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Elleuch D, Chen Y, Luo Q, Palaniyappan L. Speaking of yourself: A meta-analysis of 80 years of research on pronoun use in schizophrenia. Schizophr Res 2025; 279:22-30. [PMID: 40157253 DOI: 10.1016/j.schres.2025.03.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2024] [Revised: 02/16/2025] [Accepted: 03/19/2025] [Indexed: 04/01/2025]
Abstract
People with schizophrenia experience significant language disturbances that profoundly affect their everyday social interactions. Given its relevance to the referential function of language, aberrations in pronoun use are of particular interest in the study of schizophrenia. This systematic review and meta-analysis, adhering to PRISMA guidelines, examines the frequency of pronoun use in schizophrenia. PubMed, PsycINFO, Scopus, Google Scholar, and Web of Science were searched up to May 1, 2024. All studies analyzing pronoun frequency in various spoken language contexts in schizophrenia were included. Bias was assessed using a modified Newcastle-Ottawa Scale. A Bayesian meta-analysis with model averaging estimated effect sizes and moderating factors. 13 studies with n = 917 unique participants and 13 case-control contrasts were included. 37.9 % of patient samples were women, with a weighted mean (SD) age of 34.45 (9.72) years. 53.85 % of the studies were in languages other than English. We report a medium-sized effect for first-person pronoun impairment in schizophrenia (model-averaged d = 0.89, 95 % CrI (0.44, 1.33)). There was significant heterogeneity moderated by age. Evidence for publication bias was weak, with a strong support for first-person pronoun impairment after accounting for bias and heterogeneity. There was a small reduction of inter-individual variability in first-person pronoun use in patients compared to healthy controls (lnCVR = -0.12, 95 % CrI [-0.35, -0.13]). While all pronoun use was also high in patients, this was not robust due to heterogeneity and publication bias. Individuals with schizophrenia excessively use first-person pronouns. This may be a marker of a disturbed sense of self in this illness.
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Affiliation(s)
- Dalia Elleuch
- Higher School of Health Sciences and Techniques of Sfax, University of Sfax, Tunisia; Laboratory of Neuroscience, Faculty of Medicine of Sfax, University of Sfax, Tunisia
| | - Yinhan Chen
- Institute of Science and Technology for Brain-Inspired Intelligence, Research Institute of Intelligent Complex Systems, Fudan University, Shanghai 200433, China
| | - Qiang Luo
- Institute of Science and Technology for Brain-Inspired Intelligence, Research Institute of Intelligent Complex Systems, Fudan University, Shanghai 200433, China; State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai 200433, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Quebec, Canada; Robarts Research Institute & Lawson Health Research Institute, London, Ontario, Canada; Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
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2
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Ilie G, Jaeggi AV. The modular mind and psychiatry: toward clinical integration with a focus on self-disorders. Front Psychol 2025; 16:1570049. [PMID: 40351589 PMCID: PMC12062109 DOI: 10.3389/fpsyg.2025.1570049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2025] [Accepted: 04/07/2025] [Indexed: 05/14/2025] Open
Abstract
One of the foundational tenets of evolutionary psychology, the modular view of the mind, offers promising applications for clinical psychiatry. This perspective conceptualizes the mind as a collection of specialized information-processing modules, shaped by natural selection to address adaptive challenges faced by our ancestors. In this paper, we propose several points of integration between the modularity framework and clinical psychiatric practice. First, we argue that the descriptive psychopathology of self-disorders provides evidence supporting the modular view, demonstrating how a dysfunctional minimal self may expose the mind's modular architecture to conscious awareness. Next, we will explore how the modular perspective can illuminate the nature of intrapsychic conflicts. Finally, we will discuss how evidence from neuropsychiatric syndromes supports the modular view of the mind and, in turn, how this perspective can provide a basis for classifying mental disorders.
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Affiliation(s)
- Gheorghe Ilie
- Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland
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3
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Casten LG, Koomar T, Thomas TR, Koh JY, Hofamman D, Thenuwara S, Momany A, O'Brien M, Murra JC, Bruce Tomblin J, Michaelson JJ. Rapidly evolved genomic regions shape individual language abilities in present-day humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.07.641231. [PMID: 40161630 PMCID: PMC11952349 DOI: 10.1101/2025.03.07.641231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
1Minor genetic changes have produced profound differences in cognitive abilities between humans and our closest relatives, particularly in language. Despite decades of research, ranging from single-gene studies to broader evolutionary analyses[1, 2, 3, 4, 5], key questions about the genomic foundations of human language have persisted, including which sequences are involved, how they evolved, and whether similar changes occur in other vocal learning species. Here we provide the first evidence directly linking rapidly evolved genomic regions to language abilities in contemporary humans. Through extensive analysis of 65 million years of evolutionary events in over 30,000 individuals, we demonstrate that Human Ancestor Quickly Evolved Regions (HAQERs)[5] - sequences that rapidly accumulated mutations after the human-chimpanzee split - specifically influence language but not general cognition. These regions evolved to shape language development by altering binding of Forkhead domain transcription factors, including FOXP2. Strikingly, language-associated HAQER variants show higher prevalence in Neanderthals than modern humans, have been stable throughout recent human history, and show evidence of convergent evolution across other mammalian vocal learners. An unexpected pattern of balancing selection acting on these apparently beneficial alleles is explained by their pleiotropic effects on prenatal brain development contributing to birth complications, reflecting an evolutionary trade-off between language capability and reproductive fitness. By developing the Evolution Stratified-Polygenic Score analysis, we show that language capabilities likely emerged before the human-Neanderthal split - far earlier than previously thought[3, 6, 7]. Our findings establish the first direct link between ancient genomic divergence and present-day variation in language abilities, while revealing how evolutionary constraints continue to shape human cognitive development.
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Affiliation(s)
| | | | | | - Jin-Young Koh
- Department of Otorhinolaryngology-Head and Neck Surgery, University of Maryland
| | | | | | - Allison Momany
- Stead Family Department of Pediatrics, University of Iowa
| | - Marlea O'Brien
- Department of Communication Science and Disorders, University of Iowa
| | | | - J Bruce Tomblin
- Department of Communication Science and Disorders, University of Iowa
| | - Jacob J Michaelson
- Department of Psychiatry, University of Iowa
- Department of Communication Science and Disorders, University of Iowa
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4
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Palaniyappan L, Liddle PF. Seminal Contributions of Timothy J. Crow. Psychol Med 2025; 55:e75. [PMID: 40109883 PMCID: PMC7617505 DOI: 10.1017/s0033291725000182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2025] [Revised: 01/21/2025] [Accepted: 01/24/2025] [Indexed: 03/22/2025]
Abstract
We recall the life and work of Timothy J. Crow, whose contributions provided great insights into the pathophysiology of schizophrenia and continue to shape many questions in the field. We compile his key works relating to psychotic disorders, focusing on the trajectory of his theoretical stance. Our account is interlaced with our own interpretation of the evidence that influenced Crow's arguments over the years as well as his scientific method. Crow has had a significant impact on the neuroscience of schizophrenia. Many of his observations are still valid and several questions he raised remain unanswered to date.
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Affiliation(s)
- Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, QC, Canada
- Department of Psychiatry, Schulich School of Medicine & Dentistry, University of Western OntarioLondon, ON, Canada
- Robarts Research Institute & Lawson Health Research Institute, London, ON, Canada
| | - Peter F. Liddle
- Institute of Mental Health, University of Nottingham, Nottingham, UK
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Starr AL, Fraser HB. A general principle of neuronal evolution reveals a human-accelerated neuron type potentially underlying the high prevalence of autism in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.08.02.606407. [PMID: 39131279 PMCID: PMC11312593 DOI: 10.1101/2024.08.02.606407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
The remarkable ability of a single genome sequence to encode a diverse collection of distinct cell types, including the thousands of cell types found in the mammalian brain, is a key characteristic of multicellular life. While it has been observed that some cell types are far more evolutionarily conserved than others, the factors driving these differences in evolutionary rate remain unknown. Here, we hypothesized that highly abundant neuronal cell types may be under greater selective constraint than rarer neuronal types, leading to variation in their rates of evolution. To test this, we leveraged recently published cross-species single-nucleus RNA-sequencing datasets from three distinct regions of the mammalian neocortex. We found a strikingly consistent relationship where more abundant neuronal subtypes show greater gene expression conservation between species, which replicated across three independent datasets covering >106 neurons from six species. Based on this principle, we discovered that the most abundant type of neocortical neurons-layer 2/3 intratelencephalic excitatory neurons-has evolved exceptionally quickly in the human lineage compared to other apes. Surprisingly, this accelerated evolution was accompanied by the dramatic down-regulation of autism-associated genes, which was likely driven by polygenic positive selection specific to the human lineage. In sum, we introduce a general principle governing neuronal evolution and suggest that the exceptionally high prevalence of autism in humans may be a direct result of natural selection for lower expression of a suite of genes that conferred a fitness benefit to our ancestors while also rendering an abundant class of neurons more sensitive to perturbation.
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Affiliation(s)
| | - Hunter B. Fraser
- Department of Biology, Stanford University, Stanford, CA 94305, USA
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6
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Sandroni V, Chaumette B. Understanding the Emergence of Schizophrenia in the Light of Human Evolution: New Perspectives in Genetics. GENES, BRAIN, AND BEHAVIOR 2025; 24:e70013. [PMID: 39801370 PMCID: PMC11725983 DOI: 10.1111/gbb.70013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2024] [Revised: 12/17/2024] [Accepted: 12/21/2024] [Indexed: 01/16/2025]
Abstract
Schizophrenia is a frequent and disabling disease. The persistence of the disorder despite its harmful consequences represents an evolutionary paradox. Based on recent discoveries in genetics, scientists have formulated the "price-to-pay" hypothesis: schizophrenia would be intimately related to human evolution, particularly to brain development and human-specific higher cognitive functions. The objective of the present work is to question scientific literature about the relationship between schizophrenia and human evolution from a genetic point of view. In the last two decades, research investigated the association between schizophrenia and a few genetic evolutionary markers: Human accelerated regions, segmental duplications, and highly repetitive DNA such as the Olduvai domain. Other studies focused on the action of natural selection on schizophrenia-associated genetic variants, also thanks to the complete sequencing of archaic hominins' genomes (Neanderthal, Denisova). Results suggested that a connection between human evolution and schizophrenia may exist; nonetheless, much research is still needed, and it is possible that a definitive answer to the evolutionary paradox of schizophrenia will never be found.
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Affiliation(s)
- Veronica Sandroni
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP)ParisFrance
- GHU‐Paris Psychiatrie et NeurosciencesHôpital Sainte AnneParisFrance
| | - Boris Chaumette
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP)ParisFrance
- GHU‐Paris Psychiatrie et NeurosciencesHôpital Sainte AnneParisFrance
- Human Genetics and Cognitive FunctionsInstitut Pasteur, Université Paris CitéParisFrance
- Department of PsychiatryMcGill UniversityMontrealCanada
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Martini F, Spangaro M, Sapienza J, Cavallaro R. Cerebral asymmetries in schizophrenia. HANDBOOK OF CLINICAL NEUROLOGY 2025; 208:89-99. [PMID: 40074419 DOI: 10.1016/b978-0-443-15646-5.00018-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/14/2025]
Abstract
Historically, the first observations of a lower prevalence of right-handed patients among subjects with schizophrenia led to the hypothesis that brain asymmetry could play a significant role in the etiopathogenesis of the disease. Over the last decades, a growing number of findings obtained through many different techniques such as EEG, MEG, MRI, and fMRI, consistently reported reduction/loss of brain asymmetries as a core feature of schizophrenia, further suggesting such alterations to play a cardinal role in the pathogenesis of the disease. Moreover, several cognitive and psychopathologic dimensions have shown significant correlations with the reduced degree of asymmetry. In particular, the absence or even reversal of structural asymmetries has been documented in language-related brain such as the Sylvian fissure and planum temporale. These findings have been reprocessed within an evolutionary and psychopathologic framework pointing at the loss of asymmetry and the consequent language impairment as primum moves in the pathogenesis of schizophrenia. Overall, despite growing evidence demonstrating a heterogeneous and multifaced etiopathogenesis in schizophrenia, the "old concept" of brain asymmetry still offers intriguing hints and thought-provoking elements for clinicians and researchers who deal with schizophrenia.
