Secondary Logo

GRIK4 and GRM7 gene may be potential indicator of venlafaxine treatment reponses in Chinese of Han ethnicity

Sun, Qianqian, PhDa,c; Yuan, Fan, PhDa,b,c; Yuan, Ruixue, PhDa,c; Ren, Decheng, PhDa,c; Zhu, Yuhao, PhDa,c; Bi, Yan, PhDa,c; Hu, Jiaxin, PhDa,c; Guo, Zhenming, PhDa,c; Xu, Fei, PhDa,c; Niu, Weibo, PhDa,c; Ma, Gaini, PhDa,c; Wu, Xi, PhDa,c; Yang, Fengping, PhDa,c; Wang, Lu, PhDa,c; Li, Xingwang, PhDa,c; Yu, Tao, PhDa,c; He, Lin, PhDa,c,*; He, Guang, PhDa,c,*

Section Editor(s): Liu., Feng

doi: 10.1097/MD.0000000000015456
Research Article: Observational Study
Open

Venlafaxine is one of commonly prescribed antidepressants for major depressive disorder (MDD). Accumulated evidence implicates the involvement of glutamatergic receptors in the pathophysiology of MDD and antidepressant treatment.

By using 193 MDD patients who have been taking venlafaxine for 6 weeks, we investigated whether single nucleotide polymorphisms (SNPs) in glutamate ionotropic receptor kainate type subunit 4 (GRIK4), glutamate ionotropic receptor AMPA type subunit 1 (GRIA1) and glutamate metabotropic receptor 7 (GRM7) were associated with treatment response. 14 SNPs were selected randomly depended on association studies. Efficacy of treatment was determined by 17-item of Hamilton Rating Scale. Allele and genotype frequencies were compared between responders and non-responders.

After adjusting by the false discovery rate (FDR), rs6589847 and rs56275759 in GRIK4 and rs9870680 in GRM7 showed associating with venlafaxine treatment response at week 6. (FDR: P = .018, P = .042, and P = .040, respectively).

Our results indicated that genetic variants in the GRIK4 and GRM7 may associate with the treatment response in MDD patients treated by venlafaxine.

aBio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University

bInstitute for Nutritional Sciences, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences

cShanghai Key Laboratory of Psychotic Disorders, Shanghai Institute of Mental Health, Shanghai Jiao Tong University, Shanghai, China.

Correspondence: Lin He, and Guang He, Bio-X Institute, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, P.R. China (e-mails: helin@sjtu.edu.cn, heguangbiox@163.com).

Abbreviations: AIC = Akaike information criterion, FDR = false discovery rate, GRIA1 = glutamate ionotropic receptor AMPA type subunit 1, GRIK4 = glutamate ionotropic receptor kainate type subunit 4, GRM7 = glutamate metabotropic receptor 7, GWAS = genome-wide association study, HAMD = Hamilton Rating Scale for Depression, LD = linkage disequilibrium, MDD = major depressive disorder, PCR = polymerase chain reaction, SNPs = single nucleotide polymorphisms, SNRIs = serotonin and norepinephrine reuptake inhibitors, SSRIs = selective serotonin reuptake inhibitor, STAR*D = Treatment Alternatives to Relieve Depression.

QS is the first author

This work was supported by the National Key Research and Development Program (2016YFC0906400, 2016YFC1307000, 2016YFC0905000), the National Nature Science Foundation of China (81421061, 81361120389), the Shanghai Key Laboratory of Psychotic Disorders (13dz2260500), the National Nature Science Foundation of China (81121001, 31171237, 81421061, 81571503, 81300556), the Shanghai Municipal Commission of Science and Technology Program (09DJ1400601), the Shanghai Leading Academic Discipline Project (B205), Overseas Students Science and Technology Activities Project Merit Funding.

The authors have no conflicts of interest to disclose.

