Interaction between HTR2A rs3125 and negative life events in suicide attempts among patients with major depressive disorder: a cross-sectional study.

BACKGROUND: Both genetic and environmental factors play crucial roles in the development of major depressive disorder (MDD) and suicide attempts (SA). However, the interaction between both items remains unknown. This study aims to explore the interactions between the genetic variants of the serotonin 2 A receptor (HTR2A) and the nitric oxide synthase 1 (NOS1) and environmental factors in patients who experience MDD and SA. METHODS: A total of 334 patients with MDD and a history of SA (MDD-SA) were recruited alongside 518 patients with MDD with no history of SA (MDD-NSA), and 716 healthy controls (HC). The demographic data and clinical characteristics were collected. Sequenom mass spectrometry was used to detect eight tag-single nucleotide polymorphisms (tagSNPs) in HTR2A (rs1328683, rs17068986, and rs3125) and NOS1 (rs1123425, rs2682826, rs3741476, rs527590, and rs7959232). Generalized multifactor dimensionality reduction (GMDR) was used to analyze the gene-environment interactions. RESULTS: Four tagSNPs (rs17068986, rs3125, rs527590, and rs7959232) exhibited significant differences between the three groups. However, these differences were not significant between the MDD-SA and MDD-NSA groups after Bonferroni correction. A logistic regression analysis revealed that negative life events (OR = 1.495, 95%CI: 1.071-2.087, P = 0.018), self-guilt (OR = 2.263, 95%CI: 1.515-3.379, P < 0.001), and negative cognition (OR = 2.252, 95%CI: 1.264-4.013, P = 0.006) were all independently associated with SA in patients with MDD. Furthermore, GMDR analysis indicated a significant interaction between HTR2A rs3125 and negative life events. Negative life events in conjunction with the HTR2A rs3125 CG + GG genotype were associated with a higher SA risk in patients with MDD when compared to the absence of negative life events in conjunction with the CC genotype (OR = 2.547, 95% CI: 1.264-5.131, P = 0.009). CONCLUSION: Several risk factors and a potential interaction between HTR2A rs3125 and negative life events were identified in patients with SA and MDD. The observed interaction likely modulates the risk of MDD and SA, shedding light on the pathogenesis of SA in patients with MDD.

Identifying two distinct neuroanatomical subtypes of first-episode depression using heterogeneity through discriminative analysis.

BACKGROUND: Neurobiological heterogeneity in depression remains largely unknown, leading to inconsistent neuroimaging findings. METHODS: Here, we adopted a novel proposed machine learning method ground on gray matter volumes (GMVs) to investigate neuroanatomical subtypes of first-episode treatment-naïve depression. GMVs were obtained from high-resolution T1-weighted images of 195 patients with first-episode, treatment-naïve depression and 78 matched healthy controls (HCs). Then we explored distinct subtypes of depression by employing heterogeneity through discriminative analysis (HYDRA) with regional GMVs as features. RESULTS: Two prominently divergent subtypes of first-episode depression were identified, exhibiting opposite structural alterations compared with HCs but no different demographic features. Subtype 1 presented widespread increased GMVs mainly located in frontal, parietal, temporal cortex and partially located in limbic system. Subtype 2 presented widespread decreased GMVs mainly located in thalamus, cerebellum, limbic system and partially located in frontal, parietal, temporal cortex. Subtype 2 had smaller TIV and longer illness duration than Subtype 1. And TIV in Subtype 1 was positively correlated with age of onset while not in Subtype 2, probably implying the different potential neuropathological mechanisms. LIMITATIONS: Despite results obtained in this study were validated by employing another brain atlas, the conclusions were acquired from a single dataset. CONCLUSIONS: This study revealed two distinguishing neuroanatomical subtypes of first-episode depression, which provides new insights into underlying biological mechanisms of the heterogeneity in depression and might be helpful for accurate clinical diagnosis and future treatment.

