1
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Sportelli L, Eisenberg DP, Passiatore R, D'Ambrosio E, Antonucci LA, Bettina JS, Chen Q, Goldman AL, Gregory MD, Griffiths K, Hyde TM, Kleinman JE, Pardiñas AF, Parihar M, Popolizio T, Rampino A, Shin JH, Veronese M, Ulrich WS, Zink CF, Bertolino A, Howes OD, Berman KF, Weinberger DR, Pergola G. Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo. Nat Commun 2024; 15:3342. [PMID: 38688917 PMCID: PMC11061310 DOI: 10.1038/s41467-024-47456-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 03/22/2024] [Indexed: 05/02/2024] Open
Abstract
The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.
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Affiliation(s)
- Leonardo Sportelli
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Daniel P Eisenberg
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
| | - Roberta Passiatore
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Enrico D'Ambrosio
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Linda A Antonucci
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Jasmine S Bettina
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Aaron L Goldman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Michael D Gregory
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
| | - Kira Griffiths
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
- Holmusk Technologies, New York, NY, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Madhur Parihar
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Teresa Popolizio
- Radiology Department, IRCCS Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Antonio Rampino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Azienda Ospedaliero Universitaria Consorziale Policlinico, Bari, Italy
| | - Joo Heon Shin
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Mattia Veronese
- Department of Information Engineering, University of Padua, Padua, Italy
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - William S Ulrich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Caroline F Zink
- Baltimore Research and Education Foundation, Baltimore, MD, USA
| | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Azienda Ospedaliero Universitaria Consorziale Policlinico, Bari, Italy
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Karen F Berman
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Giulio Pergola
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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2
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Geraci F, Passiatore R, Penzel N, Laudani S, Bertolino A, Blasi G, Graziano ACE, Kikidis GC, Mazza C, Parihar M, Rampino A, Sportelli L, Trevisan N, Drago F, Papaleo F, Sambataro F, Pergola G, Leggio GM. Sex dimorphism controls dysbindin-related cognitive dysfunctions in mice and humans with the contribution of COMT. Mol Psychiatry 2024:10.1038/s41380-024-02527-3. [PMID: 38532008 DOI: 10.1038/s41380-024-02527-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 03/05/2024] [Accepted: 03/12/2024] [Indexed: 03/28/2024]
Abstract
Cognitive dysfunctions are core-enduring symptoms of schizophrenia, with important sex-related differences. Genetic variants of the DTBPN1 gene associated with reduced dysbindin-1 protein (Dys) expression negatively impact cognitive functions in schizophrenia through a functional epistatic interaction with Catechol-O-methyltransferase (COMT). Dys is involved in the trafficking of dopaminergic receptors, crucial for prefrontal cortex (PFC) signaling regulation. Moreover, dopamine signaling is modulated by estrogens via inhibition of COMT expression. We hypothesized a sex dimorphism in Dys-related cognitive functions dependent on COMT and estrogen levels. Our multidisciplinary approach combined behavioral-molecular findings on genetically modified mice, human postmortem Dys expression data, and in vivo fMRI during a working memory task performance. We found cognitive impairments in male mice related to genetic variants characterized by reduced Dys protein expression (pBonferroni = 0.0001), as well as in male humans through a COMT/Dys functional epistatic interaction involving PFC brain activity during working memory (t(23) = -3.21; pFDR = 0.004). Dorsolateral PFC activity was associated with lower working memory performance in males only (p = 0.04). Also, male humans showed decreased Dys expression in dorsolateral PFC during adulthood (pFDR = 0.05). Female Dys mice showed preserved cognitive performances with deficits only with a lack of estrogen tested in an ovariectomy model (pBonferroni = 0.0001), suggesting that genetic variants reducing Dys protein expression could probably become functional in females when the protective effect of estrogens is attenuated, i.e., during menopause. Overall, our results show the differential impact of functional variants of the DTBPN1 gene interacting with COMT on cognitive functions across sexes in mice and humans, underlying the importance of considering sex as a target for patient stratification and precision medicine in schizophrenia.
