Article
Psychology, Clinical
Xuetian Sun, Weisheng Huang, Jie Wang, Ruoxuan Xu, Xiaohan Zhang, Jianhui Zhou, Jiajia Zhu, Yinfeng Qian
Summary: This study investigates the genetic mechanisms of abnormal cerebral blood flow in patients with major depressive disorder (MDD). Through neuroimaging meta-analysis and independent sample analysis, increased cerebral blood flow in the reward circuitry and default-mode network, and decreased cerebral blood flow in the visual system were found in MDD patients. These changes in cerebral blood flow are associated with the expression of 1532 genes, related to important molecular functions, biological processes, and cellular components. These genes are associated with behaviors involving emotion and sensation and form a protein-protein interaction network supported by 60 key genes.
PSYCHOLOGICAL MEDICINE
(2023)
Article
Endocrinology & Metabolism
Jee Su Suh, Laura M. Fiori, Mohammad Ali, Kate L. Harkness, Milita Ramonas, Luciano Minuzzi, Stefanie Hassel, Stephen C. Strother, Mojdeh Zamyadi, Stephen R. Arnott, Faranak Farzan, Jane A. Foster, Raymond W. Lam, Glenda M. MacQueen, Roumen Milev, Daniel J. Muller, Sagar Parikh, Susan Rotzinger, Roberto B. Sassi, Claudio N. Soares, Rudolf Uher, Sidney H. Kennedy, Gustavo Turecki, Benicio N. Frey
Summary: This study investigated the relationship between hypothalamus volume and blood-derived DNA methylation in MDD, finding that left HV was negatively associated with duration of current episode in MDD patients. While no significant differences in HV or treatment response were observed between MDD and HC, there were differences in the number of functionally relevant CpG sites in FKBP5 and NR3C1 genes between the two groups.
PSYCHONEUROENDOCRINOLOGY
(2021)
Article
Clinical Neurology
Qian Fang, Huanhuan Cai, Ping Jiang, Han Zhao, Yu Song, Wenming Zhao, Yongqiang Yu, Jiajia Zhu
Summary: Through comprehensive multi-modal neuroimaging meta-analyses, changes in brain structure and function were identified in drug-naive first-episode patients with major depressive disorder (DF-MDD). These changes were spatially associated with the expression of 1194 and 1733 genes, revealing common and distinct genetic modulations of brain structural and functional impairments in this disorder.
JOURNAL OF AFFECTIVE DISORDERS
(2023)
Article
Multidisciplinary Sciences
Jiao Li, Jakob Seidlitz, John Suckling, Feiyang Fan, Gong-Jun Ji, Yao Meng, Siqi Yang, Kai Wang, Jiang Qiu, Huafu Chen, Wei Liao
Summary: This study investigates the correlation between cell type-specific gene expression changes and cortical structural differences in individuals with major depressive disorder. The expression of MDD-associated genes spatially correlates with morphometric differences, suggesting a link between molecular and structural changes relevant for MDD. Analysis of cell type-specific signature genes indicates that microglia and neuronal specific transcriptional changes play a significant role in the observed correlation with MDD-specific morphometric differences.
NATURE COMMUNICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Shu Liu, Abdel Abdellaoui, Karin J. H. Verweij, Guido A. van Wingen
Summary: This study investigates the impact of gene expression on brain structural and functional abnormalities in MDD. By comparing gray matter volume and resting-state functional measures in a Chinese sample, the study finds that whole gene expression is positively associated with structural abnormalities while negatively associated with functional abnormalities. Furthermore, the study identifies individual genes with opposite relationships between expression levels and brain abnormalities in MDD patients. The MDD-related genes are enriched in brain tissue, cortical cells, and biological pathways.
Article
Neurosciences
Wenshuang Zhu, Feng Liu, Jilian Fu, Wen Qin, Kaizhong Xue, Jie Tang, Yong Zhang, Chunshui Yu
Summary: This study identified 903 clinically sensitive genes and 633 clinically insensitive genes associated with ALFF alterations in MDD. The sensitive genes were enriched for cell differentiation and development, while the insensitive genes were enriched for ion transport and synaptic signaling.
CNS NEUROSCIENCE & THERAPEUTICS
(2023)
Article
Biotechnology & Applied Microbiology
Jing Zhang, Shujun Xie, Rong Xiao, Dongrong Yang, Zhi Zhan, Yan Li
Summary: This study aimed to identify potential mitophagy-related biomarkers for Major Depressive Disorder (MDD) and characterize the underlying molecular mechanisms. Through analysis of gene expression profiles, 315 differentially expressed genes related to mitophagy in MDD were identified. Functional enrichment analysis showed that these genes were mainly involved in mitophagy-related biological processes and multiple neurodegenerative disease pathways. Additionally, two distinct molecular subtypes associated with mitophagy gene signatures were identified in MDD.