Response rate and safety of antidepressants combined with electroconvulsive therapy in adolescent depression: Real-world clinical application.

BACKGROUND: METHODS: This study included 210 depression patients receiving antidepressants and ECT. The symptoms of depression were examined with the Hamilton Depression Scale (HAMD) and Clinical Global Impressions Scale (CGI) at baseline and the end of treatment. Response and safety were compared among adolescent and adult patients. RESULTS: For adolescents, the response rate (much improved or very much improved) was 80.9 %, and CGI-Severity (CGI-S), HAMD, and suicide factor scores were significantly changed as compared to baseline (P < 0.001), results of which were similar to the adult group. There were no significant differences in HAMD, CGI scores between adolescent and adult depression before or after treatment (P > 0.05). Notably, adolescents expressed stronger suicidal intent than adults, and ECT observably relieved it. Side effects (memory problems, headache, nausea/vomiting, muscle soreness) in adolescents were not statistically different from those in adults (P > 0.05). LIMITATIONS: As data were derived from a single center, the generalizability of results may be limited, and the potential factors affecting the efficacy of ECT were not further explored. CONCLUSION: Antidepressants combined with ECT are associated with high response rate and safety for treating depression, regardless of age. A stronger expression of suicide ideation was observed in depressed adolescents, and side effects of ECT were similar to the adults.

Altered structural covariance network of nucleus accumbens is modulated by illness duration and severity of symptom in depression.

The differential structural covariance of nucleus accumbens (NAcc), playing a vital role in etiology and treatment, remains unclear in depression. We aimed to investigate whether structural covariance of NAcc was altered and how it was modulated by illness duration and severity of symptom measured with Hamilton Depression scale (HAMD). T1-weighted anatomical images of never-treated first-episode patients with depression (n = 195) and matched healthy controls (HCs, n = 78) were acquired. Gray matter volumes were calculated using voxel-based morphometry analysis for each subject. Then, we explored abnormal structural covariance of NAcc and how the abnormality was modulated by illness duration and severity of symptom. Patients with depression exhibited altered structural covariance of NAcc connected to key brain regions in reward system including the medial orbitofrontal cortex, amygdala, insula, parahippocampa gyrus, precuneus, thalamus, hippocampus and cerebellum. In addition, the structural covariance of the NAcc was distinctly modulated by illness duration and the severity of symptom in patients with depression. What is more, the structural covariance of the NAcc connected to hippocampus was modulated by these two factors at the same time. These results elucidate altered structural covariance of the NAcc and its distinct modulation of illness duration and severity of symptom.

Convergent molecular and structural neuroimaging signatures of first-episode depression.

BACKGROUND: Convergent studies have demonstrated morphological abnormalities in various brain regions in depression patients. However, the molecular underpinnings of the structural impairments remain largely unknown, despite a pressing need for treatment targets and mechanisms. Here, we investigated the gray matter volume (GMV) alteration in patients with depression and its underlying molecular architecture. METHODS: We recruited 195 first-episode, treatment-naïve depression patients and 78 gender-, age-, and education level-matched healthy controls (HCs) who underwent high-resolution T1-weighted magnetic resonance scans. Voxel-based morphometry (VBM) was adopted to calculate the GMV differences between two groups. Then we analyzed the spatial correlation between depression-induced alteration in GMV and density maps of 10 receptors/transporters deriving from prior molecular imaging in healthy people. RESULTS: Compared to HCs, the depression group had significantly increased GMV in the left ventral portions of the ventral medial prefrontal cortex, parahippocampal gyrus, amygdala, the right superior parietal lobule and precuneus while decreased GMV in the bilateral hippocampus extending to the thalamus and cerebellum. The GMV alteration introduced by depression was spatially correlated with serotonin receptors (5-HT1a, 5-HT1b, and 5-HT2a), dopamine receptors (D1 and D2) and GABAergic receptor (GABAa) densities. LIMITATIONS: The conclusions drawn in this study were obtained from a single dataset. CONCLUSIONS: This study reveals abnormal GMV alteration and provides a series of neurotransmitters receptors possibly related to GMV alteration in depression, which facilitates an integrative understanding of the molecular mechanism underlying the structural abnormalities in depression and may provide clues to new treatment strategies.

