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. 2016 Sep 28;42(4):787–800. doi: 10.1038/npp.2016.149

Genetic Studies on the Tripartite Glutamate Synapse in the Pathophysiology and Therapeutics of Mood Disorders

Rafael T de Sousa 1,2,*, Alexandre A Loch 2, André F Carvalho 3, André R Brunoni 2, Marie Reine Haddad 4, Ioline D Henter 1, Carlos A Zarate 1, Rodrigo Machado-Vieira 1,2,5
PMCID: PMC5312057  PMID: 27510426

Abstract

Both bipolar disorder (BD) and major depressive disorder (MDD) have high morbidity and share a genetic background. Treatment options for these mood disorders are currently suboptimal for many patients; however, specific genetic variables may be involved in both pathophysiology and response to treatment. Agents such as the glutamatergic modulator ketamine are effective in treatment-resistant mood disorders, underscoring the potential importance of the glutamatergic system as a target for improved therapeutics. Here we review genetic studies linking the glutamatergic system to the pathophysiology and therapeutics of mood disorders. We screened 763 original genetic studies of BD or MDD that investigated genes encoding targets of the pathway/mediators related to the so-called tripartite glutamate synapse, including pre- and post-synaptic neurons and glial cells; 60 papers were included in this review. The findings suggest the involvement of glutamate-related genes in risk for mood disorders, treatment response, and phenotypic characteristics, although there was no consistent evidence for a specific gene. Target genes of high interest included GRIA3 and GRIK2 (which likely play a role in emergent suicidal ideation after antidepressant treatment), GRIK4 (which may influence treatment response), and GRM7 (which potentially affects risk for mood disorders). There was stronger evidence that glutamate-related genes influence risk for BD compared with MDD. Taken together, the studies show a preliminary relationship between glutamate-related genes and risk for mood disorders, suicide, and treatment response, particularly with regard to targets on metabotropic and ionotropic receptors.

INTRODUCTION

In the general population, bipolar disorder (BD) and major depressive disorder (MDD) have a lifetime prevalence of ~4 and 16%, respectively (Kessler et al, 2005), and both disorders share a genetic vulnerability (McGuffin et al, 2003). Despite the prevalence of mood disorders, available first-line treatment options for these illnesses have shown limited efficacy. The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study found that one-third of MDD patients do not achieve remission even after four antidepressant trials (Rush et al, 2006). Similarly, BD patients remain symptomatically ill about half of the time and experience mostly depressive symptoms despite the use of standard treatments (Judd et al, 2002).

In this context, developing novel treatments for mood disorders is crucial. However, a major obstacle to developing such treatments is our lack of understanding of the pathophysiology of these disorders and the mechanism of action of effective interventions. Although the literature has focused on the role of monoamines in mood disorders, monoamine-related theories are limited in their ability to explain the underlying pathophysiology of these disorders. For instance, it takes about 2 weeks for antidepressants to improve mood, despite the fact that they affect monoamine levels immediately after treatment begins (Machado-Vieira et al, 2008).

A large body of preclinical evidence has implicated the glutamatergic system in the pathophysiology of mood disorders (Skolnick et al, 1996), including in the antidepressant effects of N-methyl-D-aspartate (NMDA) receptor antagonists in animal models (Papp and Moryl, 1994). Evidence also exists for the role of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), supported by the knockout of the GluA1 subunit as a successful animal model of depression (Chourbaji et al, 2008) and the antidepressant properties of genetic ablation of kainate receptor subunit GluK4, also in animal models (Catches et al, 2012). Metabotropic glutamate receptors (mGluRs) have also been shown to regulate mood in several animal models (Witkin et al, 2007).

In addition to this preclinical evidence, human studies have shown that the glutamatergic modulator ketamine effectively reduces depressive symptoms in individuals with MDD or BD, including treatment-resistant patients (Zarate et al, 2006, 2012). Further evidence from postmortem studies shows that mood disorders are associated with expression of the glutamatergic genes GRIA1, GRIA3, GRM3, and GRIK1 (Sequeira et al, 2009). Identifying genes involved in the etiology and pathophysiology of mood disorders may reveal relevant mechanistic pathways that could, in turn, inform novel therapeutic targets. Although some genes have consistently been associated with BD (Craddock and Sklar, 2013), only two associations have been replicated in large MDD samples, namely SIRT1 and LHPP (CONVERGE Consortium, 2015). The lack of consistent replicated results poses both a challenge and an opportunity for investigation.

The extant evidence implicating glutamate genes in mood disorders—drawn largely from genome-wide association studies (GWASs) as well as from candidate gene studies—is inconsistent. For instance, no gene has been replicated in all the available studies to date, and associations in opposite directions have been reported for some single nucleotide polymorphisms (SNPs; Menke et al, 2008; Pu et al, 2013). Furthermore, genetic studies of glutamate-related genes have never been systematically reviewed, which hampers a synthesized view of the field and the identification of replicable targets on the glutamatergic pathway.

This paper provides a critical and systematic review of genetic studies investigating the tripartite glutamatergic synapse in patients with BD and MDD, encompassing specific mood symptoms and phenotypic characteristics, treatment response, and pathophysiology.

The Function of the Tripartite Glutamate Synapse: Pathways and Mediators

Glutamate is ubiquitous in the brain and, because it is crucial to promoting excitatory synaptic transmission (Orrego and Villanueva, 1993), plays a key role in synaptic plasticity and memory. In presynaptic neurons, glutamate is loaded into vesicles by vesicular glutamate transporter (VGLUT) proteins (Figure 1). These vesicles fuse with the presynaptic neuronal membrane by interacting with soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE), and are then released into the synaptic cleft. Sodium channels located in the presynaptic neuronal membrane depolarize the membrane, which also facilitates glutamate release (Lingamaneni et al, 2001). Glutamate acts on ionotropic AMPA, NMDA, and kainate receptors as well as mGluRs, mostly in the postsynaptic neuron. The ionotropic receptors are ligand-gated ion channels that open when an agonist binds to them. Notably, ketamine is thought to act by increasing glutamatergic throughput at the AMPA receptor relative to the NMDA receptor (Maeng et al, 2008).

Figure 1.