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Affiliation(s)
- Federica Geraci
- Department of Biomedical and Biotechnological Sciences, University of Catania, 95123, Catania, Italy
| | - Roberta Passiatore
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124, Bari, Italy
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, MD, USA
| | - Nora Penzel
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124, Bari, Italy
| | - Samuele Laudani
- Department of Biomedical and Biotechnological Sciences, University of Catania, 95123, Catania, Italy
| | - Alessandro Bertolino
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124, Bari, Italy
- Psychiatric Unit - University Hospital, 70124, Bari, Italy
| | - Giuseppe Blasi
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124, Bari, Italy
- Psychiatric Unit - University Hospital, 70124, Bari, Italy
| | - Adriana C E Graziano
- Department of Biomedical and Biotechnological Sciences, University of Catania, 95123, Catania, Italy
| | - Gianluca C Kikidis
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124, Bari, Italy
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, MD, USA
| | - Ciro Mazza
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124, Bari, Italy
| | - Madhur Parihar
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, MD, USA
| | - Antonio Rampino
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124, Bari, Italy
- Psychiatric Unit - University Hospital, 70124, Bari, Italy
| | - Leonardo Sportelli
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124, Bari, Italy
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, MD, USA
- Department of Human Genetics, Radboud University Nijmegen, 6525 GD, Nijmegen, The Netherlands
| | - Nicolò Trevisan
- Department of Neuroscience (DNS), University of Padova, 35121, Padova, Italy
| | - Filippo Drago
- Department of Biomedical and Biotechnological Sciences, University of Catania, 95123, Catania, Italy
| | - Francesco Papaleo
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, 35121, Padova, Italy
| | - Giulio Pergola
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124, Bari, Italy
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 21205, Baltimore, MD, USA
| | - Gian Marco Leggio
- Department of Biomedical and Biotechnological Sciences, University of Catania, 95123, Catania, Italy.
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3
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Pergola G, Rampino A, Sportelli L, Borcuk CJ, Passiatore R, Di Carlo P, Marakhovskaia A, Fazio L, Amoroso N, Castro MN, Domenici E, Gennarelli M, Khlghatyan J, Kikidis GC, Lella A, Magri C, Monaco A, Papalino M, Parihar M, Popolizio T, Quarto T, Romano R, Torretta S, Valsecchi P, Zunuer H, Blasi G, Dukart J, Beaulieu JM, Bertolino A. A miR-137-Related Biological Pathway of Risk for Schizophrenia Is Associated With Human Brain Emotion Processing. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:356-366. [PMID: 38000716 DOI: 10.1016/j.bpsc.2023.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 11/04/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023]
Abstract
BACKGROUND miR-137 is a microRNA involved in brain development, regulating neurogenesis and neuronal maturation. Genome-wide association studies have implicated miR-137 in schizophrenia risk but do not explain its involvement in brain function and underlying biology. Polygenic risk for schizophrenia mediated by miR-137 targets is associated with working memory, although other evidence points to emotion processing. We characterized the functional brain correlates of miR-137 target genes associated with schizophrenia while disentangling previously reported associations of miR-137 targets with working memory and emotion processing. METHODS Using RNA sequencing data from postmortem prefrontal cortex (N = 522), we identified a coexpression gene set enriched for miR-137 targets and schizophrenia risk genes. We validated the relationship of this set to miR-137 in vitro by manipulating miR-137 expression in neuroblastoma cells. We translated this gene set into polygenic scores of coexpression prediction and associated them with functional magnetic resonance imaging activation in healthy volunteers (n1 = 214; n2 = 136; n3 = 2075; n4 = 1800) and with short-term treatment response in patients with schizophrenia (N = 427). RESULTS In 4652 human participants, we found that 1) schizophrenia risk genes were coexpressed in a biologically validated set enriched for miR-137 targets; 2) increased expression of miR-137 target risk genes was mediated by low prefrontal miR-137 expression; 3) alleles that predict greater gene set coexpression were associated with greater prefrontal activation during emotion processing in 3 independent healthy cohorts (n1, n2, n3) in interaction with age (n4); and 4) these alleles predicted less improvement in negative symptoms following antipsychotic treatment in patients with schizophrenia. CONCLUSIONS The functional translation of miR-137 target gene expression linked with schizophrenia involves the neural substrates of emotion processing.