Resolving heterogeneity in depression using individualized structural covariance network analysis.

BACKGROUND: Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis. METHODS: T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges. RESULTS: As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms. CONCLUSIONS: In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.

Progressive brain structural abnormality in depression assessed with MR imaging by using causal network analysis.

BACKGROUND: As a neuroprogressive illness, depression is accompanied by brain structural abnormality that extends to many brain regions. However, the progressive structural alteration pattern remains unknown. METHODS: To elaborate the progressive structural alteration of depression according to illness duration, we recruited 195 never-treated first-episode patients with depression and 130 healthy controls (HCs) undergoing T1-weighted MRI scans. Voxel-based morphometry method was adopted to measure gray matter volume (GMV) for each participant. Patients were first divided into three stages according to the length of illness duration, then we explored stage-specific GMV alterations and the causal effect relationship between them using causal structural covariance network (CaSCN) analysis. RESULTS: Overall, patients with depression presented stage-specific GMV alterations compared with HCs. Regions including the hippocampus, the thalamus and the ventral medial prefrontal cortex (vmPFC) presented GMV alteration at onset of illness. Then as the illness advanced, others regions began to present GMV alterations. These results suggested that GMV alteration originated from the hippocampus, the thalamus and vmPFC then expanded to other brain regions. The results of CaSCN analysis revealed that the hippocampus and the vmPFC corporately exerted causal effect on regions such as nucleus accumbens, the precuneus and the cerebellum. In addition, GMV alteration in the hippocampus was also potentially causally related to that in the dorsolateral frontal gyrus. CONCLUSIONS: Consistent with the neuroprogressive hypothesis, our results reveal progressive morphological alteration originating from the vmPFC and the hippocampus and further elucidate possible details about disease progression of depression.

Integrative Functional, Molecular, and Transcriptomic Analyses of Altered Intrinsic Timescale Gradient in Depression.

The pathophysiology and pharmacology of depression are hypothesized to be related to the imbalance of excitation-inhibition that gives rise to hierarchical dynamics (or intrinsic timescale gradient), further supporting a hierarchy of cortical functions. On this assumption, intrinsic timescale gradient is theoretically altered in depression. However, it remains unknown. We investigated altered intrinsic timescale gradient recently developed to measure hierarchical brain dynamics gradient and its underlying molecular architecture and brain-wide gene expression in depression. We first presented replicable intrinsic timescale gradient in two independent Chinese Han datasets and then investigated altered intrinsic timescale gradient and its possible underlying molecular and transcriptional bases in patients with depression. As a result, patients with depression showed stage-specifically shorter timescales compared with healthy controls according to illness duration. The shorter timescales were spatially correlated with monoamine receptor/transporter densities, suggesting the underlying molecular basis of timescale aberrance and providing clues to treatment. In addition, we identified that timescale aberrance-related genes ontologically enriched for synapse-related and neurotransmitter (receptor) terms, elaborating the underlying transcriptional basis of timescale aberrance. These findings revealed atypical timescale gradient in depression and built a link between neuroimaging, transcriptome, and neurotransmitter information, facilitating an integrative understanding of depression.

Enhanced default mode network functional connectivity links with electroconvulsive therapy response in major depressive disorder.