Figure 1

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Glutamatergic pathway (on the left) and gene variants, haplotypes, and chromosome regions positively associated with mood disorders (on the right). Glutamate (Glu) is loaded into vesicles by vesicular glutamate transporter (VGLUT) proteins (a). These Glu vesicles are fused with the presynaptic neuronal membrane through interactions with soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins to be released to the synaptic cleft (b). Sodium channels located in the presynaptic neuron membrane play a role in regulating Glu release (c). In the postsynaptic neuron, Glu acts on several receptors: ionotropic receptors α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors (d), N-methyl-D-aspartate (NMDA) receptors (e), and kainate receptors (f). Glu also acts on metabotropic glutamate receptors (mGluRs) (g), which are G-protein coupled receptors attached to both the postsynaptic and the presynaptic neurons. The Glu released in the synaptic cleft is cleared by excitatory amino acid transporters (EAAT) (h), to be transformed into glutamine (Gln) in the glial cell. The Gln produced will be transformed into Glu in the neuron. The genes on the right are ranked according to the evidence as high interest (***), moderate interest (**), or low interest (*). High interest (***): at least one study with supporting evidence from a large sample (>1000 patients) and two studies with medium samples (200–1000 patients); moderate interest (**): evidence from one study with a large sample size (>1000 patients) but no more than one study with a medium sample size; low interest (*): findings from studies with medium or small sample sizes, but no study with a large sample size.

MATERIALS AND METHODS

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Included studies had enrolled participants diagnosed with BD and/or MDD as established by a validated structured diagnostic interview such as the 10th revision of the International Statistical Classification of Diseases (ICD-10) or the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV). GWASs, linkage studies, and candidate gene studies in BD or MDD were included that investigated chromosomal regions or SNPs of genes involved in pathways/mediators related to the so-called tripartite glutamate synapse, comprising pre- and post-synaptic neurons and glial cells. The following specific terms were selected for inclusion from recently published non-systematic reviews (Duman, 2014; Machado-Vieira et al, 2009; Mathews et al, 2012; Rudy et al, 2015): ‘Vesicular Glutamate Transport Proteins', ‘SNARE Proteins', ‘Voltage-Gated Sodium Channels', ‘Receptors, Metabotropic Glutamate', ‘Postsynaptic Density Proteins', ‘Receptors, AMPA', ‘Receptors, NMDA', ‘Receptors, Kainic Acid', ‘Glutamate Plasma Membrane Transport Proteins', and ‘Glutamic Acid'. A literature search was performed on PubMed and Web of Science databases in March 2016 using the medical subject heading (MeSH) ‘Mood Disorders' associated with the other aforementioned MeSH terms.

Studies published in English, French, Spanish, German, or Portuguese were considered for inclusion. Studies with non-original data, postmortem analyses, and case reports were excluded. Studies of samples comprising individuals with multiple psychiatric diagnoses were also excluded from this review unless data for MDD or BD were reported separately.

RESULTS

Two of the authors (RTDS and AAL) screened 763 abstracts for eligibility and reviewed 102 full texts of potentially eligible articles (Figure 2); reference lists in these publications were also reviewed and provided 14 other potential articles of interest. Disagreements regarding inclusion were resolved through consensus with an additional author (RMV). Sixty unique articles met inclusion criteria. Of these, 33 (55%) evaluated only BD, 23 (38%) evaluated only MDD, and four (7%) evaluated both BD and MDD.

Figure 2.

Figure 2

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Flowchart showing the identification, screening, election, and inclusion of papers in the review.

Glutamate-Related Genes

Table 1 provides extensive information for all 60 studies, including study design, demographics, diagnosis, genes and proteins identified, and main study findings. Of the 60 papers included in this review, 34 had positive results—that is, the study implicated glutamate-related genes in mood disorders. Eight of these 34 studies (23.5%) were of large samples (>1000 patients), including two GWASs; 19 (56%) were conducted in medium-sized samples (200–1000 patients); and seven (20.5%) were conducted in small samples (<200 patients).

Table 1. Genetic Studies on Glutamate-Related Genes in Major Depressive Disorder (MDD) and Bipolar Disorder (BD): (a) Genes Related to Glutamate Pathways/Mediators Showing Positive Results; (b) Genes Related to Glutamate Pathways/Mediators with Negative Results.

Gene Protein Study Study design MDD/BD N Population Assessment Main outcome
(a)a
VGLUT
 SLC17A7* VGLUT1 Li et al, 2014 Candidate gene MDD 290 patients Chinese Han Treatment response SLC17A7 rs74174284 allele C was associated with SSRI treatment response at week 6 in MDD patients (OR=0.57, 95 % CI=0.38–0.87, corrected P=0.032)
                 
SNARE proteins
 SNAP25** SNAP25 Wang et al, 2015 Candidate gene MDD 1045 patients and 1520 healthy controls Chinese Han Risk SNAP25 rs3787283 and rs3746544 were associated with MDD (adjusted P=0.00387 and adjusted P=0.0485, respectively). The haplotype AG rs3787283-rs3746544 was also significantly associated with MDD (corrected P=6 × 10−4)
    Etain et al, 2010 Candidate gene BD 197 patients with early-onset BD, 202 patients with late-onset BD, and 136 healthy controls French Risk and phenotypic characteristics SNAP25 rs6039769 allele A was associated with early-onset BD (OR=0.62, P=0.005, corrected P=0.03) but not with late-onset BD. SNAP25 rs363006 allele A was associated with late onset BD (OR=1.57, P=0.04), but did not survive correction. Homozygosity for allele C of SNAP25 rs6039769 was associated with a higher SNAP25b expression levels in prefrontal cortex (P=0.04)
 VAMP2* VAMP2 Abou Jamra et al, 2008 Candidate gene BD 409 patients and 407 healthy controls; a replication sample of 378 patients and 384 healthy controls German Risk In the initial sample, there was an association of BD and VAMP2 rs2278637 (P=0.005), rs75664430 (P=0.033), and rs8067606 (P=0.007), which was not observed in the replication sample (all P>0.45)
    Saito et al, 2006 Candidate gene MDD 106 patients Japanese Treatment response There was no association between VAMP2 rs1061032, VAMP2 rs8067606, or VAMP2 HT rs1061032-rs8067606 and response to fluvoxamine in MDD
                 
Sodium channels
 SCN8A* Nav1.6 Wang et al, 2008 Candidate gene BD 506 patients and 507 healthy controls Chinese Han Risk SCN8A rs1601012 and rs303810 showed significant differences between BD patients and controls in both allele and genotype distribution, but only SCN8A rs303810 allele distribution remained significant after correction for multiple comparisons (P=0.0164). No linkage disequilibrium or haplotypes were observed among these SNPs
                 
