Neuroimaging and epigenetic analysis reveal novel epigenetic loci in major depressive disorder.

BACKGROUND: Epigenetic modifications, such as DNA methylation, contribute to the pathophysiology of major depressive disorder (MDD). This study aimed to identify novel MDD-associated epigenetic loci using DNA methylation profiles and explore the correlations between epigenetic loci and cortical thickness changes in patients with MDD. METHODS: A total of 350 patients with MDD and 161 healthy controls (HCs) were included in the epigenome-wide association studies (EWAS). We analyzed methylation, copy number alteration (CNA), and gene network profiles in the MDD group. A total of 234 patients with MDD and 135 HCs were included in neuroimaging methylation analysis. Pearson's partial correlation analysis was used to estimate the correlation between cortical thickness of brain regions and DNA methylation levels of the loci. RESULTS: In total, 2018 differentially methylated probes (DMPs) and 351 differentially methylated regions (DMRs) were identified. DMP-related genes were enriched in two networks involved in the central nervous system. In neuroimaging analysis, patients with MDD showed cortical thinning in the prefrontal regions and cortical thickening in several occipital regions. Cortical thickness of the left ventrolateral prefrontal cortex (VLPFC, i.e. pars triangularis) was negatively correlated with eight DMPs associated with six genes (EML6, ZFP64, CLSTN3, KCNMA1, TAOK2, and NT5E). CONCLUSION: Through combining DNA methylation and neuroimaging analyses, negative correlations were identified between the cortical thickness of the left VLPFC and DNA methylation levels of eight DMPs. Our findings could improve our understanding of the pathophysiology of MDD.

Artificial Intelligence-Based Major Depressive Disorder (MDD) Diagnosis Using Raman Spectroscopic Features of Plasma Exosomes.

In vitro diagnosis using biomarkers for major depressive disorder (MDD) can offer considerable advantages in overcoming the lack of objective tests for depression and treating more patients. Plasma exosomes can be novel biomarkers for MDD based on their ability to pass through the blood-brain barrier and offer brain-related information. Here, we demonstrate a novel and precise MDD diagnosis using deep learning analysis and surface-enhanced Raman spectroscopy (SERS) of plasma exosomes. Our system is implemented based on 28,000 exosome SERS signals, providing sample-wise prediction results. Notably, this approach shows remarkable performance in predicting 70 test samples unused in the training step, with an area under the curve (AUC) of 0.939, a sensitivity of 91.4%, and a specificity of 88.6%. In addition, we confirm that the diagnostic scores were correlated with the degree of depression. These results show the utility of exosomes as novel biomarkers for MDD diagnosis and suggest a novel approach for prescreening techniques for psychiatric disorders.

Stage-Specific Brain Aging in First-Episode Schizophrenia and Treatment-Resistant Schizophrenia.

BACKGROUND: Brain age is a popular brain-based biomarker that offers a powerful strategy for using neuroscience in clinical practice. We investigated the brain-predicted age difference (PAD) in patients with schizophrenia (SCZ), first-episode schizophrenia spectrum disorders (FE-SSDs), and treatment-resistant schizophrenia (TRS) using structural magnetic resonance imaging data. The association between brain-PAD and clinical parameters was also assessed. METHODS: We developed brain age prediction models for the association between 77 average structural brain measures and age in a training sample of controls (HCs) using ridge regression, support vector regression, and relevance vector regression. The trained models in the controls were applied to the test samples of the controls and 3 patient groups to obtain brain-based age estimates. The correlations were tested between the brain PAD and clinical measures in the patient groups. RESULTS: Model performance indicated that, regardless of the type of regression metric, the best model was support vector regression and the worst model was relevance vector regression for the training HCs. Accelerated brain aging was identified in patients with SCZ, FE-SSDs, and TRS compared with the HCs. A significant difference in brain PAD was observed between FE-SSDs and TRS using the ridge regression algorithm. Symptom severity, the Social and Occupational Functioning Assessment Scale, chlorpromazine equivalents, and cognitive function were correlated with the brain PAD in the patient groups. CONCLUSIONS: These findings suggest additional progressive neuronal changes in the brain after SCZ onset. Therefore, pharmacological or psychosocial interventions targeting brain health should be developed and provided during the early course of SCZ.