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Affiliation(s)
- Francesca Martini
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco Spangaro
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Jacopo Sapienza
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy; Department of Humanities and Life Sciences, University School for Advanced Studies IUSS, Pavia, Italy.
| | - Roberto Cavallaro
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy; School of Medicine, Vita-Salute San Raffaele University, Milan, Italy
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8
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Chen J, Wei Y, Xue K, Gao X, Zhang M, Han S, Wen B, Wu G, Cheng J. Static and temporal dynamic changes of intrinsic brain activity in early-onset and adult-onset schizophrenia: a fMRI study of interaction effects. Front Neurol 2024; 15:1445599. [PMID: 39655163 PMCID: PMC11625647 DOI: 10.3389/fneur.2024.1445599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Accepted: 10/28/2024] [Indexed: 12/12/2024] Open
Abstract
Background Schizophrenia is characterized by altered static and dynamic spontaneous brain activity. However, the conclusions regarding this are inconsistent. Evidence has revealed that this inconsistency could be due to mixed effects of age of onset. Methods We enrolled 66/84 drug-naïve first-episode patients with early-onset/adult-onset schizophrenia (EOS/AOS) and matched normal controls (NCs) (46 adolescents, 73 adults), undergoing resting-state functional magnetic resonance imaging. Two-way ANOVA was used to determine the amplitude of low-frequency fluctuation (ALFF) and dynamic ALFF (dALFF) among the four groups. Result Compared to NCs, EOS had a higher ALFF in inferior frontal gyrus bilateral triangular part (IFG-tri), left opercular part (IFG-oper), left orbital part (IFG-orb), and left middle frontal gyrus (MFG). The AOS had a lower ALFF in left IFG-tri, IFG-oper, and lower dALFF in left IFG-tri. Compared to AOS, EOS had a higher ALFF in the left IFG-orb, and MFG, and higher dALFF in IFG-tri. Adult NCs had higher ALFF and dALFF in the prefrontal cortex (PFC) than adolescent NCs. The main effects of diagnosis were found in the PFC, medial temporal structures, cerebrum, visual and sensorimotor networks, the main effects of age were found in the visual and motor networks of ALFF and PFC of dALFF. Conclusion Our findings unveil the static and dynamic neural activity mechanisms involved in the interaction between disorder and age in schizophrenia. Our results underscore age-related abnormalities in the neural activity of the PFC, shedding new light on the neurobiological mechanisms underlying the development of schizophrenia. This insight may offer valuable perspectives for the specific treatment of EOS in clinical settings.
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Affiliation(s)
- Jingli Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
| | - Kangkang Xue
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
| | - Xinyu Gao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
| | - Mengzhe Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
| | - Baohong Wen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
| | - Guangyu Wu
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
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9
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Lu Y, Cui Y, Cao L, Dong Z, Cheng L, Wu W, Wang C, Liu X, Liu Y, Zhang B, Li D, Zhao B, Wang H, Li K, Ma L, Shi W, Li W, Ma Y, Du Z, Zhang J, Xiong H, Luo N, Liu Y, Hou X, Han J, Sun H, Cai T, Peng Q, Feng L, Wang J, Paxinos G, Yang Z, Fan L, Jiang T. Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology. Sci Bull (Beijing) 2024; 69:2241-2259. [PMID: 38580551 DOI: 10.1016/j.scib.2024.03.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/18/2024] [Accepted: 03/11/2024] [Indexed: 04/07/2024]
Abstract
The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.
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Affiliation(s)
- Yuheng Lu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yue Cui
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Long Cao
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China; Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Zhenwei Dong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Luqi Cheng
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China; Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Wen Wu
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Changshuo Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Xinyi Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Youtong Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Baogui Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Deying Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bokai Zhao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Kaixin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China
| | - Liang Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weiyang Shi
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wen Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yawei Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Zongchang Du
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiaqi Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Xiong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Na Luo
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yanyan Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Xiaoxiao Hou
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jinglu Han
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Hongji Sun
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Tao Cai
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Qiang Peng
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Linqing Feng
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - George Paxinos
- Neuroscience Research Australia and The University of New South Wales, Sydney NSW 2031, Australia
| | - Zhengyi Yang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, China.
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China; Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, China.
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Jiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Uyar Demir A, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Van Rheenen TE, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos SI, Jahanshad N, Cui LB, Yao D, et alJiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Uyar Demir A, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Van Rheenen TE, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos SI, Jahanshad N, Cui LB, Yao D, Thompson PM, Turner JA, van Erp TGM, Cheng W, Feng J. Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm. Nat Commun 2024; 15:5996. [PMID: 39013848 PMCID: PMC11252381 DOI: 10.1038/s41467-024-50267-3] [Show More Authors] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 07/03/2024] [Indexed: 07/18/2024] Open
Abstract
Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Canada
| | - Xiao Chang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Magdeburg, Germany
| | - Kiyotaka Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Genevieve Richard
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Sara Fernandez-Cabello
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Nadine Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapie and Center for Brain, Behavior and Metabolism, Lübeck University, Lübeck, Germany
- Institute for Transnational Psychiatry and Otto Creutzfeldt Center for Behavioral and Cognitive Neuroscience, University of Münster, Münster, Germany
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
- Chinese Institute for Brain Research, Beijing, PR China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, PR China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Enpeng Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Amanda L Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - David Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, TX, USA
| | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - María Ángeles Garcia-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Ali Saffet Gonul
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Ozgul Uslu
- Ege University Institute of Health Sciences Department of Neuroscience, Izmir, Turkey
| | | | - Aslihan Uyar Demir
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Melissa Green
- School of Clinical Medicine, University of New South Wales, SYD, Australia
| | - Yann Quidé
- School of Psychology, University of New South Wales, SYD, Australia
| | - Young Chul Chung
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Scott R Sponheim
- Minneapolis VA Medical Center, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Ian S Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Felice Iasevoli
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Annarita Barone
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Min Tae M Park
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, TO, Canada
- Centre for Addiction and Mental Health, TO, Canada
| | - Matthias Kirschner
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, MEL, Australia
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Susan L Rossell
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Matthew Hughes
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - William Woods
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Sean P Carruthers
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Philip Sumner
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Elysha Ringin
- National Institute of Mental Health, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Philipp Homan
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich & Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, Zurich, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Wolfgang Omlor
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Giacomo Cecere
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Dana D Nguyen
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, room 109, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- School of Data Science, Fudan University, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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Jiang Y, Palaniyappan L, Luo C, Chang X, Zhang J, Tang Y, Zhang T, Li C, Zhou E, Yu X, Li W, An D, Zhou D, Huang CC, Tsai SJ, Lin CP, Cheng J, Wang J, Yao D, Cheng W, Feng J, the ZIB Consortium. Neuroimaging epicenters as potential sites of onset of the neuroanatomical pathology in schizophrenia. SCIENCE ADVANCES 2024; 10:eadk6063. [PMID: 38865456 PMCID: PMC11168466 DOI: 10.1126/sciadv.adk6063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 05/08/2024] [Indexed: 06/14/2024]
Abstract
Schizophrenia lacks a clear definition at the neuroanatomical level, capturing the sites of origin and progress of this disorder. Using a network-theory approach called epicenter mapping on cross-sectional magnetic resonance imaging from 1124 individuals with schizophrenia, we identified the most likely "source of origin" of the structural pathology. Our results suggest that the Broca's area and adjacent frontoinsular cortex may be the epicenters of neuroanatomical pathophysiology in schizophrenia. These epicenters can predict an individual's response to treatment for psychosis. In addition, cross-diagnostic similarities based on epicenter mapping over of 4000 individuals diagnosed with neurological, neurodevelopmental, or psychiatric disorders appear to be limited. When present, these similarities are restricted to bipolar disorder, major depressive disorder, and obsessive-compulsive disorder. We provide a comprehensive framework linking schizophrenia-specific epicenters to multiple levels of neurobiology, including cognitive processes, neurotransmitter receptors and transporters, and human brain gene expression. Epicenter mapping may be a reliable tool for identifying the potential onset sites of neural pathophysiology in schizophrenia.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, PR China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Quebec, Canada
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
- Lawson Health Research Institute, London, Ontario, Canada
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and Technology, University of Electronic Science and Technology of China, Chengdu, PR China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, PR China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, PR China
| | - Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, PR China
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, PR China
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - Enpeng Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, PR China
- Shanghai Changning Mental Health Center, Shanghai, PR China
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, PR China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and Technology, University of Electronic Science and Technology of China, Chengdu, PR China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, PR China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, PR China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, PR China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, PR China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, PR China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, PR China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, PR China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, PR China
- Zhangjiang Fudan International Innovation Center, Shanghai, PR China
- School of Data Science, Fudan University, Shanghai, PR China
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
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Mitteroecker P, Merola GP. The cliff edge model of the evolution of schizophrenia: Mathematical, epidemiological, and genetic evidence. Neurosci Biobehav Rev 2024; 160:105636. [PMID: 38522813 DOI: 10.1016/j.neubiorev.2024.105636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/27/2024] [Accepted: 03/16/2024] [Indexed: 03/26/2024]
Abstract
How has schizophrenia, a condition that significantly reduces an individual's evolutionary fitness, remained common across generations and cultures? Numerous theories about the evolution of schizophrenia have been proposed, most of which are not consistent with modern epidemiological and genetic evidence. Here, we briefly review this evidence and explore the cliff edge model of schizophrenia. It suggests that schizophrenia is the extreme manifestation of a polygenic trait or a combination of traits that, within a normal range of variation, confer cognitive, linguistic, and/or social advantages. Only beyond a certain threshold, these traits precipitate the onset of schizophrenia and reduce fitness. We provide the first mathematical model of this qualitative concept and show that it requires only very weak positive selection of the underlying trait(s) to explain today's schizophrenia prevalence. This prediction, along with expectations about the effect size of schizophrenia risk alleles, are surprisingly well matched by empirical evidence. The cliff edge model predicts a dynamic change of selection of risk alleles, which explains the contradictory findings of evolutionary genetic studies.
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Affiliation(s)
- Philipp Mitteroecker
- Unit for Theoretical Biology, Department of Evolutionary Biology, University of Vienna, Djerassiplatz 1, Vienna, Austria; Konrad Lorenz Institute for Evolution and Cognition Research, Martinstrasse 12, Klosterneuburg, Vienna, Austria.
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13
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Dornelles E, Correia DT. The Neurobiology of Formal Thought Disorder. Curr Top Med Chem 2024; 24:1773-1783. [PMID: 38243933 DOI: 10.2174/0115680266272521240108102354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 11/01/2023] [Accepted: 11/02/2023] [Indexed: 01/22/2024]
Abstract
The concept of Formal Thought Disorder (FTD) is an ambiguous and disputed one, even though it has endured as a core psychopathological construct in clinical Psychiatry. FTD can be summarized as a multidimensional construct, reflecting difficulties or idiosyncrasies in thinking, language, and communication in general and is usually subdivided into positive versus negative. In this article, we aim to explore the putative neurobiology of FTD, ranging from changes in neurotransmitter systems to alterations in the functional anatomy of the brain. We also discuss recent critiques of the operationalist view of FTD and how they might fit in its biological underpinnings. We conclude that FTD might be the observable phenotype of many distinct underlying alterations in different proportions.