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Affiliation(s)
- Giulio Pergola
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.
| | - Antonio Rampino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy.
| | - Leonardo Sportelli
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Christopher James Borcuk
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Roberta Passiatore
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Institute of Neuroscience and Medicine, Brain & Behaviour, Research Centre Jülich, Jülich, Germany
| | - Pasquale Di Carlo
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | | | - Leonardo Fazio
- Department of Medicine and Surgery, Libera Università Mediterranea Giuseppe Degennaro, Casamassima, Italy
| | - Nicola Amoroso
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy
| | - Mariana Nair Castro
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires, Argentina (MNC); Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Fleni-Consejo Nacional de Investigaciones Científicas y Técnicas Neurosciences Institute, Ciudad Autónoma de Buenos Aires, Argentina
| | - Enrico Domenici
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy; Fondazione The Microsoft Research University of Trento, Centre for Computational and Systems Biology, Rovereto, Italy
| | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy; Genetics Unit, Istituto di Ricovero e Cura a Carattere Sanitario Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Jivan Khlghatyan
- Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy; Department of Neuroscience, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Gianluca Christos Kikidis
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Annalisa Lella
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Chiara Magri
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Alfonso Monaco
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy; Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires, Argentina (MNC); Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Fleni-Consejo Nacional de Investigaciones Científicas y Técnicas Neurosciences Institute, Ciudad Autónoma de Buenos Aires, Argentina; Università degli Studi di Bari Aldo Moro, Dipartimento Interateneo di Fisica M. Merlin, Bari, Italy
| | - Marco Papalino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Madhur Parihar
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Teresa Popolizio
- Istituto di Ricovero e Cura a Carattere Sanitario Istituto Centro San Giovanni di Dio Fatebenefratelli, Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Tiziana Quarto
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Department of Law, University of Foggia, Foggia, Italy
| | - Raffaella Romano
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Silvia Torretta
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Paolo Valsecchi
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy; Department of Mental Health and Addiction Services, Azienda Socio Sanitaria Territoriale Spedali Civili of Brescia, Brescia, Italy
| | - Hailiqiguli Zunuer
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour, Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
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4
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Gu YW, Fan JW, Zhào H, Zhao SW, Liu XF, Yu R, Ren L, Wang X, Yin H, Cui LB. Imaging Transcriptomics of the Brain for Schizophrenia. ALPHA PSYCHIATRY 2024; 25:9-14. [PMID: 38799487 PMCID: PMC11114239 DOI: 10.5152/alphapsychiatry.2024.231369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 12/04/2023] [Indexed: 05/29/2024]
Abstract
Schizophrenia is a severe mental disorder with a neurodevelopmental origin. Although schizophrenia results from changes in the brain, the underlying biological mechanisms are unknown. Transcriptomics studies quantitative expression changes or qualitative changes of all genes and isoforms, providing a more meaningful biological insight. Magnetic resonance imaging (MRI) techniques play roles in revealing brain structure and function. We give a narrative focused review on the current transcriptome combined with MRI studies related to schizophrenia and summarize the research methodology and content of these studies to identify the research commonalities as well as the implications for future research, in an attempt to provide new insights into the mechanism, clinical diagnosis, and treatments of schizophrenia.