AMPA receptor
 GRIA2** GRIA2 Perlis et al, 2009 GWAS BD 1177 patients, including 458 individuals treated with lithium carbonate or citrate. A second cohort of 359 patients Caucasian Treatment response GRIA2 rs9784453 had a non-significant low p-value (P=4 × 10−4) in a STEP-BD analysis of association of the ability of lithium to prevent recurrence. The same GRIA2 rs9784453 was found to be associated with lithium's ability to prevent recurrence in a confirmatory cohort (P=0.03, alpha set at 0.05)
    Chiesa et al, 2012b Candidate gene MDD 145 patients and 170 healthy controls Korean Risk, treatment response, and phenotypic characteristics GRIA2 rs4302506 and rs4403097 showed an association with age of onset in patients with MDD (P=0.003 and P=0.005, respectively; after Bonferroni, P set at 0.005), but no association with MDD or treatment response. Other GRIA2 SNPs (rs6536221, rs4260586, rs4441804, and rs3813296) were not associated with MDD and clinical characteristics or outcomes
    Chiesa et al, 2012a Candidate gene BD 132 patients and 170 healthy controls Korean Risk and phenotypic characteristics GRIA2 rs6536221, rs4260586, rs4302506, rs4441804, rs3813296, and rs4403097 were not associated with BD diagnosis or treatment outcomes
    Chiesa et al, 2013 Candidate gene MDD 145 patients Korean Treatment response GRIA2 rs4260586 was not associated with improvement on depression rating scale scores or other clinical/sociodemographic variables. There was no interaction between GRIA2 rs4260586, GRIA4 rs10736648, and improvement in depressive symptoms
 GRIA3*** GRIA3 Laje et al, 2007 Candidate gene MDD 1915 patients Caucasian (78%) and other (22%) Phenotypic characteristics Suicidal ideation following citalopram treatment (treatment-emergent suicidal ideation) was associated with GRIA3 rs4825476 (corrected odds ratio=1.94; corrected P<0.01)
    Menke et al, 2008 Candidate gene MDD 397 inpatients German Phenotypic characteristics Following treatment initiation, suicidal ideation was associated with GRIA3 rs4825476 (OR=2.7, uncorrected P=0.041), but with a different allele than that found in Laje et al, 2007)
    Myung et al, 2012 Candidate gene MDD 241 patients Korean Phenotypic characteristics Guilt feelings in females were associated with GRIA3 rs557762 (corrected P=0.01) and GRIA3 TT HT rs592807-rs557762 (corrected P=5.0 × 10−3)
    Gécz et al, 1999 Linkage study BD 373 patients from 40 pedigrees Caucasian Risk There was no evidence of linkage between GRIA3 and BD
    Pu et al, 2013* Candidate gene MDD 281 patients Chinese Han Treatment response SNPs in GRIA3 (rs502434 and rs3761555) showed interactions with early-onset adverse events and recent negative life stress that influence treatment response, but the analyses did not withstand correction for multiple comparisons
                 
NMDA receptor
 GRIN1* GluN1 Mundo et al, 2003 Candidate gene BD 276 patients and their parents European Caucasian (97%) Risk For both GRIN1 rs1114620 (P=0.03) and 6608-G/C (P=0.004) polymorphisms, a preferential transmission of the G allele to BD patients was observed
    Georgi et al, 2006 Candidate gene BD 306 patients and 319 healthy controls German Risk No association was found between GRIN1 and BD
    Hammer et al, 2014 Candidate gene MDD and BD 88 MDD patients, 60 BD, and 1250 controls Caucasian Risk In a study focusing on psychosis, a sub-analysis on patients with mood disorders found no association between mood disorders and GRIN1 rs524991 (P=0.13)
 GRIN2B* GluN2B Martucci et al, 2006 Candidate gene BD 318 trios (of which 158 probands had psychotic symptoms) Caucasian Risk There was an association between GRIN2B rs1805502 (corrected P=0.04) and BD and between GRIN2B A5806C and BD with psychotic symptoms (corrected P=0.008). The HT TCC-rs1019358-A5806C-rs1805502 was transmitted more frequently in BD (P=0.015)
    Avramopoulos et al, 2007 Linkage study BD 41 patients with their families Ashkenazi Jewish Risk Chromosome region 12p13.1–p12.3, which harbors the GRIN2B gene region, showed an increased association with BD in a fine-mapping analysis of regions nominally associated with BD
    Zhao et al, 2011 Candidate gene BD 480 patients and 480 healthy controls Chinese Han Risk BD diagnosis was associated with GRIN2B rs1805247 allelic distribution (corrected P=0.018) and the haplotype consisting of rs1805502 and rs1805247 (uncorrected P=3.55 × 10−9)
    Kuswanto et al, 2013 Candidate gene BD 14 patients and 22 healthy controls Chinese Han (>92% of the patients and the controls) Phenotypic characteristics T allele of GRIN2B rs890 in BD patients was associated with lower brain fractional anisotropy values in left frontal (corrected P<0.001), right frontal (corrected P<0.001), left parietal lobe (corrected P=0.001), left occipital (corrected P=0.006), right occipital region (corrected P<0.001), and left cingulate gyrus (corrected P<0.001), when compared with G allele of GRIN2B rs890 carriers
    Zhang et al, 2014 Candidate gene MDD 178 TRD patients, 612 non-TRD patients, and 779 healthy controls Chinese Han Treatment response GRIN2B HT GT-rs1805502-rs890 was more frequent in the TRD group than in the controls (corrected P=0.007). Regarding GRIN2B rs1805502, there was an excess of the G allele in the TRD group compared with the non-TRD group (OR=1.55, 95 % CI=1.18−2.05, corrected P=0.008)
    Fallin et al, 2005 Linkage study BD 337 trios from 323 families Ashkenazi Jewish Risk GRIN2B was associated with BD (uncorrected P<0.01), but this association did not survive correction for multiple comparisons
    Szczepankiewicz et al, 2009d Candidate gene BD 105 patients Polish Treatment response No association was found between treatment response to lithium in BD and the three GRIN2B polymorphisms analyzed
    Szczepankiewicz et al, 2009b Candidate gene BD 419 patients and 487 healthy subjects Polish Risk No association was found between BD and GRIN2B polymorphisms
    Dalvie et al, 2010 Candidate gene BD 191 patients and 188 healthy controls Mixed ancestry (54%) and Caucasians (46%) Phenotypic characteristics The number of hospitalizations for mania in BD was influenced by an interaction between DAOA rs701567 and GRIN2B rs10129385 (P=0.011)
 FYN* FynB Szczepankiewicz et al, 2009a Candidate gene BD 425 patients and 518 healthy subjects Polish Risk BD was associated with FYN rs6916861 T/G (uncorrected P=0.0004, significance set at 0.016) and rs3730353 T/C (uncorrected P=0.016, significance set at 0.016)
    Szczepankiewicz et al, 2009c Candidate gene BD 101 patients Polish Treatment response No significant association was found between lithium response and FYN polymorphisms. There was a trend toward an association between the TT genotype and T allele of rs3730353 FYN T/C polymorphism and decreased response to lithium
                 