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Affiliation(s)
- Erik Dornelles
- Clínica Universitária de Psicologia e Psiquiatria, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Departamento de Psiquiatria, Centro Hospitalar Universitário Lisboa Norte, Lisboa, Portugal
| | - Diogo Telles Correia
- Clínica Universitária de Psicologia e Psiquiatria, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Departamento de Psiquiatria, Centro Hospitalar Universitário Lisboa Norte, Lisboa, Portugal
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14
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Panikratova YR, Lebedeva IS, Akhutina TV, Tikhonov DV, Kaleda VG, Vlasova RM. Executive control of language in schizophrenia patients with history of auditory verbal hallucinations: A neuropsychological and resting-state fMRI study. Schizophr Res 2023; 262:201-210. [PMID: 37923596 DOI: 10.1016/j.schres.2023.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 10/23/2023] [Accepted: 10/26/2023] [Indexed: 11/07/2023]
Abstract
BACKGROUND As demonstrated by a plethora of studies, compromised executive functions (EF) and language are implicated in mechanisms of auditory verbal hallucinations (AVH), but the contribution of their interaction to AVH remains unclear. We hypothesized that schizophrenia patients with history of AVH (AVHh+) vs. without history of AVH (AVHh-) have a specific deficit of executive control of language and alterations in functional connectivity (FC) between the brain regions involved in EF and language, and these neuropsychological and neurophysiological traits are associated with each other. METHODS To explore the executive control of language and its contribution to AVH, we used an integrative approach involving analysis of neuropsychological and resting-state fMRI data of 34 AVHh+, 16 AVHh-, and 40 healthy controls. We identified the neuropsychological and FC measures that differentiated between AVHh+, AVHh-, and HC, and tested the associations between them. RESULTS AVHh+ were characterized by decreased category and phonological verbal fluency, utterance length, productivity in the planning tasks, and poorer retelling. AVHh+ had decreased FC between the left inferior frontal gyrus and the anterior cingulate cortex. Productivity in category verbal fluency was associated with the FC between these regions. CONCLUSIONS Poor executive control of word retrieval and deficient programming of sentence and narrative related to more general deficits of planning may be the neuropsychological traits specific for AVHh+. A neurophysiological trait specific for AVHh+ may be a decreased FC between regions involved in language production and differentiation between alien- vs. self-generated speech and between language production vs. comprehension.
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Affiliation(s)
- Yana R Panikratova
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, 115522, 34 Kashirskoye shosse, Moscow, Russia.
| | - Irina S Lebedeva
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, 115522, 34 Kashirskoye shosse, Moscow, Russia
| | - Tatiana V Akhutina
- Laboratory of Neuropsychology, Faculty of Psychology, Lomonosov Moscow State University, 125009, 11/9 Mokhovaya street, Moscow, Russia
| | - Denis V Tikhonov
- Department of Youth Psychiatry, Mental Health Research Center, 115522, 34 Kashirskoye shosse, Moscow, Russia
| | - Vasilii G Kaleda
- Department of Youth Psychiatry, Mental Health Research Center, 115522, 34 Kashirskoye shosse, Moscow, Russia
| | - Roza M Vlasova
- Department of Psychiatry, University of North Carolina, 101 Manning Dr # 1, Chapel Hill, NC 27514, United States of America
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15
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Jiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Demir AU, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Rheenen TEV, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos S, Jahanshad N, Cui LB, Yao D, et alJiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Demir AU, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Rheenen TEV, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos S, Jahanshad N, Cui LB, Yao D, Thompson PM, Turner JA, van Erp TG, Cheng W, ENIGMA Schizophrenia Consortium, ZIB Consortium, Feng J. Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.11.23296862. [PMID: 37873296 PMCID: PMC10593004 DOI: 10.1101/2023.10.11.23296862] [Show More Authors] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Canada
| | - Xiao Chang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Germany
| | - Kiyotaka Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, 305-8575, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, 187-8553, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, 187-8553, Japan
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Genevieve Richard
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Sara Fernandez-Cabello
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Nadine Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapie and Center for Brain, Behavior and Metabolism, Lübeck University, Lübeck, Germany
- Institute for Transnational Psychiatry and Otto Creutzfeldt Center for Behavioral and Cognitive Neuroscience, University of Münster, Münster, Germany
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
- Chinese Institute for Brain Research, Beijing, PR China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, PR China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Enpeng Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Amanda L. Rodrigue
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston MA, USA
| | - David Glahn
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston MA, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, TX, USA
| | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - María Ángeles Garcia-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Ali Saffet Gonul
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Ozgul Uslu
- Ege University Institute of Health Sciences Department of Neuroscience, Izmir, Turkey
| | | | - Aslihan Uyar Demir
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Melissa Green
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Yann Quidé
- School of Psychology, University of New South Wales, Sydney, Australia
| | - Young Chul Chung
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Scott R. Sponheim
- Minneapolis VA Medical Center, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Ian S. Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Felice Iasevoli
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Annarita Barone
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Min Tae M. Park
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Centre for Addiction and Mental Health, Toronto, Canada
| | - Matthias Kirschner
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Switzerland
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Switzerland
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Susan L Rossell
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Matthew Hughes
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - William Woods
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Sean P Carruthers
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Philip Sumner
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Elysha Ringin
- National Institute of Mental Health, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Philipp Homan
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich & Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Switzerland
| | - Wolfgang Omlor
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Giacomo Cecere
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Dana D Nguyen
- Department of Pediatrics, University of California Irvine, Irvine, California, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California, USA
| | - Sophia Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi’an, PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, USA
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, room 109, Irvine, CA, 92697-3950, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | | | | | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
- School of Data Science, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
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16
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González-Peñas J, de Hoyos L, Díaz-Caneja CM, Andreu-Bernabeu Á, Stella C, Gurriarán X, Fañanás L, Bobes J, González-Pinto A, Crespo-Facorro B, Martorell L, Vilella E, Muntané G, Molto MD, Gonzalez-Piqueras JC, Parellada M, Arango C, Costas J. Recent natural selection conferred protection against schizophrenia by non-antagonistic pleiotropy. Sci Rep 2023; 13:15500. [PMID: 37726359 PMCID: PMC10509162 DOI: 10.1038/s41598-023-42578-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 09/12/2023] [Indexed: 09/21/2023] Open
Abstract
Schizophrenia is a debilitating psychiatric disorder associated with a reduced fertility and decreased life expectancy, yet common predisposing variation substantially contributes to the onset of the disorder, which poses an evolutionary paradox. Previous research has suggested balanced selection, a mechanism by which schizophrenia risk alleles could also provide advantages under certain environments, as a reliable explanation. However, recent studies have shown strong evidence against a positive selection of predisposing loci. Furthermore, evolutionary pressures on schizophrenia risk alleles could have changed throughout human history as new environments emerged. Here in this study, we used 1000 Genomes Project data to explore the relationship between schizophrenia predisposing loci and recent natural selection (RNS) signatures after the human diaspora out of Africa around 100,000 years ago on a genome-wide scale. We found evidence for significant enrichment of RNS markers in derived alleles arisen during human evolution conferring protection to schizophrenia. Moreover, both partitioned heritability and gene set enrichment analyses of mapped genes from schizophrenia predisposing loci subject to RNS revealed a lower involvement in brain and neuronal related functions compared to those not subject to RNS. Taken together, our results suggest non-antagonistic pleiotropy as a likely mechanism behind RNS that could explain the persistence of schizophrenia common predisposing variation in human populations due to its association to other non-psychiatric phenotypes.
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Affiliation(s)
- Javier González-Peñas
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain.
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain.
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain.
| | - Lucía de Hoyos
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Álvaro Andreu-Bernabeu
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Carol Stella
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
| | - Xaquín Gurriarán
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
| | - Lourdes Fañanás
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Barcelona, Spain
| | - Julio Bobes
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Faculty of Medicine and Health Sciences - Psychiatry, Universidad de Oviedo, ISPA, INEUROPA, Oviedo, Spain
| | - Ana González-Pinto
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- BIOARABA Health Research Institute, OSI Araba, University Hospital, University of the Basque Country, Vitoria, Spain
| | - Benedicto Crespo-Facorro
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Psychiatry, Hospital Universitario Virgen del Rocío, Universidad de Sevilla, Seville, Spain
| | - Lourdes Martorell
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira I Virgili, Reus, Spain
| | - Elisabet Vilella
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira I Virgili, Reus, Spain
| | - Gerard Muntané
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira I Virgili, Reus, Spain
| | - María Dolores Molto
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Genetics, University of Valencia, Campus of Burjassot, Valencia, Spain
- Department of Medicine, Universitat de València, Valencia, Spain
| | - Jose Carlos Gonzalez-Piqueras
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Medicine, Universitat de València, Valencia, Spain
- Fundación Investigación Hospital Clínico de Valencia, INCLIVA, 46010, Valencia, Spain
| | - Mara Parellada
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Javier Costas
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain
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17
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Abstract
Evolutionary biology provides a crucial foundation for medicine and behavioral science that has been missing from psychiatry. Its absence helps to explain slow progress; its advent promises major advances. Instead of offering a new kind of treatment, evolutionary psychiatry provides a scientific foundation useful for all kinds of treatment. It expands the search for causes from mechanistic explanations for disease in some individuals to evolutionary explanations for traits that make all members of a species vulnerable to disease. For instance, capacities for symptoms such as pain, cough, anxiety and low mood are universal because they are useful in certain situations. Failing to recognize the utility of anxiety and low mood is at the root of many problems in psychiatry. Determining if an emotion is normal and if it is useful requires understanding an individual's life situation. Conducting a review of social systems, parallel to the review of systems in the rest of medicine, can help achieve that understanding. Coping with substance abuse is advanced by acknowledging how substances available in modern environments hijack chemically mediated learning mechanisms. Understanding why eating spirals out of control in modern environments is aided by recognizing the motivations for caloric restriction and how it arouses famine protection mechanisms that induce binge eating. Finally, explaining the persistence of alleles that cause serious mental disorders requires evolutionary explanations of why some systems are intrinsically vulnerable to failure. The thrill of finding functions for apparent diseases is evolutionary psychiatry's greatest strength and weakness. Recognizing bad feelings as evolved adaptations corrects psychiatry's pervasive mistake of viewing all symptoms as if they were disease manifestations. However, viewing diseases such as panic disorder, melancholia and schizophrenia as if they are adaptations is an equally serious mistake in evolutionary psychiatry. Progress will come from framing and testing specific hypotheses about why natural selection left us vulnerable to mental disorders. The efforts of many people over many years will be needed before we will know if evolutionary biology can provide a new paradigm for understanding and treating mental disorders.
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Affiliation(s)
- Randolph M Nesse
- Departments of Psychiatry and Psychology, University of Michigan, Ann Arbor, MI, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
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18
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Pruunsild P, Bengtson CP, Loss I, Lohrer B, Bading H. Expression of the primate-specific LINC00473 RNA in mouse neurons promotes excitability and CREB-regulated transcription. J Biol Chem 2023; 299:104671. [PMID: 37019214 DOI: 10.1016/j.jbc.2023.104671] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 03/27/2023] [Accepted: 03/30/2023] [Indexed: 04/05/2023] Open
Abstract
The LINC00473 (Lnc473) gene has previously been shown to be associated with cancer and psychiatric disorders. Its expression is elevated in several types of tumors and decreased in the brains of patients diagnosed with schizophrenia or major depression. In neurons, Lnc473 transcription is strongly responsive to synaptic activity, suggesting a role in adaptive, plasticity-related mechanisms. However, the function of Lnc473 is largely unknown. Here, using a recombinant adeno-associated viral vector, we introduced a primate-specific human Lnc473 RNA into mouse primary neurons. We show that this resulted in a transcriptomic shift comprising downregulation of epilepsy-associated genes and a rise in cAMP response element binding protein (CREB) activity, which was driven by augmented CREB-regulated transcription coactivator 1 (CRTC1) nuclear localization. Moreover, we demonstrate that ectopic Lnc473 expression increased neuronal excitability as well as network excitability. These findings suggest that primates may possess a lineage-specific activity-dependent modulator of CREB-regulated neuronal excitability.