This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0

Received October 19, 2018

Received in revised form March 6, 2019

Accepted April 8, 2019

Back to Top | Article Outline

1 Introduction

Major depressive disorder (MDD), a common debilitating psychiatric disorder, affects 10% to 15% of population annually in global.[1–3] Antidepressants, classified by slightly different mechanisms of pharmacological actions, are most commonly prescribed agents for MDD.[4] According to the study, 30% to 40% of the patients still do not respond to the currently available antidepressants. Moreover, the balance among the efficacy, safety, and tolerability of those drugs are always far from ideal.

The serotonin and norepinephrine reuptake inhibitors (SNRIs) venlafaxine is one of the available first-line antidepressant medications in many countries.[5] Venlafaxine has sorts of advantages such as better tolerance and higher remission rate in MDD compared with selective serotonin reuptake inhibitor (SSRIs) and other antidepressants.[6] A systematic meta-analysis compared with 21 antidepressant drugs for MDD indicated that response and remission rates of venlafaxine are greater than other antidepressants (range of odds ratio [ORs] 1.19–1.96).[4] Although the efficacy of venlafaxine is certain, inconsistent pharmacogenetic studies have led to a renewed focus on the substantially genetic factors in the antidepressant response.[7,8]

Glutamate is a major excitatory neurotransmitter in the central nervous system. MDD patients always show aberrant glutamatergic neurotransmission. This is partially caused by the polymorphism in glutamate receptor genes.[9] Glutamate receptor genes are potential therapeutic targets for MDD, for instance, ketamine, an antagonist of the N-methyl-d-aspartate (NMDA) glutamate receptor (GluR), has rapid antidepressant efficacy in clinical application.[10,11] Previous studies indicated that venlafaxine can regulate the expression levels of NMDA receptor genes, such as GRIN2B, GRIN2A, and GRIA3. The upregulation of GRIA3 gene by venlafaxine in MDD patients is accorded with the theory that SSRIs play a role in the glutamatergic-system.[12] In recent pharmacogenomics investigations, the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) demonstrated several glutamate receptor genes (glutamate ionotropic receptor kainate type subunit 4 [GRIK4], GRIN2A, and GRIK1) showed to associate with citalopram response.[13,14]GRIA3 and GRIK2 are associated with treatment-emergent suicidal ideation.[15,16] Otherwise, within up to 6 weeks of treatment with several types of antidepressants, GRIK4 is not significantly associated with Caucasian MDD patients.[17] The contradictory results rekindled the importance between antidepressant treatment and glutamic system gene variants. However, there are a few pharmacogenetic studies on association of glutamate receptor and venlafaxine antidepressant response in the literature. Therefore, we hypothesized that genetic variants in glutamate receptor genes may influence the antidepressant response[18,19] and we carried out the association study between GRIK4, GAR1A, and GMR7 and venlafaxine treatment response in MDD individuals.

Back to Top | Article Outline

2 Materials and methods

2.1 Subjects

The 193 unrelated individuals (aged 18–65 years old), fulfilled with DSM-V (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) criteria for MDD were recruited. The MDD patients had a minimum baseline Hamilton Rating Scale for Depression (HAMD) score at 18 points. Interrater reliability was evaluated by Kappa coefficients (Kappa value = 0.85).[20] Clinical interviews were performed by board-certified and experienced psychiatrists. The study was approved by the Ethics Committee of the Human Genetics Center in Shanghai and all subjects signed the informed consent form.

Participants were first-onset patients. They cannot receive any antidepressant treatment for at least 2 weeks and had no electroconvulsive therapy treatment. Patients with other axis I psychiatric disorders, such as schizophrenia, rapid cycling bipolar disorder, dementia, generalized anxiety disorder, obsessive-compulsive disorder, or substance abuse, and those with axis II disorders (including personality disorders), major medical/neurological disorders, or pregnancy were excluded. All the patients were of unrelated (no blood relationship) Chinese population of Han ethnicity.