Decreased cortical gyrification in major depressive disorder.

BACKGROUND: Early neurodevelopmental deviations, such as abnormal cortical folding patterns, are candidate biomarkers of major depressive disorder (MDD). We aimed to investigate the association of MDD with the local gyrification index (LGI) in each cortical region at the whole-brain level, and the association of the LGI with clinical characteristics of MDD. METHODS: We obtained T1-weighted images from 234 patients with MDD and 215 healthy controls (HCs). The LGI values from 66 cortical regions in the bilateral hemispheres were automatically calculated according to the Desikan-Killiany atlas. We compared the LGI values between the MDD and HC groups using analysis of covariance, including age, sex, and years of education as covariates. The association between the clinical characteristics and LGI values was investigated in the MDD group. RESULTS: Compared with HCs, patients with MDD showed significantly decreased LGI values in the cortical regions, including the bilateral ventrolateral and dorsolateral prefrontal cortices, medial and lateral orbitofrontal cortices, insula, right rostral anterior cingulate cortex, and several temporal and parietal regions, with the largest effect size in the left pars triangularis (Cohen's f2 = 0.361; p = 1.78 × 10-13). Regarding the association of clinical characteristics with LGIs within the MDD group, recurrence and longer illness duration were associated with increased gyrification in several occipital and temporal regions, which showed no significant difference in LGIs between the MDD and HC groups. CONCLUSIONS: These findings suggest that the LGI may be a relatively stable neuroimaging marker associated with MDD predisposition.

Correlation between immune-related genes and depression-like features in an animal model and in humans.

A growing body of evidence suggests that immune-related genes play pivotal roles in the pathophysiology of depression. In the present study, we investigated a plausible connection between gene expression, DNA methylation, and brain structural changes in the pathophysiology of depression using a combined approach of murine and human studies. We ranked the immobility behaviors of 30 outbred Crl:CD1 (ICR) mice in the forced swim test (FST) and harvested their prefrontal cortices for RNA sequencing. Of the 24,532 analyzed genes, 141 showed significant correlations with FST immobility time, as determined through linear regression analysis with p ≤ 0.01. The identified genes were mostly involved in immune responses, especially interferon signaling pathways. Moreover, induction of virus-like neuroinflammation in the brains of two separate mouse cohorts (n = 30 each) using intracerebroventricular polyinosinic:polycytidylic acid injection resulted in increased immobility during FST and similar expression of top immobility-correlated genes. In human blood samples, candidate gene (top 5%) expression profiling using DNA methylation analysis found the interferon-related USP18 (cg25484698, p = 7.04 × 10-11, Δß = 1.57 × 10-2; cg02518889, p = 2.92 × 10-3, Δß =  - 8.20 × 10-3) and IFI44 (cg07107453, p = 3.76 × 10-3, Δß =  - 4.94 × 10-3) genes to be differentially methylated between patients with major depressive disorder (n = 350) and healthy controls (n = 161). Furthermore, cortical thickness analyses using T1-weighted images revealed that the DNA methylation scores for USP18 were negatively correlated with the thicknesses of several cortical regions, including the prefrontal cortex. Our results reveal the important role of the interferon pathway in depression and suggest USP18 as a potential candidate target. The results of the correlation analysis between transcriptomic data and animal behavior carried out in this study provide insights that could enhance our understanding of depression in humans.

Decreased cortical gyrification in patients with bipolar disorder.

BACKGROUND: An aberrant neural connectivity has been known to be associated with bipolar disorder (BD). Local gyrification may reflect the early neural development of cortical connectivity and has been studied as a possible endophenotype of psychiatric disorders. This study aimed to investigate differences in the local gyrification index (LGI) in each cortical region between patients with BD and healthy controls (HCs). METHODS: LGI values, as measured using FreeSurfer software, were compared between 61 patients with BD and 183 HCs. The values were also compared between patients with BD type I and type II as a sub-group analysis. Furthermore, we evaluated whether there was a correlation between LGI values and illness duration or depressive symptom severity in patients with BD. RESULTS: Patients with BD showed significant hypogyria in various cortical regions, including the left inferior frontal gyrus (pars opercularis), precentral gyrus, postcentral gyrus, superior temporal cortex, insula, right entorhinal cortex, and both transverse temporal cortices, compared to HCs after the Bonferroni correction (p < 0.05/66, 0.000758). LGI was not associated with clinical factors such as illness duration, depressive symptom severity, and lithium treatment. No significant differences in cortical gyrification according to the BD subtype were found. CONCLUSIONS: BD appears to be characterized by a significant regionally localized hypogyria, in various cortical areas. This abnormality may be a structural and developmental endophenotype marking the risk for BD, and it might help to clarify the etiology of BD.