BACKGROUND: Electroconvulsive therapy (ECT) is an effective neuromodulatory treatment for major depressive disorder (MDD), especially for cases resistant to antidepressant drugs. While the precise mechanisms underlying ECT efficacy are still unclear, it is speculated that ECT modulates brain connectivity. The current study aimed to investigate the longitudinal effects of ECT on resting-state functional connectivity (FC) in MDD patients and test if baseline FC can be used to predict therapeutic response. METHOD: Resting-state functional magnetic resonance imaging data were collected at baseline and following ECT from 33 MDD patients. Whole-brain multi-voxel pattern analysis (MVPA) and region of interest-wise FC analysis were employed to fully investigate ECT effects on brain connectivity. Linear support vector regression was further utilized to predict the improvement in depressive symptoms based on baseline connectivity. RESULTS: MVPA revealed a significant ECT effect on FC in the default mode network (DMN), central executive network (CEN), sensorimotor network (SMN), and cerebellar posterior lobe. The FCs within the DMN and between DMN and CEN were enhanced in patients after ECT, and the changed FC between the medial prefrontal cortex and ventrolateral prefrontal cortex was negatively correlated with depressive symptom improvement. Moreover, baseline FC within the DMN and between the DMN and CEN could effectively predict the improvement of depressive symptoms. CONCLUSIONS: The findings suggest that the FCs within the DMN and between DMN and CEN may be critical therapeutic targets for effective antidepressant treatment as well as neuromarkers for predicting treatment response.

Correlation between Aß1-42, Dnmt3a2, urinary AD7c-NTP and cognitive dysfunction in first-episode and recurrent MDD: A case-control study.

Background and Aim: Major depressive disorder (MDD) is one of the most prevalent mental illnesses worldwide and involves cognitive dysfunction that may negatively impact clinical and social outcomes. Previous studies have suggested that beta-amyloid peptide (Aß1-42), DNA methyltransferase (Dnmt3a2), and urinary Alzheimer-associated neuronal thread protein (AD7c-NTP) are associated with cognitive impairment. However, there are no relevant studies in MDD. The aim of this study was to assess the correlation between serum Aß1-42, Dnmt3a2, and urinary AD7c-NTP and cognitive dysfunction in MDD. Materials and Methods: A total of 59 eligible patients were included in the study, including 29 patients with first-episode MDD (FEDs) and 30 patients with recurrent MDD (RMDDs), and 30 matched healthy controls (HCs) were selected. Participants' cognitive functioning was evaluated using the MATRICS consensus cognitive battery (MCCB). The enzyme-linked immunosorbent assay (ELISA) method was used to measure the concentrations of the three proteins. Statistical analysis was completed using Statistical Package for the Social Sciences (SPSS) 20.0. The statistical significance was set as P < 0.05. Results: Serum Dnmt3a2 and urinary AD7c-NTP showed significant differences among the three groups (both P < 0.001), but there were no significant differences in Aß1-42 levels. Upon examining the results of cognitive testing, we found that serum Aß1-42 was negatively associated with working memory scores in RMDDs (P = 0.020), but Dnmt3a2 was positively associated with working memory and verbal learning scores in the same cohort (P = 0.012 and P = 0.037, respectively). In contrast, urinary AD7c-NTP was negatively correlated with verbal learning scores in FEDs (P = 0.013). Conclusions: Serum Dnmt3a2 and Aß1-42 levels may be associated with cognitive impairment in RMDDs and may act as potential biomarkers of cognitive impairment. Although urinary AD7c-NTP was closely related to cognitive dysfunction in FEDs, this relationship did not hold in RMDDs.

The stage-specifically accelerated brain aging in never-treated first-episode patients with depression.

