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Depression is a severe and debilitating disease characterized by a wide variety of symptoms. These symptoms include at least one of the two core criteria: a persistent depressed mood and a loss of interest, motivation, or pleasure. In addition, individuals with depression experience at least four of several additional symptoms related to the physical axis (such as changes in appetite, sleep disturbances, pain, and lack of energy), psychomotor symptoms, and symptoms related to cognitive functions (including difficulties in planning, slowed thinking, memory problems, and attention issues).
Depression can also encompass thoughts of death, dying, suicide, and overwhelming guilt. These symptoms not only significantly reduce an individual's functioning but also interfere with their normal activities in academic or work settings, as well as in social and family domains, leading to significant suffering and distress. Despite being a widely recognized diagnosis, affecting more than 300 million people worldwide, the full extent of its severity and complexity remains insufficiently understood and acknowledged.
A comprehensive meta-analysis conducted in 2008 examined 393 genetic polymorphisms associated with depression, with results published in 183 research papers (Lopez-Leon et al., 2008).
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However, in genetic studies, the importance of replication cannot be overstated. Remarkably, only 22 out of the 393 investigated genetic variants were examined in at least three different studies and, thus, were eligible for inclusion in a meta-analysis. This meta-analysis supported a significantly increased odds ratio for depression in cases of specific genetic variants, including APOE, GNB3 (C825T), MTHFR (C677T), SLC6A4 (40bp VNTR, serotonin-transporter-linked polymorphic region (5HTTLPR)), and SLC6A3 (44 bp Ins/Del), while it found no significant effects for several other variants of genes that had been repeatedly implicated in depression (such as HTR1A, HTR1B, HTR2A, HTR2C, TPH1, MAOA, COMT, BDNF, SLC6A2, DRD3, GABRA3, and ACE) (Lopez-Leon et al., 2008).
Out of these 22 genes, this study focuses on the GNB3 gene and its potential role in major depressive disorder (MD).
Specifically, this research explores the interaction between variations in the G-protein beta 3 subunit (GNB3) and cAMP response element binding protein 1 (CREB1) genes in relation to negative life events in the pathogenesis of MD. The study investigates one GNB3 polymorphism (rs5443) and four CREB1 polymorphisms (rs2253206, rs2551941, rs6740584, rs11904814) based on their known associations with MD.
Guanine nucleotide binding proteins (G-proteins) serve as key regulators of cellular responses through the cyclic adenosine monophosphate (cAMP) pathways. Abnormal expression and function of G-proteins are closely linked to the pathophysiology of various mental illnesses, including MD. A functional polymorphism (C825T or rs5443) of the G-protein beta3 subunit (GNB3), located on chromosome 12p13.31, has been associated with increased signal transduction and ion transport activity, thereby increasing the risk of MD and influencing responses to antidepressant treatments. Additionally, cAMP response element binding protein 1 (CREB1) has been demonstrated to play a significant role in the response of MD patients to antidepressant therapies. Genetic variations in CREB1 have been confirmed to substantially contribute to mood disorders and MD.
Despite an expanding body of research indicating associations between MD and single nucleotide polymorphisms (SNPs) in the GNB3 and CREB1 genes, the findings have not been consistently replicated. This inconsistency is primarily due to the omission of the consideration of interactions between genetic and environmental factors. In the study at hand, researchers aim to analyze the association of GNB3 (rs5443) and CREB1 (rs2253206, rs2551941, rs6740584, rs11904814) SNPs with MD while evaluating the contribution of environmental factors to the incidence of MD.
A total of 512 patients diagnosed with Major Depressive Disorder (MD) and 513 control subjects without a history of neuropsychiatric disorders were recruited between September 2013 and March 2015. Both groups consisted of Han Chinese individuals residing in northern China. To establish an MD diagnosis, participants underwent interviews conducted by at least two trained psychiatrists using the Structured Clinical Interview for DSM-IV (SCID-I).
Negative life events were assessed using the Life Events Scale (LES), developed by Desen Yang and Yalin Zhang, and validated for the Chinese population. The LES comprises 48 items categorized into three dimensions: family life (28 items), work (13 items), and other aspects (7 items). Negative life events encompassed social housing, relationship and social difficulties, serious illness, unemployment, and financial crises, as well as relationship breakdowns.
Genomic DNA was extracted from 250μl EDTA-anticoagulated venous blood samples using the AxyPrep Blood Genomic DNA Miniprep Kit. Genotyping was conducted for five single nucleotide polymorphisms (SNPs) in the GNB3 and CREB1 genes: GNB3 (rs5443) and CREB1 (rs2253206, rs2551941, rs6740584, rs11904814). DNA samples were genotyped using the 5ʹ nuclease assay with a 7900HT Fast Real-Time PCR System.
Statistical analysis included the calculation of the Hardy-Weinberg equilibrium (HWE) for the genotypic distribution of each SNP using the chi-square goodness-of-fit test. The χ2 test was employed to compare the frequencies of individual SNP genotypes and alleles between the patient group and the control group. A significance level of P < 0.05 (two-tailed) was considered statistically significant.
Significant differences were observed in GNB3 rs5443 allele frequencies and genotype distributions between MD patients and controls. Notably, significant gene-environment interactions were detected between negative life events and genotypic variations in all five SNPs.