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19
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Jiang Y, Wang J, Zhou E, Palaniyappan L, Luo C, Ji G, Yang J, Wang Y, Zhang Y, Huang CC, Tsai SJ, Chang X, Xie C, Zhang W, Lv J, Chen D, Shen C, Wu X, Zhang B, Kuang N, Sun YJ, Kang J, Zhang J, Huang H, He H, Duan M, Tang Y, Zhang T, Li C, Yu X, Si T, Yue W, Liu Z, Cui LB, Wang K, Cheng J, Lin CP, Yao D, Cheng W, Feng J, the ZIB Consortium. Neuroimaging biomarkers define neurophysiological subtypes with distinct trajectories in schizophrenia. NATURE MENTAL HEALTH 2023; 1:186-199. [DOI: 10.1038/s44220-023-00024-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 01/23/2023] [Indexed: 03/04/2025]
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20
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Whalen S, Inoue F, Ryu H, Fair T, Markenscoff-Papadimitriou E, Keough K, Kircher M, Martin B, Alvarado B, Elor O, Laboy Cintron D, Williams A, Hassan Samee MA, Thomas S, Krencik R, Ullian EM, Kriegstein A, Rubenstein JL, Shendure J, Pollen AA, Ahituv N, Pollard KS. Machine learning dissection of human accelerated regions in primate neurodevelopment. Neuron 2023; 111:857-873.e8. [PMID: 36640767 PMCID: PMC10023452 DOI: 10.1016/j.neuron.2022.12.026] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 09/29/2022] [Accepted: 12/18/2022] [Indexed: 01/15/2023]
Abstract
Using machine learning (ML), we interrogated the function of all human-chimpanzee variants in 2,645 human accelerated regions (HARs), finding 43% of HARs have variants with large opposing effects on chromatin state and 14% on neurodevelopmental enhancer activity. This pattern, consistent with compensatory evolution, was confirmed using massively parallel reporter assays in chimpanzee and human neural progenitor cells. The species-specific enhancer activity of HARs was accurately predicted from the presence and absence of transcription factor footprints in each species. Despite these striking cis effects, activity of a given HAR sequence was nearly identical in human and chimpanzee cells. This suggests that HARs did not evolve to compensate for changes in the trans environment but instead altered their ability to bind factors present in both species. Thus, ML prioritized variants with functional effects on human neurodevelopment and revealed an unexpected reason why HARs may have evolved so rapidly.
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Affiliation(s)
- Sean Whalen
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Fumitaka Inoue
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Hane Ryu
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA; Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, USA
| | | | - Kathleen Keough
- Gladstone Institutes, San Francisco, CA 94158, USA; Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Martin Kircher
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany; Institute of Human Genetics, University Medical Center Schleswig-Holstein, University of Lübeck, 23562 Lübeck, Germany
| | - Beth Martin
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Beatriz Alvarado
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Orry Elor
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Dianne Laboy Cintron
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | | | | | - Sean Thomas
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Robert Krencik
- Department of Neurosurgery, Center for Neuroregeneration, Houston Methodist Research Institute, Houston, TX, USA
| | - Erik M Ullian
- Departments of Ophthalmology and Physiology, University of California, San Francisco, San Francisco, CA, USA; Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Arnold Kriegstein
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - John L Rubenstein
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Howard Hughes Medical Institute, Seattle, WA 98195, USA; Brotman Baty Institute for Precision Medicine, Seattle, WA 98195, USA
| | - Alex A Pollen
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA; Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
| | - Katherine S Pollard
- Gladstone Institutes, San Francisco, CA 94158, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology and Biostatistics and Institute for Computational Health Sciences, University of California, San Francisco, San Francisco, CA, USA; Chan-Zuckerberg Biohub, San Francisco, CA, USA.
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21
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How to reap the benefits of language for psychiatry. Psychiatry Res 2022; 318:114932. [PMID: 36332505 DOI: 10.1016/j.psychres.2022.114932] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/06/2022] [Accepted: 10/08/2022] [Indexed: 11/19/2022]
Abstract
Our aim is to find accurate and valid markers for diagnosis, prognosis, and the monitoring of treatment to improve outcome for patients with schizophrenia-spectrum disorders. This search has led us into the disciplines of computational linguistics and artificial intelligence, as automatic analysis of spoken language may provide useful markers for psychiatry. Together with our language team at UMC Groningen and with great colleagues around the globe, we intend to push this field forward and provide tools that can support service users in self-monitoring and help clinicians with diagnosis, treatment monitoring and risk prediction.
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22
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Zug R, Uller T. Evolution and dysfunction of human cognitive and social traits: A transcriptional regulation perspective. EVOLUTIONARY HUMAN SCIENCES 2022; 4:e43. [PMID: 37588924 PMCID: PMC10426018 DOI: 10.1017/ehs.2022.42] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/11/2022] [Accepted: 09/11/2022] [Indexed: 11/07/2022] Open
Abstract
Evolutionary changes in brain and craniofacial development have endowed humans with unique cognitive and social skills, but also predisposed us to debilitating disorders in which these traits are disrupted. What are the developmental genetic underpinnings that connect the adaptive evolution of our cognition and sociality with the persistence of mental disorders with severe negative fitness effects? We argue that loss of function of genes involved in transcriptional regulation represents a crucial link between the evolution and dysfunction of human cognitive and social traits. The argument is based on the haploinsufficiency of many transcriptional regulator genes, which makes them particularly sensitive to loss-of-function mutations. We discuss how human brain and craniofacial traits evolved through partial loss of function (i.e. reduced expression) of these genes, a perspective compatible with the idea of human self-domestication. Moreover, we explain why selection against loss-of-function variants supports the view that mutation-selection-drift, rather than balancing selection, underlies the persistence of psychiatric disorders. Finally, we discuss testable predictions.
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Affiliation(s)
- Roman Zug
- Department of Biology, Lund University, Lund, Sweden
| | - Tobias Uller
- Department of Biology, Lund University, Lund, Sweden
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23
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Gargano G, Caletti E, Perlini C, Turtulici N, Bellani M, Bonivento C, Garzitto M, Siri FM, Longo C, Bonetto C, Cristofalo D, Scocco P, Semrov E, Preti A, Lazzarotto L, Gardellin F, Lasalvia A, Ruggeri M, Marini A, Brambilla P, GET UP Group. Language production impairments in patients with a first episode of psychosis. PLoS One 2022; 17:e0272873. [PMID: 35951619 PMCID: PMC9371299 DOI: 10.1371/journal.pone.0272873] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 07/27/2022] [Indexed: 11/18/2022] Open
Abstract
Language production has often been described as impaired in psychiatric diseases such as in psychosis. Nevertheless, little is known about the characteristics of linguistic difficulties and their relation with other cognitive domains in patients with a first episode of psychosis (FEP), either affective or non-affective. To deepen our comprehension of linguistic profile in FEP, 133 patients with FEP (95 non-affective, FEP-NA; 38 affective, FEP-A) and 133 healthy controls (HC) were assessed with a narrative discourse task. Speech samples were systematically analyzed with a well-established multilevel procedure investigating both micro- (lexicon, morphology, syntax) and macro-linguistic (discourse coherence, pragmatics) levels of linguistic processing. Executive functioning and IQ were also evaluated. Both linguistic and neuropsychological measures were secondarily implemented with a machine learning approach in order to explore their predictive accuracy in classifying participants as FEP or HC. Compared to HC, FEP patients showed language production difficulty at both micro- and macro-linguistic levels. As for the former, FEP produced shorter and simpler sentences and fewer words per minute, along with a reduced number of lexical fillers, compared to HC. At the macro-linguistic level, FEP performance was impaired in local coherence, which was paired with a higher percentage of utterances with semantic errors. Linguistic measures were not correlated with any neuropsychological variables. No significant differences emerged between FEP-NA and FEP-A (p≥0.02, after Bonferroni correction). Machine learning analysis showed an accuracy of group prediction of 76.36% using language features only, with semantic variables being the most impactful. Such a percentage was enhanced when paired with clinical and neuropsychological variables. Results confirm the presence of language production deficits already at the first episode of the illness, being such impairment not related to other cognitive domains. The high accuracy obtained by the linguistic set of features in classifying groups support the use of machine learning methods in neuroscience investigations.
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Affiliation(s)
- Giulia Gargano
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Elisabetta Caletti
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan, Italy
| | - Cinzia Perlini
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Verona Hospital Trust–Azienda Ospedaliera Universitaria Integrata Verona–AOUI, Verona, Italy
| | - Nunzio Turtulici
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Marcella Bellani
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Verona Hospital Trust–Azienda Ospedaliera Universitaria Integrata Verona–AOUI, Verona, Italy
| | - Carolina Bonivento
- IRCCS “E.Medea” Polo Friuli Venezia Giulia, San Vito al Tagliamento, PN, Italy
| | - Marco Garzitto
- Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy
| | - Francesca Marzia Siri
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan, Italy
| | - Chiara Longo
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan, Italy
| | - Chiara Bonetto
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Doriana Cristofalo
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Paolo Scocco
- Department of Mental Health, Azienda ULSS 16, Padua, Italy
| | | | - Antonio Preti
- Department of Mental Health, Niguarda Ca’ Granda Hospital, Milan, Italy
| | - Lorenza Lazzarotto
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | | | - Antonio Lasalvia
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Verona Hospital Trust–Azienda Ospedaliera Universitaria Integrata Verona–AOUI, Verona, Italy
| | - Mirella Ruggeri
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Verona Hospital Trust–Azienda Ospedaliera Universitaria Integrata Verona–AOUI, Verona, Italy
| | - Andrea Marini
- Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan, Italy
- * E-mail:
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24
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Genetic variations in evolutionary accelerated regions disrupt cognition in schizophrenia. Psychiatry Res 2022; 314:114586. [PMID: 35623238 PMCID: PMC10150587 DOI: 10.1016/j.psychres.2022.114586] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 04/03/2022] [Accepted: 04/30/2022] [Indexed: 02/03/2023]
Abstract
Cognition is believed to be a product of human evolution, while schizophrenia is ascribed as the by-product with cognitive impairment as it's genetically mediated endophenotype. Genomic loci associated with these traits are enriched with recent evolutionary markers such as Human accelerated regions (HARs). HARs are markedly different in humans since their divergence with chimpanzees and mostly regulate gene expression by binding to transcription factors and/or modulating chromatin interactions. We hypothesize that variants within HARs may alter such functions and thus contribute to disease pathogenesis. 49 systematically prioritized variants from 2737 genome-wide HARs were genotyped in a north-Indian schizophrenia cohort (331 cases, 235 controls). Six variants were significantly associated with cognitive impairment in schizophrenia, thirteen with general cognition in healthy individuals. These variants were mapped to 122 genes; predicted to alter 79 transcription factors binding sites and overlapped with promoters, enhancers and/or repressors. These genes and TFs are implicated in neurocognitive phenotypes, autism, schizophrenia and bipolar disorders; a few are targets of common or repurposable antipsychotics suggesting their draggability; and enriched for immune response and brain developmental pathways. Immune response has been more strongly targeted by natural selection during human evolution and has a prominent role in neurodevelopment. Thus, its disruption may have deleterious consequences for neuronal and cognitive functions. Importantly, among the 15 associated SNPs, 12 showed association in several independent GWASs of different neurocognitive functions. Further analysis of HARs may be valuable to understand their role in cognition biology and identify improved therapeutics for schizophrenia.
