A joint study of whole exome sequencing and structural MRI analysis in major depressive disorder

2019 ◽  
Vol 50 (3) ◽  
pp. 384-395 ◽  
Author(s):  
Yamin Zhang ◽  
Mingli Li ◽  
Qiang Wang ◽  
Jacob Shujui Hsu ◽  
Wei Deng ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Rare Variants ◽  
Clinical Symptoms ◽  
Gray Matter Volume ◽  
Structural Mri ◽  
Genetic Component ◽  
Major Depressive ◽  
Genetic Components ◽  
Burden Test

AbstractBackgroundMajor depressive disorder (MDD) is a leading cause of disability worldwide and influenced by both environmental and genetic factors. Genetic studies of MDD have focused on common variants and have been constrained by the heterogeneity of clinical symptoms.MethodsWe sequenced the exome of 77 cases and 245 controls of Han Chinese ancestry and scanned their brain. Burden tests of rare variants were performed first to explore the association between genes/pathways and MDD. Secondly, parallel Independent Component Analysis was conducted to investigate genetic underpinnings of gray matter volume (GMV) changes of MDD.ResultsTwo genes (CSMD1, p = 5.32×10−6; CNTNAP5, p = 1.32×10−6) and one pathway (Neuroactive Ligand Receptor Interactive, p = 1.29×10−5) achieved significance in burden test. In addition, we identified one pair of imaging-genetic components of significant correlation (r = 0.38, p = 9.92×10−6). The imaging component reflected decreased GMV in cases and correlated with intelligence quotient (IQ). IQ mediated the effects of GMV on MDD. The genetic component enriched in two gene sets, namely Singling by G-protein coupled receptors [false discovery rate (FDR) q = 3.23×10−4) and Alzheimer Disease Up (FDR q = 6.12×10−4).ConclusionsBoth rare variants analysis and imaging–genetic analysis found evidence corresponding with the neuroinflammation and synaptic plasticity hypotheses of MDD. The mediation of IQ indicates that genetic component may act on MDD through GMV alteration and cognitive impairment.

scholarly journals Microstructural deficits in the thalamus of major depressive disorder

2021 ◽  
Author(s):  
Pengfei Xu ◽  
Gangqiang Hou ◽  
Yuxuan Zhang ◽  
Yingli Zhang ◽  
Hui Ai ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Large Scale ◽  
Gray Matter Volume ◽  
Structural Connectivity ◽  
Brain Network ◽  
Microstructural Properties ◽  
Major Depressive ◽  
T1 Relaxation ◽  
Structural Abnormalities

Macroscopic structural abnormalities in the thalamus and thalamic circuits have been shown to contribute to the neuropathology of major depressive disorder (MDD). However, cytoarchitectonic properties underlying these macroscopic abnormalities remain unknown. The purpose of this study was to identify systematic deficits of brain architecture in depression, from structural brain network organization to microstructural properties. A multi-modal neuroimaging approach including diffusion, anatomical and quantitative magnetic resonance imaging (MRI) was used to examine structural-related alternations in 56 MDD patients compared with 35 age- and sex-matched controls. Structural networks were constructed and analyzed using seed-based probabilistic tractography. Morphometric measurements, including cortical thickness and voxel-based morphometry (VBM), were evaluated across the whole brain. A conjunction analysis was then conducted to identify key regions showing common structural alternations across modalities. The microstructural properties, macromolecular tissue volume (MTV) and T1 relaxation times of identified key regions were then calculated. Results showed multiple alterations of structural connectivity within a set of subcortical areas and their connections to cortical regions in MDD patients. These subcortical regions included the putamen, thalamus and caudate, which are predominately involved in the limbic-cortical-striatal-pallidal-thalamic network (LCSPT). Structural connectivity was disrupted within and between large-scale networks, mainly including subcortical networks, default mode networks and salience/ventral attention networks. Consistently, these regions also exhibited widespread volume reductions in MDD patients, specifically the bilateral thalamus, left putamen and right caudate. Importantly, the microstructural properties, T1 relaxation time of left thalamus were increased and negatively correlated with its gray matter volume in MDD patients. The present work to date sheds light on the neuropathological disruptions of LCSPT circuit in MDD, providing the first multi-modal neuroimaging evidence for the macro-micro structural abnormalities of the thalamus in patients with MDD. These findings have implications in understanding the abnormal changes of brain structures across development of MDD.

scholarly journals Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Chenglong Yu ◽  
Mauricio Arcos-Burgos ◽  
Bernhard T. Baune ◽  
Volker Arolt ◽  
Udo Dannlowski ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Rare Variants ◽  
Low Frequency ◽  
Major Depressive

scholarly journals Association between cytomegalovirus infection, reduced gray matter volume, and resting-state functional hypoconnectivity in major depressive disorder: a replication and extension

