Transcriptional substrates of brain structural and functional impairments in drug-naive first-episode patients with major depressive disorder.

[1]  Jiajia Zhu,et al.  Transcriptional substrates underlying functional connectivity profiles of subregions within the human sensorimotor cortex , 2022, Human brain mapping.

[2]  Jiajia Zhu,et al.  Genetic mechanisms underlying brain functional homotopy: a combined transcriptome and resting-state functional MRI study. , 2022, Cerebral cortex.

[3]  Ping Jiang,et al.  Molecular basis underlying functional connectivity of fusiform gyrus subregions: A transcriptome-neuroimaging spatial correlation study , 2022, Cortex.

[4]  OUP accepted manuscript , 2022, Cerebral Cortex.

[5]  OUP accepted manuscript , 2022, Cerebral Cortex.

[6]  G. Northoff,et al.  From Molecular to Behavior: Higher Order Occipital Cortex in Major Depressive Disorder. , 2021, Cerebral cortex.

[7]  Jiajia Zhu,et al.  Genetic Architecture Underlying Differential Resting-state Functional Connectivity of Subregions Within the Human Visual Cortex. , 2021, Cerebral cortex.

[8]  M. Sabuncu,et al.  Heritability and interindividual variability of regional structure-function coupling , 2021, Nature Communications.

[9]  M. Banasr,et al.  Macro- and Microscale Stress–Associated Alterations in Brain Structure: Translational Link With Depression , 2021, Biological Psychiatry.

[10]  N. Mechawar,et al.  Implication of cerebral astrocytes in major depression: A review of fine neuroanatomical evidence in humans , 2021, Glia.

[11]  J. Qiu,et al.  Cortical structural differences in major depressive disorder correlate with cell type-specific transcriptional signatures , 2021, Nature Communications.

[12]  E. Isometsä,et al.  Reduced visual contrast suppression during major depressive episodes , 2021, Journal of psychiatry & neuroscience : JPN.

[13]  Feng Liu,et al.  Genes associated with gray matter volume alterations in schizophrenia , 2020, NeuroImage.

[14]  Chunshui Yu,et al.  Local dynamic spontaneous brain activity changes in first-episode, treatment-naïve patients with major depressive disorder and their associated gene expression profiles , 2020, Psychological Medicine.

[15]  Ying Wang,et al.  Common and distinct patterns of intrinsic brain activity alterations in major depression and bipolar disorder: voxel-based meta-analysis , 2020, Translational Psychiatry.

[16]  Ying Yang,et al.  Cerebellar-cerebral dynamic functional connectivity alterations in major depressive disorder. , 2020, Journal of affective disorders.

[17]  A. Holmes,et al.  Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder , 2020, Proceedings of the National Academy of Sciences.

[18]  Chunshui Yu,et al.  Brain mRNA Expression Associated with Cortical Volume Alterations in Autism Spectrum Disorder. , 2020, Cell reports.

[19]  D. Geschwind,et al.  Transcriptomic and cellular decoding of regional brain vulnerability to neurogenetic disorders , 2020, Nature Communications.

[20]  S. Russo,et al.  Depression and Social Defeat Stress Are Associated with Inhibitory Synaptic Changes in the Nucleus Accumbens , 2020, The Journal of Neuroscience.

[21]  Zheng Sun,et al.  Nuclear Receptor Coactivators (NCOAs) and Corepressors (NCORs) in the Brain , 2020, Endocrinology.

[22]  P. Xie,et al.  Circulating microRNA 134 sheds light on the diagnosis of major depressive disorder , 2020, Translational Psychiatry.

[23]  Simon B Eickhoff,et al.  Multimodal Abnormalities of Brain Structure and Function in Major Depressive Disorder: A Meta-Analysis of Neuroimaging Studies. , 2020, The American journal of psychiatry.

[24]  Richard F. Betzel,et al.  Linking Structure and Function in Macroscale Brain Networks , 2020, Trends in Cognitive Sciences.

[25]  Le Li,et al.  Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression , 2020, NeuroImage.

[26]  Peter B. Jones,et al.  Schizotypy-Related Magnetization of Cortex in Healthy Adolescence Is Colocated With Expression of Schizophrenia-Related Genes , 2019, Biological Psychiatry.