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25
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Cheung JP, Tubbs JD, Sham PC. Extended gene set analysis of human neuro-psychiatric traits shows enrichment in brain-expressed human accelerated regions across development. Schizophr Res 2022; 246:148-155. [PMID: 35779326 DOI: 10.1016/j.schres.2022.06.023] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 04/25/2022] [Accepted: 06/20/2022] [Indexed: 11/18/2022]
Abstract
Human neuropsychiatric disorders are associated with genetic and environmental factors affecting the brain, which has been subjected to strong evolutionary pressures resulting in an enlarged cerebral cortex and improved cognitive performance. Thus, genes involved in human brain evolution may also play a role in neuropsychiatric disorders. We test whether genes associated with 7 neuropsychiatric phenotypes are enriched in genomic regions that have experienced rapid changes in human evolution (HARs) and importantly, whether HAR status interacts with developmental brain expression to predict associated genes. We used the most recent publicly available GWAS and gene expression data to test for enrichment of HARs, brain expression, and their interaction. These revealed significant interactions between HAR status and whole-brain expression across developmental stages, indicating that the relationship between brain expression and association with schizophrenia and intelligence is stronger among HAR than non-HAR genes. Follow-up regional analyses indicated that predicted HAR-expression interaction effects may vary substantially across regions and developmental stages. Although depression indicated significant enrichment of HAR genes, little support was found for HAR enrichment among bipolar, autism, ADHD, or Alzheimer's associated genes. Our results indicate that intelligence, schizophrenia, and depression-associated genes are enriched for those involved in the evolution of the human brain. These findings highlight promising candidates for follow-up study and considerations for novel drug development, but also caution careful assessment of the translational ability of animal models for studying neuropsychiatric traits in the context of HARs, and the importance of using humanized animal models or human-derived tissues when researching these traits.
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Affiliation(s)
- Justin P Cheung
- Department of Psychiatry, The University of Hong Kong, Hong Kong, China
| | - Justin D Tubbs
- Department of Psychiatry, The University of Hong Kong, Hong Kong, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China.
| | - Pak C Sham
- Department of Psychiatry, The University of Hong Kong, Hong Kong, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Centre for PanorOmic Sciences, The University of Hong Kong, Hong Kong, China.
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Zhao W, Voon V, Xue K, Xie C, Kang J, Lin CP, Wang J, Cheng J, Feng J. Common abnormal connectivity in first-episode and chronic schizophrenia in pre- and post-central regions: Implications for neuromodulation targeting. Prog Neuropsychopharmacol Biol Psychiatry 2022; 117:110556. [PMID: 35367293 DOI: 10.1016/j.pnpbp.2022.110556] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 03/23/2022] [Accepted: 03/27/2022] [Indexed: 11/30/2022]
Abstract
Schizophrenia is a neurodevelopmental disorder manifesting differing impairments at early onset and chronic disease stages. Brain imaging research suggests a core pathological region in patients with first-episode schizophrenia is Broca's area. With disease progression, alterations in thalamic connectivity becomes more prevalent. Understanding the common circuitry underlying pathology in these two groups might highlight a critical common network and novel targets for treatment. In this study, 937 subject samples were collected including patients with first-episode schizophrenia and those with chronic schizophrenia. We used hypothesis-based voxel-level functional connectivity analyses to calculate functional connectivity using the left Broca's area and thalamus as regions of interest in those with first-episode and chronic schizophrenia, respectively. We show for the first time that in both patients with first-episode and chronic schizophrenia the greatest functional connectivity disruption ended in the pre- and postcentral regions. At the early-onset stage, the core brain region is abnormally connected to pre- and postcentral areas responsible for mouth movement, while in the chronic stage, it expanded to a wider range of sensorimotor areas. Our findings suggest that expanding the focus on the low-order sensory-motor systems beyond high-order cognitive impairments in schizophrenia may show potential for neuromodulation treatment, given the relative accessibility of these cortical regions and their functional and structural connections to the core region at different stages of illness.
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Affiliation(s)
- Wei Zhao
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Kangkang Xue
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Ching-Po Lin
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders (No. 13dz2260500), Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China; Shanghai Center for Mathematical Sciences, Shanghai, China.
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Kang J, Jiao Z, Qin Y, Wang Y, Wang J, Jin L, Feng J, Wang F, Tang Y, Gong X. Associations between polygenic risk scores and amplitude of low-frequency fluctuation of inferior frontal gyrus in schizophrenia. J Psychiatr Res 2022; 147:4-12. [PMID: 34999338 DOI: 10.1016/j.jpsychires.2021.12.043] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 12/14/2021] [Accepted: 12/20/2021] [Indexed: 10/19/2022]
Abstract
Schizophrenia (SCZ) is a serious and complex mental disorder with high heritability. Polygenic risk score (PRS) is a useful tool calculating the accumulating effects of multiple common genetic variants of schizophrenia. The amplitude of low-frequency fluctuation (ALFF) is an efficient index to reflect spontaneous, intrinsic neuronal activity. Aberrant ALFF of brain regions were reported in schizophrenia frequently, but the relationship between PRS and ALFF has not been studied. In the present study, we compared PRS and ALFF in 101 schizophrenia patients and 106 age-matched healthy controls to test their associations with schizophrenia. Then, the correlation of PRS with ALFF was measured to reveal the effect of polygenic risk on brain activity in schizophrenia. We found that schizophrenia patients showed significant differences in PRS and ALFF compared with controls. Twenty-six brain regions showed significant difference of ALFF between schizophrenia cases and controls, of which left inferior frontal gyrus, triangular part (IFGtriang.L) showed increased activity in schizophrenia. PRS-SCZ was positively correlated with ALFF in IFGtriang.L in 57 non-chronic patients. Genes involved in synaptic organization and transmission, especially in glutamatergic synapse, were highly enriched in PRS-SCZ genes, suggesting the dysfunction of synapses in schizophrenia. These results help to understand the molecular mechanism underlying schizophrenia and related brain dysfunction.
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Affiliation(s)
- Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Zeyu Jiao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Yue Qin
- School of Life Sciences, Fudan University, Shanghai, China
| | - Yi Wang
- School of Life Sciences, Fudan University, Shanghai, China
| | - Jiucun Wang
- School of Life Sciences, Fudan University, Shanghai, China; Human Phoneme Institute, Fudan University, Shanghai, China
| | - Li Jin
- School of Life Sciences, Fudan University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China; Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK
| | - Fei Wang
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, China.
| | - Xiaohong Gong
- School of Life Sciences, Fudan University, Shanghai, China.
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Erady C, Amin K, Onilogbo TOAE, Tomasik J, Jukes-Jones R, Umrania Y, Bahn S, Prabakaran S. Novel open reading frames in human accelerated regions and transposable elements reveal new leads to understand schizophrenia and bipolar disorder. Mol Psychiatry 2022; 27:1455-1468. [PMID: 34937870 PMCID: PMC9095477 DOI: 10.1038/s41380-021-01405-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 11/16/2021] [Accepted: 11/24/2021] [Indexed: 12/13/2022]
Abstract
Schizophrenia (SCZ) and bipolar disorder are debilitating neuropsychiatric disorders arising from a combination of environmental and genetic factors. Novel open reading frames (nORFs) are genomic loci that give rise to previously uncharacterized transcripts and protein products. In our previous work, we have shown that nORFs can be biologically regulated and that they may play a role in cancer and rare diseases. More importantly, we have shown that nORFs may emerge in accelerated regions of the genome giving rise to species-specific functions. We hypothesize that nORFs represent a potentially important group of biological factors that may contribute to SCZ and bipolar disorder pathophysiology. Human accelerated regions (HARs) are genomic features showing human-lineage-specific rapid evolution that may be involved in biological regulation and have additionally been found to associate with SCZ genes. Transposable elements (TEs) are another set of genomic features that have been shown to regulate gene expression. As with HARs, their relevance to SCZ has also been suggested. Here, nORFs are investigated in the context of HARs and TEs. This work shows that nORFs whose expression is disrupted in SCZ and bipolar disorder are in close proximity to HARs and TEs and that some of them are significantly associated with SCZ and bipolar disorder genomic hotspots. We also show that nORF encoded proteins can form structures and potentially constitute novel drug targets.
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Affiliation(s)
- Chaitanya Erady
- grid.5335.00000000121885934Department of Genetics, University of Cambridge, Cambridge, CB2 3EH UK
| | - Krishna Amin
- grid.5335.00000000121885934Department of Genetics, University of Cambridge, Cambridge, CB2 3EH UK
| | - Temiloluwa O. A. E. Onilogbo
- grid.5335.00000000121885934Department of Genetics, University of Cambridge, Cambridge, CB2 3EH UK ,grid.5335.00000000121885934Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Jakub Tomasik
- grid.5335.00000000121885934Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Rebekah Jukes-Jones
- grid.9918.90000 0004 1936 8411Leicester Cancer Research Centre, RKCSB, University of Leicester, University Road, Leicester, LE1 7RH UK
| | - Yagnesh Umrania
- grid.5335.00000000121885934Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QR UK
| | - Sabine Bahn
- grid.5335.00000000121885934Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
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Panov G. Comparative Analysis of Lateral Preferences in Patients With Resistant Schizophrenia. Front Psychiatry 2022; 13:868285. [PMID: 35479496 PMCID: PMC9037324 DOI: 10.3389/fpsyt.2022.868285] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 02/22/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Schizophrenia is a chronic brain disorder of diverse etiology and clinical presentation. Despite the expansion of treatment methods, between 30 and 50% of cases remain resistant to treatment. In patients with schizophrenia, specifics in the dominant lateralization in the brain function have been discovered. This gave a reason to seek the relation between functional lateralization and the effect of treatment. METHODS Of the 105 people observed with schizophrenia, 45 (42.9%) were treatment resistant, and 60 (57.1%) were considered responders. We compared functional lateralization (hand, foot, and eye) between the two groups. Handedness was ascertained by using the Edinburgh Handedness Inventory. The assessment was made at 12 weeks of treatment. RESULTS Of all patients with schizophrenia, 41.89% have mixed lateralization, 53.34% are right winged, and 4.76% of the patients are left winged. Resistance of the symptoms shows that 26 (57.78%) are cross-dominated, 18 (40%) are right winged, and 1 (2.22%) is left winged. In patients with clinical remission, 18 (30%) are of mixed dominance, 38 (63.33%) are right winged, and 4 (6.66%) are left winged. From the results for the separate lateralization of the hand, foot, and eye, we found a significant difference only in terms of the dominance of the eye. In 44 (41.9%) of the patients, we found dominance of the left eye. In patients with resistance, the percentage established by us is higher-at 26 (57.8%). These results indicate that the increased percentage of mixed dominance in patients with schizophrenia is mainly due to left-sided lateralization of the eye, especially in those with resistance to treatment. CONCLUSION We find an increased number of patients with cross-dominance left eye dominance in patients with schizophrenia. Cross-dominance and left eye dominance are associated with a higher probability of symptom resistance than other forms of lateralization (left-handed or right-handed). The high percentage of cross-dominance is due to the high percentage of left-sided dominance of the eye.
