Association of HHV‑6 reactivation and SLC6A3 (C>T, rs40184), BDNF (C>T, rs6265), and JARID2 (G>A, rs9383046) single nucleotide polymorphisms in depression
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- Published online on: October 3, 2024 https://doi.org/10.3892/br.2024.1869
- Article Number: 181
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Copyright : © Bumrungthai et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].
Abstract
Introduction
Major depressive disorder (MDD) is a global health concern that can lead to suicide. The World Health Organization estimates that 350 million individuals worldwide have MDD (1). MDD is common in Thailand and its incidence varies by age group; studies have reported rates of 7.0-21.4% in individuals aged 19-22 years, 12.0% in individuals >30 years, 39.10% in those >40 years, 9.8-29.2% in those >45 years and 6.5-18.5% in those >47 years (2-7). Its etiology is not entirely known. Many factors are associated with MDD, including viral infection that causes inflammation in the brain, abnormal hormone, neurotransmitter and proinflammatory cytokine levels and genetic factors (8-10).
Acute and latent infection can affect behavior and mental health. Increased proinflammatory cytokine levels and decreased serotonin and norepinephrine levels cause an inflammatory reaction in response to viral infection of microglia, oligodendrocytes and astrocytes (11,12). Previous research has revealed that elevated proinflammatory cytokine levels are associated with MDD and infection by the varicella zoster, Epstein-Barr, cytomegalovirus, Borna disease and herpes simplex viruses (12-16). Human herpes virus 6 (HHV-6) is a β-HV subfamily of HV family that can lead to chromatin modification and DNA methylation in target cells (17). Several studies have identified HHV-6 as a risk factor for MDD (16,18-21).
MDD is a complex mental disorder influenced by environmental, genetic and epigenetic factors. Genome-wide association studies (GWASs) have identified 178 genetic risk loci and >200 candidate genes (22-24). There is an association between epigenetic/genetic changes and aberrant neuromediators (serotonin, norepinephrine and dopamine) that can lead to MDD (1,25-27). These effects are hypothesized to be mediated by the metabolic disturbance of brain-derived neurotrophic factor (BDNF) in nerve tissue. The single nucleotide polymorphism (SNP) rs6265 in BDNF changes a valine to a methionine at codon 66 (Val66Met), which decreases activity-dependent release of BDNF and is associated with low BDNF levels and MDD pathogenesis (28-30). The dopaminergic system, including dopamine-producing cells, receptors and transporters, may serve a key role in MDD. Solute carrier family 6 member 3 (SLC6A3) regulates dopamine levels in the brain by inhibiting synaptic activity and inducing dopamine reuptake into presynaptic neurons (31-35). In addition, jumonji and AT-rich interaction domain containing 2 (JARID2) is a DNA-binding protein that regulates gene expression by modifying chromatin. SNP rs9383046 in JARID2 has been identified as a potential candidate gene for schizophrenia (36-38).
The interaction between several variables, including viral infection and genetic characteristics, may serve an important role in MDD onset. The present study investigated the association between HHV-6 infection and specific genetic factors [SLC6A3 (g.1394961C>T, rs40184), BDNF (g.27658368C>T, rs6265) and JARID2 (g.15281336G>A, rs9383046)] to elucidate their role in MDD onset. High-resolution melt analysis (HRM) for genetic analysis was performed, along with HHV-6 infection data and viral load assessment from a previous study (39). SNPs were assessed using whole-exome sequencing.
Materials and methods
Specimens
The present study, approved by the Committee on Human Research Ethics (approval nos. UP-HEC 1.3/013/65 and UBU-REC-68/2567), analyzed 471 buccal cell samples from a previous study (39). The MDD samples were collected using mail-in submissions following social media advertising in Thailand. A total of 376 female and 95 male participants were enrolled between July 2022 and June 2023. The participants included 360 healthy individuals, 59 MDD patients, 36 blood relatives of MDD patients, and 16 non-blood relatives of MDD patients. All participants' HHV-6 status was confirmed with quantitative PCR. The study specifically targeted patients aged 18-45 years, diagnosed based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (40). Both recurrent MDD and first-episode cases were included. Certified hospital psychiatrists confirmed diagnoses using the Patient Health Questionnaire-9 (PHQ-9), with a score of ≥9 indicating MDD (39). Patients with MDD exhibited various forms of MDD, including recurrent episodes, acute phase and persistent MDD. Notably, patients with MDD did not present with comorbid conditions such as diabetes, hypertension, chronic obstructive pulmonary disease or coronary artery disease. Family members of patients with MDD were recruited to determine potential risk factors for the condition. Healthy controls were individuals with no present or lifetime psychiatric problems, PHQ-9 score <9 and no congenital disease (39). First-degree relatives of individuals with suicidal ideation or MDD diagnosis were excluded from the control group.