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Haixia Zheng ◽  
Bart N. Ford ◽  
Rayus Kuplicki ◽  
Kaiping Burrows ◽  
Peter W. Hunt ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Gray Matter ◽  
Resting State ◽  
Gray Matter Volume ◽  
Brain Regions ◽  
Affective Processing ◽  
Resting State Functional Connectivity ◽  
Major Depressive ◽  
Matter Volume

AbstractHuman cytomegalovirus (HCMV) is a neurotropic herpes virus known to cause neuropathology in patients with impaired immunity. Previously, we reported a reduction in the gray matter volume (GMV) of several brain regions in two independent samples of participants who were seropositive for HCMV (HCMV+) compared to matched participants who were seronegative for HCMV (HCMV−). In addition to an independent replication of the GMV findings, this study aimed to examine whether HCMV+ was associated with differences in resting-state functional connectivity (rsfMRI-FC). After balancing on 11 clinical/demographic variables using inverse probability of treatment weighting (IPTW), GMV and rsfMRI-FC were obtained from 99 participants with major depressive disorder (MDD) who were classified into 42 HCMV+ and 57 HCMV− individuals. Relative to the HCMV− group, the HCMV+ group showed a significant reduction of GMV in nine cortical regions. Volume reduction in the right lateral orbitofrontal cortex (standardized beta coefficient (SBC) = −0.32, [95%CI, −0.62 to −0.02]) and the left pars orbitalis (SBC = −0.34, [95%CI, −0.63 to −0.05]) in the HCMV+ group was also observed in the previous study. Regardless of the parcellation method or analytical approach, relative to the HCMV− group, the HCMV+ group showed hypoconnectivity between the hubs of the sensorimotor network (bilateral postcentral gyrus) and the hubs of the salience network (bilateral insula) with effect sizes ranging from SBC = −0.57 to −0.99. These findings support the hypothesis that a positive HCMV serostatus is associated with altered connectivity of regions that are important for stress and affective processing and further supports a possible etiological role of HCMV in depression.

Effect of electroconvulsive therapy on gray matter volume in major depressive disorder

2015 ◽  
Vol 186 ◽  
pp. 186-191 ◽  
Author(s):  
Miho Ota ◽  
Takamasa Noda ◽  
Noriko Sato ◽  
Mitsutoshi Okazaki ◽  
Masatoshi Ishikawa ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Electroconvulsive Therapy ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Major Depressive ◽  
Matter Volume

scholarly journals Pharmacogenetics of Major Depressive Disorder (MDD): Progress in Two Serotonergic Targets

2018 ◽  
Vol 8 (2) ◽  
pp. 35-39
Author(s):  
Chidiebere Michael Iro ◽  
Rami Hamati
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Selective Serotonin Reuptake Inhibitors ◽  
Molecular Mechanisms ◽  
Conclusive Evidence ◽  
Nucleotide Polymorphisms ◽  
Social Psychological ◽  
Major Depressive ◽  
Genetic Components ◽  
The One

Major depressive disorder (MDD) is a multifaceted, debilitating condition affecting over 300 million people worldwide. It contributes significantly to social, psychological and economic burdens on individuals and on society at large. Currently, the most widely prescribed antidepressant medications are selective serotonin reuptake inhibitors (SSRIs), which act by blocking serotonin (5-HT) reuptake into presynaptic neurons, thereby increasing the extracellular 5-HT concentration in the brain. However, response to SSRIs and other psychotropic medications used to treat depression is highly variable, with only about one third of patients responding to treatment with an SSRI. This may reflect, at least in part, the genetic heterogeneity of depressed individuals. Studies investigating the genetic components of depression aim to improve treatment outcomes and possibly pave the way for personalized medicine in which the first medication prescribed is the one most likely to result in remission. This review presents the results of several studies on two 5-HT related genes: SLC6A4 and HTR2A, which encode for the serotonin transporter and the serotonin-2A receptor, respectively. Extensive studies have demonstrated that possessing two copies of the long allele (L/L) of the SLC6A4 gene can predict better responses to the SSRI Escitalopram. However, this finding was significant only in the Caucasian population. In addition to this, several single nucleotide polymorphisms in the HTR2A gene also predict clinical outcome, although molecular mechanisms remain unclear. Hence, the results indicate that while there is significant potential for predicting treatment response associated with these and other genetic targets, there is much work left to be done to establish conclusive evidence for and feasibility of pharmacogenetic testing.

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