[27]  Anders M. Dale,et al.  The genetic architecture of the human cerebral cortex , 2020, Science.

[28]  E. Bullmore,et al.  Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes , 2018, Proceedings of the National Academy of Sciences.

[29]  J. Qiu,et al.  Reduced default mode network functional connectivity in patients with recurrent major depressive disorder , 2019, Proceedings of the National Academy of Sciences.

[30]  Joaquim Radua,et al.  Voxel-based meta-analysis via permutation of subject images (PSI): Theory and implementation for SDM , 2019, NeuroImage.

[31]  Ben D. Fulcher,et al.  Bridging the Gap between Connectome and Transcriptome , 2019, Trends in Cognitive Sciences.

[32]  R. Marioni,et al.  Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions , 2018, Nature Neuroscience.

[33]  Ben D. Fulcher,et al.  A practical guide to linking brain-wide gene expression and neuroimaging data , 2018, NeuroImage.

[34]  A. Cleare,et al.  Meta-analyses of the neural mechanisms and predictors of response to psychotherapy in depression and anxiety , 2018, Neuroscience & Biobehavioral Reviews.

[35]  J. Mann,et al.  Depression , 2018, The Lancet.

[36]  J. Marchini,et al.  Genome-wide association studies of brain imaging phenotypes in UK Biobank , 2018, Nature.

[37]  R. Marioni,et al.  Edinburgh Research Explorer Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways , 2022 .

[38]  Warren W. Kretzschmar,et al.  Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression , 2017, Nature Genetics.

[39]  Angela R. Laird,et al.  Ten simple rules for neuroimaging meta-analysis , 2018, Neuroscience & Biobehavioral Reviews.

[40]  S. Horvath,et al.  Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap , 2016, Science.

[41]  C. Zhuo,et al.  Selective functional dysconnectivity of the dorsal-anterior subregion of the precuneus in drug-naive major depressive disorder. , 2018, Journal of affective disorders.

[42]  J. Rottenberg.  Emotions in Depression: What Do We Really Know? , 2017, Annual review of clinical psychology.

[43]  M. Lazar.  Maturing of the nuclear receptor family. , 2017, The Journal of clinical investigation.

[44]  René S. Kahn,et al.  Connectome Disconnectivity and Cortical Gene Expression in Patients With Schizophrenia , 2017, Biological Psychiatry.

[45]  K. Yamamoto,et al.  Glucocorticoid receptor control of transcription: precision and plasticity via allostery , 2017, Nature Reviews Molecular Cell Biology.

[46]  Doron Lancet,et al.  MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search , 2016, Nucleic Acids Res..

[47]  Thomas E. Nichols,et al.  The coordinate-based meta-analysis of neuroimaging data. , 2016, Statistical science : a review journal of the Institute of Mathematical Statistics.

[48]  O. Abe,et al.  Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis , 2016, Molecular Psychiatry.

[49]  Lachlan T. Strike,et al.  Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group , 2016, Molecular Psychiatry.

[50]  D. Mohr,et al.  Major depressive disorder , 2016, Nature Reviews Disease Primers.

[51]  Q. Gong,et al.  Essential brain structural alterations in major depressive disorder: A voxel-wise meta-analysis on first episode, medication-naive patients. , 2016, Journal of affective disorders.

[52]  A. Grace.  Dysregulation of the dopamine system in the pathophysiology of schizophrenia and depression , 2016, Nature Reviews Neuroscience.

[53]  Andrew H. Miller,et al.  The role of inflammation in depression: from evolutionary imperative to modern treatment target , 2015, Nature Reviews Immunology.

[54]  Allan R. Jones,et al.  Canonical Genetic Signatures of the Adult Human Brain , 2015, Nature Neuroscience.

[55]  M. Raichle.  The brain's default mode network. , 2015, Annual review of neuroscience.

[56]  Warren W. Kretzschmar,et al.  Sparse whole genome sequencing identifies two loci for major depressive disorder , 2015, Nature.

[57]  S. Thompson,et al.  An excitatory synapse hypothesis of depression , 2015, Trends in Neurosciences.

