Association Analysis of the Brain-Derived Neurotrophic Factor Gene Val66Met Polymorphism and Gender with Efficacy of Antidepressants in the Chinese Han Population with Generalized Anxiety Disorder

Abstract

Background and Aim:

This study was designed to explore the relationship between the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and antidepressants' efficacy in the Chinese Han population with generalized anxiety disorder (GAD).

Materials and Methods:

We recruited 206 patients who met the diagnostic criteria for GAD into the test group, and assigned 209 healthy participants to the control group. All participants were genotyped for the BDNF Val66Met polymorphism. GAD patients were treated with escitalopram or extended-release venlafaxine. We used the Hamilton Rating Scale for Anxiety (HAM-A) to assess the response to 8-weeks of antidepressant treatment for GAD.

Results:

We did not identify any significant differences in the allelic or genotype frequencies of the BDNF Val66Met polymorphism between the test and control group. Furthermore, we did not detect any significant difference in the allele or genotype frequency of BDNF Val66Met between patients with different treatment responses. Finally, we did not detect any significant difference in the HAM-A score reduction rate among patients with different genotypes, gender, or treatment drugs.

Conclusions:

No significant difference was found in the BDNF Val66Met polymorphism between patients with GAD and healthy controls, nor was this polymorphism significantly associated with antidepressant drug efficacy for GAD.

Introduction

Generalized anxiety disorder (GAD) is a common and chronic anxiety disorder characterized by persistent worry, with 1-month prevalence approaching 1316 in 100,000 Chinese people (Phillips et al., 2009). Antidepressants, including selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs), represent the first-line psychopharmacological treatment for GAD (Huh et al., 2011; Katzman et al., 2014). According to guidelines from evidence-based medicine, escitalopram and extended-release venlafaxine are the most representative and suggested drugs in clinical practice for the treatment of GAD (Katzman et al., 2014).

Treatment response, however, varies greatly among patients. Among numerous factors influencing antidepressant response in GAD, gene polymorphism has been a focus of research, with particular interest in the brain-derived neurotrophic factor (BDNF) (Choi et al., 2006), serotonin transporter gene, and serotonin receptor 2A gene (Lohoff et al., 2013). Although genetic polymorphisms in general have been studied, no studies have found gene polymorphism to be significantly associated with an antidepressant treatment response in GAD. Further research is needed to investigate the relationship between gene polymorphism and antidepressant treatment response in GAD.

As a member of the neurotrophin family, BDNF plays an important role in the survival and differentiation of neurons. A number of studies have found that BDNF may be involved in the pathogenesis of depression and anxiety (Martinowich et al., 2007; Sleiman et al., 2016). Our previous study showed that the baseline plasma BDNF levels in subjects with GAD are higher than in healthy controls, and the increased BDNF levels are restored after the remission of GAD (Shen et al., 2011). Additionally, Carlino et al. (2015) reported a significant decrease in serum BDNF only in female patients with GAD and not in male patients with GAD. Many researchers found that BDNF did not seem to cause depressive behaviors, but it did influence the effect of antidepressant drugs (Fornaro et al., 2015; Bus and Molendijk, 2016; Gupta et al., 2016; Martinotti et al., 2016; Nase et al., 2016).

Evidence from a GAD animal model suggested that the BDNF level is related to a decrease in newborn neurons and to the length of tertiary dendrites in the hippocampus (Dias et al., 2014), and acute BDNF injection into the rat dorsal hippocampus could reduce anxiety behaviors by enhancing 5-hydroxytryptamine 1A (5-HT1A) receptor-mediated neurotransmission (Casarotto et al., 2012). A study of human samples (Uguz et al., 2014) also found that the cord blood BDNF levels of newborn infants of healthy women were significantly lower than those of women with GAD. These studies suggest that a relationship exists between BDNF and GAD. Among a great number of BDNF-influencing factors, BDNF-related gene polymorphism is a potential factor that could regulate the secretion of BDNF and thereby influence the development and outcome of GAD.