Depression associated with structural brain abnormalities is hypothesized to be related with accelerated brain aging. However, there is far from a unified conclusion because of clinical variations such as medication status, cumulative illness burden. To explore whether brain age is accelerated in never-treated first-episode patients with depression and its association with clinical characteristics, we constructed a prediction model where gray matter volumes measured by voxel-based morphometry derived from T1-weighted MRI scans were treated as features. The prediction model was first validated using healthy controls (HCs) in two Chinese Han datasets (Dataset 1, N = 130 for HCs and N = 195 for patients with depression; Dataset 2, N = 270 for HCs) separately or jointly, then the trained prediction model using HCs (N = 400) was applied to never-treated first-episode patients with depression (N = 195). The brain-predicted age difference (brain-PAD) scores defined as the difference between predicted brain age and chronological age, were calculated for all participants and compared between patients with age-, gender-, educational level-matched HCs in Dataset 1. Overall, patients presented higher brain-PAD scores suggesting patients with depression having an "older" brain than expected. More specially, this difference occurred at illness onset (illness duration <3 months) and following 2 years then disappeared as the illness further advanced (>2 years) in patients. This phenomenon was verified by another data-driven method and significant correlation between brain-PAD scores and illness duration in patients. Our results reveal that accelerated brain aging occurs at illness onset and suggest it is a stage-dependent phenomenon in depression.

Efficacy of simplified-cognitive behavioral therapy for insomnia(S-CBTI) among female COVID-19 patients with insomnia symptom in Wuhan mobile cabin hospital.

BACKGROUND: The outbreak of Coronavirus Disease-2019 (COVID-19) caused great psychological distress often with comorbid insomnia. Insomnia is common in patients with COVID-19 admitted to mobile cabin hospitals. Insomnia may lead to immune dysfunction, a condition not conducive to recovery from COVID-19. The use of sedative-hypnotic drugs is limited by their inhibitory effect on the respiratory system. A paucity of research is available regarding psychotherapy interventions to improve insomnia symptoms among  patients with COVID-19. In the general population, sleep problems are more common in women than in men; insomnia in women patients requires special attention. The aim of this study was to develop simplified-cognitive behavioral therapy for insomnia (S-CBTI) for patients with COVID-19 and comorbid insomnia symptoms and to verify its effectiveness through a self-control trial. A second aim was to compare the effectiveness of S-CBTI between acute and chronic insomnia among women with COVID-19 and comorbid insomnia symptoms in Wuhan Jianghan Cabin Hospital. METHODS: S-CBTI consisted of education on COVID-19 and sleep hygiene, stimulus control, sleep restriction, and self-suggestion relaxation training over a period of two consecutive weeks. Of 67 women, 66 completed psychological intervention and baseline and post-intervention assessments. There were 31 women with acute insomnia and 35 with chronic insomnia. The Insomnia Severity Index (ISI) score and self-compiled sleep data were assessed at baseline and post-intervention, and subjective sleep evaluations were assessed at days 4, 7, 12, and 14. RESULTS: The ISI score, sleep latency, night sleep time, and sleep efficiency were statistically significantlly improved from baseline to post-intervention by paired T-test. After the intervention, the mean ISI score of the acute insomnia group was lower than that of the chronic insomnia group. The reduction of the ISI score and the improvement of sleep time from baseline to post-intervention in the acute insomnia group were greater than those in the chronic insomnia group. Utilization of sedative-hypnotic drugs in the acute insomnia group was less than that in the chronic insomnia group, and the difference was statistically significant. CONCLUSIONS: S-CBTI can improve the insomnia symptoms of women with COVID-19 in mobile cabin hospitals, especially for stress-related acute insomnia.

The T-182C Polymorphism Enhances Promoter Activity of the Norepinephrine Transporter Gene, but may not be Associated with Antidepressant Response.