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Affiliation(s)
- Yue-Wen Gu
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
- Department of Radiology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Jing-Wen Fan
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
- Department of Radiology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Hóngyi Zhào
- Department of Neurology, NO. 984 Hospital of PLA, Beijing, China
| | - Shu-Wan Zhao
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
- Department of Radiology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Xiao-Fan Liu
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
| | - Renqiang Yu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lei Ren
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
| | - Xinjiang Wang
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Air Force Medical University, Xi’an, China
- Department of Radiology, Xi’an People’s Hospital (Xi’an Fourth Hospital), Xi’an, China
| | - Long-Biao Cui
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
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5
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Radulescu E, Chen Q, Pergola G, Di Carlo P, Han S, Shin JH, Hyde TM, Kleinman JE, Weinberger DR. Investigating trait variability of gene co-expression network architecture in brain by controlling for genomic risk of schizophrenia. PLoS Genet 2023; 19:e1010989. [PMID: 37831723 PMCID: PMC10599557 DOI: 10.1371/journal.pgen.1010989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 10/25/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
The effect of schizophrenia (SCZ) genetic risk on gene expression in brain remains elusive. A popular approach to this problem has been the application of gene co-expression network algorithms (e.g., WGCNA). To improve reliability with this method it is critical to remove unwanted sources of variance while also preserving biological signals of interest. In this WCGNA study of RNA-Seq data from postmortem prefrontal cortex (78 neurotypical donors, EUR ancestry), we tested the effects of SCZ genetic risk on co-expression networks. Specifically, we implemented a novel design in which gene expression was adjusted by linear regression models to preserve or remove variance explained by biological signal of interest (GWAS genomic scores for SCZ risk-(GS-SCZ), and genomic scores- GS of height (GS-Ht) as a negative control), while removing variance explained by covariates of non-interest. We calculated co-expression networks from adjusted expression (GS-SCZ and GS-Ht preserved or removed), and consensus between them (representative of a "background" network free of genomic scores effects). We then tested the overlap between GS-SCZ preserved modules and background networks reasoning that modules with reduced overlap would be most affected by GS-SCZ biology. Additionally, we tested these modules for convergence of SCZ risk (i.e., enrichment in PGC3 SCZ GWAS priority genes, enrichment in SCZ risk heritability and relevant biological ontologies. Our results highlight key aspects of GS-SCZ effects on brain co-expression networks, specifically: 1) preserving/removing SCZ genetic risk alters the co-expression modules; 2) biological pathways enriched in modules affected by GS-SCZ implicate processes of transcription, translation and metabolism that converge to influence synaptic transmission; 3) priority PGC3 SCZ GWAS genes and SCZ risk heritability are enriched in modules associated with GS-SCZ effects. Overall, our results indicate that gene co-expression networks that selectively integrate information about genetic risk can reveal novel combinations of biological pathways involved in schizophrenia.
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Affiliation(s)
- Eugenia Radulescu
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland United States of America
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland United States of America
| | - Giulio Pergola
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland United States of America
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Pasquale Di Carlo
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland United States of America
| | - Shizhong Han
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland United States of America
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Joo Heon Shin
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland United States of America
| | - Thomas M. Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland United States of America
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Joel E. Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland United States of America
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Daniel R. Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland United States of America
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
- Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
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6
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Selvaggi P, Fazio L, Toro VD, Mucci A, Rocca P, Martinotti G, Cascino G, Siracusano A, Zeppegno P, Pergola G, Bertolino A, Blasi G, Galderisi S. Effect of anticholinergic burden on brain activity during Working Memory and real-world functioning in patients with schizophrenia. Schizophr Res 2023; 260:76-84. [PMID: 37633126 DOI: 10.1016/j.schres.2023.08.015] [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: 12/13/2022] [Revised: 06/30/2023] [Accepted: 08/13/2023] [Indexed: 08/28/2023]
Abstract
Cognitive impairment has been associated with poor real-world functioning in patients with Schizophrenia. Previous studies have shown that pharmacological treatment with anticholinergic properties may contribute to cognitive impairment in Schizophrenia. We investigated the effect of the anticholinergic burden (ACB) on brain activity, cognition, and real-world functioning in Schizophrenia. We hypothesized that greater ACB would be associated with altered brain activity along with poorer cognitive performance and lower real-world functioning. A sample of 100 patients with a diagnosis of schizophrenia or schizoaffective disorder was recruited in the naturalistic multicenter study of the Italian Network for Research on Psychoses (NIRP) across 7 centres. For each participant, ACB was evaluated using the Anticholinergic Cognitive Burden scale. The association of ACB with brain function was assessed using BOLD fMRI during the N-Back Working Memory (WM) task in a nested cohort (N = 31). Real-world functioning was assessed using the Specific Level of Functioning (SLOF) scale. Patients with high ACB scores (≥3) showed lower brain activity in the WM frontoparietal network (TFCE corrected alpha <0.05) and poorer cognitive performance (p = 0.05) than patients with low ACB scores (<3). Both effects were unaffected by demographic characteristics, clinical severity, and antipsychotic dosage. Moreover, patients with high ACB showed poorer real-world functioning than patients with lower ACB (p = 0.03). Our results suggest that ACB in Schizophrenia is associated with impaired WM and abnormal underlying brain function along with reduced real-world functioning. Clinical practice should consider the potential adverse cognitive effects of ACB in the treatment decision-making process.