Kainate receptor
 GRIK2*** GluK2 Laje et al, 2007 Candidate gene MDD 1915 patients Caucasian (78%) and other (22%) Phenotypic characteristics Suicidal ideation following citalopram treatment (treatment-emergent suicidal ideation) was associated with GRIK2 rs2518224 (odds ratio=8.23; corrected P<0.003)
    Menke et al, 2008 Candidate gene MDD 397 inpatients German Phenotypic characteristics Following treatment initiation, suicidal ideation was associated with 15 GRIK2 SNPs; the SNPs with the best association were GRIK2 rs2852618 (OR=9.0, uncorrected P=0.005) and GRIK2 rs2782900 (OR=4.3, uncorrected P=0.007)
    Myung et al, 2012 Candidate gene MDD 241 patients Korean Phenotypic characteristics GRIK2 HT ACAG rs1556994-rs1340282-rs1340277-rs141717 was associated with somatic anxiety (corrected P=5.9 × 10−4)
 GRIK3* GluK3 Schiffer and Heinemann, 2007 Linkage analysis MDD and BD 153 families with at least one sib-pair affected by MDD or BD and replication in 81 trios (early-onset MDD) > 90% European ancestry Risk GRIK3 rs6691840 was preferentially transmitted to MDD patients (P=0.01), but not to BD type I patients in the first sample. In the replication sample GRIK3 rs6691840 did not show an association with maternal transmission (P=0.07)
 GRIK4*** GluK2 Pickard et al, 2006 Candidate gene BD 368 patients and 458 controls Scottish Risk GRIK4 HT GC—rs2282586/rs1944522 was protective against BD (OR=0.62, P=0.0002), which remained significant after correction for multiple testing
    Paddock et al, 2007 Candidate gene MDD 1199 patients for discovery and 617 patients for replication Caucasian (78%) and other (22%) Treatment response GRIK4 rs1954787 was associated with both response and remission after citalopram treatment in the discovery and replication groups
    Pickard et al, 2008 Candidate gene BD 356 patients and 286 controls (sample set overlapping with Pickard et al, 2006) and replication in 274 patients and 376 controls Scottish Risk A deletion in the GRIK4 ss79314275 was associated with BD when analyzing genotype (P=2.73 × 10−6) and allele frequencies (P=1.9 × 10−7, OR=0.462). The replication confirmed the results for genotype (P=0.0166) and allele (P=0.0107, OR=0.694). Also, the combination of datasets showed an additive/dose-dependent protection: the association of deletion heterozygosity with BD was higher (OR=0.471) than deletion homozygosity (OR=0.325)
    Horstmann et al, 2010 Candidate gene MDD 275 patients Caucasian Treatment response and phenotypic characteristics GRIK4 SNPs analyzed were not significantly associated with response and remission to five weeks of antidepressant treatment. Although GRIK4 rs12800734 association with remission did not survive correction for multiple comparisons, a sub-analysis in MDD patients with the GG genotype of GRIK4 rs12800734 showed a significant downregulation of hypothalamic-pituitary-adrenal (HPA) axis hyperactivity
    Pu et al, 2013 Candidate gene MDD 281 patients Chinese Han Treatment response Antidepressant response in MDD patients receiving different SSRIs or SNRIs for 6 weeks was associated with GRIK4 rs1954787 (adjusted P=0.016, OR=1.87, CI 95% 1.17–2.98) and the A-G-G haplotype of GRIK4 (rs1954787-rs2230297-rs2298725) (adjusted P=0.004, OR=0.14, CI 95% 0.04–0.54)
    Milanesi et al, 2015 Candidate gene MDD 380 patients with treatment-resistant depression and 247 patients without treatment resistant depression Caucasian of Italian descent Treatment response and phenotypic characteristics GRIK4 rs11218030 was associated with treatment resistance (corrected P=0.025) and GRIK4 rs1954787 was associated with the presence of psychotic symptoms (uncorrected P=0.005)
    Perlis et al, 2010 Candidate gene MDD 250 patients 78% white, 10% African, 12% Hispanic or other descent Treatment response GRIK4 was not associated with treatment response to a six-week trial of duloxetine
    Serretti et al, 2012 Candidate gene MDD 223 MDD patients and 76 healthy controls Caucasian Risk, treatment response, and phenotypic characteristics GRIK4 rs195478 was not associated with treatment response to antidepressants, with risk for MDD, or with characteristics of MDD
    Drago et al, 2013 Candidate gene BD 470 mania patients Caucasian Treatment response GRIK4 rs2298723 was nominally associated with decreased manic symptoms after treatment, but did not survive correction for multiple testing
                 