Background: Previous evidence has suggested that norepinephrine transporter (NET) gene (solute carrier family 6, member 2 [SLC6A2]) polymorphisms are involved in antidepressant response. Specifically, the polymorphism T-182C (rs2242446) located in the promoter region of SLC6A2 has been found to be associated with antidepressant response in multiple ethnic backgrounds. However, the results are inconsistent. Moreover, few studies have focused on how this T-182C polymorphism might regulate SLC6A2 promoter function. Methods: In this study, luciferase reporter assays were performed to examine the functional significance of the T-182C polymorphism. In addition, we performed a meta-analysis to explore whether this genetic variant is significantly involved in the antidepressant response. Results: We found that the -182(T) allele significantly increased promoter function compared to the C allele based on luciferase reporter assays. For the meta-analysis, six articles were identified that explored the relationship between the NET T-182C polymorphisms and antidepressant response. This study revealed no significant association between these polymorphisms and response to antidepressants (OR = 1.23, 95% CI = 0.77 - 1.97, p = 0.38 for T-182C). Conclusions: The T-182C polymorphism enhances promoter activity, but may not be associated with antidepressant response.

Predicting SSRI-Resistance: Clinical Features and tagSNPs Prediction Models Based on Support Vector Machine.

BACKGROUND: A large proportion of major depressive patients will experience recurring episodes. Many patients still do not response to available antidepressants. In order to meaningfully predict who will not respond to which antidepressant, it may be necessary to combine multiple biomarkers and clinical variables. METHODS: Eight hundred fifty-seven patients with recurrent major depressive disorder who were followed up 3-10 years involved 32 variables including socio-demographic, clinical features, and SSRIs treatment features when they received the first treatment. Also, 34 tagSNPs related to 5-HT signaling pathway, were detected by using mass spectrometry analysis. The training samples which had 12 clinical variables and four tagSNPs with statistical differences were learned repeatedly to establish prediction models based on support vector machine (SVM). RESULTS: Twelve clinical features (psychomotor retardation, psychotic symptoms, suicidality, weight loss, SSRIs average dose, first-course treatment response, sleep disturbance, residual symptoms, personality, onset age, frequency of episode, and duration) were found significantly difference (P< 0.05) between 302 SSRI-resistance and 304 SSRI non-resistance group. Ten SSRI-resistance predicting models were finally selected by using support vector machine, and our study found that mutations in tagSNPs increased the accuracy of these models to a certain degree. CONCLUSION: Using a data-driven machine learning method, we found 10 predictive models by mining existing clinical data, which might enable prospective identification of patients who are likely to resistance to SSRIs antidepressant.

Development of the psychosomatic symptom scale (PSSS) and assessment of its reliability and validity in general hospital patients in China.

OBJECTIVES: To develop and verify the Psychosomatic Symptom Scale (PSSS) among psychosomatic patients and the cut-off value of PSSS in distinguishing psychosomatic patients from health controls. METHODS: The PSSS was drafted by an expert workgroup. 996 patients and 366 controls from 14 general hospitals in China were recruited to complete PSSS, Patient Health Questionnaire-15 (PHQ-15) and Symptom Checklist-90 (SCL-90). Student's t-test, Kruskal-Wallis test, Cronbach's α, Spearman's correlation, and confirmatory factor analysis (CFA) were used to verify the PSSS. Receiver operating characteristic (ROC) analyses were used to determine the cut-off value. RESULTS: Cronbach α of PSSS was 0.907. The PSSS was significantly correlated with SCL-90 somatization subscale (r = 0.682, P < 0.001) and PHQ-15 (r = 0.724, P < 0.001). CFA supported the theoretical two-factor structure of the PSSS, with comparative fit index (CFI) = 0.979, Tucker-Lewis index (TLI) = 0.977, root mean square error of approximation (RMSEA) = 0.039 (90% CI: 0.035-0.042), and standardized root mean residual (SRMR) = 0.054. As the sum score of PSSS was significantly higher in female, cut-off values were determined as 11 in females and 10 in males respectively. CONCLUSIONS: The PSSS is a reliable and valid instrument for measuring psychosomatic symptoms.

A meta-analysis of selective serotonin reuptake inhibitors (SSRIs) use during prenatal depression and risk of low birth weight and small for gestational age.