Back to Top | Article Outline

2.2 Treatment and Data collection

We used 17-item HAMD to evaluate the severity of symptoms and medication efficacy. All MDD individuals received a 6-week continuous antidepressant treatment. A total dose of 75 to 375 mg per day of venlafaxine were used according to patients’ conditions. Then the patients were evaluated at the beginning and later at week 1, 2, 4, and 6 of continuous treatment. Other psychotropic medications were not allowed during the study except an eligible dosage of benzodiazepine for insomnia at bedtime.

Two independent experienced psychiatrists performed the HAMD score and they were blind to patients’ genotype. The responders were defined as a no less than 50% reduction of HAMD score at the end of week 6. The reduction of HAMD score less than 50% at the end of week-6 was defined as non-response group. It is reasonable to select the sixth week as the time point to calculate reduction rate since this duration of treatment is thought to be sufficient for an antidepressant drug to show its clinical efficacy.[21]

Back to Top | Article Outline

2.3 Genotyping

Genomic DNA was extracted from venous blood leukocytes using the phenol-chloroform method. Considering that the coverage of a gene and minor allele frequency should be above 0.03, glutamate ionotropic receptor AMPA type subunit 1 (GRIA1), GRIK4, and glutamate metabotropic receptor 7 (GRM7) gene were selected on the literature[19,22–25] and the NCBI dbSNP database (http://www.ncbi.nlm.nih.gov/SNP) (Table 1). Genotyping of all single nucleotide polymorphisms (SNPs) was performed by a matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometer using the MassARRAY Analyzer 4 platform (Sequenom, CA). All primers were designed by the accompanying software Spectro designer. The polymerase chain reaction (PCRs) were carried out in a total volume of 5 μL, with 10 ng genomic DNA, using the cycling conditions recommended by the manufacturer. Detailed information about primers and PCR conditions is available on request. The determination of genotypes was performed by researchers who were blind to the clinical outcome of the antidepressant treatment. The clinical laboratory of the West China Hospital was participants in it.

Table 1

Table 1

Back to Top | Article Outline

2.4 Statistical analysis

Differences in demographic between responders and non-responders were calculated by the Student t test (age, age onset, body mass index, and HAMD score) or Pearson χ2 test (gender, marital states, educated, and family history). The SPSS Statistics version 22 and R software (Lucent Technologies, NJ, version 3.2.2.) were used to carry out the above analyses.

The online software SHEsis (http://202.120.31.177/myanalysis.php) was used to analyze allelic and genotypic distributions and pairwise linkage disequilibria (LD).[26] χ2 test was used to compare the discrepancies of allele and genotype frequencies between responders and non-responders. We used HaploView version 4.2 to estimated LD of all pairs of SNPs with D’, which is the standard measurement.[27] Hardy–Weinberg equilibrium (HWE) was calculated on SHEsis. Odd ratios (ORs) and their 95% confidence intervals (CIs) were also figured out. Further analyses of genotype frequency between groups were compared using R in 5 genetic models. The logistic regression analysis was used to test the relationships between variables and treatment outcomes. The lowest Akaike information criterion (AIC) in the 5 model was considered as the best one.[28] The FDR was adjusted to control the procedure by R (version 3.2.2.). FDR is the expected proportion of false discoveries among the discoveries. It can discover more real differences compared with other methods.[29] For all analyses, P values were 2 tailed and P <.05 means statistical significances.

Back to Top | Article Outline

3 Results

3.1 Demographic

In our study, a total of 193 patients with MDD were recruited, 175 patients completed the 6-week venlafaxine treatment. Detailed information of demographic was listed in Table 2. 146 patients actually responded to venlafaxine treatment in the end of week 6 and the rate was 83.4%. The responders had an end-point value of HAMD of 16.24 ± 5.49. The significant difference cannot be found between responders and non-responders in age, BMI, number of episode, HAMD baseline, family history, educate background, or gender (P >.05) except the 6-week HAMD score. Therefore, it is reasonable to conclude that no systematic differences potentially affect clinical outcomes between responders and non-responders.