Article
Genetics & Heredity
Bao Zhao, Qingyue Fan, Jintong Liu, Aihua Yin, Pingping Wang, Wenxin Zhang
Summary: This study used weighted gene co-expression network analysis to identify the relationship between co-expression modules and major depressive disorder in adolescents. The results showed that inflammation, stress, and immune responses were significantly associated with MDD. Key genes related to these processes were identified. These findings contribute to a better understanding of the molecular mechanism behind adolescent depression and provide potential biomarkers for diagnosis and treatment.
Article
Clinical Neurology
Xiaoqin Wang, Yi Xia, Rui Yan, Hao Sun, Yinghong Huang, Haowen Zou, Yishan Du, Lingling Hua, Hao Tang, Hongliang Zhou, Zhijian Yao, Qing Lu
Summary: This study aimed to explore the sex differences in the regional brain neuroimaging features of anhedonia in the context of major depressive disorder (MDD). The results showed significant differences in brain activity between males and females in relation to anhedonia, which may have clinical implications for treating anhedonia symptoms in MDD.
JOURNAL OF AFFECTIVE DISORDERS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Qinghe Li, Fanghui Dong, Qun Gai, Kaili Che, Heng Ma, Feng Zhao, Tongpeng Chu, Ning Mao, Peiyuan Wang
Summary: Machine-learning models combined with multisequence MRI neuroimaging features significantly improve the diagnosis of major depressive disorder and accurately predict suicide risk in patients with MDD.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Review
Biochemistry & Molecular Biology
Monika Liguz-Lecznar, Grzegorz Dobrzanski, Malgorzata Kossut
Summary: Despite differences in pathophysiology, many neuropsychiatric and neurodegenerative disorders share the disruption of excitation/inhibition balance as a pivotal mechanism. This article briefly describes the somatostatinergic system and the role of somatostatin and SOM-INs in physiological and pathological brain processes, emphasizing their importance in neuroplasticity and various brain pathologies.
Article
Psychology, Clinical
Hannah Lemke, Lina Romankiewicz, Katharina Foerster, Susanne Meinert, Lena Waltemate, Stella M. Fingas, Dominik Grotegerd, Ronny Redlich, Katharina Dohm, Elisabeth J. Leehr, Katharina Thiel, Verena Enneking, Katharina Brosch, Tina Meller, Kai Ringwald, Simon Schmitt, Frederike Stein, Olaf Steinstraeter, Jochen Bauer, Walter Heindel, Andreas Jansen, Axel Krug, Igor Nenadic, Tilo Kircher, Udo Dannlowski
Summary: This study investigates the association between disease course in Major Depressive Disorder (MDD) and brain structural alterations. The results suggest that a more severe and chronic disease course in MDD is associated with reduced volume in brain regions relevant for executive and cognitive functions and emotion regulation.
DEPRESSION AND ANXIETY
(2022)
Article
Clinical Neurology
Rubai Zhou, Jun Chen, Guoqing Zhao, Zuowei Wang, Daihui Peng, Weiping Xia, Ruizhi Mao, Jingjing Xu, Fan Wang, Chen Zhang, Yong Wang, Chengmei Yuan, Yousong Su, Jia Huang, Tao Yang, Chenglei Wang, Lvchun Cui, Jijun Wang, Lena Palaniyappan, Yiru Fang
Summary: The study identified a link between greater GM volume in the right parahippocampal gyrus and higher social function in patients with MDD. Even with improved overall social function over 12 weeks, there were continued differences in social function between high and low-functioning subgroups.
PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY
(2021)
Review
Psychiatry
Lan Hu, Hui He, Neil Roberts, Jiajia Chen, Guojian Yan, Li Pu, Xufeng Song, Cheng Luo
Summary: Interoception plays an important role in maintaining bodily homeostasis and promoting survival, and dysfunction of interoception is commonly observed in individuals with Major Depressive Disorder (MDD). Neuroimaging studies have revealed alterations in the structure and function of the insula, a major brain structure involved in interoception, in individuals with depression, but the precise relationship between these alterations and interoceptive dysfunction is still unclear. This review aims to examine the evidence of interoceptive dysfunction in people with MDD and the specific alterations in insular structure and function revealed by neuroimaging.