Association of DNA Methylation of the NLRP3 Gene with Changes in Cortical Thickness in Major Depressive Disorder.

The Nod-like receptor pyrin containing 3 (NLRP3) inflammasome has been reported to be a convergent point linking the peripheral immune response induced by psychological stress and neuroinflammatory processes in the brain. We aimed to identify differences in the methylation profiles of the NLRP3 gene between major depressive disorder (MDD) patients and healthy controls (HCs). We also investigated the correlation of the methylation score of loci in NLRP3 with cortical thickness in the MDD group using magnetic resonance imaging (MRI) data. A total of 220 patients with MDD and 82 HCs were included in the study, and genome-wide DNA methylation profiling of the NLRP3 gene was performed. Among the total sample, 88 patients with MDD and 74 HCs underwent T1-weighted structural MRI and were included in the neuroimaging-methylation analysis. We identified five significant differentially methylated positions (DMPs) in NLRP3. In the MDD group, the methylation scores of cg18793688 and cg09418290 showed significant positive or negative correlations with cortical thickness in the occipital, parietal, temporal, and frontal regions, which showed significant differences in cortical thickness between the MDD and HC groups. Our findings suggest that NLRP3 DNA methylation may predispose to depression-related brain structural changes by increasing NLRP3 inflammasome-related neuroinflammatory processes in MDD.

Development of Neuroimaging-Based Biomarkers in Major Depression.

A leading goal in the field of biological psychiatry for depression is to find a promising diagnostic biomarker and selection of specific psychiatric treatment mode that is most likely to benefit patients with depression. Recent neuroimaging studies have characterized the pathophysiology of major depressive disorder (MDD) with functional and structural alterations in the neural circuitry involved in emotion or reward processing. Particularly, structural and functional magnetic resonance imaging (MRI) studies have reported that the brain structures deeply involved in emotion regulation or reward processing including the amygdala, prefrontal cortex (PFC), anterior cingulate cortex (ACC), ventral striatum, and hippocampus are key regions that provide useful information about diagnosis and treatment outcome prediction in MDD. For example, it has been consistently reported that elevated activity of the ACC is associated with better antidepressant response in patients with MDD. This chapter will discuss a growing body of evidence that suggests that diagnosis or prediction of outcome for specific treatment can be assisted by a neuroimaging-based biomarker in MDD.

Identifying resting-state effective connectivity abnormalities in drug-naïve major depressive disorder diagnosis via graph convolutional networks.

Major depressive disorder (MDD) is a leading cause of disability; its symptoms interfere with social, occupational, interpersonal, and academic functioning. However, the diagnosis of MDD is still made by phenomenological approach. The advent of neuroimaging techniques allowed numerous studies to use resting-state functional magnetic resonance imaging (rs-fMRI) and estimate functional connectivity for brain-disease identification. Recently, attempts have been made to investigate effective connectivity (EC) that represents causal relations among regions of interest. In the meantime, to identify meaningful phenotypes for clinical diagnosis, graph-based approaches such as graph convolutional networks (GCNs) have been leveraged recently to explore complex pairwise similarities in imaging/nonimaging features among subjects. In this study, we validate the use of EC for MDD identification by estimating its measures via a group sparse representation along with a structured equation modeling approach in a whole-brain data-driven manner from rs-fMRI. To distinguish drug-naïve MDD patients from healthy controls, we utilize spectral GCNs based on a population graph to successfully integrate EC and nonimaging phenotypic information. Furthermore, we devise a novel sensitivity analysis method to investigate the discriminant connections for MDD identification in our trained GCNs. Our experimental results validated the effectiveness of our method in various scenarios, and we identified altered connectivities associated with the diagnosis of MDD.