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Affiliation(s)
- Pierluigi Selvaggi
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Leonardo Fazio
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy; Department of Medicine and Surgery, LUM University, Casamassima, Bari, Italy
| | - Veronica Debora Toro
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy
| | - Armida Mucci
- Department of Psychiatry, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Paola Rocca
- Department of Neuroscience, Section of Psychiatry, University of Turin, Turin, Italy
| | - Giovanni Martinotti
- Department of Neuroscience and Imaging, G. D'Annunzio University, Chieti, Italy
| | - Giammarco Cascino
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Section of Neuroscience, University of Salerno, Salerno, Italy
| | - Alberto Siracusano
- Department of Systems Medicine, Psychiatry and Clinical Psychology Unit, Tor Vergata University of Rome, Rome, Italy
| | - Patrizia Zeppegno
- Department of Translational Medicine, Psychiatric Unit, University of Eastern Piedmont, Novara, Italy
| | - Giulio Pergola
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy
| | - Alessandro Bertolino
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy
| | - Giuseppe Blasi
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy.
| | - Silvana Galderisi
- Department of Psychiatry, University of Campania "Luigi Vanvitelli", Naples, Italy
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Sportelli L, Eisenberg DP, Passiatore R, D'Ambrosio E, Antonucci LA, Chen Q, Czarapata J, Goldman AL, Gregory M, Griffiths K, Hyde TM, Kleinman JE, Pardiñas AF, Parihar M, Popolizio T, Rampino A, Shin JH, Veronese M, Ulrich WS, Zink CF, Bertolino A, Howes OD, Berman KF, Weinberger DR, Pergola G. Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.20.558594. [PMID: 37786720 PMCID: PMC10541621 DOI: 10.1101/2023.09.20.558594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [ 18 F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a 'bench to bedside' translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.
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Quarto T, Lella A, Di Carlo P, Rampino A, Paladini V, Papalino M, Romano R, Fazio L, Marvulli D, Popolizio T, Blasi G, Pergola G, Bertolino A. Heritability of amygdala reactivity to angry faces and its replicable association with the schizophrenia risk locus of miR-137. J Psychiatry Neurosci 2023; 48:E357-E366. [PMID: 37751917 PMCID: PMC10521919 DOI: 10.1503/jpn.230013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 07/11/2023] [Accepted: 07/30/2023] [Indexed: 09/28/2023] Open
Abstract
BACKGROUND Among healthy participants, the interindividual variability of brain response to facial emotions is associated with genetic variation, including common risk variants for schizophrenia, a heritable brain disorder characterized by anomalies in emotion processing. We aimed to identify genetic variants associated with heritable brain activity during processing of facial emotions among healthy participants and to explore the impact of these identified variants among patients with schizophrenia. METHODS We conducted a data-driven stepwise study including samples of healthy twins, unrelated healthy participants and patients with schizophrenia. Participants approached or avoided pictures of faces with negative emotional valence during functional magnetic resonance imaging (fMRI). RESULTS We investigated 3 samples of healthy participants - including 28 healthy twin pairs, 289 unrelated healthy participants (genome-wide association study [GWAS] discovery sample) and 90 unrelated healthy participants (replication sample) - and 1 sample of 48 patients with schizophrenia. Among healthy twins, we identified the amygdala as the brain region with the highest heritability during processing of angry faces (heritability estimate 0.54, p < 0.001). Subsequent GWAS in both discovery and replication samples of healthy non-twins indicated that amygdala activity was associated with a polymorphism in the miR-137 locus (rs1198575), a micro-RNA strongly involved in risk for schizophrenia. A significant effect in the same direction was found among patients with schizophrenia (p = 0.03). LIMITATIONS The limited sample size available for GWAS analyses may require further replication of results. CONCLUSION Our data-driven approach shows preliminary evidence that amygdala activity, as evaluated with our task, is heritable. Our genetic associations preliminarily suggest a role for miR-137 in brain activity during explicit processing of facial emotions among healthy participants and patients with schizophrenia, pointing to the amygdala as a brain region whose activity is related to miR-137.