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Affiliation(s)
- Georgi Panov
- Psychiatric Clinic, University Hospital for Active Treatment "Prof. Dr. Stoian Kirkovic", Trakia University, Stara Zagora, Bulgaria
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30
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Historical pursuits of the language pathway hypothesis of schizophrenia. NPJ SCHIZOPHRENIA 2021; 7:53. [PMID: 34753947 PMCID: PMC8578658 DOI: 10.1038/s41537-021-00182-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 09/13/2021] [Indexed: 12/21/2022]
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Berto S, Liu Y, Konopka G. Genomics at cellular resolution: insights into cognitive disorders and their evolution. Hum Mol Genet 2021; 29:R1-R9. [PMID: 32566943 DOI: 10.1093/hmg/ddaa117] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 06/05/2020] [Accepted: 06/11/2020] [Indexed: 02/06/2023] Open
Abstract
High-throughput genomic sequencing approaches have held the promise of understanding and ultimately leading to treatments for cognitive disorders such as autism spectrum disorders, schizophrenia and Alzheimer's disease. Although significant progress has been made into identifying genetic variants associated with these diseases, these studies have also uncovered that these disorders are mostly genetically complex and thus challenging to model in non-human systems. Improvements in such models might benefit from understanding the evolution of the human genome and how such modifications have affected brain development and function. The intersection of genome-wide variant information with cell-type-specific expression and epigenetic information will further assist in resolving the contribution of particular cell types in evolution or disease. For example, the role of non-neuronal cells in brain evolution and cognitive disorders has gone mostly underappreciated until the recent availability of single-cell transcriptomic approaches. In this review, we discuss recent studies that carry out cell-type-specific assessments of gene expression in brain tissue across primates and between healthy and disease populations. The emerging results from these studies are beginning to elucidate how specific cell types in the evolved human brain are contributing to cognitive disorders.
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Abstract
For decades clinicians and researchers have been thinking and writing about the spectrum of schizophrenia disorders. Indeed both Kraepelin and Bleuler believed in schizophrenia as a spectrum, both in a clinical (individual) and hereditary (family) continuum, from just some exquisite personality traits to unquestionable chronic and debilitating psychosis. Other authors would put the schizophrenia spectrum disorders on different levels of continuum: developmental, psychofunctional, existential, and genetic. Here, we would like to present an historical chronology for the schizophrenia-schizoaffective-bipolar spectra plus a tridimensional model for these spectra: the first axis for categories (affective versus nonaffective psychoses), the second axis for dimensions (personality versus full blown psychosis), and a third axis for biomarkers (remission versus relapse). We believe that without the schizophrenia-schizoaffective-bipolar spectra concept in our minds all our efforts will keep failing one the hardest quest: searching for biomarkers in schizophrenia and related disorders.
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Guevara EE, Hopkins WD, Hof PR, Ely JJ, Bradley BJ, Sherwood CC. Comparative analysis reveals distinctive epigenetic features of the human cerebellum. PLoS Genet 2021; 17:e1009506. [PMID: 33956822 PMCID: PMC8101944 DOI: 10.1371/journal.pgen.1009506] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Accepted: 03/24/2021] [Indexed: 12/13/2022] Open
Abstract
Identifying the molecular underpinnings of the neural specializations that underlie human cognitive and behavioral traits has long been of considerable interest. Much research on human-specific changes in gene expression and epigenetic marks has focused on the prefrontal cortex, a brain structure distinguished by its role in executive functions. The cerebellum shows expansion in great apes and is gaining increasing attention for its role in motor skills and cognitive processing, including language. However, relatively few molecular studies of the cerebellum in a comparative evolutionary context have been conducted. Here, we identify human-specific methylation in the lateral cerebellum relative to the dorsolateral prefrontal cortex, in a comparative study with chimpanzees (Pan troglodytes) and rhesus macaques (Macaca mulatta). Specifically, we profiled genome-wide methylation levels in the three species for each of the two brain structures and identified human-specific differentially methylated genomic regions unique to each structure. We further identified which differentially methylated regions (DMRs) overlap likely regulatory elements and determined whether associated genes show corresponding species differences in gene expression. We found greater human-specific methylation in the cerebellum than the dorsolateral prefrontal cortex, with differentially methylated regions overlapping genes involved in several conditions or processes relevant to human neurobiology, including synaptic plasticity, lipid metabolism, neuroinflammation and neurodegeneration, and neurodevelopment, including developmental disorders. Moreover, our results show some overlap with those of previous studies focused on the neocortex, indicating that such results may be common to multiple brain structures. These findings further our understanding of the cerebellum in human brain evolution. Humans are distinguished from other species by several aspects of cognition. While much comparative evolutionary neuroscience has focused on the neocortex, increasing recognition of the cerebellum’s role in cognition and motor processing has inspired considerable new research. Comparative molecular studies, however, generally continue to focus on the neocortex. We sought to characterize potential genetic regulatory traits distinguishing the human cerebellum by undertaking genome-wide epigenetic profiling of the lateral cerebellum, and compared this to the prefrontal cortex of humans, chimpanzees, and rhesus macaque monkeys. We found that humans showed greater differential CpG methylation–an epigenetic modification of DNA that can reflect past or present gene expression–in the cerebellum than the prefrontal cortex, highlighting the importance of this structure in human brain evolution. Humans also specifically show methylation differences at genes involved in neurodevelopment, neuroinflammation, synaptic plasticity, and lipid metabolism. These differences are relevant for understanding processes specific to humans, such as extensive plasticity, as well as pronounced and prevalent neurodegenerative conditions associated with aging.
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Affiliation(s)
- Elaine E. Guevara
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina, United States of America
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, District of Columbia, United States of America
- * E-mail:
| | - William D. Hopkins
- Keeling Center for Comparative Medicine and Research, University of Texas MD Anderson Cancer Center, Bastrop, Texas, United States of America
| | - Patrick R. Hof
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- New York Consortium in Evolutionary Primatology, New York, New York, United States of America
| | - John J. Ely
- MAEBIOS, Alamogordo, New Mexico, United States of America
| | - Brenda J. Bradley
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, District of Columbia, United States of America
| | - Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, District of Columbia, United States of America
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Bhattacharyya U, Deshpande SN, Bhatia T, Thelma BK. Revisiting Schizophrenia from an Evolutionary Perspective: An Association Study of Recent Evolutionary Markers and Schizophrenia. Schizophr Bull 2021; 47:827-836. [PMID: 33350444 PMCID: PMC8759809 DOI: 10.1093/schbul/sbaa179] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The persistence of schizophrenia in human populations at a high prevalence and with a large heritability estimate despite reduced fertility and increased mortality rate is a Darwinian paradox. This may be likely if the genomic components that predispose to schizophrenia are also advantageous for the acquisition of important human traits, such as language and cognition. Accordingly, an emerging group of genomic markers of recent evolution in humans, namely human accelerated regions (HARs), since our divergence from chimpanzees, are gaining importance for neurodevelopmental disorders, such as schizophrenia. We hypothesize that variants within HARs may affect the expression of genes under their control, thus contributing to disease etiology. A total of 49 HAR single nucleotide polymorphisms (SNPs) were prioritized from the complete repertoire of HARs (n = 2737) based on their functional relevance and prevalence in the South Asian population. Test of association using 2 independent schizophrenia case-control cohorts of north Indian ethnicity (discovery: n = 930; replication: n = 1104) revealed 3 SNPs (rs3800926, rs3801844, and rs764453) from chromosome 7 and rs77047799 from chromosome 3 to be significantly associated (combined analysis: Bonferroni corrected P < .002-.000004). Of note, these SNPs were found to alter the expression of neurodevelopmental genes such as SLC25A13, MAD1L1, and ULK4; a few from the HOX gene family; and a few genes that are implicated in mitochondrial function. These SNPs may most likely alter binding sites of transcription factors, including TFCP2, MAFK, SREBF2, E2F1, and/or methylation signatures around these genes. These findings reiterate a neurodevelopmental basis of schizophrenia and also open up a promising avenue to investigate HAR-mediated mitochondrial dysfunction in schizophrenia etiology.
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Affiliation(s)
| | | | | | - B K Thelma
- Department of Genetics, University of Delhi South Campus, New Delhi, India
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Wortinger LA, Jørgensen KN, Barth C, Nerland S, Smelror RE, Vaskinn A, Ueland T, Andreassen OA, Agartz I. Significant association between intracranial volume and verbal intellectual abilities in patients with schizophrenia and a history of birth asphyxia. Psychol Med 2021; 52:1-10. [PMID: 33750510 PMCID: PMC9772907 DOI: 10.1017/s0033291721000489] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 01/20/2021] [Accepted: 02/04/2021] [Indexed: 12/30/2022]
Abstract
BACKGROUND The etiology of schizophrenia (SZ) is proposed to include an interplay between a genetic risk for disease development and the biological environment of pregnancy and birth, where early adversities may contribute to the poorer developmental outcome. We investigated whether a history of birth asphyxia (ASP) moderates the relationship between intracranial volume (ICV) and intelligence in SZ, bipolar disorder (BD) and healthy controls (HC). METHODS Two hundred seventy-nine adult patients (18-42 years) on the SZ and BD spectrums and 216 HC were evaluated for ASP based on information from the Medical Birth Registry of Norway. Participants underwent structural magnetic resonance imaging (MRI) to estimate ICV and intelligence quotient (IQ) assessment using the Wechsler Abbreviated Scale of Intelligence (WASI). Multiple linear regressions were used for analyses. RESULTS We found a significant three-way interaction (ICV × ASP × diagnosis) on the outcome variable, IQ, indicating that the correlation between ICV and IQ was stronger in patients with SZ who experienced ASP compared to SZ patients without ASP. This moderation by ASP was not found in BD or HC groups. In patients with SZ, the interaction between ICV and a history of the ASP was specifically related to the verbal subcomponent of IQ as measured by WASI. CONCLUSIONS The significant positive association between ICV and IQ in patients with SZ who had experienced ASP might indicate abnormal neurodevelopment. Our findings give support for ICV together with verbal intellectual abilities as clinically relevant markers that can be added to prediction tools to enhance evaluations of SZ risk.
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Affiliation(s)
- Laura Anne Wortinger
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kjetil Nordbø Jørgensen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Runar Elle Smelror
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anja Vaskinn
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, NORMENT, Oslo University Hospital, Oslo, Norway
| | - Torill Ueland
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, NORMENT, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, NORMENT, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
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Du J, Palaniyappan L, Liu Z, Cheng W, Gong W, Zhu M, Wang J, Zhang J, Feng J. The genetic determinants of language network dysconnectivity in drug-naïve early stage schizophrenia. NPJ SCHIZOPHRENIA 2021; 7:18. [PMID: 33658499 PMCID: PMC7930279 DOI: 10.1038/s41537-021-00141-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 01/12/2021] [Indexed: 01/31/2023]
Abstract
Schizophrenia is a neurocognitive illness of synaptic and brain network-level dysconnectivity that often reaches a persistent chronic stage in many patients. Subtle language deficits are a core feature even in the early stages of schizophrenia. However, the primacy of language network dysconnectivity and language-related genetic variants in the observed phenotype in early stages of illness remains unclear. This study used two independent schizophrenia dataset consisting of 138 and 53 drug-naïve first-episode schizophrenia (FES) patients, and 112 and 56 healthy controls, respectively. A brain-wide voxel-level functional connectivity analysis was conducted to investigate functional dysconnectivity and its relationship with illness duration. We also explored the association between critical language-related genetic (such as FOXP2) mutations and the altered functional connectivity in patients. We found elevated functional connectivity involving Broca's area, thalamus and temporal cortex that were replicated in two FES datasets. In particular, Broca's area - anterior cingulate cortex dysconnectivity was more pronounced for patients with shorter illness duration, while thalamic dysconnectivity was predominant in those with longer illness duration. Polygenic risk scores obtained from FOXP2-related genes were strongly associated with functional dysconnectivity identified in patients with shorter illness duration. Our results highlight the criticality of language network dysconnectivity, involving the Broca's area in early stages of schizophrenia, and the role of language-related genes in this aberration, providing both imaging and genetic evidence for the association between schizophrenia and the determinants of language.