In recent years, increasing research has been conducted on the BDNF gene as a potential influencing factor on antidepressant effectiveness. BDNF Val66Met polymorphism, a functional variant of the BDNF gene, is a methionine (Met) substitution for valine (Val) at codon 66 (Val66Met). BDNF Val66Met has been demonstrated to modify the intracellular trafficking and activity-dependent secretion of BDNF, and it has led to new insights into the molecular genetics mechanism underlying anxiety (Montag et al., 2010).

Moreira et al. (2015) suggested that the Met allele of BDNF Val66Met polymorphism was associated with increased BDNF levels in patients with GAD. It is, therefore, reasonable to hypothesize that BDNF Val66Met polymorphism may be associated with antidepressant treatment response in GAD by regulating serum (or plasma) BDNF levels. Importantly, identifying the drug efficacy on the basis of BDNF Val66Met polymorphism will be helpful to prompt the individualized therapy for the treatment of GAD, which may help reduce the number of people suffering from this disease as well as decrease the medical burden.

Some studies have found BDNF Val66Met polymorphism to be associated with the treatment response to antidepressants for patients with major depressive disorder (MDD) (Choi et al., 2006; Yoshida et al., 2007; Zou et al., 2010; Xu et al., 2012; El-Hage et al., 2015; Colle et al., 2015). Several studies, however, have suggested that BDNF Val66Met polymorphism was not associated with antidepressant treatment effects (Tsai et al., 2003; Wilkie et al., 2007; Gratacos et al., 2008; Kang et al., 2010; Taylor et al., 2011; Katsuki et al., 2012; Ji et al., 2013; Musil et al., 2013).

Regrettably, to date, only a few studies have examined the relationship between BDNF Val66Met polymorphism and the treatment response to antidepressants in patients with GAD. Narasimhan et al. (2011) found no significant relationship between BDNF Val66Met polymorphism and the treatment effect of venlafaxine-extended release (XR) in the population with GAD. Further research is needed to elucidate the relationship between Val66Met and antidepressants with various therapeutic mechanisms. This study was designed to explore the relationship between BDNF Val66Met polymorphism and the treatment effects of venlafaxine XR (an SNRI) and escitalopram (an SSRI) in patients with GAD.

Materials and Methods

Subjects

We recruited all participants (≥18 years of age) from Huzhou 3rd Hospital between February 2010 and February 2013. The participants (51 men and 155 women; average age = 49.92 ± 11.466) who met the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) (American Psychiatric Association, 2000) diagnostic criteria for GAD and had a Hamilton Rating Scale for Anxiety (HAM-A) (Hamilton, 1959) score ≥14 (Matza et al., 2010) were assigned to the test group. HAM-A is the most commonly used tool to assess the severity of anxiety symptom and treatment outcomes in clinical research. Exclusion criteria included any illness requiring medical intervention, anxiety-depression comorbidity, substance abuse disorders, bipolar disorder, or personality disorder diagnosed by the DSM-IV-TR.

Participants were excluded if they had taken any psychoactive drugs or antidepressants (apart from venlafaxine XR and escitalopram), received electric shock treatment, or underwent psychological therapy within 2 months of the start of the study. The participants were also excluded if they were pregnant or lactating or if they were allergic to the drugs used in the study. Participants with strong suicide ideation or severe physical diseases (e.g., liver and kidney function deficiency, cardiovascular disease) detected by laboratory or auxiliary examinations also were excluded.

We randomly sorted patients with GAD into different medication groups using the method of random number table. The patients in the test group were treated with venlafaxine XR (75-225 mg/day, n = 104; four patients dropped out because of side effects) or escitalopram (10-20 mg/day, n = 102; seven patients dropped out because of side effects) for 8 weeks and instructed them not to take other antidepressants or antipsychotic drugs; short-term zolpidem treatment could be used for insomnia. Healthy participants (57 men and 152 women; average age = 35.81 ± 14.105) without any mental illness categorized under DSM-IV-TR Axis I and with a HAM-A score ≤7 were assigned to the control group. We obtained each participant's written consent after the study procedures were fully explained. All of the protocols were approved by the Research Ethics Review Board of Huzhou 3rd Hospital.