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Affiliation(s)
- Tiziana Quarto
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Annalisa Lella
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Pasquale Di Carlo
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Antonio Rampino
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Vittoria Paladini
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Marco Papalino
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Raffaella Romano
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Leonardo Fazio
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Daniela Marvulli
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Teresa Popolizio
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Giuseppe Blasi
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Giulio Pergola
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
| | - Alessandro Bertolino
- From the Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy (Quarto, Lella, Di Carlo, Rampino, Paladini, Papalino, Romano, Fazio, Marvulli, Blasi, Pergola, Bertolino); the Department of Humanities, University of Foggia, Foggia, Italy (Quarto); the Psychiatry Unit, Bari University Hospital, Bari, Italy (Rampino, Blasi, Bertolino); the LUM (Fazio); the IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy (Popolizio); the Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD (Pergola)
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Fan JW, Gu YW, Wang DB, Liu XF, Zhao SW, Li X, Li B, Yin H, Wu WJ, Cui LB. Transcriptomics and magnetic resonance imaging in major psychiatric disorders. Front Psychiatry 2023; 14:1185471. [PMID: 37383618 PMCID: PMC10296768 DOI: 10.3389/fpsyt.2023.1185471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 05/16/2023] [Indexed: 06/30/2023] Open
Abstract
Major psychiatric disorders create a significant public health burden, and mental disorders such as major depressive disorder, bipolar disorder, and schizophrenia are major contributors to the national disease burden. The search for biomarkers has been a leading endeavor in the field of biological psychiatry in recent decades. And the application of cross-scale and multi-omics approaches combining genes and imaging in major psychiatric studies has facilitated the elucidation of gene-related pathogenesis and the exploration of potential biomarkers. In this article, we summarize the results of using combined transcriptomics and magnetic resonance imaging to understand structural and functional brain changes associated with major psychiatric disorders in the last decade, demonstrating the neurobiological mechanisms of genetically related structural and functional brain alterations in multiple directions, and providing new avenues for the development of quantifiable objective biomarkers, as well as clinical diagnostic and prognostic indicators.
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Affiliation(s)
- Jing-Wen Fan
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yue-Wen Gu
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Dong-Bao Wang
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi’an, China
| | - Xiao-Fan Liu
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
| | - Shu-Wan Zhao
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xiao Li
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Baojuan Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Wen-Jun Wu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi’an, China
- Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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Liu H, Li W, Liu N, Tang J, Sun L, Xu J, Ji Y, Xie Y, Ding H, Ye Z, Yu C, Qin W. Structural covariances of prefrontal subregions selectively associate with dopamine-related gene coexpression and schizophrenia. Cereb Cortex 2023; 33:8035-8045. [PMID: 36935097 DOI: 10.1093/cercor/bhad096] [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: 12/16/2022] [Revised: 02/24/2023] [Accepted: 02/25/2023] [Indexed: 03/20/2023] Open
Abstract
Evidence highlights that dopamine (DA) system dysregulation and prefrontal cortex (PFC) dysfunction may underlie the pathophysiology of schizophrenia. However, the associations among DA genes, PFC morphometry, and schizophrenia have not yet been fully clarified. Based on the brain gene expression dataset from Allen Human Brain Atlas and structural magnetic resonance imaging data (NDIS = 1727, NREP = 408), we first identified 10 out of 22 PFC subregions whose gray matter volume (GMV) covariance profiles were reliably associated with their DA genes coexpression profiles, then four out of the identified 10 PFC subregions demonstrated abnormally increased GMV covariance with the hippocampus, insula, and medial frontal areas in schizophrenia patients (NCASE = 100; NCONTROL = 102). Moreover, based on a schizophrenia postmortem expression dataset, we found that the DA genes coexpression of schizophrenia was significantly reduced between the middle frontal gyrus and hippocampus, in which 21 DA genes showed significantly unsynchronized expression changes, and the 21 genes' brain expression were enriched in brain activity invoked by working memory, reward, speech production, and episodic memory. Our findings indicate the DA genes selectively regulate the structural covariance of PFC subregions by their coexpression profiles, which may underlie the disrupted GMV covariance and impaired cognitive functions in schizophrenia.