DNA extraction
DNA was extracted from buccal cells using the Genomic DNA Isolation kit (cat. no. PDC11-0100; Bio-Helix Co.) following the manufacturer's protocol as previously described (39).
HHV-6 DNA detection by quantitative (q)PCR and viral load
qPCR-based HHV-6 DNA (U97 gene) status and viral load data were taken from a previous study (39).
SNP detection by HRM
SNPs in SLC6A3 (g.1394961C>T, rs40184), JARID2 (g.15281336G>A, rs9383046) and BDNF (g.27658368C>T, rs6265) were detected by HRM analysis with amplicon sizes of 100, 88 and 146 bp, respectively. Table I shows primer sequences used for HRM analysis. PCR was performed in duplicate using the 5X FiREPOL Eva Green HRM Mix Plus (Solis Bio Dyne) as previously described (39,41,42). Positive controls for SLC6A3 (C/T, rs40184), JARID2 (G/A, rs9383046), and BDNF (C/T, rs6265) were utilized following sequencing confirmation. The primers used for HRM analysis are listed in Table I.
DNA sequencing
Sanger sequencing was performed to confirm the SNPs in SLC6A3 (g.1394961C>T, rs40184), JARID2 (g.15281336G>A, rs9383046), and BDNF (g.27658368C>T, rs6265). A total of 10 samples were analyzed for BDNF, 45 for SLC6A3, and 15 for JARID2, randomly selected from different patterns of HRM. The primers used for sequencing are listed in Table I. The sequences were analyzed by comparison with GenBank reference sequences, BDNF (accession no. NC_000011.10:27658340-27658399) on Homo sapiens chromosome 11, DAT1 (accession no. NC_000005.10:1394924-1394997) on chromosome 5 and JARID (accession no. NC_000006.12:15281287-15281391) on chromosome 6] using BioEdit version 7.2; bioedit.software.informer.com/7.2/).
Whole-exome sequencing
Whole-exome sequencing data to identify SNPs in samples taken from patients with MDD, blood relatives and the healthy controls was obtained from a previous study (39).
Statistical analysis
Data were analyzed using IBM SPSS software (Version 16.0, SPSS Inc.). Categorical variables were compared using Pearson's χ2 test. Continuous variables, reported as the mean ± standard deviation of ≥2 independent experimental repeats were compared between two groups using independent Student's or unpaired t-test and between more >2 groups using a one-way analysis of variance followed by LSD test or Median or Mann-Whitney U test. P<0.05 was considered to indicate a statistically significant difference.
Results
Association between SLC6A3 (g.1394961C>T, rs40184), BDNF (g.27658368C>T, rs6265), and JARID2 (g.15281336G>A, rs9383046) SNPs with MDD
SNPs were detected in healthy controls, patients with MDD and their blood and non-blood relatives using HRM analysis (Tables II and III). The variant T allele of rs40184 in SLC6A3 was significantly more common in patients with MDD (18/40, 45%) than in healthy controls [29/231, 12.6%; odds ratio (OR), 5.699, 95% confidence interval (CI), 2.734-11.879. Similarly, the variant T allele of rs6265 in BDNF was significantly more common in patients with MDD (30/54, 55.56%) than in healthy controls (117/292, 40.06%; OR, 1.870, 95% CI, 1.041-3.358). However, the frequency of variant A allele of rs9383046 in JARID2 did not differ significantly between patients with MDD and healthy controls.
HHV-6 infection status was associated with SNP rs9383046 (G>A) in JARID2 but not with SNP rs40184 (C>T) in SLC6A3 or SNP rs6265 (C>T) in BDNF (Fig. 1; Table IV). The A allele of SNP rs9383046 in JARID2 was significantly more common in individuals with HHV-6 infection (80.0%, or 12 out of 15) than in those with the wild-type G allele (75/363, 20.7%; OR, 15.360, 95% CI, 4.226-55.823). This suggests that SNP rs9383046 (G>A) in JARID2 may be associated with HHV-6 infection.
High HHV-6 viral load associated with JARID2 SNP (g.15281336G>A)
Our previous study used qPCR to determine viral load in HHV-6-positive cases (39). HHV-6 loads were significantly higher in individuals with the G>A genotype (99,990.85±118,392.64) than in those with the G genotype (48,249.30±101,216.28 copies/ng DNA) for SNP rs9383046 in JARID2 (Fig. 2).