Local shape volume alterations in subcortical structures of suicide attempters with major depressive disorder.

Suicide is among the most important global health concerns; accordingly, an increasing number of studies have shown the risks for suicide attempt(s) in terms of brain morphometric features and their clinical correlates. However, brain studies addressing suicidal vulnerability have been more focused on demonstrating impairments in cortical structures than in the subcortical structures. Using local shape volumes (LSV) analysis, we investigated subcortical structures with their clinical correlates in depressed patients who attempted suicide. Then we compared them with depressed patients without a suicidal history and age- and sex-matched healthy controls (HCs; i.e., 47 suicide attempters with depression, 47 non-suicide attempters with depression, and 109 HCs). Significant volumetric differences were found between suicidal and nonsuicidal depressed patients in several vertices: 16 in the left amygdala; 201 in the left hippocampus; 1,057 in the left putamen; and 140 in the left pallidum; 1 in the right pallidum; and 6 in the bilateral thalamus. These findings indicated subcortical alterations in LSV in components of the limbic-cortical-striatal-pallidal-thalamic circuits. Moreover, our results demonstrated that the basal ganglia was correlated with perceived stress levels, and the thalamus was correlated with suicidal ideation. We suggest that suicidality in major depressive disorder may involve subcortical volume alterations.

Serum FAM19A5 levels: A novel biomarker for neuroinflammation and neurodegeneration in major depressive disorder.

Chronic low-grade inflammation contributes to the pathophysiology of major depressive disorder (MDD). This study aimed to examine the association between serum levels of FAM19A5, a novel chemokine-like peptide that reflects reactive astrogliosis and inflammatory activation in the brain, and the neurodegenerative changes of MDD by investigating the correlation between serum FAM19A5 levels and cortical thickness changes in patients with MDD. We included 52 drug-naïve patients with MDD and 60 healthy controls (HCs). Serum FAM19A5 levels were determined in peripheral venous blood samples using a sandwich enzyme-linked immunosorbent assay. All participants underwent T1-weighted structural magnetic resonance imaging. Serum FAM19A5 levels were greater in patients with MDD than in HCs. In the MDD group, there were significant inverse correlations between serum FAM19A5 levels and cortical thickness in the prefrontal regions (i.e., the left inferior and right medial superior frontal gyri), left posterior cingulate gyrus, right cuneus, and both precunei, which showed significantly reduced thickness in patients with MDD compared to HCs. However, no correlation between serum FAM19A5 level and cortical thickness was observed in the HC group. The results of our study indicate that serum FAM19A5 levels may reflect reactive astrogliosis and related neuroinflammation in MDD. Our findings also suggest that serum FAM19A5 may be a potential biomarker for the neurodegenerative changes of MDD.

Predicting Carcinogenic Mechanisms of Non-Genotoxic Carcinogens via Combined Analysis of Global DNA Methylation and In Vitro Cell Transformation.

An in vitro cell transformation assay (CTA) is useful for the detection of non-genotoxic carcinogens (NGTXCs); however, it does not provide information on their modes of action. In this study, to pursue a mechanism-based approach in the risk assessment of NGTXCs, we aimed to develop an integrated strategy comprising an in vitro Bhas 42 CTA and global DNA methylation analysis. For this purpose, 10 NGTXCs, which were also predicted to be negative through Derek/Sarah structure-activity relationship analysis, were first tested for transforming activity in Bhas 42 cells. Methylation profiles using reduced representation bisulfite sequencing were generated for seven NGTXCs that were positive in CTAs. In general, the differentially methylated regions (DMRs) within promoter regions showed slightly more bias toward hypermethylation than the DMRs across the whole genome. We also identified 13 genes associated with overlapping DMRs within the promoter regions in four NGTXCs, of which seven were hypermethylated and six were hypomethylated. Using ingenuity pathway analysis, the genes with DMRs at the CpG sites were found to be enriched in cancer-related categories, including "cell-to-cell signaling and interaction" as well as "cell death and survival". Moreover, the networks related to "cell death and survival", which were considered to be associated with carcinogenesis, were identified in six NGTXCs. These results suggest that epigenetic changes supporting cell transformation processes occur during non-genotoxic carcinogenesis. Taken together, our combined system can become an attractive component for an integrated approach for the testing and assessment of NGTXCs.