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Affiliation(s)
- Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Wei Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Nana Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jie Tang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Lixin Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yuan Ji
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yingying Xie
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Hao Ding
- School of Medical Imaging, Tianjin Medical University, Tianjin 300070, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
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Pergola G, Parihar M, Sportelli L, Bharadwaj R, Borcuk C, Radulescu E, Bellantuono L, Blasi G, Chen Q, Kleinman JE, Wang Y, Sripathy SR, Maher BJ, Monaco A, Rossi F, Shin JH, Hyde TM, Bertolino A, Weinberger DR. Consensus molecular environment of schizophrenia risk genes in coexpression networks shifting across age and brain regions. SCIENCE ADVANCES 2023; 9:eade2812. [PMID: 37058565 PMCID: PMC10104472 DOI: 10.1126/sciadv.ade2812] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 03/10/2023] [Indexed: 06/19/2023]
Abstract
Schizophrenia is a neurodevelopmental brain disorder whose genetic risk is associated with shifting clinical phenomena across the life span. We investigated the convergence of putative schizophrenia risk genes in brain coexpression networks in postmortem human prefrontal cortex (DLPFC), hippocampus, caudate nucleus, and dentate gyrus granule cells, parsed by specific age periods (total N = 833). The results support an early prefrontal involvement in the biology underlying schizophrenia and reveal a dynamic interplay of regions in which age parsing explains more variance in schizophrenia risk compared to lumping all age periods together. Across multiple data sources and publications, we identify 28 genes that are the most consistently found partners in modules enriched for schizophrenia risk genes in DLPFC; twenty-three are previously unidentified associations with schizophrenia. In iPSC-derived neurons, the relationship of these genes with schizophrenia risk genes is maintained. The genetic architecture of schizophrenia is embedded in shifting coexpression patterns across brain regions and time, potentially underwriting its shifting clinical presentation.
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Affiliation(s)
- Giulio Pergola
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Madhur Parihar
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Leonardo Sportelli
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Rahul Bharadwaj
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Christopher Borcuk
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Eugenia Radulescu
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Loredana Bellantuono
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Istituto Nazionale di Fisica Nucleare, Bari, Italy
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Azienda Ospedaliero Universitaria Consorziale Policlinico, Bari, Italy
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Joel E. Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yanhong Wang
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Srinidhi Rao Sripathy
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Brady J. Maher
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alfonso Monaco
- Istituto Nazionale di Fisica Nucleare, Bari, Italy
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Bari, Italy
| | - Fabiana Rossi
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Joo Heon Shin
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Thomas M. Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Azienda Ospedaliero Universitaria Consorziale Policlinico, Bari, Italy
| | - Daniel R. Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Cao H, Hong X, Tost H, Meyer-Lindenberg A, Schwarz E. Advancing translational research in neuroscience through multi-task learning. Front Psychiatry 2022; 13:993289. [PMID: 36465289 PMCID: PMC9714033 DOI: 10.3389/fpsyt.2022.993289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 10/24/2022] [Indexed: 11/18/2022] Open
Abstract
Translational research in neuroscience is increasingly focusing on the analysis of multi-modal data, in order to account for the biological complexity of suspected disease mechanisms. Recent advances in machine learning have the potential to substantially advance such translational research through the simultaneous analysis of different data modalities. This review focuses on one of such approaches, the so-called "multi-task learning" (MTL), and describes its potential utility for multi-modal data analyses in neuroscience. We summarize the methodological development of MTL starting from conventional machine learning, and present several scenarios that appear particularly suitable for its application. For these scenarios, we highlight different types of MTL algorithms, discuss emerging technological adaptations, and provide a step-by-step guide for readers to apply the MTL approach in their own studies. With its ability to simultaneously analyze multiple data modalities, MTL may become an important element of the analytics repertoire used in future neuroscience research and beyond.