mGlu receptors
 GRM1* mGluR1 Menke et al, 2012 Candidate gene MDD 350 patients and 370 controls and replication sample of 904 patients and 1012 controls German (>89%) Risk, treatment response, and phenotypic characteristics 22 GRM1 SNPs were associated with MDD, of which six SNPs remained associated after correction for multiple testing (rs2268666 with best allelic P=7.0 × 10−5; corrected P set at 0.0002). In the replication sample, GRM1 rs2268666 was again associated with MDD in the genotypic and carrier-based tests (P=0.02/0.04). GRM1 rs2268666 genotype was also associated with brain hippocampal Glu, with regulation of the HPA-axis, and with treatment response at discharge.
 GRM3* mGluR3 Tsunoka et al, 2009 Candidate gene MDD and BD 325 MDD patients, 155 BD patients, and 802 controls Japanese Risk and treatment response An association was found between GRM3 rs6465084 and MDD (corrected P=0.0371), but no association between GRM3 and fluvoxamine response in MDD. Also, no association was found between GRM2/GRM3 and BD, or between GRM2 and MDD. GRM2 was not associated with fluvoxamine response in MDD.
    Dalvie et al, 2010 Candidate gene BD 191 patients and 188 healthy controls Mixed ancestry (54%) and Caucasians (46%) Risk and phenotypic characteristics GRM3 rs6465084 G-allele increased the risk of psychosis in BD (OR=3.9, P=0.004)
    Kandaswamy et al, 2013 Candidate gene BD One sample of 506 patients and 510 controls and another sample of 593 patients and 642 controls British or Irish descent Risk An analysis on the discovery and the replication samples combined showed an association between BD and GRM3 rs148754219 (OR=4.20, 95% CI, 1.43–12.37, uncorrected P=0.005; corrected P=0.047). The study also shows evidence that GRM3 rs148754219 affects gene expression.
    Sklar et al, 2008 GWAS and linkage analysis BD 1461 patients and 2008 controls; replication on 409 trios (from 256 nuclear families) and 365 patients and 351 controls Caucasian Risk GRM3 rs2237554 was nominally associated with BD in the initial scan (121st variant most associated, uncorrected P=0.001) and was associated with BD in the replication analysis (uncorrected P=0.035), though the results in the replication sample could be found by chance
    Martí et al, 2002 Candidate gene BD 283 BD patients and 162 healthy controls German Risk There was no association between BD and the GRM3 rs2228595
    Fallin et al, 2005 Linkage study BD 337 trios from 323 families Ashkenazi Jewish Risk GRM3 was associated with BD (all uncorrected P<0.01), but did not survive correction for multiple comparisons
    Jia et al, 2014 Candidate gene MDD 409 patients and 619 healthy controls Chinese Han Risk The GRM3 polymorphisms were not associated with MDD
 GRM7*** mGluR7 Breen et al, 2011 GW linkage study MDD 971 sibling pairs concordant for recurrent depression European descent Risk Significant linkage of MDD to chromosome 3p25–26 (GRM7) when restricting diagnoses by severity, with a maximum LOD score of 4.0 centered at the linkage marker D3S1515 (corrected P=0.015). However, a fine mapping of the region in a case-control replication study could not replicate the finding
    Pergadia et al, 2011 Linkage study MDD 220 sibling pairs with history of heavy smoking Australian Risk On a region that harbors GRM7 on chromosome 3 at 24.9 cM (3p26–3p25), there was a genome-wide significant multipoint LOD score of 4.14 for MDD (corrected P=0.004)
    Fabbri et al, 2013 Candidate gene MDD 1541 patients for discovery and 1109 patients for replication White non-Hispanic (72%), white Hispanic (12%), and African-American (16%) on first sample. Second sample of white non-Hispanic Treatment response GRM7 GG genotype of rs1083801 was associated with early response in comparison with late response (P=2.03e−06) and to non-response (P=1.82e−05) to citalopram in a white and African-American sample. The results were confirmed in a white non-Hispanic sample, with GRM7 GG genotype of rs1083801 associated with early response when compared with late response (P=6.7 × 10−7) and non-response (P=2.1 × 10−5) (after Bonferroni, alpha set at 2.5 × 10−5)
    Kandaswamy et al, 2014 Candidate gene BD 506 patients and 510 healthy controls for discovery and 593 BD patients and 642 controls for replication British or Irish descent Risk There was no association between BD and GRM7 SNPs in the replication sample. However, the analysis of the discovery and replication samples combined showed an association between BD and GRM7 rs1508724, rs56173829, and rs6769814.
    Muglia et al, 2010 GWAS MDD 926 patients and 866 controls and 494 and 1052 controls for replication Caucasian Risk No significant variants were associated with MDD. In a sub-analysis on candidate genes, GRM7 rs162209 had the lowest P-value (P=0.0001) in the first sample, but was not significant in the replication (P=0.1); an analysis of the two samples found the lowest P-value for GRM7 rs 162209 (P=0.0002)
    Alliey-Rodriguez et al, 2011 GWAS BD 944 patients evaluated with Cloninger's Temperament and Character Inventory and 1007 patients with the Zuckerman-Kuhlman Personality Questionnaire European Phenotypic characteristics The Zuckerman-Kuhlman Personality Questionnaire subscale evaluating Neuroticism-Anxiety was associated with GRM7 rs13080594 (uncorrected P=7.68 × 10−7), which did not survive correction for multiple comparisons
    Shyn et al, 2011 GWAS MDD 1221 patients and 1636 healthy controls European descent Risk No genome-wide evidence for an association was found. A GRM7 SNP was the third most associated with MDD (P=1.11 × 10−6)
    Verbeek et al, 2013 Candidate gene MDD and BD 1738 patients and 1802 healthy controls Dutch Risk No variants of GRM7 were associated with MDD in GAIN-MDD cohort
                 
EAATs
 SLC1A2* EAAT2 Dallaspezia, et al, 2012 Candidate gene BD 110 patients Caucasian Treatment response SLC1A2 rs4354668 T/T genotype in BD patients was associated with a lower frequency of episodes (p<0.001). An interaction between lithium treatment and SLC1A2 genotype influenced the frequency of episodes in BD patients (P=0.026)
    Poletti et al, 2014 Candidate gene BD 86 patients Caucasian Phenotypic characteristics SLC1A2 rs4354668 affected only BD patients exposed to fewer adverse childhood experiences, with T/T homozygotes showing the lowest, and G/G the highest right hippocampal volume (corrected P=0.001) and left hippocampal volume (corrected P=0.001)
                 
(b)
SNARE proteins
 SNAP29 SNAP29 Saito et al, 2001 Candidate gene BD 124 patients and 107 healthy controls Caucasian Risk There was no association between BD and four SNPs of SNAP29
 VAMP3 VAMP3 Abou Jamra et al, 2008 Candidate gene BD 409 patients and 407 healthy controls; a replication sample of 378 patients and 384 healthy controls German Risk No association was found between VAMP3 rs707455, rs2071987,rs2301489, or rs228729 and BD
 VAMP7 VAMP7 Saito et al, 2000 Candidate gene BD 110 patients not selected forsex-linked transmission and 119 control subjects. Caucasian Risk There was a trend for association of one VAMP7 SNP in males with BD (P=0.06) but not females (P=0.66)
    Müller et al, 2002 Candidate gene BD 164 patients and 267 controls German Risk There was an association of homozygosity between one VAMP7 SNP in females and BD compared with controls (uncorrected P=0.017), which became a trend after correction for multiple comparisons (corrected P=0.051)
                 
AMPA receptor
 GRIA1 GluA1 Chiesa et al, 2012a Candidate gene BD 132 patients and 170 healthy controls Korean Risk GRIA1 rs707176 and rs6875572 were not associated with BD diagnosis or treatment outcomes
    Chiesa et al, 2012b Candidate gene MDD 145 patients and 170 healthy controls Korean Risk and treatment response GRIA1 rs707176 and rs6875572 were not associated with MDD diagnosis or treatment response
    Drago et al, 2013 Candidate gene BD 470 BD mania patients Caucasian Treatment response GRIA1 rs1461224 was nominally associated with a decrease in manic symptoms after treatment, but did not survive correction for multiple testing
 GRIA4 GluA4 Chiesa et al, 2012a Candidate gene BD 132 patients and 170 healthy controls Korean Risk and phenotypic characteristics GRIA4 rs11226805, rs2166318, rs11822168, rs1938956, rs10736648, rs528205, rs11226867, rs667174, and rs641574 were not associated with BD diagnosis or treatment outcomes
    Chiesa et al, 2012b Candidate gene MDD 145 patients and 170 healthy controls Korean Risk and treatment response GRIA4 rs11226805, rs2166318, rs11822168, rs1938956, rs10736648, rs528205, rs11226867, rs667174, and rs641574 were not associated with MDD diagnosis or treatment response
    Chiesa et al, 2013 Candidate gene MDD 145 patients Korean Treatment response and phenotypic characteristics GRIA4 rs10736648 was not associated with improvement on depression rating scale scores or other clinical/sociodemographic variables. There was no interaction between GRIA2 rs4260586, GRIA4 rs10736648, and improvement in depressive symptoms
                 