Increased plasma complement factor H is associated with geriatric depression.

ABSTRACTBackground:Complement factor H (CFH) plays a key role in regulating the cascade of the alternative pathway of the complement system. Dysregulation of CFH may be involved in the pathophysiology of various inflammation-mediated diseases including neuropsychiatric illnesses. This study aimed to investigate this relationship by examining determining CFH levels in elderly individuals with and without depression. METHODS: A total of 152 elderly individuals (major depressive disorder (MDD) group, n = 76; comparison sample, n = 76) were selected from the Ansan Geriatric study. The plasma level of CFH was measured. MDD was diagnosed with the Mini-International Neuropsychiatric Interview as per DSM-IV criteria. The severity of depression was evaluated with the geriatric depression scale (GDS). Mean CFH levels were compared using the Mann-Whitney U test. After adjusting for possible confounding factors including age, sex, marital status, education, alcohol use, hemoglobin levels, and the Korean version of the Mini-Mental State Examination (MMSE-KC), a multiple regression analysis was conducted. The GDS score and plasma level of CFH were analyzed using Spearman's correlation. RESULTS: Plasma CFH level was significantly higher in individuals with MDD than in the comparison sample (289.51 ± 21.16 vs. 339.67 ± 66.23, p < 0.001). In a regression model adjusted for possible confounders, CFH was significantly associated with geriatric depression (p < 0.001). CFH levels were not significantly related to GDS scores in the depressed group. CONCLUSION: This study revealed an association between high plasma levels of CFH and geriatric depression, thereby suggesting the alternative pathway of the complement system contributing to the development of geriatric depression.

Specificity Assessment of CRISPR Genome Editing of Oncogenic EGFR Point Mutation with Single-Base Differences.

In CRISPR genome editing, CRISPR proteins form ribonucleoprotein complexes with guide RNAs to bind and cleave the target DNAs with complete sequence complementarity. CRISPR genome editing has a high potential for use in precision gene therapy for various diseases, including cancer and genetic disorders, which are caused by DNA mutations within the genome. However, several studies have shown that targeting the DNA via sequence complementarity is imperfect and subject to unintended genome editing of other genomic loci with similar sequences. These off-target problems pose critical safety issues in the therapeutic applications of CRISPR technology, with particular concerns in terms of the genome editing of pathogenic point mutations, where non-mutant alleles can become an off-target with only a one-base difference. In this study, we sought to assess a novel CRISPR genome editing technique that has been proposed to achieve a high specificity by positioning the mismatches within the protospacer adjacent motif (PAM) sequence. To this end, we compared the genome editing specificities of the PAM-based and conventional methods on an oncogenic single-base mutation in the endothelial growth factor receptor (EGFR). The results indicated that the PAM-based method provided a significantly increased genome editing specificity for pathogenic mutant alleles with single-base precision.

Local gyrification index in patients with major depressive disorder and its association with tryptophan hydroxylase-2 (TPH2) polymorphism.

The tryptophan hydroxylase-2 (TPH2) gene is considered a promising genetic candidate regarding its association with a predisposition to major depressive disorder (MDD). Local gyrification reflects the early neural development of cortical connectivity, and is regarded as a potential neural endophenotype in psychiatric disorders. They aimed to investigate the alterations in the cortical gyrification of the prefrontal cortex and anterior cingulate cortex and their association with the TPH2 rs4570625 polymorphism in patients with MDD. One hundred and thirteen patients with MDD and eighty-six healthy controls underwent T1-weighted structural magnetic resonance imaging and genotyping for TPH2 rs4570625. The local gyrification index of 22 cortical regions in the prefrontal cortex and anterior cingulate cortex was analyzed using the FreeSurfer. The patients with MDD showed significant hypergyria in the right rostral anterior cingulate cortex (P = 0.001), medial orbitofrontal cortex (P = 0.003), and frontal pole (P = 0.001). There was a significant genotype-by-diagnosis interaction for the local gyrification index in the right rostral anterior cingulate cortex (P = 0.003). Their study revealed significant hypergyria of the anterior cingulate cortex and prefrontal cortex and an interactive effect between the diagnosis of MDD and the genotype in the anterior cingulate cortex. This might be associated with the dysfunction of neural circuits mediating emotion processing, which could contribute to pathophysiology of MDD. Hum Brain Mapp 38:1299-1310, 2017. © 2016 Wiley Periodicals, Inc.