Table 2

Table 2

Back to Top | Article Outline

3.2 Genotype and allele frequencies

None of the SNPs were significantly deviate Hardy–Weinberg equilibrium (P <.05) (shown in Table 3). The allele type and genotype of rs6589847 and rs56275759 in GRIK4 significantly associated with MDD patients after venlafaxine treatment at week 6 (rs6589847: P = .017, P = .016; rs56275759: P = .010, P = .030 respectively). Rs11218016 locus within GRIK4 showed statistical significance in allele distribution (P = .029). The genotype of rs9870680 within GRM7 gene associated with antidepressant treatment (P = .025). There were no significant associations in the other genetic variants between responders and non-responders. LD between the 14 markers was conducted between the response and non-response groups. No Strong LD was observed between the 2 groups (data not shown).

Table 3

Table 3

Since many variable genetic factors may affect the response to treatment, we further analyzed those positive SNPs. R was used to exam the SNPs in 5 genetic models between response and non-response groups. The results are shown in Table 4. Similar association was found among the polymorphisms. Within GRIK4 gene, according to the lowest AIC, rs11218016 in log-Additive genetic model was the best (P = .031). Rs6589847 exhibited a stronger significant difference in genotype between responders and non-responders (P = .006) in over-dominant genetic model. Rs56275759 polymorphism between them revealed differences genotype distribution (P = .023) in codominant model. For the rs9870680 marker in GMR7, the analysis between 2 groups showed different genotypes distribution in recessive genetic model (P = .008). The genotype of rs6589847, rs56275759, and rs9870680 was still associated with venlafaxine treatment after FDR correction (P = .018, P = .042, P = .040, respectively).

Table 4

Table 4

Back to Top | Article Outline

4 Discussion

Our studies investigated the association between genetic variation in glutamatergic receptor genes and response to venlafaxine treatment in MDD patients and found significant associations for SNPs in GRIK4 and GMR7. According to HAMD criteria, as many as 83.4% of patients were positive to treatment response in our study, which was consistent with previous studies.[8,30] The gene and polymorphism were selected based on the research of MDD association studies or other antidepressant treatments.[14,19,22,31] We intended to examine the previous genetic analyses of the MDD treatment cohort.

Glutamate is synthesized in presynaptic neurons and acts via metabotropic and ionotropic receptors. Glutamate level and glutamatergic neurotransmission are abnormal in patients with MDD. [32]Pharmacological compounds that influent the production of glutamate and the expression of its cognate receptors have been proposed as an alternative candidate treatment. The relationship between the glutamate-related genes and treatment response was highlighted by several studies.[33–35]

In GRIK4 gene, 2 SNPs (rs6589847 and rs56275759) significantly associated with venlafaxine response after correction. The associations between response and non-response groups were confirmed by implementing R to make the results more convincing. To our knowledge, GRIK4 is one of controversial MDD candidate genes in antidepressant response.[18,35] Previously study proved rs1954787 and rs11218030 were directly associated to both response and remission after treatment resistance in Caucasian sample.[10,18] Pu et al found rs1954787 of GRIK4 gene were associated antidepressant response in Chinese Han MDD patients.[36] Discovery of polymorphisms in candidate gene seems a milestone, but the repetitions in subsequent studies are difficult to achieve. In Caucasian MDD patients, the analysis of GRIK4 SNPs was in accord with response or remission within up to 5 or 6 weeks of treatment.[35] Daniel et al investigated the association of GRIK4 with antidepressant response by meta-analysis. They analyzed 2169 depressed patients and concluded GRIK4 polymorphism rs1954787 was more likely to respond to antidepressant medications.[37] Two positive SNPs (rs6589847 and rs56275759) found in our study, had not been reported previously, and rs56275759 in GRIK4 gene was related to MDD in association study.[22] The polymorphisms or GRIK4 gene can be a candidate of a genetic factor aimed to predict antidepressant response.