According to the reduction in HAM-A scores in treatment week 8, the patients in the test group were divided into responsive (reduction ≥50%; n = 159) and nonresponsive (reduction <50%; n = 36). Additionally, the patients in the test group were divided into remitters (≤7; n = 92) and nonremitters (>7; n = 103) according to their HAM-A score (Table 1).

Table 1.

Comparison of Demographic and Clinical Variables Between Test Group and Control Group (Mean ± Standard Deviation)

	Cases (n = 206)	Controls (n = 209)	χ²/T	p
Sex (male/female)	51/155	61/148	1.033	0.322^*
Age (years)	49.92 ± 11.466	35.81 ± 14.105	11.185	<0.001^**
Age of onset (years)	43.83 ± 12.55	NA
Family history of GAD	46 (23.6%)	NA
HAM-A	21.31 ± 3.136	NA
HAM-D	12.49 ± 2.719	NA
Escitalopram, n (%)	95 (48.7)	NA
Venlafaxine XR, n (%)	100 (51.3)	NA
Response
Responsive	n = 159	NA
Nonresponsive	n = 36	NA
Remission
Remitter	n = 92	NA
Nonremitter	n = 103	NA

p Value was obtained by Chi-squared test.

p Value was obtained by two sample t-test.

GAD, generalized anxiety disorder; HAM-A, Hamilton Rating Scale for Anxiety in baseline; HAM-D, Hamilton Rating Scale for Depression in baseline; NA, not applicable; nonremitter, HAM-A score >7; nonresponsive, HAM-A score reduction rate <50%; remitter, HAM-A score ≤7; responsive, HAM-A score reduction rate ≥50%; XR, extended release.

It was noted that there was no significant difference in the sex ratio between the test group and control group, but the average age of the test group was significantly higher than that of the control group. The reason for this difference might be that most participants in the test group were inpatients, and young patients tend to refuse hospitalization because of their work life.

Questionnaire

This study adopted the HAM-A (Hamilton, 1959) to estimate the symptom severity and improvement of GAD. HAM-A, which is a 14-item clinical interview measure of psychic and somatic anxiety symptoms, is the most commonly used tool to assess the severity of anxiety symptom and treatment outcomes in clinical research (Bruss et al., 1994; Shear et al., 2001). According to HAM-A rules, the severity of anxiety ranges from 0 to 4: 0 = absent, no anxiety symptom; 1 = mild, occurs irregularly and for short periods of time; 2 = moderate, occurs more constantly and of longer duration, requiring considerable effort on the part of the patient to cope with it; 3 = severe, continuous anxiety and dominates patient's life; and 4 = very severe, incapacitating.

The inter-rater reliability has been reported as an intraclass correlation coefficient (ICC) of 0.74-0.96 (Bruss et al., 1994). Test-retest reliability was assessed and the ICC was 0.86 (confidence interval [CI] 95%, 0.83-0.93), and Cronbach's alpha was 0.83 (Bruss et al., 1994).

Genotyping

We determined BDNF Val66Met polymorphism using polymerase chain reaction (PCR)-restriction fragment length polymorphism. We extracted DNA from peripheral blood leukocytes with the TIANamp Blood DNA Kit (Tiangen Biotech, Beijing, China) and stored at −80°C. According to Sklar et al. (2002), DNA fragments of interest were amplified by PCR with the forward primers 5′-ACTCTGGAGAGCGTGAAT-3′ (sense) and 5′-ATACTGTCACACACGCTC-3′ (antisense), which we verified according to the GenBank database. The PCR conditions were as follows: predegeneration at 95°C for 5 min, 30 cycles of denaturation at 94°C for 30 s, annealing at 60°C for 30 s, and extending at 72°C for 45 s. The thermal cycle was completed at 72°C for 5 min. The PCR products were visualized by 1.5% agarose electrophoresis.