NMDA receptor
 GRIN3A GluN3A Takata et al, 2013 Candidate gene BD 865 patients and 2781 controls Japanese Risk In a sub-analysis of 865 Japanese BD patients compared with 2781 controls, GRIN3A rs149729514 was not associated with BD (P=0.14).
 GRIN2D GluN2D Dorval et al, 2009 Linkage study MDD 370 nuclear families with 450 children Hungarian Risk Only GRIN2D rs276713 was associated with childhood-onset mood disorders (uncorrected P=0.04), but the association did not remain significant after correction for multiple testing
                 
mGlu receptors
 GRM4 mGluR4 Fallin et al, 2005 Linkage study BD 337 trios from 323 families Ashkenazi Jewish Risk GRM4 was associated with BD (all uncorrected P<0.01), but did not survive correction for multiple comparisons
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Abbreviations: BD, bipolar disorder; GW, genome-wide; GWAS, genome-wide association study; MDD, major depressive disorder; SNRI, serotonin-norepinephrine reuptake inhibitor; SSRI, selective serotonin reuptake inhibitor; TRD, treatment resistant depression.

The studies retrieved in the systematic search were reviewed based on the following proteins related to the glutamatergic pathway: vesicular glutamate transport proteins (VGLUTs), soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor, N-methyl-D-aspartate (NMDA) receptor, kainate receptor, metabotropic glutamate receptor (mGluR), excitatory amino acid transporters (EAATs).

Most studies evaluated several genes; the study is located in the line(s) that correspond(s) to the most relevant results on glutamate-related genes.

a

Studies are underlined when they demonstrated a positive association between glutamate-related genes and mood disorders. The genes are ranked according to the following system: high interest***: at least one study with a large sample (>1000 patients) and two studies with medium-sized samples (200–1000 patients); moderate interest**: evidence from one study with a large sample size (>1000 patients) but no more than one study with a medium-sized sample; low interest*: findings from studies with medium or small sample sizes, but no study with a large sample size.

Interestingly, most of the positive findings (18 of 34 studies (53%)) came from studies that analyzed risk for mood disorders, particularly in BD. Twelve of the 34 positive studies (35%) showed an association between risk for BD and glutamate-related genes, and 7 (21%) showed an association between glutamate-related genes and risk for MDD. The influence of the glutamatergic system on treatment response was supported by 10 of the 34 positive studies (29% eight in MDD, two in BD). Eleven of the 34 positive studies (32% seven in MDD, four in BD) explored the links between phenotypic characteristics and glutamate-related genes.

The variants and regions of those genes showing a positive association with mood disorders are depicted in Figure 1 and Table 1. Specifically, positive evidence was obtained for 16 genes. The importance of these individual findings is highlighted throughout the manuscript, and in the tables and figures, via the following ranking system: high interest (***), moderate interest (**), and low interest (*). Evidence of high interest (***) was supported by at least one study with a large sample size (>1000 patients) and by two studies with medium sample sizes (200–1000 patients). Evidence of moderate interest (**) was supported by at least one study with a large sample size but no more than one study of medium sample size. Evidence of low interest (*) was supported by findings from studies with medium or low sample sizes (<200 patients), but no studies with large sample sizes.

Although to date no specific glutamate-related gene has consistently been associated with mood disorders, below we discuss four genes of high interest. As noted above, an additional 12 genes of moderate and low interest were identified; these are described only in Figure 1 and Table 1. Corroborating evidence from preclinical or postmortem studies is noted throughout the manuscript when extant.

AMPA Receptor

The ionotropic AMPA receptor encompasses several subunits encoded by the GRIA1–4 genes.

GRIA3***

GRIA3 rs4825476 of the gene encoding GluA3 was associated with emergent suicidal ideation following citalopram treatment in a mostly Caucasian sample (78%) of 1915 MDD patients drawn from the STAR*D study (Laje et al, 2007). The same GRIA3 rs4825476 was further associated with suicidal ideation following antidepressant treatment in a German sample of 397 MDD inpatients drawn from the Munich Antidepressant Response Signature (MARS) project; however, these findings implicated a different allele (AA; Menke et al, 2008).

Interestingly, another study found that GRIA3 rs557762 and GRIA3 TT HT rs592807-rs557762 were associated with guilt feelings in a subanalysis of 183 Korean MDD females (Myung et al, 2012). In a Chinese Han sample of 281 patients with MDD, the GRIA3 rs502434 and rs3761555 SNPs were also linked to early-onset adverse events and recent negative life stress that influenced treatment outcome, though the analyses did not withstand correction for multiple comparisons (Pu et al, 2013). In addition, a family study of 373 Caucasian individuals from 40 BD pedigrees from the US and Israel found no linkage between GRIA3 and BD (Gécz et al, 1999).

It should also be noted that a postmortem study found that levels of the GluA3 subunit of the glutamate receptor encoded by GRIA3 was significantly downregulated in the hippocampus of MDD subjects (Duric et al, 2013).

Kainate Receptor

GRIK2***

GRIK2 encodes a kainate receptor subunit that alters the structure and function of the GluK2 kainate receptor. GRIK2 rs2518224 was associated with suicidal ideation following citalopram treatment in the aforementioned sample of MDD patients (n=1915) drawn from the STAR*D study that analyzed 68 candidate genes (odds ratio (OR)=8.23; corrected P<0.003; Laje et al, 2007). In a subsequent replication study conducted in a German sample of 397 MDD inpatients who were part of the MARS project, 15 GRIK2 SNPs were further associated with suicidal ideation following antidepressant treatment; the SNPs with the strongest association with MDD were GRIK2 rs2852618 (OR=9.0, uncorrected P=0.005) and GRIK2 rs2782900 (OR=4.3, uncorrected P=0.007; Menke et al, 2008). Another study found that GRIK2 HT ACAG rs1556994-rs1340282-rs1340277-rs141717 was associated with somatic anxiety in a sample of 241 Korean MDD patients (Myung et al, 2012).