JARID2 SNP in MDD
Whole-exome sequencing was used to analyze the point mutation status of samples from four participants: Patient with MDD, their first-degree relative and a healthy female and male, all aged between 21 and 30 years. The sample was randomly selected from patients with MDD who had a first-degree (healthy) relative in the same age group. The whole-exome sequencing results are shown in Fig. 3, revealing 484 SNPs in JARID2 in MDD. Previous literature reviews have reported that the following genes are associated with JARID2 and its associated pathways: AE Binding Protein 2 (AEBP2), AT-rich interaction domain (ARID), AT-rich sequences (AT-rich), ataxin 1 (ATXN1), brain-derived neurotrophic factor (BDNF), cluster of differentiation 82 (CD82), cadherin 13 (CDH13), cyclin D1 (CCND1), D-Amino acid oxidase activator (DAOA), differentially methylated regions (DMRs), dystrobrevin-binding protein 1 (DTNBP1), enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2), histone 3 lysine 27 (H3K27), histone methyltransferases, homeobox A cluster (HOXA), IFN-γ), isoflavone reductase (IFR), IL-18), IL-6), Jumonji domain-containing protein-3 (JMJD3), lysine acetyltransferase 5 (KAT5), Lysine Demethylase 2B (KDM2B), Neuregulin 1 (NRG1), PHD finger protein 1 (PHF1), polycomb repressive complex 2 (PRC2), RB Binding Protein 4 (RBBP4), RB transcriptional corepressor like 2 (RBL2), regulator of G protein signaling 4 (RGS4), Sirtuin (SIRT5), SLC6A3, SMAD family member 2 (SMAD2), SOX, STAT3, transcription factor AP-2α (FAP2A), transforming growth factor beta (TGF-ß), Vascular endothelial growth factor (VEGF) and zinc finger E-box binding homeobox 1 (ZEB) (36,37,42-44). There was a total of two SNPs each in JARID2 (rs11757092 and rs9383050) and JMJD4 (rs2295994 and rs7419238) and three SNPs in BDNF (rs2242341, rs2353512, and rs10835210; Table V).
Discussion
The present study aimed to identify genetic factors associated with MDD. SLC6A3, BDNF and JARID2 were chosen because of their potential involvement in MDD pathways and previous research findings (28,30,31,34,36,38). To the best of our knowledge, the present study is the first to report on JARID2 and BDNF variations between patients with MDD and healthy individuals in Thailand. The present findings revealed an association between the SNP rs40184 in SLC6A3 and MDD, aligning with the results of other studies (34,45). This SNP alters SLC6A3 expression, which is associated with dopamine levels in the brain and depression severity (46,47). Previous studies have reported associations between dopamine transporter (DAT) levels and various psychiatric disorders including MDD and bipolar disorder (33,45,48). However, further investigation is necessary to elucidate these relationships. To comprehend the role of SLC6A3 (which encodes DAT) in psychiatric conditions, it must be explored within the broader context of phenotypical and allelic heterogeneity, as well as gene-environment interactions. Various SNPs in BDNF have been associated with MDD and suicide, including rs12273363, rs7124442, rs10767664, rs962369, rs908867 and especially rs6265 (Val66Met) (49-54). The rs6265 SNP decreases the activity-dependent release of BDNF (55). Furthermore, a previous study indicated an association between low BDNF levels and MDD pathogenesis (30).
To date, 500,000-1,000,000 SNPs have been identified in individuals with MDD compared with healthy controls. However, GWASs have not definitively demonstrated the influence of these SNPs on underlying mechanisms of mental disorders. These SNPs typically exhibit minimal phenotypic effects, with ORs ranging from 1.0 to 1.2 (9,56-59). Despite the subtle effects of individual SNPs, twin studies have revealed a significant genetic component in MDD (60,61). For example, one study found 37% heritability for recurrent unipolar MDD, with only minor environmental risk factors (62). More broadly, various studies have estimated the heritability of MDD to be between 30 and 50% (21,24). SNPs and other factors appear to be weakly associated with MDD. However, genetic variation varies between population, genetic background, and sequencing technology. The genetic mechanism for heritability remains unclear. Viruses or other factors may contribute to MDD pathophysiology (8,10,59). HHV-6 is often transmitted from mother to child and within families and can persist for life, this genetic polymorphism in HHV-6 may impact the heritability of MDD (21).
The present study identified a novel association between HHV-6 status and an SNP in JARID2. To the best of our knowledge, the present study is the first to explore the relationship between JARID2 and HHV-6, including both infection status and viral load, in the context of MDD. Variant A allele of SNP rs9383046 in JARID2 was more prevalent among individuals positive for HHV-6 infection and was positively associated with viral load. Previous research has linked pathogenic polymorphisms in JARID2 to a neurodevelopmental syndrome marked by developmental delays, cognitive impairment, hypotonia, autism and behavioral abnormalities (39,63). Additionally, rs326221458 SNP has been shown to affect JARID2 expression, which influences aggressive behavior in weaned pigs (64).