We differentiated the BDNF Val66Met polymorphism using the NlaIII restriction enzyme (5 U/μL), and examined the product using native polyacrylamide gel electrophoresis analysis.

Statistical data analysis

We analyzed genotype and allele frequency through Chi-squared test with SPSS Statistics version 13.0 (SPSS, Inc., Chicago, IL). The relationship analysis between genotype or allele and treatment effect was performed with UNPHASED v.3.0.13 (Dudbridge, 2003). Haploview version 4.0 was applied to analyze the Hardy-Weinberg equilibrium (HWE) and minor allele frequency of BDNF Val66Met, determining the SNP with a HWE p value <0.01 and minor allele frequency <0.05 (Emigh, 1980). Except in specified, all the tests were two tailed, and the level of significance for all of the statistical results was set at p < 0.05.

Results

Comparison of BDNF Val66Met polymorphism between test group and control group

BDNF Val66Met was found to be in HWE in the control samples (p > 0.05 by χ²). There were no significant differences in the A and G allele (odds ratio [OR] = 0.91; CI 95%, 0.69-1.19; p > 0.05). The results between the test and control groups (Table 2) were identical in the A/A and A/G genotype (OR = 1.27; CI 95%, 0.79-2.05; p > 0.05), and the A/G and G/G genotype (OR = 0.83; CI 95%, 0.48-1.43; p > 0.05).

Table 2.

Comparison of Brain-Derived Neurotrophic Factor Val66Met Polymorphism Between Test Group and Control Group

	Cases		Controls
	n = 206		n = 209
Allele/genotype for HWE	n	%	n	%	OR (CI 95%)	χ²		p
A	200	48.5	213	51.0				0.21
G	212	51.5	205	49.0	0.91 (0.69-1.19)	0.48	0.49
A/A	53	25.7	50	23.9
A/G	94	45.6	113	54.1	1.27 (0.79-2.05)	1.01	0.32
G/G	59	28.6	46	22.0	0.83 (0.48-1.43)	0.47	0.49

CI, confidence interval; HWE, Hardy-Weinberg equilibrium; OR, odds ratio.

Allele and genotype frequencies of different genders between test group and control group

There were no significant differences in the BDNF Val66Met allele and genotype frequencies of male or female participants between the test group and control group (Table 3).

Table 3.

Allele and Genotype Frequencies of Different Genders Between Test Group and Control Group

		Allele frequency (%)			Genotype frequency (%)
Gender	Number	A	G	p	A/A	A/G	G/G	p
Male
Test group	51	51 (50.0)	51 (50.0)	0.903	17 (33.3)	17 (33.3)	17 (33.3)
Control group	61	60 (49.2)	62 (50.8)		13 (21.3)	34 (55.7)	14 (23.0)	0.060
Female
Test group	155	149 (48.1)	161 (51.9)	0.372	36 (23.2)	77 (49.7)	42 (27.1)
Control group	148	153 (51.7)	143 (48.3)		37 (25.0)	79 (53.4)	32 (21.6)	0.541

Analysis of genotype and allele frequency of different patients in the test group

There were no significant differences in BDNF Val66Met allele and genotype frequencies among patients with different responses to treatment (Table 4). Response rates at week 8 were 83% for venlafaxine XR (responders = 83, nonresponders = 17) and 80% for escitalopram (responders = 76, nonresponders = 19). Remission rates at week 8 were 45.0% for venlafaxine XR (remitters = 45, nonremitters = 45) and 49.5% for escitalopram (remitters = 47, nonremitters = 95). According to the results of this study, both treatments were successful. Our findings were similar to other studies (Nimatoudis et al., 2004; Zhang et al., 2013; Maity et al., 2014).