[58]  G. Papakostas,et al.  Understanding and managing Cognition in the Depressed Patient. , 2015, The Journal of clinical psychiatry.

[59]  P. Fox,et al.  Identification of a common neurobiological substrate for mental illness. , 2015, JAMA psychiatry.

[60]  Q. Gong,et al.  Depression, Neuroimaging and Connectomics: A Selective Overview , 2015, Biological Psychiatry.

[61]  Thomas E. Nichols,et al.  Common genetic variants influence human subcortical brain structures , 2015, Nature.

[62]  Jonathan P. McNulty,et al.  The salience network is responsible for switching between the default mode network and the central executive network: Replication from DCM , 2014, NeuroImage.

[63]  Simon B Eickhoff,et al.  Meta-analysis in human neuroimaging: computational modeling of large-scale databases. , 2014, Annual review of neuroscience.

[64]  R. Evans,et al.  Nuclear Receptors, RXR, and the Big Bang , 2014, Cell.

[65]  J. Flint,et al.  The Genetics of Major Depression , 2014, Neuron.

[66]  David R. O'Brien,et al.  Cell Type-Specific Expression Analysis to Identify Putative Cellular Mechanisms for Neurogenetic Disorders , 2014, The Journal of Neuroscience.

[67]  Valentin Riedl,et al.  Insular dysfunction within the salience network is associated with severity of symptoms and aberrant inter-network connectivity in major depressive disorder , 2014, Front. Hum. Neurosci..

[68]  Chien-Han Lai.  Patterns of cortico-limbic activations during visual processing of sad faces in depression patients: a coordinate-based meta-analysis. , 2014, The Journal of neuropsychiatry and clinical neurosciences.

[69]  N. Vasic,et al.  Revisiting default mode network function in major depression: evidence for disrupted subsystem connectivity , 2013, Psychological Medicine.

[70]  J. Roiser,et al.  Cognitive impairment in depression: a systematic review and meta-analysis , 2013, Psychological Medicine.

[71]  C. Luu,et al.  Visual contrast sensitivity in major depressive disorder. , 2013, Journal of psychosomatic research.

[72]  N. Wray,et al.  A mega-analysis of genome-wide association studies for major depressive disorder , 2013, Molecular Psychiatry.

[73]  R. Landgraf,et al.  Balance of brain oxytocin and vasopressin: implications for anxiety, depression, and social behaviors , 2012, Trends in Neurosciences.

[74]  J Radua,et al.  A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps , 2012, European Psychiatry.

[75]  G. Aghajanian,et al.  Synaptic Dysfunction in Depression: Potential Therapeutic Targets , 2012, Science.

[76]  R. Lee,et al.  A meta-analysis of cognitive deficits in first-episode Major Depressive Disorder. , 2012, Journal of affective disorders.

[77]  Allan R. Jones,et al.  An anatomically comprehensive atlas of the adult human brain transcriptome , 2012, Nature.

[78]  Daniella J. Furman,et al.  Functional neuroimaging of major depressive disorder: a meta-analysis and new integration of base line activation and neural response data. , 2012, The American journal of psychiatry.

[79]  Katie L McMahon,et al.  Genetic and Environmental Influences on Neuroimaging Phenotypes: A Meta-Analytical Perspective on Twin Imaging Studies , 2012, Twin Research and Human Genetics.

[80]  Marisa O. Hollinshead,et al.  Identification of common variants associated with human hippocampal and intracranial volumes , 2012, Nature Genetics.

[81]  Allan R. Jones,et al.  Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures , 2012, Cell.

[82]  J. Ford,et al.  Default mode network activity and connectivity in psychopathology. , 2012, Annual review of clinical psychology.

[83]  E. R. Kloet,et al.  Mineralocorticoid and glucocorticoid receptors at the neuronal membrane, regulators of nongenomic corticosteroid signalling , 2012, Molecular and Cellular Endocrinology.

[84]  Georges J. Han,et al.  Selective neurocognitive impairments in adolescents with major depressive disorder. , 2012, Journal of adolescence.

[85]  K. Ahn,et al.  Regional Cortical Thickness and Subcortical Volume Changes Are Associated with Cognitive Impairments in the Drug-Naive Patients with Late-Onset Depression , 2012, Neuropsychopharmacology.