FRONTIERS IN PSYCHIATRY
(2023)
Article
Psychiatry
Victor De la Pena-Arteaga, Mercedes Berruga-Sanchez, Trevor Steward, Ignacio Martinez-Zalacain, Ximena Goldberg, Agustina Wainsztein, Carolina Abulafia, Narcis Cardoner, Mariana N. Castro, Mirta Villarreal, Jose M. Menchon, Salvador M. Guinjoan, Carles Soriano-Mas
Summary: This study identified a shared neurobiological contributor to emotion regulation deficits in MDD and BPD characterized by decreased vlPFC activity, while also observing disorder-specific alterations. In MDD, there is a primary deficit in prefrontal activations, while BPD is defined by connectivity disruptions between the vlPFC and temporal emotion processing regions. These findings substantiate the different profiles of emotion regulation alterations observed in these disorders in neurobiological terms.
EUROPEAN PSYCHIATRY
(2021)
Article
Psychology
Rowena Chin, Steve W. C. Chang, Avram J. Holmes
Summary: Human evolution is characterized by an increase in total brain volume relative to body size, particularly the expansion of association cortex. However, the majority of research on human brain evolution in the psychological sciences has focused solely on the cortex, neglecting the influence of other neural systems. This review challenges the mischaracterization of human cognition and behavior as a competition between recent cortical territories and ancient subcortical and cerebellar systems, proposing a comprehensive view of human brain evolution that has important implications for animal models, theory development, and network-focused approaches in studying behavior across health and disease.
PSYCHOLOGICAL REVIEW
(2023)
Review
Neurosciences
Ji Chen, Kaustubh R. Patil, B. T. Thomas Yeo, Simon B. Eickhoff
Summary: Much attention is being paid to developing diagnostic classifiers for mental disorders. In addition, machine learning is highlighted as a potential tool for gaining biological insights into the psychopathology and nosology of mental disorders. Brain imaging data, obtained noninvasively from large cohorts, has been used in studies to reveal intermediate phenotypes and refine the taxonomy of mental illness. Machine learning models' accuracy can identify pathophysiology-related features, addressing the dimensional and overlapping symptomatology of psychiatric illness. A multiview perspective combining molecular and system-level data and efforts toward data-driven definition of subtypes or disease entities through unsupervised and semisupervised approaches have also been emphasized.
BIOLOGICAL PSYCHIATRY
(2023)
Review
Neurosciences
Elvisha Dhamala, B. T. Thomas Yeo, Avram J. Holmes
Summary: Psychiatric illnesses are heterogeneous and have varied symptom profiles. Neuroimaging-based machine learning models have been used to study these illnesses, identify disease subtypes, predict symptom profiles, and recommend personalized treatments. However, methodological choices can influence the accuracy of these models, and understanding these effects is crucial for their proper implementation in psychiatry.
BIOLOGICAL PSYCHIATRY
(2023)
Article
Neurosciences
J. A. Ricard, T. C. Parker, E. Dhamala, J. Kwasa, A. Allsop, A. J. Holmes
Summary: Across the brain sciences, there is increasing acknowledgment of racism, bias, and inclusivity barriers. However, inadequate attention has been given to inequities in research methods and analytic approaches. This article discusses actionable ways and important questions to address exclusionary practices in human brain mapping and improve the equity and generalizability of scientific discoveries.
NATURE NEUROSCIENCE
(2023)
Article
Neurosciences
Gustavo Deco, Yonatan Sanz Perl, Laura de la Fuente, Jacobo D. Sitt, B. T. Thomas Yeo, Enzo Tagliazucchi, Morten L. Kringelbach
Summary: In this study, a thermodynamics-inspired, deep learning based Temporal Evolution NETwork (TENET) framework was used to assess the asymmetry in the flow of events, 'arrow of time', in human brain signals. The framework was applied to large-scale HCP neuroimaging data and revealed significant changes in the hierarchy of orchestration for resting state and cognitive tasks, as well as differences between health and neuropsychiatric disorders. This study provides new insights into brain dynamics in different brain states.
NETWORK NEUROSCIENCE
(2023)
Letter
Multidisciplinary Sciences
Brenden Tervo-Clemmens, Scott Marek, Roselyne J. Chauvin, Andrew N. Van, Benjamin P. Kay, Timothy O. Laumann, Wesley K. Thompson, Thomas E. Nichols, B. T. Thomas Yeo, Deanna M. Barch, Beatriz Luna, Damien A. Fair, Nico U. F. Dosenbach
Article
Neurosciences
Xiaoxuan Yan, Ru Kong, Aihuiping Xue, Qing Yang, Csaba Orban, Lijun An, Avram J. Holmes, Xing Qian, Jianzhong Chen, Xi-Nian Zuo, Juan Helen Zhou, Marielle Fortier, Ai Peng Tan, Peter Gluckman, Yap Seng Chong, Michael J. Meaney, Danilo Bzdok, Simon B. Eickhoff, B. T. Thomas Yeo
Summary: Resting-state fMRI is used to derive brain parcellations, and researchers have developed a model for estimating areal-level cortical parcellations. They extended the model to derive homotopic parcellations and demonstrated their potential applications in studying brain lateralization. The results highlight the significance of homotopic parcellations in subdividing the cerebral cortex into functional regions.
