Introduction

Depression is a common psychiatric disorder characterized by widespread and persistent depression and loss of interest [1]. Previous studies have shown that depression has become the second most common disease after cardiovascular disease [2, 3]. Depression is not only a burden to individuals, but is also a burden to society because it is associated with a 20 times higher suicide rate than that in normal individuals [4, 5]. Previously, a large number of studies have clarified that environmental, genetic, endocrine, and other factors together lead to the occurrence of depression [2], but the specific cause of depression is not clear. Therefore, the pathogenesis of depression still needs further study.

The role of genetics in increasing susceptibility to depression is recognized [6]. Cyclic adenosine monophosphate response element binding protein (CREB1)—a transcription factor that controls the transcription of numerous neuronal expressed genes—has been shown to be related to both the pathogenesis and treatment of depression [7, 8]. The CREB1 gene is located on chromosome 2q34 and encodes a protein that is a member of the leucine zipper family of DNA-binding proteins [9]. Daniela et al. reported that CREB1 plays an antidepressant role by regulating the expression of certain genes [10]. Additionally, studies have shown that CREB1 plays a role in the effects of antipsychotics and mood stabilizers [11,12,13]. Several standard antidepressant treatment agents, including norepinephrine reuptake inhibitors and selective serotonin reuptake inhibitors, were found to result in elevated CREB1 activity in the hippocampus [9, 14, 15]. With regard to depression, Serretti et al. investigated five single nucleotide polymorphisms (SNPs) in CREB1 in a sample of depression patients for their association with antidepressant response, remission, and treatment resistance, and they found that some genetic polymorphisms in CREB1 could be related to treatment resistance [16].

Apart from CREB1, metabotropic glutamate receptor 7 (GRM7), which mediates the effect of glutamate on neurotransmitter release and cell excitability [17, 18], has been found to be related to depression. GRM7 is located at 3p26 and spans over 900 KB, and is expressed in many regions of the human central nervous system [19]. GRM7 plays a protective role against neuronal excitotoxicity by inhibiting the secondary messenger adenylate cyclase and reducing the activity of the N-methyl-d-aspartate receptor. It can also regulate the release of l-glutamate and GABA, affect mood, and lead to anxiety and even depression [20, 21]. Wierońska et al. found that the GRM7 agonist AMN082 had an antidepressant effect on mice that could be blocked by GRM7 gene knockout [22]. They also found that chronic antidepressant treatment of rodents with citalopram reduced GRM7 immunoreactivity in the hippocampus and frontal cortex [22]. Further, Zhou’s study showed that GRM7 was involved in the regulation of antidepressant response [23]. The amygdala and hippocampus in the brain are known to play a key role in alleviating anxiety and antidepressant, and GRM7 is abundant in these regions [24]. Thus, GRM7 may be involved in the regulatory circuit that affects anxiety and/or depressive behavior [24]. With regard to depression, a meta-analysis showed that the rs162209 polymorphism in the GRM7 gene was closely associated with depression [25].

Previous work has shown that the rs2253206 and rs10932201 in CREB1 and rs162209 in GRM7 may light on the pathogenesis of depression [7, 26, 27]. However, there are few reports on the genetic susceptibility of CREB1 SNPs rs2253206 and rs10932201 and GRM7 SNPs rs162209 involved in depression. In order to verify their correlation with depression and explore their possible mechanisms, we investigated the association of the CREB1 SNPs rs2253206 and rs10932201 and the GRM7 rs162209 with first onset, family history, and suicidal tendency in patients with depression.

Materials and methods

Study participants

This case-control study included 480 patients with depression and 329 healthy controls who were recruited from Jining Psychiatric Hospital and the Sichuan Provincial People's Hospital between March 2018 and December 2019. Chengdu Medical College ethics committee approved of the study (NO.201815), and all the participants signed a complete written consent form after they were informed of the purpose of the project. The patients were diagnosed based on the DSM-IV criteria, and the ratings for symptom severity were evaluated using the 24-item version of the Hamilton rating scale for depression (HAMD-24). The structured interview of depression includes information about mood, insomnia, interests, general condition, and suicide attempt. As described in the previous study of Liang et al., the exclusion criteria were neurodegenerative diseases (for instance, Alzheimer's disease and Parkinson's disease), cognitive impairment, other mental disorders (such as drug abuse), neurological diseases, infections (acute or chronic), thyroid dysfunction, pregnancy, and lactation [28]. The following information was obtained from the participants’ medical records: age, gender, age of onset, HAMD score, pulse rate, depressive episode, family history, suicide attempt, and whether it was their first episode (yes or no). The control group included healthy volunteers without psychiatric conditions who consulted the hospital for physical examination during the same period, and the same exclusion criteria were applied. The control participants were frequency-matched with the patients by age, gender, ethnicity, and living area. The mean age of the depression patients (139 males and 341 females) was 41.8 ± 17.9 years, while the mean age of the controls (105 males and 224 females) was 44.0 ± 16.9 years (Table 1).