BACKGROUND: Selective Serotonin Reuptake Inhibitors (SSRIs) act as the first-line antidepressants prescribed for the treatment of prenatal depression. Evidence from previous studies has suggested that the use of SSRIs treatment for prenatal depression has adversely affected fetal growth. However, these results are inconsistent and inconclusive. METHODS: In this study, we examined whether SSRIs use during pregnancy was related to low birth weight (LBW) and small for gestational age (SGA) using a meta-analysis approach. Relevant studies were retrieved by database searching and selected according to established inclusion criteria. RESULTS: Fifteen articles involved 1,977,446 subjects were identified that tested the relationship between the SSRIs use, LBW and SGA outcomes. Statistical analyses revealed a significant association between SSRIs use and suboptimal fetal growth (RR = 1.45, 95% CI = 1.18 - 1.76, Z = 3.62, p = 0.00 for SGA; RR = 1.38, 95% CI = 1.13 - 1.69, Z = 3.14, p = 0.00 for LBW). LIMITATIONS: These results must be treated with caution as we did not take the confounding factors into account (e.g., trimester SSRIs taken, specific SSRIs prescribed and maternal lifestyle during pregnancy) to elucidate their specific roles in the relationship between SSRIs use during pregnancy and fetal growth. CONCLUSION: Our findings suggested that SSRIs use for prenatal depression is associated with suboptimal fetal growth.

Association between T-182C, G1287A polymorphism in NET gene and suicidality in major depressive disorder in Chinese patients.

Objective: Previous studies have implicated norepinephrine transporter gene (NET) polymorphisms in the etiology of major depressive disorder (MDD). A functional NET T-182C polymorphism (rs2242446) in the promoter region and a synonymous polymorphisms G1287A in the exon 9 (rs5569) were associated with MDD in different populations. However, few studies have focused on the relationship between these polymorphisms and MDD patients with suicidality. The objective of the present study was to examine whether the two polymorphisms are associated with MDD patients with suicidality in the Han Chinese population. Methods: Two hundred and sixty-three suicidal depressed patients and 241 non-suicidal depressed patients who met DSM-IV criteria for MDD were recruited from our hospital. Three hundred and three unrelated, age- and sex-matched healthy control subjects participated in this case-control study. Suicidality was assessed using Mini International Neuropsychiatric Interview (MINI) and the Hamilton rating scale for depression (HAMD). Genotypes of T-182C polymorphism (rs2242446) and G1287A (rs5569) were screened by polymerase chain reaction. Results: No statistical significant differences between patients and controls were found for any of the analysed polymorphisms, either in the genotype or allele distribution. Conclusions: Our results suggest that the investigated polymorphisms are not major susceptibility factors in the etiology of MDD with suicidality. However, the results must be verified in larger samples and different ethnicities.

Association study between 5-HT2A and NET gene polymorphisms and recurrent major depression disorder in Chinese Han population.

A functional NET T-182C polymorphism (rs2242446) in the promoter region, a synonymous polymorphisms G1287A in the exon 9(rs5569) and a functional serotonin 2A (5-HT2A) receptor (rs6311) genes in the promoter region were associated with MDD in different populations. However, few studies have focused on the relationship between these three polymorphisms and recurrent MDD patients in Chinese Han population. Three hundred MDD patients (112 males, 188 females) and three hundre unrelated healthy controls were enrolled in the study. POST-PCR ligase detection reaction genotype assay method was used for the genotypic analyses. There existed significant differences both in the frequencies of alleles and genotypes between patients and controls for the 5-HT2A receptor gene polymorphism (χ2=9.267, p=0.01 for genotype; χ2=7.615,p=0.006 for allele). No difference in genotype and allele distribution of G1287A, T182C were found in MDD patients and controls. Our results suggest that the rs6311 polymorphism seems to be the susceptibility factor in etiology of recurrent MDD. In conclusion, 5-HT2A receptor gene variants may be involved in the etiology of MDD, although the results must be verified in larger samples and different ethnicities.