Table 4.

Analysis of Genotype and Allele Frequency of Different Patients in the Test Group

		Allele frequency (%)			Genotype frequency (%)
Case	Number	A	G	p	A/A	A/G	G/G	p
Response
Responsive	159	155 (48.7)	163 (51.3)		39 (24.5)	77 (48.4)	43 (27.0)
Nonresponsive	36	35 (48.6)	37 (51.4)	0.984^a	11 (30.6)	13 (36.1)	12 (33.3)	0.408^a
Remission
Remitter	92	90 (48.9)	94 (51.1)		22 (23.9)	46 (50.0)	24 (26.1)
Nonremitter	103	100 (48.5)	106 (51.5)	0.942^b	28 (27.2)	44 (42.7)	31 (30.1)	0.595^b
Escitalopram
Responsive	76	72 (47.4)	80 (52.6)		17 (22.4)	38 (50.0)	21 (27.6)
Nonresponsive	19	15 (39.5)	23 (60.5)	0.382^c	4 (21.1)	7 (36.8)	8 (42.1)	0.452^{*, c}
Remitter	47	45 (47.9)	49 (52.1)		11 (23.4)	23 (48.9)	13 (27.7)
Nonremitter	48	42 (43.8)	54 (56.3)	0.569^d	10 (20.8)	22 (45.8)	16 (33.3)	0.831^d
Venlafaxine XR
Responsive	83	83 (50.0)	83 (50.0)		22 (26.5)	39 (47.0)	22 (26.5)
Nonresponsive	17	20 (58.8)	14 (41.2)	0.348^e	7 (41.2)	6 (35.3)	4 (23.5)	0.491^{*, e}
Remitter	45	45 (50.0)	45 (50.0)		11 (24.4)	23 (51.1)	11 (24.4)
Nonremitter	55	58 (52.7)	52 (47.3)	0.701^f	18 (32.7)	22 (40.0)	15 (27.3)	0.512^f

Fisher's exact test.

Responsive compared with nonresponsive.

Remitter compared with nonremitter.

Responsive compared with nonresponsive of treatment by escitalopram.

Remitter compared with nonremitter of treatment by escitalopram.

Responsive compared with nonresponsive of treatment by venlafaxine XR.

Remitter compared with nonremitter of treatment by venlafaxine XR.

Comparative analysis of HAM-A reduction in different genotypes, gender, and drugs in test group

In the test group, there were no significant differences in HAM-A-decreased score between male and female patients after 1, 2, 4, or 8 weeks of treatment (Table 5). Furthermore, there were no significant differences in HAM-A-decreased score between the patients treated with venlafaxine XR and the patients treated with escitalopram after 1, 2, 4, or 8 weeks of treatment (Table 5). Finally, there were no significant differences in HAM-A-decreased score among patients with various genotypes after 1, 2, 4, or 8 weeks of treatment with venlafaxine XR or escitalopram.

Table 5.

Comparative Analysis of Hamilton Anxiety Rating Scale Reduction in Different Genotypes, Gender, and Drugs in the Test Group