Article
Neurosciences
Hadis Kalantar-Hormozi, Raihaan Patel, Alyssa Dai, Justine Ziolkowski, Hao-Ming Dong, Avram Holmes, Armin Raznahan, Gabriel A. Devenyi, M. Mallar Chakravarty
Summary: This study examines the relationships between multiple cortical features during brain maturation, revealing the covariation of cortical thickness, surface area, gyrification index, and mean curvature. It also highlights the associations of these features with behavior, age, and biological sex.
Article
Neurosciences
Ru Kong, Yan Rui Tan, Naren Wulan, Leon Qi Rong Ooi, Seyedeh-Rezvan Farahibozorg, Samuel Harrison, Janine D. Bijsterbosch, Boris C. Bernhardt, Simon Eickhoff, B. T. Thomas Yeo
Summary: This study compares the performance of parcellation and gradient approaches in predicting behavioral measures using resting-state functional connectivity (RSFC) in two datasets. Results show that individual-specific hard-parcellation performs the best in the HCP dataset, while principal gradients, spatial independent component analysis, and group-average hard-parcellations exhibit similar performance. In the ABCD dataset, principal gradients and all parcellation approaches perform similarly. Overall, local gradients perform the worst, and the principal gradient approach requires at least 40 to 60 gradients to perform as well as parcellation approaches. These findings suggest that incorporating higher order gradients can provide significant behaviorally relevant information.
Article
Multidisciplinary Sciences
Loic Labache, Tian Ge, B. T. Thomas Yeo, Avram J. Holmes
Summary: Hemispheric specialization is a fundamental aspect of human brain organization. In this study, the authors used twin and family data from the Human Connectome Project to provide evidence that atypical language dominance is associated with global shifts in cortical organization. These findings highlight the role of genetic factors in both language lateralization and gradient asymmetries, contributing to a deeper understanding of population-level variability in hemispheric specialization and cortical organization.
NATURE COMMUNICATIONS
(2023)
Correction
Biology
Eliana Nicolaisen-Sobesky, Agoston Mihalik, Shahrzad Kharabian-Masouleh, Fabio S. Ferreira, Felix Hoffstaedter, Holger Schwender, Somayeh Maleki Balajoo, Sofie L. Valk, Simon B. Eickhoff, B. T. Thomas Yeo, Janaina Mourao-Miranda, Sarah Genon
COMMUNICATIONS BIOLOGY
(2023)
Article
Neurosciences
Lucina Q. Uddin, Richard F. Betzel, Jessica R. Cohen, Jessica S. Damoiseaux, Felipe De Brigard, Simon B. Eickhoff, Alex Fornito, Caterina Gratton, Evan M. Gordon, Angela R. Laird, Linda Larson-Prior, A. Randal McIntosh, Lisa D. Nickerson, Luiz Pessoa, Ana Luisa Pinho, Russell A. Poldrack, Adeel Razi, Sepideh Sadaghiani, James M. Shine, Anastasia Yendiki, B. T. Thomas Yeo, R. Nathan Spreng
Summary: Progress in network neuroscience requires the development of a standardized taxonomy for fundamental constructs. The WHATNET committee conducted a survey on current practices in brain network nomenclature and identified challenges such as network scale, interindividual variability, dynamics, and multimodal information. They provide initial considerations and recommendations for standardized reporting.
NETWORK NEUROSCIENCE
(2023)
Article
Neurosciences
Jianzhong Chen, Leon Qi Rong Ooi, Trevor Wei Kiat Tan, Shaoshi Zhang, Jingwei Li, Christopher L. Asplund, Simon B. Eickhofffg, Danilo Bzdokk, Avram J. Holmesm, B. T. Thomas Yeo
Summary: This study finds that feature importance in predicting behavior using neuroimaging data has certain reliability and is positively correlated with prediction accuracy. Moreover, there is no clear relationship between prediction performance and feature importance reliability in specific behavioral domains. These findings provide empirical and theoretical insights into the relationship between prediction accuracy and feature importance reliability.
Article
Multidisciplinary Sciences
Enning Yang, Filip Milisav, Jakub Kopal, Avram J. Holmes, Georgios D. Mitsis, Bratislav Misic, Emily S. Finn, Danilo Bzdok
Summary: The study shows that brain states in the default network capture the semantic aspects of an unfolding narrative during movie watching, using machine learning tools for natural language processing. This finding is important for understanding how the brain processes dynamic real-world stimuli.
NATURE COMMUNICATIONS
(2023)