Table 1 Characteristics of the study population
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Genotyping

Peripheral blood samples were collected in EDTA-containing test tubes, and genomic DNA was extracted using a DNA isolation kit according to the manufacturer’s instructions (Bioteke, Beijing, China). Information about candidate genes and SNPs involved in this study are shown in Table 2. The rs2253206 and rs10932201 SNPs were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis. The primers for rs2253206 and rs10932201 are shown in Table 2. PCR was performed under the following conditions: 98°C for 5 min, followed by 35 cycles of 98°C for 30 s, annealing for 30 s, 72°C for 10 s, and 72°C for 10 min. The annealing temperature for rs2253206 was 58°C, while that for rs10932201 was 57°C. The PCR product of rs2253206 was digested for 4 h at 37°C with Msel (New England Biolabs, Ipswich, MA, USA), and the rs10932201 product was digested with Hinfl (Thermo Fisher Scientific, Waltham, USA) under the same conditions. After digestion, for rs2253206, the heterozygosis GA genotype was indicated by bands at 191, 128 and 63 bp; the GG genotype was indicated by a band at 191 bp; and the AA genotype was indicated by bands at 128 and 63 bp (Fig. 1). For rs10932201, the heterozygosis GA genotype was indicated by bands at 196, 176 and 20 bp; the GG genotype was indicated by a band at 196 bp; and the AA genotype was indicated by bands at 176 and 20 bp (Fig. 2). DNA sequencing was used to confirm the genotyping results. The rs162209 polymorphism was analyzed by DNA direct sequencing.

Table 2 Information about candidate genes and SNPs involved in this study
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Fig. 1
figure 1

Results of enzymatic digestion of rs2253206 PCR products

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Fig. 2
figure 2

Results of enzymatic digestion of rs10932201 PCR products

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Statistical analyses

The SPSS26.0 statistical software (SPSS Inc., Chicago, Illinois, USA) was used for data analysis. The rs2253206, rs10932201, and rs162209 genotype frequencies were determined by direct counting. Concordance with the Hardy–Weinberg equilibrium was assessed with the χ2 test. The rs2253206, rs10932201, and rs162209 genotype frequencies in the cases and controls were examined using the χ2 test, and the correlation between the three polymorphisms and depression risk was assessed using odds ratios (ORs) and 95% confidence intervals (CIs). The comparison was analyzed using different inheritance patterns, such as codominant, dominant, and recessive genetic model. A P value of <0.05 was considered to indicate statistical significance.

Results

The genotype frequencies of the three polymorphisms in the control participants and patients with depression are presented in Table 3. Due to poor DNA quality in some cases, individual samples could not be genotyped successfully and were thus excluded from the analysis. The genotype distribution in the control group did not deviate from the Hardy–Weinberg equilibrium (P ≥ 0.05). In the codominant model, the rs2253206 AA genotype showed significantly different distribution between the depression patients and controls (adjusted OR = 2.00, 95% CI = 1.15–3.49, P value = 0.01). Similarly, in the recessive model, the AA genotype also showed significantly different frequency between depression patients and controls (adjusted OR = 1.93, 95% CI = 1.13–3.29, P = 0.01). Accordingly, with regard to allele distribution, too, the frequency of A was significantly higher in the depression group (adjusted OR = 1.25, 95% CI = 1.00–1.56, P = 0.05). With regard to the rs10932201 polymorphism, the GA genotype in the codominant model and the GA/GG genotype in the dominant model showed significantly higher frequencies in the depression group (GA: adjusted OR = 1.81, 95% CI = 1.27–2.58, P = 0.001; GA/GG: adjusted OR = 0.74, 95% CI = 0.52–1.04, P = 0.002), as did the G allele (adjusted OR = 1.29, 95% CI = 1.01–1.65, P = 0.04). In contrast, there was no obvious difference in the distribution of the rs162209 genotypes between depression patients and controls.

Table 3 Association of the rs2253206, rs10932201, and rs162209 polymorphisms with depression risk
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Stratification analyses according to depressive episodes (severe vs. mild/moderate), suicide attempt (yes vs. no) and first episode (yes vs. no) showed that the rs10932201, rs2253206, and rs162209 polymorphisms were not significantly correlated with these variables (P > 0.05) (Table 4).