[86]  Conor Liston,et al.  Glucocorticoids are critical regulators of dendritic spine development and plasticity in vivo , 2011, Proceedings of the National Academy of Sciences.

[87]  Russell A. Poldrack,et al.  Large-scale automated synthesis of human functional neuroimaging data , 2011, Nature Methods.

[88]  André Aleman,et al.  Depression and the role of genes involved in dopamine metabolism and signalling , 2010, Progress in Neurobiology.

[89]  M. Bach,et al.  Seeing Gray When Feeling Blue? Depression Can Be Measured in the Eye of the Diseased , 2010, Biological Psychiatry.

[90]  V. Menon,et al.  Saliency, switching, attention and control: a network model of insula function , 2010, Brain Structure and Function.

[91]  Miho Nakajima,et al.  Analytical approaches to RNA profiling data for the identification of genes enriched in specific cells , 2010, Nucleic acids research.

[92]  Georg Northoff,et al.  Is subcortical–cortical midline activity in depression mediated by glutamate and GABA? A cross-species translational approach , 2010, Neuroscience & Biobehavioral Reviews.

[93]  P. McGuire,et al.  Functional atlas of emotional faces processing: a voxel-based meta-analysis of 105 functional magnetic resonance imaging studies. , 2009, Journal of psychiatry & neuroscience : JPN.

[94]  J. Raduà,et al.  Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. , 2009, The British journal of psychiatry : the journal of mental science.

[95]  D. Moher,et al.  Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement , 2009, BMJ : British Medical Journal.

[96]  Jing Chen,et al.  ToppGene Suite for gene list enrichment analysis and candidate gene prioritization , 2009, Nucleic Acids Res..

[97]  O Sporns,et al.  Predicting human resting-state functional connectivity from structural connectivity , 2009, Proceedings of the National Academy of Sciences.

[98]  A. Sequeira,et al.  Altered expression of genes involved in ATP biosynthesis and GABAergic neurotransmission in the ventral prefrontal cortex of suicides with and without major depression , 2009, Molecular Psychiatry.

[99]  T. Paus,et al.  Why do many psychiatric disorders emerge during adolescence? , 2008, Nature Reviews Neuroscience.

[100]  Stafford L. Lightman,et al.  The HPA axis in major depression: classical theories and new developments , 2008, Trends in Neurosciences.

[101]  V. Menon,et al.  A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks , 2008, Proceedings of the National Academy of Sciences.

[102]  Chaozhe Zhu,et al.  An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF , 2008, Journal of Neuroscience Methods.

[103]  P. Boesiger,et al.  GABA concentrations in the human anterior cingulate cortex predict negative BOLD responses in fMRI , 2007, Nature Neuroscience.

[104]  Michael J. Martinez,et al.  Bias between MNI and Talairach coordinates analyzed using the ICBM‐152 brain template , 2007, Human brain mapping.

[105]  Yong He,et al.  Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. , 2007, Brain & development.

[106]  G. Glover,et al.  Dissociable Intrinsic Connectivity Networks for Salience Processing and Executive Control , 2007, The Journal of Neuroscience.

[107]  Mario Beauregard,et al.  Dysfunction in the neural circuitry of emotional self-regulation in major depressive disorder , 2006, Neuroreport.

[108]  R. Myers,et al.  Altered cortical glutamatergic and GABAergic signal transmission with glial involvement in depression , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[109]  Richard Levy,et al.  Cognitive control and brain resources in major depression: An fMRI study using the n-back task , 2005, NeuroImage.

[110]  Yingli Lu,et al.  Regional homogeneity approach to fMRI data analysis , 2004, NeuroImage.

[111]  G. Rajkowska,et al.  Postmortem studies in mood disorders indicate altered numbers of neurons and glial cells , 2000, Biological Psychiatry.

[112]  P. Sullivan,et al.  Genetic epidemiology of major depression: review and meta-analysis. , 2000, The American journal of psychiatry.

[113]  B. Roth,et al.  Morphometric evidence for neuronal and glial prefrontal cell pathology in major depression∗ ∗ See accompanying Editorial, in this issue. , 1999, Biological Psychiatry.