GRIK4***

GRIK4 encodes a protein that belongs to the kainate acid-type glutamate receptor GluK4. In a mostly (78%) Caucasian sample (divided into 1199 MDD patients for discovery and 617 for replication), the G allele of GRIK4 rs1954787 was directly associated with both response and remission after citalopram treatment (Paddock et al, 2007). In another Caucasian sample of 627 MDD patients, GRIK4 rs11218030 was associated with treatment resistance (corrected P=0.025), while the G allele of GRIK4 rs1954787 was linked to the presence of psychotic symptoms (Milanesi et al, 2015). Consistent with the study by Paddock and colleagues (Paddock et al, 2007), antidepressant response in a Chinese Han sample of 281 MDD patients receiving different SSRIs or serotonin norepinephrine reuptake inhibitors (SNRIs) for 6 weeks was directly and inversely associated with the G allele of the GRIK4 rs1954787 SNP and with the A-G-G HT of GRIK4 (rs1954787-rs2230297-rs2298725), respectively (Pu et al, 2013). GRIK4 SNPs analyzed in a Caucasian sample of 275 MDD patients were not significantly associated with response and remission within up to 5 weeks of treatment with several types of antidepressants, but the GG genotype of GRIK4 rs12800734 was associated with downregulation of hypothalamic–pituitary–adrenal (HPA) axis hyperactivity (Horstmann et al, 2010). In contrast, GRIK4 was not associated with treatment response to 6 weeks of duloxetine in a sample of 250 mostly Caucasian MDD patients (Perlis et al, 2010). GRIK4 was also not associated with response to antidepressants, risk for MDD, or phenotypic characteristics in a sample of 223 Caucasian MDD patients and 76 healthy controls (Serretti et al, 2012).

As regards BD, an association was observed between decreased manic symptoms and GRIK4 rs2298723 in a sample of 470 manic BD patients in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) Study who were treated with several antipsychotics, but this result did not survive correction for multiple testing (Drago et al, 2013). Notably, a Scottish sample of 368 BD patients and 458 controls found that the GRIK4 HT GC-rs2282586-rs1944522 protected against BD (OR=0.62, P=0.0002), an association that remained significant after correction for multiple testing (Pickard et al, 2006). In another Scottish sample of 356 patients and 286 controls (which overlapped with the 2006 study by Pickard and colleagues), a deletion in GRIK4 ss79314275 was associated with BD when analyzing genotype (P=2.73 × 10−6) and allele frequencies (P=1.9 × 10−7, OR=0.462); an independent replication sample of 274 patients and 376 controls confirmed this association for genotype (P=0.0166) and allele (P=0.0107, OR=0.694) with BD (Pickard et al, 2008). Interestingly, the combined discovery and replication samples showed an additive/dose-dependent protection: the association of deletion heterozygosity with BD was higher (OR=0.471) than with deletion homozygosity (OR=0.325) (Pickard et al, 2008). Thus, it appears that both of these kainate receptors—GRIK2 and GRIK4—are potentially implicated in mood disorders.

mGluRs

GRM7***

GRM7 encodes mGluR7. Linkage analyses encompass extensive regions, and GRM7 is one of the genes that could explain the signal associating the 3p25-26 region with MDD. One family study of 187 Australian sibling pairs, all them heavy smokers with a history of MDD, found that chromosome 3 at 24.9 cM (3p26–3p25) showed a genome-wide significant multipoint LOD score of 4.14 for MDD (corrected P=0.004; Pergadia et al, 2011). Another genome-wide study that replicated the finding showed significant linkage between severe MDD and chromosome 3p25–26, with a maximum LOD score of 4.0 centered at linkage marker D3S1515 (corrected P=0.015; Breen et al, 2011); the latter study analyzed 971 concordant sibling pairs for recurrent MDD, 118 discordant sibling pairs, and 12 unaffected sibling pairs, all of European descent.

A GWAS evaluating 926 Caucasian MDD patients and 866 controls in the discovery phase and 494 Caucasian MDD patients and 1052 controls in the replication phase obtained mixed results regarding GRM7. Although no significant variants were associated with MDD in the main analysis (Muglia et al, 2010), a sub-analysis of candidate genes found that GRM7 rs162209 had the lowest P-value (P=0.0001) in the first sample, but this finding was not significant in the replication study (P=0.1); when the two samples were analyzed together via meta-analysis, GRM7 rs162209 again had the lowest P-value, and the association occurred in the same direction (P=0.0002; Muglia et al, 2010). Another study of 1541 Caucasian and African-American MDD patients found that the GRM7 GG genotype of rs1083801 was associated with early response to citalopram compared with late response (P=2.03 × 10−6) and non-response (P=1.82 × 10−5; Fabbri et al, 2013). The result was confirmed in a Caucasian, non-Hispanic sample that found that the GRM7 GG genotype of rs1083801 was associated with early response to citalopram compared with late response (P=6.75 × 10−7) and non-response (P=2.12 × 10−5; after Bonferroni correction, alpha set at 2.51 × 10−5; Fabbri et al, 2013). Notably, after stratification by gender, the association between GRM7 rs1083801 and response to citalopram was shown to be significant only in females (females, uncorrected P=1.54 × 10−5; males, uncorrected P=0.0003). Finally, an analysis of 1221 MDD patients and 1636 controls of European ancestry drawn from the STAR*D study found no genome-wide evidence of an association between MDD and GRM7 (Shyn et al, 2011); however, the GRM7 rs9870680 SNP showed one of the lowest P-values (uncorrected P=1.1 × 10−6). Nevertheless, another study of 1738 MDD patients drawn from the Dutch GAIN-MDD sample found that none of the 204 GRM7 SNPs were associated with MDD (Verbeek et al, 2013).

As regards BD, a case–control study in BD patients of Irish or British descent found that three GRM7 SNPs were associated with BD in the discovery sample, a finding not replicated in a second sample (Kandaswamy et al, 2014). After combining the genotype data for the two samples (1099 BD patients and 1235 healthy controls), BD was significantly associated with GRM7 rs1508724 (OR=1.15, corrected P=0.043) and GRM7 rs6769814 (OR=1.15, corrected P=0.045; Kandaswamy et al, 2014). Another analysis of SNPs selected based on increased frequency in BD cases detected an association between GRM7 rs56173829 and BD in the two samples combined (OR=0.4829, P=0.035; Kandaswamy et al, 2014). Another study found that the GRM7 rs13080594 SNP was associated with Neuroticism-Anxiety (uncorrected P=7.68 × 10−7) as assessed by the Zuckerman-Kuhlman Personality Questionnaire in 1007 BD patients of European ancestry, but this finding did not survive correction for multiple comparisons (Alliey-Rodriguez et al, 2011). Interestingly, a GWAS in individuals of European ancestry with BD found one of the strongest P-values (uncorrected P=0.0001) for the glutamatergic SNP GRM7 rs1485171; however, it should be noted that 15% of the sample was diagnosed with schizoaffective disorder, BD subtype (CONVERGE Consortium, 2015).

Preclinical data also support the association between GRM7 and mood disorders. Specifically, mice with the GRM7 deletion had substantially less behavioral immobility in both the forced swim and tail suspension tests than their wild-type littermates (Cryan et al, 2003).

DISCUSSION

Here we reviewed the links between glutamate-related genes and mood disorders risk, treatment response, and phenotypic characteristics such as emergent suicidal ideation. As the evidence reviewed above demonstrates, more evidence exists linking glutamate-related genes to BD than MDD, but no specific glutamate-related gene has been consistently associated with mood disorders. However, several genes appear worthy of further exploration, including GRIA3, GRIK2, GRIK4, and GRM7.