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Affiliation(s)
- Jingnan Du
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Lena Palaniyappan
- Department of Psychiatry and Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Lawson Health Research Institute, London, ON, Canada
| | - Zhaowen Liu
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Weikang Gong
- Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Mengmeng Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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Gualtieri CT. Genomic Variation, Evolvability, and the Paradox of Mental Illness. Front Psychiatry 2021; 11:593233. [PMID: 33551865 PMCID: PMC7859268 DOI: 10.3389/fpsyt.2020.593233] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 11/27/2020] [Indexed: 12/30/2022] Open
Abstract
Twentieth-century genetics was hard put to explain the irregular behavior of neuropsychiatric disorders. Autism and schizophrenia defy a principle of natural selection; they are highly heritable but associated with low reproductive success. Nevertheless, they persist. The genetic origins of such conditions are confounded by the problem of variable expression, that is, when a given genetic aberration can lead to any one of several distinct disorders. Also, autism and schizophrenia occur on a spectrum of severity, from mild and subclinical cases to the overt and disabling. Such irregularities reflect the problem of missing heritability; although hundreds of genes may be associated with autism or schizophrenia, together they account for only a small proportion of cases. Techniques for higher resolution, genomewide analysis have begun to illuminate the irregular and unpredictable behavior of the human genome. Thus, the origins of neuropsychiatric disorders in particular and complex disease in general have been illuminated. The human genome is characterized by a high degree of structural and behavioral variability: DNA content variation, epistasis, stochasticity in gene expression, and epigenetic changes. These elements have grown more complex as evolution scaled the phylogenetic tree. They are especially pertinent to brain development and function. Genomic variability is a window on the origins of complex disease, neuropsychiatric disorders, and neurodevelopmental disorders in particular. Genomic variability, as it happens, is also the fuel of evolvability. The genomic events that presided over the evolution of the primate and hominid lineages are over-represented in patients with autism and schizophrenia, as well as intellectual disability and epilepsy. That the special qualities of the human genome that drove evolution might, in some way, contribute to neuropsychiatric disorders is a matter of no little interest.
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38
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Giosan C. ‘Slow’ reproductive strategy: A negative predictor of depressive symptomatology. AUSTRALIAN JOURNAL OF PSYCHOLOGY 2020. [DOI: 10.1111/ajpy.12016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Cezar Giosan
- Berkeley College, New York, USA; Babeş‐Bolyai University, Cluj‐Napoca, Romania
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39
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Zhang X, Braun U, Harneit A, Zang Z, Geiger LS, Betzel RF, Chen J, Schweiger JI, Schwarz K, Reinwald JR, Fritze S, Witt S, Rietschel M, Nöthen MM, Degenhardt F, Schwarz E, Hirjak D, Meyer-Lindenberg A, Bassett DS, Tost H. Generative network models of altered structural brain connectivity in schizophrenia. Neuroimage 2020; 225:117510. [PMID: 33160087 DOI: 10.1016/j.neuroimage.2020.117510] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 10/20/2020] [Accepted: 10/22/2020] [Indexed: 12/30/2022] Open
Abstract
Alterations in the structural connectome of schizophrenia patients have been widely characterized, but the mechanisms remain largely unknown. Generative network models have recently been introduced as a tool to test the biological underpinnings of altered brain network formation. We evaluated different generative network models in healthy controls (n=152), schizophrenia patients (n=66), and their unaffected first-degree relatives (n=32), and we identified spatial and topological factors contributing to network formation. We further investigated how these factors relate to cognition and to polygenic risk for schizophrenia. Our data show that among the four tested classes of generative network models, structural brain networks were optimally accounted for by a two-factor model combining spatial constraints and topological neighborhood structure. The same wiring model explained brain network formation across study groups. However, relatives and schizophrenia patients exhibited significantly lower spatial constraints and lower topological facilitation compared to healthy controls. Further exploratory analyses point to potential associations of the model parameter reflecting spatial constraints with the polygenic risk for schizophrenia and cognitive performance. Our results identify spatial constraints and local topological structure as two interrelated mechanisms contributing to regular brain network formation as well as altered connectomes in schizophrenia and healthy individuals at familial risk for schizophrenia. On an exploratory level, our data further point to the potential relevance of spatial constraints for the genetic risk for schizophrenia and general cognitive functioning, thereby encouraging future studies in following up on these observations to gain further insights into the biological basis and behavioral relevance of model parameters.
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Affiliation(s)
- Xiaolong Zhang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Urs Braun
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany; Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
| | - Anais Harneit
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Zhenxiang Zang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Lena S Geiger
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Richard F Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Junfang Chen
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Janina I Schweiger
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Kristina Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Jonathan Rochus Reinwald
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Stefan Fritze
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Stephanie Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
| | - Danielle S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Department of Electrical & Systems Engineering, Department of Neurology, and Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, USA; Santa Fe Institute, Santa Fe, NM USA
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5 68159 Mannheim, Germany
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Panikratova YR, Vlasova RM, Akhutina TV, Tikhonov DV, Pluzhnikov IV, Kaleda VG. [Executive control of language production in schizophrenia: a pilot neuropsychological study]. Zh Nevrol Psikhiatr Im S S Korsakova 2020; 120:14-22. [PMID: 32929919 DOI: 10.17116/jnevro202012008114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
OBJECTIVE To test the general hypothesis about executive deficits in language production in schizophrenia as well as more specific hypothesis that this deficit would be more pronounced in the case of higher demand on executive functions. MATERIAL AND METHODS Twenty-five patients with schizophrenia and twenty-seven healthy controls were asked to tell a story based on a series of pictures and then to give an oral composition on the given topic. RESULTS AND CONCLUSION Schizophrenia patients, compared to controls, demonstrated poorer programming as well as shorter text and phrase length in both tasks. Oral composition on the given topic in patients was characterized by the presence of agrammatism, need for leading questions due to the difficulties of story plot generation as well as higher variance in syntactic complexity and text length. Therefore, the authors revealed executive deficit in language production, more pronounced in the task with less numerous external cues for planning and sequential text explication, in schizophrenia patients.
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Affiliation(s)
| | - R M Vlasova
- University of North Carolina, Chapel Hill, USA
| | - T V Akhutina
- Lomonosov Moscow State University, Moscow, Russia
| | | | | | - V G Kaleda
- Mental Health Research Center, Moscow, Russia
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41
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Smeland OB, Frei O, Dale AM, Andreassen OA. The polygenic architecture of schizophrenia — rethinking pathogenesis and nosology. Nat Rev Neurol 2020; 16:366-379. [DOI: 10.1038/s41582-020-0364-0] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2020] [Indexed: 02/07/2023]
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42
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Hunter RG. Stress, Adaptation, and the Deep Genome: Why Transposons Matter. Integr Comp Biol 2020; 60:1495-1505. [DOI: 10.1093/icb/icaa050] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Synopsis
Stress is a common, if often unpredictable life event. It can be defined from an evolutionary perspective as a force an organism perceives it must adapt to. Thus stress is a useful tool to study adaptation and the adaptive capacity of organisms. The deep genome, long neglected as a pile of “junk” has emerged as a source of regulatory DNA and RNA as well as a potential stockpile of adaptive capacity at the organismal and species levels. Recent work on the regulation of transposable elements (TEs), the principle constituents of the deep genome, by stress has shown that these elements are responsive to host stress and other environmental cues. Further, we have shown that some are likely directly regulated by the glucocorticoid receptor (GR), one of the two major vertebrate stress steroid receptors in a fashion that appears adaptive. On the basis of this and other emerging evidence I argue that the deep genome may represent an adaptive toolkit for organisms to respond to their environments at both individual and evolutionary scales. This argues that genomes may be adapted for what Waddington called “trait adaptability” rather than being purely passive objects of natural selection and single nucleotide level mutation.
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Affiliation(s)
- Richard G Hunter
- Department of Psychology, University of Massachusetts Boston, 100 William T. Morrissey Blvd, Boston, MA 02125, USA
- Laboratory of Neuroendocrinology, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA
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43
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Diagnosis and Construction of Speech Coherence Disorders in Schizophasia. CURRENT PROBLEMS OF PSYCHIATRY 2020. [DOI: 10.2478/cpp-2019-0012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Abstract
Introduction: Language disorders defined as schizophasia are one of the key symptoms of schizophrenia, especially in the disorganized form of this psychosis, which is reflected in the description of “loose associations” as one of the core negative symptoms according to P. E. Bleuler. At present, the disruption of text at the level of discourse coherence and syntactic impoverishment at the sentence level are regarded as the linguistic basis of schizophasia. The most often applied tool for clinical assessment of schizophasia is the Scale for the Assessment of Thought, Language, and Communication (TLC) devised by N. Andreasen.
Objective: The paper presents language samples of patients suffering from schizophrenia with a high intensity of schizophasia, but above all, text samples created by speech therapy students, which were supposed to simulate the language pathology of the sick. The aim of the study was to compare these two corps of the text in order to assess how classes on schizophasia affect the understanding of specific language phenomena in the field of text coherence disorders, such as derailment, incoherence, distractible speech, loss of goal.
Material:
1. Text body obtained from two patients suffering from schizophrenia with a high level of schizophasia.
2. Corpus of the text constructed by two students of speech therapy, during academic classes on schizophasia.
Results: This study presents specimens of speech by schizophrenic patients with a high intensity of schizophasia, but first of all text specimens authored by logopedics students, which were intended to simulate the language pathology of patients suffering from schizophasia.
Conclusions: The essence of schizophasic language disorders is apparently the disorders of text coherence at the pragmatic, semantic and syntactic levels. The presented schizophasic utterances constructed by logopedics students are very similar to genuine specimens of schizophasic speech – they are proof of the understanding of what schizophasia is. We may hope that the presentation of language disorders from the texts spoken by patients with schizophrenia, and then the attempt to construct analogous utterances, is conducive to better understanding of the essence of schizophasia, i.e. the disruption of text at the level of building the whole utterance but also at the sentence (phrase) level in the form of syntactic impoverishment.
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44
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Wallentin M. Gender differences in language are small but matter for disorders. HANDBOOK OF CLINICAL NEUROLOGY 2020; 175:81-102. [DOI: 10.1016/b978-0-444-64123-6.00007-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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45
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Wang K, Zhao YL, Tan SP, Zhang JG, Li D, Chen JX, Zhang LG, Yu XY, Zhao D, Cheung EFC, Turetsky BI, Gur RC, Chan RCK. Semantic processing event‐related potential features in patients with schizophrenia and bipolar disorder. Psych J 2019; 9:247-257. [PMID: 31788984 DOI: 10.1002/pchj.321] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2019] [Revised: 10/15/2019] [Accepted: 10/16/2019] [Indexed: 11/07/2022]
Affiliation(s)
- Kui Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yan-Li Zhao
- Beijing Huilongguan Hospital, Beijing, China
| | | | | | - Dong Li
- Beijing Huilongguan Hospital, Beijing, China
| | | | | | - Xin-Yang Yu
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Dan Zhao
- School of Education, Changchun Normal University, Changchun, China
| | | | - Bruce I Turetsky
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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46
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Abstract
This scientific commentary refers to ‘Evolutionary modifications in human brain connectivity associated with schizophrenia’ by van den Heuvel et al. (doi:10.1093/brain/awz330).