Additionally, GMR7 rs9870680 was significantly associated with antidepressant efficacy in MDD patients receiving drugs. GRM7, one of the Group III glutamate metabotropic receptors, is essential in modulating early antidepressant efficacy and antipsychotic response according to previous evidences.[38] The expression of GRM7 has prominent role in neuronal signaling and maintaining cellular structure in MDD.[31,39] Genome-Wide Association Studies (GWAS) meta-analysis revealed that GRM7 gene is one of the strong genes for association with MDD. Recent studies highlight the potential role of GRM7 in risk for depressive symptoms and it also works as a profound therapeutic target.[40,41] A study in Caucasian and African–American MDD patients found that rs1083801 in GRM7 associated with early response to citalopram. The result was tested in Caucasian, non-Hispanic samples, but the association between rs1083801 and citalopram response was only positive in female after stratification by gender.[42] Though meta-analysis of the GWAS of STAR*D for the MDD phenotype (1221 cases and 1636 controls) did not reveal genome-wide significant findings, the biological evidence suggests that GRM7 merits further investigation.[31]

Our results cannot provide evidence for association of variations in GRIA1 antidepressant treatment response. The polymeric markers rs707176 and rs6875572 within GRIA1 cannot be associated with MDD and antidepressants in Korean in-patients.[19] In addition, evidence showed GRIA1 associated with orgasm difficulty in Caucasian subjects, who were treated with SSRIs.[43] Since 5 SNPs did not cover all the region of GRIA1 and the limited sample size, we predicted GRIA1 gene may not affect venlafaxine response in our study.

Although we found 3 polymorphisms of GRIK4 and GRM7 gene associated with venlafaxine treatment in our participants, the result needed to be prudently interpreted. There are some limitations in our study. First, we did not use placebo as normal control as MDD patients are at the risk of suicide. A placebo control would offer a convincing estimation of the response rate and validate the association between the SNPs and venlafaxine treatment. Second, the influence of glutamate receptor gene on regulated response would be clearer if more SNPs detected and larger sample size used in our study. Indeed the demonstration regarding GRIK4 and GRM7 gene in antidepressant treatment response may provide a new clue to the mechanism of action of venlafaxine.

Back to Top | Article Outline

5 Conclusion

In summary, our results indicate that rs6589847 and rs56275759 in GRIK4 and rs9870680 in GRM7 might associate with venlafaxine treatment responses in the Chinese MDD individuals. No significant associations were observed for the GRIA1 gene. It is necessary to replicate and verify this possibility with more samples and more ethnics. Despite those limitations, this study may provide a reference for future glutamate-related genes studies, particular in predicting SNRIs responses in population suffering MDD.

Back to Top | Article Outline

Acknowledgments

We appreciate the contribution of the members participating in this study.

Back to Top | Article Outline

Author contributions

Investigation: Qianqian Sun.

Methodology: Qianqian Sun, Yan Bi, Weibo Niu, Fei Xu, Fengping Yang.

Project administration: Xingwang Li, Lin He, Guang He.

Software: Fan Yuan, Ruixue Yuan, Decheng Ren, Jiaxin Hu, Zhenming Guo, Gaini Ma, Yuhao Zhu, Tao Yu.

Supervision: Xi Wu, Lu Wang.

Writing – original draft: Qianqian Sun.

Writing – review & editing: Qianqian Sun.