	1W HAM-A decreased score			2W HAM-A decreased score			4W HAM-A decreased score			8W HAM-A decreased score
Factors	X ± s	F	p	X ± s	F	p	X ± s	F	p	X ± s	F	p
Sex
Male	3.10 ± 2.05			6.98 ± 3.00			10.60 ± 3.94			13.06 ± 4.47
Female	3.27 ± 1.64	0.306	0.581	6.46 ± 2.66	1.282	0.259	10.42 ± 3.33	0.099	0.753	13.09 ± 4.02	0.001	0.970
Drug
Esc	3.12 ± 1.78			6.58 ± 2.93			10.43 ± 3.71			13.45 ± 4.49
Ven XR	3.3 ± 1.72	0.729	0.394	6.60 ± 2.57	0.003	0.957	10.50 ± 3.26	0.019	0.891	12.73 ± 3.73	1.499	0.222
Gene (Esc)
A/A	2.57 ± 1.54			6.29 ± 3.70			9.76 ± 4.23			13.00 ± 4.31
A/G	3.18 ± 1.60			6.82 ± 2.28			11.07 ± 3.53			13.97 ± 4.70
G/G	3.41 ± 2.15	1.429	0.245	6.41 ± 3.27	0.301	0.741	9.93 ± 3.55	1.273	0.285	12.97 ± 4.34	0.580	0.562
Gene (Ven XR)
A/A	3.34 ± 1.72			6.31 ± 2.79			10.38 ± 3.20			12.48 ± 3.9
A/G	3.18 ± 1.92			6.69 ± 2.46			10.69 ± 3.08			13.11 ± 3.71
G/G	3.58 ± 1.36	0.438	0.646	6.77 ± 2.58	0.263	0.769	10.31 ± 3.72	0.138	0.871	12.35 ± 4.10	0.431	0.651

Esc, escitalopram; 1W HAM-A decreased score, HAM-A decreased score after 1 week of treatment; 2W HAM-A decreased score, HAM-A decreased score after 2 weeks of treatment; 4W HAM-A decreased score, HAM-A decreased score after 4 weeks of treatment; 8W HAM-A decreased score, HAM-A decreased score after 8 weeks of treatment; Ven XR, venlafaxine XR.

Cross-analysis of different genotypes, gender, effectiveness of patients with GAD in test group

There were no significant differences in the ratios of test group patients with different genotypes, sex, or response to treatment (Table 6).

Table 6.

Cross Analysis of Different Genotypes, Gender, Effectiveness of Patients with Generalized Anxiety Disorder in the Test Group

		Response				Remission
Variables		Responsive	Nonresponsive			Remitter	Nonremitter
Sex	Genotype	Frequency (%)		χ²	p	Frequency (%)		χ²	p
Male	A/A	11 (68.8)	5 (31.2)			8 (50.0)	8 (50.0)
	A/G	14 (87.5)	2 (12.5)			9 (56.3)	7 (43.8)
	G/G	12 (75.0)	4 (25.0)	1.675	0.528^*	6 (37.5)	10 (62.5)	1.169	0.557
Female	A/A	28 (82.4)	6 (17.6)			14 (41.2)	20 (58.8)
	A/G	63 (85.1)	11 (14.9)			37 (50.0)	37 (50.0)
	G/G	31 (79.5)	8 (20.5)	0.590	0.745	18 (46.2)	21 (53.8)	0.741	0.690

Fisher's exact test.

Discussion

Although GAD and depression present different symptoms, they may share similar neurobiological mechanisms. For instance, GAD and depression are both associated with 5-HT, norepinephrine, and BDNF. In recent years, most studies have focused on investigating the relationship between BDNF level and antidepressant efficacy in patients with MDD. Domschke et al.'s (2010) study provided some preliminary support for a potential minor role of genetic variation in BDNF and antidepressant treatment outcome in the context of melancholic depression. Furthermore, some researchers found that people with the A-allele of BDNF Val66Met responded better to treatment (Choi et al., 2006; Kato and Serretti, 2010). Zou et al.'s (2010) study on BDNF Val66Met showed that heterozygous patients with MDD tended to have better remission with fluoxetine compared with homozygous MDD patients.

Additionally, Romain et al.'s (2015) study reported that SSRI should be preferred for patients who are Val/Val carriers and SNRI/TCA should be preferred for Caucasian patients who are Met carries. Some studies, however, have reported inconsistent results regarding the different efficacy of these treatments in Asian and Caucasian populations, as well as no difference in response and remission rate between Met and Val carriers (Choi et al., 2006; Xu et al., 2012; El-Hage et al., 2015).