Computational meta-analysis of statistical parametric maps in major depression.

OBJECTIVE: Several neuroimaging meta-analyses have summarized structural brain changes in major depression using coordinate-based methods. These methods might be biased toward brain regions where significant differences were found in the original studies. In this study, a novel voxel-based technique is implemented that estimates and meta-analyses between-group differences in grey matter from individual MRI studies, which are then applied to the study of major depression. METHODS: A systematic review and meta-analysis of voxel-based morphometry studies were conducted comparing participants with major depression and healthy controls by using statistical parametric maps. Summary effect sizes were computed correcting for multiple comparisons at the voxel level. Publication bias and heterogeneity were also estimated and the excess of heterogeneity was investigated with metaregression analyses. RESULTS: Patients with major depression were characterized by diffuse bilateral grey matter loss in ventrolateral and ventromedial frontal systems extending into temporal gyri compared to healthy controls. Grey matter reduction was also detected in the right parahippocampal and fusiform gyri, hippocampus, and bilateral thalamus. Other areas included parietal lobes and cerebellum. There was no evidence of statistically significant publication bias or heterogeneity. CONCLUSIONS: The novel computational meta-analytic approach used in this study identified extensive grey matter loss in key brain regions implicated in emotion generation and regulation. Results are not biased toward the findings of the original studies because they include all available imaging data, irrespective of statistically significant regions, resulting in enhanced detection of additional areas of grey matter loss.

A functional neuroimaging study of the clinical reasoning of medical students.

As clinical reasoning is a fundamental competence of physicians for good clinical practices, medical academics have endeavored to teach reasoning skills to undergraduate students. However, our current understanding of student-level clinical reasoning is limited, mainly because of the lack of evaluation tools for this internal cognitive process. This functional magnetic resonance imaging (fMRI) study aimed to examine the clinical reasoning processes of medical students in response to problem-solving questions. We recruited 24 2nd-year medical students who had completed their preclinical curriculum. They answered 40 clinical vignette-based multiple-choice questions during fMRI scanning. We compared the imaging data for 20 problem-solving questions (reasoning task) and 20 recall questions (recall task). Compared to the recall task, the reasoning task resulted in significantly greater activation in nine brain regions, including the dorsolateral prefrontal cortex and inferior parietal cortex, which are known to be associated with executive function and deductive reasoning. During the recall task, significant activation was observed in the brain regions that are related to memory and emotions, including the amygdala and ventromedial prefrontal cortex. Our results support that medical students mainly solve clinical questions with deductive reasoning involving prior knowledge structures and executive functions. The problem-solving questions induced the students to utilize higher cognitive functions compared with the recall questions. Interestingly, the results suggested that the students experienced some emotional distress while they were solving the recall questions. In addition, these results suggest that fMRI is a promising research tool for investigating students' cognitive processes.

Regional cortical thinning of the orbitofrontal cortex in medication-naïve female patients with major depressive disorder is not associated with MAOA-uVNTR polymorphism.

BACKGROUND: Orbitofrontal cortex alterations have been suggested to underlie the impaired mood regulation in depression. MAOA-uVNTR (monoamine oxidase A-upstream variable number of tandem repeats) polymorphism has been reported to be associated with major depressive disorder by various studies. The influence of MAOA-uVNTR genotype on function and structure of the orbitofrontal cortex has previously been reported. In this study, we investigated the difference in orbitofrontal cortex thickness between medication-naïve female patients with major depressive disorder and healthy controls, and the influence of MAOA-uVNTR genotype on orbitofrontal cortex thickness in depression. METHODS: Thirty-one patients with major depressive disorder and 43 healthy controls were included. All participants were subjected to T1-weighted structural magnetic resonance imaging and genotyped for MAOA-uVNTR polymorphism. An automated procedure of FreeSurfer was used to analyze difference in orbitofrontal cortex thickness. RESULTS: Patients showed a significantly thinner left orbitofrontal cortex (F(1,71) = 7.941, p = 0.006) and right orbitofrontal cortex (F(1,71) = 17.447, p < 0.001). For the orbitofrontal cortex sub-region analysis, patients showed a significantly thinner left medial orbitofrontal cortex (F(1,71) = 8.117, p = 0.006), right medial orbitofrontal cortex (F(1,71) = 21.795, p < 0.001) and right lateral orbitofrontal cortex (F(1,71) = 9.932, p = 0.002) compared to healthy controls. No significant interaction of diagnosis and MAOA-uVNTR genotype on orbitofrontal cortex thickness was revealed. CONCLUSIONS: Our results suggest that structural alterations of the orbitofrontal cortex may be associated with the pathophysiology of major depressive disorder. Future studies with larger sample sizes are needed to detect a possible association between MAOA-uVNTR genotype and orbitofrontal cortex thickness in depression.