Back to Top | Article Outline

References

[1]. Al-Harbi KS. Treatment-resistant depression: therapeutic trends, challenges, and future directions. Patient Preference Adherence 2012;6:369–88.
[2]. Carvalho AF, Berk M, Hyphantis TN, et al. The integrative management of treatment-resistant depression: a comprehensive review and perspectives. Psychother Psychosomat 2014;83:70–88.
[3]. Agrawal A, Nelson EC, Bucholz KK, et al. Major depressive disorder, suicidal thoughts and behaviours, and cannabis involvement in discordant twins: a retrospective cohort study. Lancet Psychiatry 2017;4:706–14.
[4]. Cipriani A, Furukawa TA, Salanti G, et al. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet 2018;391:1357–66.
[5]. Machado-Vieira R, Henter ID, Zarate CA Jr. New targets for rapid antidepressant action. Prog Neurobiol 2017;152:21–37.
[6]. Papakostas GI, Thase ME, Fava M, et al. Are antidepressant drugs that combine serotonergic and noradrenergic mechanisms of action more effective than the selective serotonin reuptake inhibitors in treating major depressive disorder? A meta-analysis of studies of newer agents. Biol Psychiatry 2007;62:1217–27.
[7]. Richards JS, Bombardier CH, Wilson CS, et al. Efficacy of venlafaxine XR for the treatment of pain in patients with spinal cord injury and major depression: a randomized, controlled trial. Arch Phys Med Rehabil 2015;96:680–9.
[8]. Narasimhan S, Aquino TD, Hodge R, et al. Association analysis between the Val66Met polymorphism in the brain-derived neurotrophic factor (BDNF) gene and treatment response to venlafaxine XR in generalized anxiety disorder. Neurosci Lett 2011;503:200–2.
[9]. Murrough JW, Abdallah CG, Mathew SJ. Targeting glutamate signalling in depression: progress and prospects. Nat Rev Drug Discov 2017;16:472–86.
[10]. Milanesi E, Bonvicini C, Congiu C, et al. The role of GRIK4 gene in treatment-resistant depression. Genet Res 2015;97:e14.
[11]. Lopez-Leon S, Janssens AC, Gonzalez-Zuloeta Ladd AM, et al. Meta-analyses of genetic studies on major depressive disorder. Mol Psychiatry 2008;13:772–85.
[12]. Tamasi V, Petschner P, Adori C, et al. Transcriptional evidence for the role of chronic venlafaxine treatment in neurotrophic signaling and neuroplasticity including also Glutamatergic [corrected] - and insulin-mediated neuronal processes. PLoS One 2014;9:e113662.
[13]. Laje G, Perlis RH, Rush AJ, et al. Pharmacogenetics studies in STAR*D: strengths, limitations, and results. Psychiatr Serv 2009;60:1446–57.
[14]. de Sousa RT, Loch AA, Carvalho AF, et al. Genetic studies on the tripartite glutamate synapse in the pathophysiology and therapeutics of mood disorders. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol 2017;42:787–800.
[15]. Laje G, Allen AS, Akula N, et al. Genome-wide association study of suicidal ideation emerging during citalopram treatment of depressed outpatients. Pharmacogenet Genomics 2009;19:666–74.
[16]. Laje G, Paddock S, Manji H, et al. Genetic markers of suicidal ideation emerging during citalopram treatment of major depression. Am J Psychiatry 2007;164:1530–8.
[17]. Perlis RH, Fijal B, Dharia S, et al. Failure to replicate genetic associations with antidepressant treatment response in duloxetine-treated patients. Biol Psychiatry 2010;67:1110–3.
[18]. Paddock S, Laje G, Charney D, et al. Association of GRIK4 with outcome of antidepressant treatment in the STAR*D cohort. Am J Psychiatry 2007;164:1181–8.
[19]. Chiesa A, Crisafulli C, Porcelli S, et al. Influence of GRIA1, GRIA2 and GRIA4 polymorphisms on diagnosis and response to treatment in patients with major depressive disorder. Eur Arch Psychiatry Clin Neurosci 2012;262:305–11.
[20]. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56–62.
[21]. Chuang HY, Chang YH, Cheng LY, et al. Venlafaxine, paroxetine and milnacipran for major depressive disorder: a pragmatic 24-week study. Chin J Physiol 2014;57:265–70.
[22]. Ren D, Bi Y, Xu F, et al. Common variants in GRIK4 and major depressive disorder: an association study in the Chinese Han population. Neurosci Lett 2017;653:239–43.