Ball et al. (2013) found no significant association between baseline plasma BDNF levels and anxiety disorder severity. However, Wang et al.'s (2015) study of the Chinese Han population, however, found that patients with GAD showed lower BDNF plasma levels than healthy controls and suggested that BDNF plasma level was not associated with Val66Met variation. This finding implied that Val66Met polymorphism had nothing to do with the development of GAD, even though BDNF might be associated with GAD.

Notably in Wang et al.'s (2015) study, the data of 108 patients with GAD and 99 healthy control participants were included in the BDNF level analysis, but only the data of 102 patients with GAD and 63 healthy controls were included in the analysis of BDNF Val66Met polymorphism. The significant difference in the size of the test group and control group, and the limited number of participants could have influenced their research results.

The association results for BDNF Val66Met polymorphism and antidepressants' efficacy are conflicting in Asian populations with GAD. The research regarding the effects of gender and BDNF on the antidepressants efficacy is lacking. Kreinin et al. (2015) reported a positive correlation between blood BDNF levels and severity of depression only among untreated women with severe MDD. Our study did not support this association between Val66Met polymorphism and gender with GAD vulnerability. Some possible reasons for this difference include the complex etiology and numerous influencing factors of GAD, a weak effect of Val66Met on GAD, and the limited sample size in this study resulting in no statistical difference. Additionally, these results may imply that BDNF Val66Met polymorphism simply is not related to GAD.

Conversely, the relationship between BDNF Val66Met polymorphism and antidepressant efficacy for GAD needs to be verified. One study compared the 6-week treatment response of venlafaxine XR and placebo, and found that BDNF Val66Met polymorphism was not related to the therapeutic effect of venlafaxine XR (Narasimhan et al., 2011). Our study used venlafaxine XR (SNRI) and escitalopram (SSRI) as the treatment drugs. We found no significant difference in the effects of these drugs after 8 weeks of treatment. Furthermore, BDNF Val66Met polymorphism and gender showed no relationship with treatment response. Additionally, the BDNF Val66Met polymorphism of the patients and the control subjects were not significantly different from that of the control subjects.

The inconsistent results of the studies in this field may be explained by differences in the race and location of the test subjects, sample heterogeneity, sample size, or sex ratio. In this study, although sample size of the antidepressant treatment group is 195, it is still not sufficient to study the effect of sex factors on antidepressants' efficacy. In addition, the whole observation time is 8 weeks in the present study, which may be insufficient to judge the effect of BDNF on drug efficacy (Romain et al., 2015). This short observation time may be a reason for the negative results of observing the effect of BDNF Val66Met polymorphism on drug efficacy.

The results of the present study suggest that BDNF Val66Met polymorphism is not associated with antidepressant efficacy for GAD, which implies that there may be many influencing factors for antidepressant efficacy. Antidepressant efficacy also could be influenced by other BDNF gene loci or by interactions among numerous gene loci. Although the results of the present study were negative, given the lack of objective biological evidence for selecting a treatment method for GAD, the current results may provide a new perspective on the potential relationships among BDNF gene polymorphism, gender, and antidepressants efficacy in the treatment of GAD.

Limitations

The sample size in this study was relatively small, and the percentage of male subjects was low. Most of the participants in the test group were inpatients, and the average age of the test group subjects was significantly higher than that of the control group subjects. Furthermore, this study examined only one of the gene loci of BDNF.. In future studies, more outpatients should be recruited, the sample size should be increased, and more types of gene loci should be investigated. Because the subject's education level in the study is relatively low, other self-assessed anxiety scale cannot be validly completed. The single application of HAM-A in the present study is insufficient to assess anxiety symptoms comprehensively and the observation time is relatively short, which is another deficiency of this study. Future research will benefit from the application of other statistical methods with higher power to detect the potential significance.

Footnotes

Acknowledgments

This work was supported by the Public Welfare Applied Technology Research Project of Huzhou City (2014GY16, X.S.) and General Projects of Medicine and Health of Zhejiang Province (2015127505, X.S.). The authors thank all participants who took part in this study.

Author Disclosure Statement

No competing financial interests exist.

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