Dataset Information

COMT polymorphism regulates the hippocampal subfield volumes in first-episode, drug-naive patients with major depressive disorder.

ABSTRACT: Purpose: Compared with healthy subjects (HS), patients with major depressive disorder (MDD) exhibit volume differences that affect the volume changes in several areas such as the limbic, cortical, subcortical, and white matter. Catechol-O-methyltransferase (COMT) is a methylation enzyme that catalyzes endogenous catecholamines. The Val158Met polymorphism of COMT has been reported to affect the dopamine (DA) levels, which plays an important role in psychiatric diseases. However, the relationships among both DA levels, COMT genotype, and brain morphology are complicated and controversial. In previous studies that investigated the hippocampal subfields, the greatest brain abnormalities in MDD patients were observed in Cornu Ammonis (CA)1 and the subiculum, followed by that in CA2-3. We have prospectively demonstrated the relationship between the single-nucleotide polymorphism of the Val158Met COMT gene (rs4680) and the hippocampal subfields in drug-naive MDD patients. Patients and methods: In this study, we compared 27 MDD patients and 42 HS who were divided into groups based on their COMT genotype. The effects of the diagnosis, genotype, and genotype-diagnosis interaction related to CA1 and the subiculum volumes, as well as the whole-brain cortical thickness, were evaluated by performing a FreeSurfer statistical analysis of high-resolution magnetic resonance imaging (MRI) findings. Results: The results revealed that there was a statistically significant interaction between the effects of diagnosis and genotype on the right subiculum (a component of the hippocampus). Conclusion: This Val158Met COMT polymorphism may influence the subiculum volume in drug-naive, first-episode MDD patients.

SUBMITTER: Otsuka Y

PROVIDER: S-EPMC6560253 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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COMT polymorphism regulates the hippocampal subfield volumes in first-episode, drug-naive patients with major depressive disorder.

Otsuka Yuka Y Kakeda Shingo S Sugimoto Koichiro K Katsuki Asuka A Nguyen Le Hoa LH Igata Ryohei R Watanabe Keita K Ueda Issei I Kishi Taro T Iwata Nakao N Korogi Yukunori Y Yoshimura Reiji R

Neuropsychiatric disease and treatment 20190606

<b>Purpose:</b> Compared with healthy subjects (HS), patients with major depressive disorder (MDD) exhibit volume differences that affect the volume changes in several areas such as the limbic, cortical, subcortical, and white matter. Catechol-O-methyltransferase (COMT) is a methylation enzyme that catalyzes endogenous catecholamines. The Val158Met polymorphism of COMT has been reported to affect the dopamine (DA) levels, which plays an important role in psychiatric diseases. However, the relati ...[more]

PMID: 31239688

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Project description:Complex networks inside the hippocampus could provide new insights into hippocampal abnormalities in various psychiatric disorders and dementia. However, evaluating intra-networks in the hippocampus using MRI is challenging. Here, we employed a high spatial resolution of conventional structural imaging and independent component analysis to investigate intra-networks structural covariance in the hippocampus. We extracted the intra-networks based on the intrinsic connectivity of each 0.9 mm isotropic voxel to every other voxel using a data-driven approach. With a total volume of 3 cc, the hippocampus contains 4115 voxels for a 0.9 mm isotropic voxel size or 375 voxels for a 2 mm isotropic voxel of high-resolution functional or diffusion tensor imaging. Therefore, the novel method presented in the current study could evaluate the hippocampal intra-networks in detail. Furthermore, we investigated the abnormality of the intra-networks in major depressive disorders. A total of 77 patients with first-episode drug-naïve major depressive disorder and 79 healthy subjects were recruited. The independent component analysis extracted seven intra-networks from hippocampal structural images, which were divided into four bilateral networks and three networks along the longitudinal axis. A significant difference was observed in the bilateral hippocampal tail network between patients with major depressive disorder and healthy subjects. In the logistic regression analysis, two bilateral networks were significant predictors of major depressive disorder, with an accuracy of 78.1%. In conclusion, we present a novel method for evaluating intra-networks in the hippocampus. One advantage of this method is that a detailed network can be estimated using conventional structural imaging. In addition, we found novel bilateral networks in the hippocampus that were disturbed in patients with major depressive disorders, and these bilateral networks could predict major depressive disorders.

Project description:Major depressive disorder (MDD) has been associated with disruptions in the topological organization of brain morphological networks in group-level data. Such disruptions have not yet been identified in single-patients, which is needed to show relations with symptom severity and to evaluate their potential as biomarkers for illness. To address this issue, we conducted a cross-sectional structural brain network study of 33 treatment-naive, first-episode MDD patients and 33 age-, gender-, and education-matched healthy controls (HCs). Weighted graph-theory based network models were used to characterize the topological organization of brain networks between the two groups. Compared with HCs, MDD patients exhibited lower normalized global efficiency and higher modularity in their whole-brain morphological networks, suggesting impaired integration and increased segregation of morphological brain networks in the patients. Locally, MDD patients exhibited lower efficiency in anatomic organization for transferring information predominantly in default-mode regions including the hippocampus, parahippocampal gyrus, precuneus and superior parietal lobule, and higher efficiency in the insula, calcarine and posterior cingulate cortex, and in the cerebellum. Morphological connectivity comparisons revealed two subnetworks that exhibited higher connectivity strength in MDD mainly involving neocortex-striatum-thalamus-cerebellum and thalamo-hippocampal circuitry. MDD-related alterations correlated with symptom severity and differentiated individuals with MDD from HCs with a sensitivity of 87.9% and specificity of 81.8%. Our findings indicate that single subject grey matter morphological networks are often disrupted in clinically relevant ways in treatment-naive, first episode MDD patients. Circuit-specific changes in brain anatomic network organization suggest alterations in the efficiency of information transfer within particular brain networks in MDD. Hum Brain Mapp 38:2482-2494, 2017. © 2017 Wiley Periodicals, Inc.

Dataset Information

COMT polymorphism regulates the hippocampal subfield volumes in first-episode, drug-naive patients with major depressive disorder.

Publications

COMT polymorphism regulates the hippocampal subfield volumes in first-episode, drug-naive patients with major depressive disorder.

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