[23]. Ren D, Xu F, Bi Y, et al. No association of GRIK4 polymorphisms with schizophrenia in the Chinese Han population. Psychiatr Genet 2017;27:159–60.
[24]. Niu W, Huang X, Yu T, et al. Association study of GRM7 polymorphisms and schizophrenia in the Chinese Han population. Neurosci Lett 2015;604:109–12.
[25]. Niu W, Huang X, Yu T, et al. Association study of GRM7 polymorphisms with major depressive disorder in the Chinese Han population. Psychiatr Genet 2017;27:78–9.
[26]. Shi YY, He L. SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci. Cell Res 2005;15:97–8.
[27]. Barrett JC, Fry B, Maller J, et al. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005;21:263–5.
[28]. Marami Milani MR, Hense A, Rahmani E, et al. Applying least absolute shrinkage selection operator and Akaike information criterion analysis to find the best multiple linear regression models between climate indices and components of cow's milk. Foods 2016;5:
[29]. Benjamini Y, Drai D, Elmer G, et al. Controlling the false discovery rate in behavior genetics research. Behav Brain Res 2001;125:279–84.
[30]. Zarate CA Jr, Mathews D, Ibrahim L, et al. A randomized trial of a low-trapping nonselective N-methyl-D-aspartate channel blocker in major depression. Biol Psychiatry 2013;74:257–64.
[31]. Shyn SI, Shi J, Kraft JB, et al. Novel loci for major depression identified by genome-wide association study of Sequenced Treatment Alternatives to Relieve Depression and meta-analysis of three studies. Mol Psychiatry 2011;16:202–15.
[32]. Shyn SI, Hamilton SP. The genetics of major depression: moving beyond the monoamine hypothesis. Psychiatr Clin North Am 2010;33:125–40.
[33]. Shibata H, Aramaki T, Sakai M, et al. Association study of polymorphisms in the GluR7, KA1 and KA2 kainate receptor genes (GRIK3, GRIK4, GRIK5) with schizophrenia. Psychiatry Res 2006;141:39–51.
[34]. Whalley HC, Pickard BS, McIntosh AM, et al. A GRIK4 variant conferring protection against bipolar disorder modulates hippocampal function. Mol Psychiatry 2009;14:467–8.
[35]. Horstmann S, Lucae S, Menke A, et al. Polymorphisms in GRIK4, HTR2A, and FKBP5 show interactive effects in predicting remission to antidepressant treatment. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol 2010;35:727–40.
[36]. Pu M, Zhang Z, Xu Z, et al. Influence of genetic polymorphisms in the glutamatergic and GABAergic systems and their interactions with environmental stressors on antidepressant response. Pharmacogenomics 2013;14:277–88.
[37]. Kawaguchi DM, Glatt SJ. GRIK4 polymorphism and its association with antidepressant response in depressed patients: a meta-analysis. Pharmacogenomics 2014;15:1451–9.
[38]. Ryan J, Artero S, Carriere I, et al. GWAS-identified risk variants for major depressive disorder: Preliminary support for an association with late-life depressive symptoms and brain structural alterations. Eur Neuropsychopharmacol J Eur Coll Neuropsychopharmacol 2016;26:113–25.
[39]. Nho K, Ramanan VK, Horgusluoglu E, et al. Comprehensive gene- and pathway-based analysis of depressive symptoms in older adults. J Alzheimer Dis JAD 2015;45:1197–206.
[40]. Palucha A, Klak K, Branski P, et al. Activation of the mGlu7 receptor elicits antidepressant-like effects in mice. Psychopharmacology 2007;194:555–62.
[41]. Zhou R, Yuan P, Wang Y, et al. Evidence for selective microRNAs and their effectors as common long-term targets for the actions of mood stabilizers. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol 2009;34:1395–405.
[42]. Fabbri C, Drago A, Serretti A. Early antidepressant efficacy modulation by glutamatergic gene variants in the STAR*D. Eur Neuropsychopharmacol J Eur Coll Neuropsychopharmacol 2013;23:612–21.
[43]. Perlis RH, Laje G, Smoller JW, et al. Genetic and clinical predictors of sexual dysfunction in citalopram-treated depressed patients. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol 2009;34:1819–28.
Keywords:

GRIA1; GRIK4; GRM7; major depressive disorder; response; venlafaxine

Copyright © 2019 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.