Most of the studies reviewed here were candidate gene studies; only six GWASs were included. GWASs have advantages over other study designs because they use larger samples and analyze variants over the entire genome, thus providing more robust results. Indeed, in this review, four-fifths of the studies that found evidence of a relationship between glutamate-related genes and mood disorders were of medium or large samples. However, of the large studies evaluating glutamate-related genes, no analysis of a gene associated with mood disorders has yet been replicated.

The multiple glutamate-related gene targets of small relevance reviewed above are consistent with the overall sparse findings in genetic studies of mood disorders (Craddock and Sklar, 2013). As noted above, genetic studies in BD have been more conclusive than in MDD (13 studies in BD vs six in MDD), which could be explained by factors such as the much higher lifetime prevalence of MDD, which is over 16% (Kessler et al, 2005), the higher heritability of BD vs MDD (roughly 85% compared with 40% Lohoff, 2010; McGuffin et al, 2003), or the more diffuse phenotype of MDD compared with BD. Studies that focus on specific clinical characteristics of MDD, such as age of onset, could be more successful in this context, as could research focused on groups with specific endophenotypes, such as neuroimaging abnormalities.

Taken together, the studies reviewed above implicate several glutamate-related genes of high interest (***) in mood disorders: GRIA3, GRIK2, GRIK4, and GRM7. Specifically, several MDD (n=7) and BD (n=2) studies support the link between glutamate-related genes and treatment response. For instance, two large studies in MDD found evidence of a relationship between GRIK4 (Paddock et al, 2007) and GRM7 (Fabbri et al, 2013) and treatment response to SSRIs. Phenotypic characteristics were associated with both MDD (six studies) and BD (four studies). Notably, emergent suicidal ideation after SSRI treatment in MDD was linked to GRIA3 and GRIK2 in one large (Laje et al, 2007) and one medium-sized (Menke et al, 2008) study. In addition, a region spanning GRM7 was significantly associated with risk for MDD in one GWAS (Breen et al, 2011), and GRM7 was one of the best candidate genes emerging from two GWASs that evaluated risk for MDD (Muglia et al, 2010; Shyn et al, 2011). GRM7 was also linked to BD in one large study (Kandaswamy et al, 2014) and to MDD in one medium-sized study (Pergadia et al, 2011). Finally, GRIK4 influenced treatment response in one large and two medium-sized studies in MDD (Horstmann et al, 2010; Paddock et al, 2007; Pu et al, 2013) and was associated with risk for BD in two medium-sized samples (Pickard et al, 2006, 2008). All four of these genes (GRIA3, GRIK2, GRIK4, and GRM7) stand out as highly interesting candidates for further study. In addition, further clinical or preclinical evidence exists for all of these genes of functional involvement such as altered mRNA expression or induction of depressive-like behaviors (Beneyto et al, 2007; Catches et al, 2012; Cryan et al, 2003; Duric et al, 2013).

Though preliminary, evidence also suggests an association between glutamate genes with neuroimaging correlates in mood disorders. In MDD, GRM1 was associated with brain hippocampal glutamate levels (Menke et al, 2012). In BD patients, GRIN2B was associated with white matter integrity (Kuswanto et al, 2013), and SLC1A2 was found to modulate gray matter volume (Poletti et al, 2014). However, the results reported across studies have also obtained inconsistent results, which might be due to the high prevalence, relatively moderate heritability, and phenotypic heterogeneity of mood disorders. Another potential reason for inconsistencies is that common variants with small effects likely combine to make a large contribution to risk for mood disorders (Craddock and Sklar, 2013; Flint and Kendler, 2014), which leads to low power to detect effects for the SNPs studied as well as lack of replication.

Importantly, the availability of less costly exome sequencing or whole-genome sequencing techniques has improved the field; both methods are especially useful at finding rare variants that may have larger effects on mood disorders. Successful strategies for future studies could include focusing on more severe cases of MDD to retrieve a clearer signal (CONVERGE Consortium, 2015); using very large sample sizes to study depressive symptoms (Okbay et al, 2016); or studying families with a dense prevalence of mood disorders (Collins et al, 2013).

Pathway analyses are a powerful tool for overcoming limitations associated with studies that explain only a small proportion of phenotypic variance because they use previous knowledge of molecular and cellular processes to detect associations between genes and disorders (Wang et al, 2007). Interestingly, pathway analyses of large datasets support the involvement of the glutamatergic system—and specific glutamatergic pathways—in risk for MDD (Lee et al, 2012) and BD (Nurnberger et al, 2014; Torkamani et al, 2008). In addition, postsynaptic density was found to be related to risk for mood disorders (as well as schizophrenia; Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, 2015), and the long-term potentiation pathway encompassing several glutamate genes was involved with response to citalopram in MDD (Hunter et al, 2013).

Another pathway analysis also found an association between BD and the glia-astrocyte pathway (Duncan et al, 2014); glial cells are central to glutamatergic uptake and recycling. Although the glutamatergic modulator ketamine is consistently associated with an effective antidepressant response (Zarate et al, 2006, 2012), research into ketamine is still in its infancy and we found no studies specifically investigating the genetics of response to ketamine, perhaps because no cohorts to date have been large enough to perform adequately powered GWASs. The lack of genetic studies on ketamine and other glutamatergic modulators could partly explain the low-interest evidence for the NMDA receptor in our review.

Limitations of this review include a methodology limited to searching for articles focused on glutamate-related genes and the diversity of the study designs. However, the inclusion of all genetic studies on the glutamate pathway in mood disorders is a strength of the present review. In future analyses, it might be valuable to explore the glutamatergic pathway in the context of patients enrolled in clinical trials with glutamatergic drugs.

Despite the absence of consistent results, these findings suggest directions that could help decipher the etiology and pathogenesis of mood disorders. The body of evidence suggests that glutamatergic genes are indeed involved in the pathophysiology and treatment of mood disorders. In particular, several targets identified by the present review—including GRIA3, GRIK2, GRIK4, and GRM7—are worthy of further exploration in future studies.

FUNDING AND DISCLOSURE

Funding for this work was supported by the Intramural Research Program at the National Institute of Mental Health, National Institutes of Health (IRP-NIMH-NIH; ZIA MH002857), by a NARSAD Independent Investigator toDr Zarate, and by a Brain & Behavior Mood Disorders Research Award to Dr Zarate. Dr Zarate is listed as aco-inventor on a patent for the use of ketamine and its metabolites in major depression. He has assigned his rights in the patent to the US government but will share a percentage of any royalties that may be received by the government. The remaining authors declare no conflict of interest.

Acknowledgments

We thank the 7SE research unit and staff for their support.

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