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Affiliation(s)
- Petra E Vértes
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK.,The Alan Turing Institute, London NW1 2DB, UK
| | - Jakob Seidlitz
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA
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47
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van den Heuvel MP, Scholtens LH, de Lange SC, Pijnenburg R, Cahn W, van Haren NEM, Sommer IE, Bozzali M, Koch K, Boks MP, Repple J, Pievani M, Li L, Preuss TM, Rilling JK. Evolutionary modifications in human brain connectivity associated with schizophrenia. Brain 2019; 142:3991-4002. [PMID: 31724729 PMCID: PMC6906591 DOI: 10.1093/brain/awz330] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 08/13/2019] [Accepted: 09/05/2019] [Indexed: 12/21/2022] Open
Abstract
The genetic basis and human-specific character of schizophrenia has led to the hypothesis that human brain evolution may have played a role in the development of the disorder. We examined schizophrenia-related changes in brain connectivity in the context of evolutionary changes in human brain wiring by comparing in vivo neuroimaging data from humans and chimpanzees, one of our closest living evolutionary relatives and a species with which we share a very recent common ancestor. We contrasted the connectome layout between the chimpanzee and human brain and compared differences with the pattern of schizophrenia-related changes in brain connectivity as observed in patients. We show evidence of evolutionary modifications of human brain connectivity to significantly overlap with the cortical pattern of schizophrenia-related dysconnectivity (P < 0.001, permutation testing). We validated these effects in three additional, independent schizophrenia datasets. We further assessed the specificity of effects by examining brain dysconnectivity patterns in seven other psychiatric and neurological brain disorders (including, among others, major depressive disorder and obsessive-compulsive disorder, arguably characterized by behavioural symptoms that are less specific to humans), which showed no such associations with modifications of human brain connectivity. Comparisons of brain connectivity across humans, chimpanzee and macaques further suggest that features of connectivity that evolved in the human lineage showed the strongest association to the disorder, that is, brain circuits potentially related to human evolutionary specializations. Taken together, our findings suggest that human-specific features of connectome organization may be enriched for changes in brain connectivity related to schizophrenia. Modifications in human brain connectivity in service of higher order brain functions may have potentially also rendered the brain vulnerable to brain dysfunction.
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Affiliation(s)
- Martijn P van den Heuvel
- Connectome Lab, Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Lianne H Scholtens
- Connectome Lab, Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Siemon C de Lange
- Connectome Lab, Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Rory Pijnenburg
- Connectome Lab, Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, The Netherlands
| | - Neeltje E M van Haren
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Iris E Sommer
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, The Netherlands
- Department of Neuroscience and Department of Psychiatry, University Medical Center Groningen, The Netherlands
| | - Marco Bozzali
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, East Sussex, UK
- Neuroimaging Laboratory, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Kathrin Koch
- Department of Neuroradiology and TUM-Neuroimaging Center (TUM-NIC), School of Medicine, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- Graduate School of Systemic Neurosciences GSN, Ludwig-Maximilians-Universität, Biocenter, Munich, Germany
| | - Marco P Boks
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, The Netherlands
| | - Jonathan Repple
- Department of Psychiatry, University of Muenster, Muenster, Germany
| | - Michela Pievani
- Lab Alzheimer’s Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Longchuan Li
- Marcus Autism Center, Children’s Healthcare of Atlanta, Emory University School of Medicine, Atlanta, GA, USA
| | - Todd M Preuss
- Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA
- Center for Translational Social Neuroscience, Emory University, Atlanta, GA, USA
- Center for Behavioral Neuroscience, Atlanta, GA, USA
| | - James K Rilling
- Center for Translational Social Neuroscience, Emory University, Atlanta, GA, USA
- Center for Behavioral Neuroscience, Atlanta, GA, USA
- Department of Anthropology, Emory University, 1557 Dickey Drive, Atlanta, GA 30322, USA
- Department of Psychiatry and Behavioral Sciences, Emory University, 201 Dowman Drive, Atlanta, GA 30322, USA
- Division of Developmental and Cognitive Neuroscience, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA
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Wei Y, de Lange SC, Scholtens LH, Watanabe K, Ardesch DJ, Jansen PR, Savage JE, Li L, Preuss TM, Rilling JK, Posthuma D, van den Heuvel MP. Genetic mapping and evolutionary analysis of human-expanded cognitive networks. Nat Commun 2019; 10:4839. [PMID: 31649260 PMCID: PMC6813316 DOI: 10.1038/s41467-019-12764-8] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 09/24/2019] [Indexed: 01/04/2023] Open
Abstract
Cognitive brain networks such as the default-mode network (DMN), frontoparietal network, and salience network, are key functional networks of the human brain. Here we show that the rapid evolutionary cortical expansion of cognitive networks in the human brain, and most pronounced the DMN, runs parallel with high expression of human-accelerated genes (HAR genes). Using comparative transcriptomics analysis, we present that HAR genes are differentially more expressed in higher-order cognitive networks in humans compared to chimpanzees and macaques and that genes with high expression in the DMN are involved in synapse and dendrite formation. Moreover, HAR and DMN genes show significant associations with individual variations in DMN functional activity, intelligence, sociability, and mental conditions such as schizophrenia and autism. Our results suggest that the expansion of higher-order functional networks subserving increasing cognitive properties has been an important locus of genetic changes in recent human brain evolution.
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Affiliation(s)
- Yongbin Wei
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Siemon C de Lange
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Lianne H Scholtens
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Kyoko Watanabe
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Dirk Jan Ardesch
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Philip R Jansen
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Longchuan Li
- Marcus Autism Center, Children's Healthcare of Atlanta, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Todd M Preuss
- Division of Neuropharmacology and Neurologic Diseases, Emory University, Atlanta, GA, 30322, USA
- Center for Translational Social Neuroscience, Emory University, Atlanta, GA, 30322, USA
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30322, USA
| | - James K Rilling
- Center for Translational Social Neuroscience, Emory University, Atlanta, GA, 30322, USA
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30322, USA
- Department of Anthropology, Emory University, Atlanta, GA, 30322, USA
- Center for Behavioral Neuroscience, Emory University, Atlanta, GA, 30322, USA
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, 30322, USA
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, Amsterdam UMC, 1081 HV, Amsterdam, The Netherlands
| | - Martijn P van den Heuvel
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands.
- Department of Clinical Genetics, Amsterdam Neuroscience, Amsterdam UMC, 1081 HV, Amsterdam, The Netherlands.
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A biocultural approach to psychiatric illnesses. Psychopharmacology (Berl) 2019; 236:2923-2936. [PMID: 30721322 DOI: 10.1007/s00213-019-5178-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 01/21/2019] [Indexed: 12/13/2022]
Abstract
RATIONALE As a species, humans are vulnerable to numerous mental disorders, including depression and schizophrenia. This susceptibility may be due to the evolution of our large, complex brains, or perhaps because these illnesses counterintuitively confer some adaptive advantage. Additionally, cultural and biological factors may contribute to susceptibility and variation in mental illness experience and expression. Taking a holistic perspective could strengthen our understanding of these illnesses in diverse cultural contexts. OBJECTIVES This paper reviews some of these potential factors and contextualizes mental disorders within a biocultural framework. RESULTS There is growing evidence that suggests cultural norms may influence inflammation, neurotransmitters, and neurobiology, as well as the illness experience. Specific examples include variation in schizophrenia delusions between countries, differences in links between inflammation and emotion between the United States and Japan, and differences in brain activity between Caucasian and Asian participants indicating that cultural values may moderate cognitive processes related to social cognition and interoception. CONCLUSIONS Research agendas that are grounded in an appreciation of biocultural diversity as it relates to psychiatric illness represent key areas for truly interdisciplinary research that can result in culturally sensitive treatments and highlight possible biological variation affecting medical treatment.
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Delvecchio G, Caletti E, Perlini C, Siri FM, Andreella A, Finos L, Bellani M, Fabbro F, Lasalvia A, Bonetto C, Cristofalo D, Scocco P, D'Agostino A, Torresani S, Imbesi M, Bellini F, Veronese A, Bressi C, Ruggeri M, Brambilla P. Altered syntactic abilities in first episode patients: An inner phenomenon characterizing psychosis. Eur Psychiatry 2019; 61:119-126. [PMID: 31442739 DOI: 10.1016/j.eurpsy.2019.08.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 08/01/2019] [Accepted: 08/02/2019] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Research has consistently shown that language abilities represent a core dimension of psychosis; however, to date, very little is known about syntactic comprehension performance in the early stages of psychosis. This study aims to compare the linguistic abilities involved in syntactic comprehension in a large group of First Episode Psychosis (FEP) patients and healthy controls (HCs). METHODS A multiple choice test of comprehension of syntax was administered to 218 FEP patients (166 non-affective FEP patients [FEP-NA] and 52 affective FEP patients [FEP-A]) and 106 HCs. All participants were asked to match a sentence they listen with one out of four vignettes on a pc screen. Only one vignette represents the stimulus target, while the others are grammatical or non-grammatical (visual) distractors. Both grammatical and non-grammatical errors and performance in different syntactic constructions were considered. RESULTS FEP committed greater number of errors in the majority of TCGB language domains compared to HCs. Moreover, FEP-NA patients committed significantly more non-grammatical (z = -3.2, p = 0.007), locative (z = -4.7, p < 0.001), passive-negative (z = -3.2, p = 0.02), and relative (z = -4.6, p < 0.001) errors compared to HCs as well as more passive-affirmative errors compared to both HCs (z = -4.3, p < 0.001) and FEP-A (z = 3.1, p = 0.04). Finally, we also found that both FEP-NA and FEP-A committed more grammatical (FEP-NA: z = -9.2, p < 0.001 and FEP-A: z = -4.4, p < 0.001), total (FEP-NA: z = -8.2, p < 0.001 and FEP-A: z = 3.9, p = 0.002), and active-negative (FEP-NA: z = -5.8, p < 0.001 and FEP-A: z = -3.5, p = 0.01) errors compared to HCs. CONCLUSIONS This study shows that the access to syntactic structures is already impaired in FEP patients, especially in those with FEP-NA, ultimately suggesting that language impairments represent a core and inner feature of psychosis even at early stages.
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Affiliation(s)
- Giuseppe Delvecchio
- University of Milan, Department of Pathophysiology and Transplantation, Milan, Italy
| | - Elisabetta Caletti
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, Milan, Italy
| | - Cinzia Perlini
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Clinical Psychology, University of Verona, Italy
| | - Francesca Marzia Siri
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, Milan, Italy
| | | | - Livio Finos
- Department of Developmental Psychology and Socialization, University of Padua, Italy
| | - Marcella Bellani
- UOC of Psychiatry, Azienda Ospedaliera Universitaria Integrata (AOUI) of Verona, Italy
| | - Franco Fabbro
- Department of Medicine, University of Udine, Udine, Italy
| | - Antonio Lasalvia
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Clinical Psychology, University of Verona, Italy; UOC of Psychiatry, Azienda Ospedaliera Universitaria Integrata (AOUI) of Verona, Italy
| | - Chiara Bonetto
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Clinical Psychology, University of Verona, Italy
| | - Doriana Cristofalo
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Clinical Psychology, University of Verona, Italy
| | - Paolo Scocco
- Department of Mental Health, AULSS 6 Euganea, Padua, Italy
| | - Armando D'Agostino
- Department of Health Sciences, San Paolo University Hospital, University of Milan, Milan, Italy
| | | | | | | | | | - Cinzia Bressi
- University of Milan, Department of Pathophysiology and Transplantation, Milan, Italy; Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, Milan, Italy
| | - Mirella Ruggeri
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Clinical Psychology, University of Verona, Italy; UOC of Psychiatry, Azienda Ospedaliera Universitaria Integrata (AOUI) of Verona, Italy
| | - Paolo Brambilla
- University of Milan, Department of Pathophysiology and Transplantation, Milan, Italy; Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, Milan, Italy.
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