Individuals carrying the T-allele of rs5443 (CC), A-allele of rs2253206 (GG), T-allele of rs2551941 (AA), C-allele of rs6740584 (TT), or G-allele of rs11904814 (TT) were found to be more susceptible to MD when exposed to high-negative life events. Conversely, individuals with the T+ allele of rs5443 (CT, TT) were susceptible to MD when exposed to low-negative life events.
In terms of demographic and clinical data, the mean ages for cases (145 males and 367 females) and controls (187 males and 326 females) were 42.97 and 42.50 years, respectively. Mean negative LES scores for cases and controls were 10.39 and 3.23, respectively.
Single nucleotide polymorphism association analyses indicated that the genotypic distributions of all five polymorphisms adhered to the Hardy-Weinberg equilibrium for both patients and controls. A significant difference in genotypic distribution between patients and controls was observed for rs5443 (χ2 = 45.27, P < 0.00), as well as in allelic association (χ2 = 8.76, P = 0.00, OR = 0.77, 95% CI: 0.65–0.92). However, no significant association was found between CREB1 SNPs and MD.
Gene-environment interaction analysis was conducted using the GMDR method, with the number of interacting factors set at either 2 or 6. The model with the highest values for CV and PE indicated the most significant interaction. The interaction between rs5443 and negative life events showed a CV consistency of 10 and PE of 0.36, which was considered the best two-factor model. Additionally, the interaction between the combination of rs5443-rs2253206-rs2551941-rs6740584-rs11904814 and negative life events had a CV consistency of 10 and PE of 0.31, considered the best six-factor model. The permutation test results confirmed the significance of the prediction error of the interaction at the 0.00 level.
OR (odds ratio) values with 95% confidence intervals (CI) were calculated to assess the set of risk factors selected by the GMDR method. Analyses assuming a single contribution of each gene-environment interaction to MD risk revealed an OR value of 6.63 (95% CI 3.71–11.84) in individuals carrying the T-allele (CC) of rs5443 associated with high-negative life events. In individuals with other genotypes of rs5443, low-negative life events yielded OR values of 3.35 (95% CI 2.24–5.01). Furthermore, among individuals carrying the A-allele (GG) of rs2253206, T-allele (AA) of rs2551941, C-allele (TT) of rs6740584, or G-allele (TT) of rs11904814, highly-negative life events resulted in OR values of 7.45 (95% CI 3.84–14.45), 3.89 (95% CI 2.03–7.48), 3.72 (95% CI 1.78–7.76), and 7.26 (95% CI 3.74–14.08), indicating a higher susceptibility to MD.
In this study, the negative life events encompassed various stressors, including the loss of relatives due to death or illness, marital problems, unemployment, economic difficulties, and the erosion of social relationships. It is well-established that life stress can lead to structural and functional changes in the brain, and these changes can be modulated by genetic factors. Previous research has reported significant interactions between genes such as 5-HTTPR and BDNF and stressful life events in patients with depression. Additionally, certain single nucleotide polymorphisms (SNPs) in the FKBP5 gene have been associated with an increased risk of psychotic symptoms in young adults, especially when combined with a history of childhood maltreatment.
The findings of this study have revealed an intriguing interaction between the genotypes of GNB3 (rs5443) and CREB1 (rs2253206, rs2551941, rs6740584, rs11904814) SNPs and negative life events in the context of Major Depressive Disorder (MD). Specifically, individuals with the CC genotype of rs5443, GG genotype of rs2253206, AA genotype of rs2551941, TT genotype of rs6740584, or TT genotype of rs11904814 exhibited susceptibility to MD when exposed to high-negative life events. Conversely, individuals with other genotypes of rs5443 were more prone to MD when exposed to low-negative life events.
It is crucial to acknowledge certain limitations of the present study. Firstly, the assessment of negative life events relied on subjective interpretation, introducing potential bias. Secondly, the study focused exclusively on individuals of Chinese Han origin from northern China, and the sample sizes were relatively modest. Consequently, it is essential to exercise caution when attempting to generalize these findings to other populations. Nevertheless, it is worth noting that a homogeneous population can provide advantages in unveiling specific gene-disease associations, particularly when studying gene-environment effects.
The interactions elucidated between GNB3, CREB1, and negative life events are noteworthy. This study delineated allelic variations within the GNB3 and CREB1 genes that confer susceptibility to MD in conjunction with negative life events among individuals of Chinese Han descent. Notably, the C825T (rs5443) SNP, located in the coding exon region of GNB3, was associated with an increased risk of MD. Previous research by Zill et al. reported a link between rs5443 and MD, with a significantly higher frequency of the T allele observed in MD patients compared to healthy controls. Subsequently, Lee et al. identified rs5443 as being associated with the symptomatology and treatment responses of MD in the Korean population. The present study further corroborates the notion that rs5443 may represent a potential susceptibility locus for the onset of MD.
It is essential to recognize that highly prevalent diseases, such as mental disorders, often involve multiple genes, each making a modest contribution. These allelic variants can also interact with one another and with environmental factors, collectively influencing the risk of psychiatric illnesses. Clinical investigations have consistently demonstrated the impact of negative life events on the risk and severity of MD. However, it is crucial to acknowledge that individuals exhibit substantial variability in their behavioral responses to life events, a phenomenon attributed to differences in genetic predisposition and life experiences. These multifaceted factors converge to modulate the neural systems implicated in MD.
Gene-Environment Interactions in Major Depressive Disorder. (2024, Jan 23). Retrieved from https://studymoose.com/document/gene-environment-interactions-in-major-depressive-disorder
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