the CEU population (0.22 in our study and 0.18 according to HapMap phase III release on NCBI B36 assembly, dbSNP b126). The availability of more evaluation time points could have provided information about response timing in the two treatment groups. Finally, the use of a naturalistic setting in the pharmacological arm of the study could be seen as a limitation, but also provided a perspective that is more near to real clinical practice, and the major part of patients were treated with SSRIs. Despite these limitations, the present study is among the few that have investigated the impact of genetic variants on brief psychotherapy response. Previous studies were mainly focused on the effect of genetic variants on personality characteristics that may in turn affect psychotherapy outcome. Further genetic studies directly focused on the efficacy of psychological interventions in MDD are clearly needed. Personality features should be considered as modulators. However, in the present sample the comorbidity with personality disorders did not affect IPC outcomes [48], as found by an independent study [76]. IPC interpersonal counseling
p = 0.709 22 (91.67) 2 (8.33) No
Values reported in parentheses represent percentage values corresponding to the reported numeric values
p = 0.82 57 (77.03)
31 (18.24) v2 = 0.053, df = 1 91 (78.45) 25 (21.55) v2 = 0.139, df = 1 6 (11.11) Yes
48 (88.89)
17 (22.97)
v2 = 0.054, df = 1 139 (81.76)
p = 0.49 76 (79.17) 20 (20.83) p = 0.11 19 (28.79) p = 0.11 No
Remission
1 (3.33)
29 (96.67)
47 (71.21)
G A G A Statistics G A
IPC (N = 39)
Table 3 continued
Antidepressants (N = 95)
Statistics
Whole sample (N = 134)
Statistics
Y. Matsumoto et al.
5 Conclusions Our study suggests that SLC6A4 rs8076005 may impact on antidepressant response at week 8, especially in patients treated with antidepressant drugs. TPH2 may be a selective modulator of IPC response, even if this result is even more preliminary given the limited size of the IPC-treated group and the non-significance of the finding after Bonferroni
Serotonergic Genes in Response to Antidepressants and Psychotherapy
correction. IPC, an effective treatment in mild to moderate MDD, is worthy of further investigation in genetic studies. Acknowledgments (2008XWR4SB).
The
study
was
funded
by
14.
MIUR
Disclosure statement Dr Serretti is, or has been, a consultant/ speaker for Abbott, Astra Zeneca, Clinical Data, Boheringer, Bristol Myers Squibb, Eli Lily, GlaxoSmithkline, Janssen, Lundbeck, Pfizer, Sanofi, and Servier. Yoshihiko Matsumoto, Chiara Fabbri, Silvia Pellegrini, Stefano Porcelli, Pierluigi Politi, Silvio Bellino, Caterina Iofrida, Veronica Mariotti, Erika Melissari, Marco Menchetti, Valentina Martinelli, MarcoCappucciati, Paola Bozzatello, Elena Brignolo, Paolo Brambilla, and Matteo Balestrieri have no conflicts of interest.
15.
16.
17.
18.
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