The association of proopiomelanocortin polymorphisms with the risk of major depressive disorder and the response to antidepressants via interactions with stressful life events.

Hyperactivity of the hypothalamic-pituitary-adrenal (HPA) axis is among the most consistent neuroendocrine abnormalities in major depressive disorder (MDD). The peptide adrenocorticotropin hormone (ACTH) mediates HPA axis function during stress and is encoded by the proopiomelanocortin (POMC) gene polycistronically. After screening 39 POMC polymorphisms, we evaluated the association of polymorphisms with susceptibility to MDD in 145 MDD patients and 193 normal subjects; in patients, we also evaluated the response to treatment with antidepressants. Additionally, we investigated the role of gene-environment interaction between POMC haplotypes and stressful life events (SLE) in the treatment response. Although genotypes and haplotypes were not significantly associated with the risk of MDD, non-remitters were more likely to carry haplotype 1 (ht1) and to have no ht2 than were remitters (corrected P = 0.010-0.035). Although observations were limited in patients without SLE, a significant haplotype-SLE interaction was observed (P = 0.020). Additionally, at 1, 2, and 8 weeks of treatment, the 21-item Hamilton Depression Rating scores of MDD subjects with POMC ht2 were significantly (P = 0.003-0.044) lower than those of patients with ht1 in subjects those did not experience SLE. MDD subjects possessing POMC ht2 achieved remission significantly (P = 0.013; survival analysis) faster than patients with ht1. This study suggests that POMC haplotypes, via an interaction with SLE, are associated with antidepressant treatment outcomes in MDD patients. Regarding SLE, haplotypes of the POMC gene could be useful markers for predicting the response to antidepressant treatment in MDD patients.

Interaction of 5-HTT and HTR1A gene polymorphisms in treatment responses to mirtazapine in patients with major depressive disorder.

We tested for the association of HTR1A and 5-HTT genetic polymorphisms with treatment response to mirtazapine and evaluated the interactive effect between the polymorphisms in 283 patients with major depressive disorder. Korean subjects with diagnosis of major depressive disorder using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Axis I disorders were recruited. Clinical symptoms were evaluated using the 17-item Hamilton Depression Rating (HAMD-17) Scale at baseline and after 1, 2, 4, 8, and 12 weeks of treatment with mirtazapine. The genetic association of 5-HTTLPR and HTR1A+272G>A with treatment response was analyzed. We found a significant association of the 12.12-repeat genotype of 5-HTT various number tandem repeat (VNTR) with a large percentage decline in HAMD-17 Scale score after 4, 8, and 12 weeks of treatment with mirtazapine. We also found that the frequency of the 12.12-repeat genotype was higher in responders than in nonresponders at week 8. The HTR1A+272GG genotype was significantly associated with a large percentage decline in HAMD-17 Scale score at 4, 8, and 12 weeks, although the genotypic frequencies were comparable between responders and nonresponders during the study period. Patients with the 12.12-repeat 5-HTT VNTR and GG of HTR1A+272G>A showed the highest HAMD-17 Scale percentage reduction during the study period and a better treatment response status after 4 weeks. These results suggest that the interaction between HTR1A+272G>A and 5-HTT VNTR is involved in the response to mirtazapine treatment and that a combination of these may be a useful marker for predicting treatment response to mirtazapine.