Table 4 Stratified analyses of the rs10932201, rs2253206, and rs162209 polymorphisms in depression patients
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Discussion

In this study, we explored the association between SNPs of candidate genes CREB1 and GRM7 in depression among Chinese people. We found that the CREB1 rs2253206 AA and rs10932201 GA genotypes were associated with an increased risk of depression. Specifically, the rs2253206 AA genotype in the recessive model showed a significantly different frequency between depression patients and controls, indicating that the absence of rs2253206 G allele has a significant correlation with MDD risk compared with the G allele. Similarly, the rs10932201 GA/GG genotype in the dominant model showed a significantly different frequency between depression patients and controls, indicating that the rs10932201 G allele has an obvious correlation with MDD risk. These findings indicate that the CREB1 rs2253206 and rs10932201 polymorphisms may be associated with the occurrence of depression in the Chinese population.

As a transcription factor, CREB1 participates in synaptic and neuronal plasticity on the basis of BDNF pathway [9]. CREB-BDNF pathway is closely related to many neurobiological processes, including synapse and neural plasticity, which may be a potential mechanism for the occurrence and development of depression [8]. Our present findings are consistent with the findings of previous studies, and verifying the correlation between CREB1 and depression in Chinese people [7, 27].

Previous studies on rs2253206 were mostly about panic disorder and memory, but less about depression [8, 29, 30]. Interestingly, in Ma et al.'s study, GG genotype of rs2253206 was susceptible to depression when exposed to high negative life events, but our study found that rs2253206 AA genotype increases the susceptibility to depression [7]. However, there is no research report on the susceptibility of rs10932201 to depression. This may be related to the different characteristics of the selected population, such as age, gender, or our limited sample size. In the future, we will verify our findings in a larger sample size and different populations. Additionally, a meta-analysis showed that an SNP located in CREB1 was associated with depression, and that a decrease in CREB1 expression may be a risk factor for depression [9]. It has been found that antidepressants may reduce the level of CREB1 protein by affecting hippocampal function and activity [31, 32]. On the other hand, gene modification to increase the level of CREB1 protein in the mouse hippocampus was also found to produce an antidepressant effect [33]. These contradictory results imply that further study of CREB1 is urgently needed to describe the overall picture of the genetic and biological basis of CREB1 and its protein product in susceptibility to depression. Therefore, it will be our next research goal.

The present findings showed that the GRM7 SNP rs162209 did not increase susceptibility to depression. However, other studies have reported that GRM7 is associated with depression [17, 34], and Genome-wide association study (GWAS) and meta-analyses have also shown that GRM7 is associated with depression [35,36,37]. Further, Jun et al. proposed the hypothesis that GRM7 affects mood by regulating glutamate as a supplement to the monoamine hypothesis of depression [38]. Specifically, change in the glutamine/glutamate ratio is associated with the onset of depression [39]. In 2010, a study reported that the SNP rs162209 in the GRM7 gene was related to depression, but there have been no subsequent reports on the role of this SNP in depression [40]. In the current study, we failed to find any association of the SNP of rs162209 with the susceptibility to depression. Few studies on the relationship between SNPs of GRM7 and depression were reported, and thus comparison analysis between our data and others cannot be performed and the negative conclusion should be made with caution. Therefore, irrespective of the present findings, other SNPs of GRM7 should be examined to explore the potential relationship between GRM7 and depression.

In the present study, the polymorphisms examined were not correlated with disease severity, onset, family history, or suicidal tendency.

One of the main limitations of this study is that we have only focused on a small number of SNPs in a limited sample, and this may have led to a false null hypothesis. Our research has not found that rs10932201, rs2253206 and rs162209 polymorphisms are significantly related to the variables of depressive episodes, suicide attempt and first episode, which may be caused by small sample size. In addition, the control group we selected may not represent the general population, even though there is no evidence of deviation from the Hardy-Weinberg equilibrium in this group.

In order to reveal the biological basis of the SNPs in the occurrence and development of depression, future research could target these SNPs and examine in bigger cohorts and different populations, and explore the expression of related genes and the impact of protein products on depression.

This study provides preliminary evidence for the correlation between rs2253206 and rs10932201 polymorphisms of CREB1 and susceptibility to depression. In the future, these SNPs should be examined in bigger cohorts in order to understand how they affect depression susceptibility. However, there was no evidence of the GRM7 polymorphism rs162209 and its effect on susceptibility to depression.