A total of six main hypotheses have been proposed to explain MDD pathogenesis: Hypothalamic/pituitary/adrenal axis dysfunction, monoamine imbalance, inflammation, genetic and epigenetic anomalies, structural and functional brain remodeling and social psychological factors. However, no single hypothesis can fully explain the pathology of MDD (8,10). The present study did not identify a direct association between MDD and JARID2. However, JARID2 may be directly associated with HHV-6 infection and indirectly with neurodevelopmental disorders, potentially increasing the risk of developing MDD. JARID2 polymorphisms may increase HHV-6 viral load, which is associated with inflammation and may contribute to MDD development (22,40). JARID2 serves as a transcriptional repressor protein and regulates histone methyltransferase complexes (65). Viral infections alter the expression of lysine demethylase 2B (KDM2B/NDY1), enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) and JARID2. This alteration actively degrades growth factor-independent 1 transcriptional repressor (GFI1), thereby promoting activation of the major immediate early promoter (MIEP) of human cytomegalovirus (HCMV). The combination of KDM2B/NDY1, EZH2 and JARID2 promotes histone H3 K27 trimethylation, which is associated with transcriptional suppression. EZH2, responsible for histone H3 K27 trimethylation, interacts with JARID2, a non-canonical jumonji domain protein that modulates EZH2 methyltransferase activity. HCMV infects cells by targeting GFI1 through various mechanisms. GFI1 mRNA and protein levels are rapidly downregulated upon viral exposure, likely via degradation (18,66-68). HHV-6 is similarly activated, with GFI1 rapidly degrading after HHV-6 infection, activating the MIEP.
Future research should further examine the roles of KDM2B/NDY1, EZH2, JARID2 and JMJD3 using the SNPs in JMJD1, JMJD4, JMJD7, JMJD8, and JARID2 identified in the present study (18,66-68). Moreover, a common feature of HHV is the association of latent genomes with polycomb group proteins, specifically PRC2.2, which includes JARID2 and is associated with H3K27me3 (43,69).
Several mechanisms have been proposed for MDD onset, including monoamine theory, neuroendocrine mechanisms, neurotrophic hypothesis and neuroinflammation (8,10). JARID2 may influence HHV-6 and tumor necrosis factor-alpha (TNF-α)-induced inflammation through various indirect pathways. Neuroinflammation and cytokines are connected to monoamine deficiency, suppressed neurogenesis, and dysregulation of the hypothalamic/pituitary/adrenal axis. Chronic stress and inflammation can cause peripheral inflammatory markers to cross the blood-brain barrier into the central nervous system, activating microglia (70-73). TNF-α promoter SNP (G>A) and elevated HHV-6 viral load, including factors like JARID2, lead to TNF-α overexpression and subsequent inflammation (39). Therefore, the current data suggest that HHV-6 may enhance viral load by promoting neuroinflammation through JARID2.
The present study had limitations. The primary limitation was small sample size. Another was the difference in mean ages between the MDD group and the healthy control group, which may cause bias in the results. The present study investigated SLC6A3 as a biomarker for MDD diagnosis, as well as JARID2 and HHV-6 as potential therapeutic targets. The role of JARID2 in MDD should be assessed by investigating its expression patterns.
In conclusion, the present study demonstrated significant association between SNPs in BDNF (rs6265) and SLC6A3 (rs28363170) and MDD. A higher HHV-6 viral load was found in participants carrying variant A allele of SNP rs9383046 (G>A) in JARID2. Whole-exome sequencing identified SNPs in JARID2 in patients with MDD, indicating interactions between HHV-6 infection, SNPs and MDD development.
Acknowledgements
The authors would like to thank the Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand, for use of the qPCR machine.
Funding
Funding: The present study was supported by Faculty of Pharmaceutical Sciences, Ubon Ratchathani University (grant no. Phar.UBU.0604.11-4/2567), The University of Phayao (grant no. FF64-RIB005) and Department of Medical Technology, Faculty of Allied Health Sciences, Burapha University (grant no. AHS04/2567).
Availability of data and materials
The data generated in the present study may be found in the Sequence Read Archive database under accession number PRJNA1146872 or at the following URL: ncbi.nlm.nih.gov/sra/?term=PRJNA1146872.
Authors' contributions
SBum, SBud and NP conceived the study and designed and performed experiments. SS performed experiments. SBum and NP wrote and reviewed the manuscript. SD and SP conceived the study and designed experiments. SBum, SBud and NP confirm the authenticity of all the raw data. All authors have read and approved the final manuscript.
Ethics approval and consent to participate
The present study was approved by the Committee on Human Research Ethics in Health Sciences and Science and Technology, University of Phayao, Thailand (UP-HEC 1.3/013/65). The participants provided written informed consent before the start of the study. All protocols involving human subjects adhered to the Declaration of Helsinki, Belmont Report, the International Conference on Harmonization in Good Clinical Practice and the Council for International Organizations of Medical Sciences.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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