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Affiliation(s)
- Han Cao
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Xudong Hong
- Department of Computer Vision and Machine Learning, Max Planck Institute for Informatics, Saarbrücken, Germany
- Department of Language Science and Technology, Saarland University, Saarbrücken, Germany
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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13
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Lahti J, Tuominen S, Yang Q, Pergola G, Ahmad S, Amin N, Armstrong NJ, Beiser A, Bey K, Bis JC, Boerwinkle E, Bressler J, Campbell A, Campbell H, Chen Q, Corley J, Cox SR, Davies G, De Jager PL, Derks EM, Faul JD, Fitzpatrick AL, Fohner AE, Ford I, Fornage M, Gerring Z, Grabe HJ, Grodstein F, Gudnason V, Simonsick E, Holliday EG, Joshi PK, Kajantie E, Kaprio J, Karell P, Kleineidam L, Knol MJ, Kochan NA, Kwok JB, Leber M, Lam M, Lee T, Li S, Loukola A, Luck T, Marioni RE, Mather KA, Medland S, Mirza SS, Nalls MA, Nho K, O'Donnell A, Oldmeadow C, Painter J, Pattie A, Reppermund S, Risacher SL, Rose RJ, Sadashivaiah V, Scholz M, Satizabal CL, Schofield PW, Schraut KE, Scott RJ, Simino J, Smith AV, Smith JA, Stott DJ, Surakka I, Teumer A, Thalamuthu A, Trompet S, Turner ST, van der Lee SJ, Villringer A, Völker U, Wilson RS, Wittfeld K, Vuoksimaa E, Xia R, Yaffe K, Yu L, Zare H, Zhao W, Ames D, Attia J, Bennett DA, Brodaty H, Chasman DI, Goldman AL, Hayward C, Ikram MA, Jukema JW, Kardia SLR, Lencz T, Loeffler M, Mattay VS, Palotie A, Psaty BM, Ramirez A, Ridker PM, Riedel-Heller SG, Sachdev PS, Saykin AJ, Scherer M, Schofield PR, Sidney S, Starr JM, Trollor J, Ulrich W, Wagner M, Weir DR, Wilson JF, Wright MJ, Weinberger DR, Debette S, Eriksson JG, Mosley TH, Launer LJ, van Duijn CM, Deary IJ, Seshadri S, Räikkönen K. Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning. Mol Psychiatry 2022; 27:4419-4431. [PMID: 35974141 PMCID: PMC9734053 DOI: 10.1038/s41380-022-01710-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 07/11/2022] [Accepted: 07/13/2022] [Indexed: 12/14/2022]
Abstract
Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.
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Affiliation(s)
- Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland.
- Turku Institute of Advanced Studies, University of Turku, Turku, Finland.
| | - Samuli Tuominen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Qiong Yang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Giulio Pergola
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Nicola J Armstrong
- Department of Mathematics and Statistics, Murdoch University, Murdoch, WA, Australia
| | - Alexa Beiser
- Department of Biostatistics, Boston University, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Katharina Bey
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Janie Corley
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Columbia University Medical Center, New York, NY, USA
| | - Eske M Derks
- Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Annette L Fitzpatrick
- Department of Family Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Global Health, University of Washington, Seattle, WA, USA
| | - Alison E Fohner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Institute of Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Ian Ford
- Robertson Center for Biostatistics, University of Glasgow, Glasgow, UK
| | - Myriam Fornage
- McGovern Medical School, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Zachary Gerring
- Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases, Greifswald, Germany
| | - Francine Grodstein
- Channing Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Harvard School of Public Health, Boston, MA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Assocation, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Eleanor Simonsick
- Translational Gerontology Branch, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Elizabeth G Holliday
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Institute of Social and Preventive Medicine, University of Lausanne, Lausanne, Switzerland
| | - Eero Kajantie
- National Institute for Health and Welfare, Helsinki and Oulu, Oulu, Finland
- Hospital for Children and Adolescents, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
- PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Pauliina Karell
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases, Bonn, Germany
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Nicole A Kochan
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - John B Kwok
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Markus Leber
- Department of Psychiatry, University of Cologne, Cologne, Germany
| | - Max Lam
- Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
| | - Teresa Lee
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - Shuo Li
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Anu Loukola
- Helsinki Biobank, University of Helsinki Central Hospital, Helsinki, Finland
| | - Tobias Luck
- Department of Economic and Social Sciences & Institute of Social Medicine, Rehabilitation Sciences and Healthcare Research, University of Applied Sciences Nordhausen, Nordhausen, Germany
- University of Leipzig, Leipzig, Germany
- LIFE Leipzig Research Center for Civilization Diseases, Leipzig, Germany
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Karen A Mather
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Sunnybrook Health Sciences Centre, University of Toronto, Randwick, NSW, Australia
| | - Sarah Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Saira S Mirza
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adrienne O'Donnell
- Department of Biostatistics, Boston University, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Christopher Oldmeadow
- Clinical Research Design, IT and Statistical Support Unit, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Jodie Painter
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Alison Pattie
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Simone Reppermund
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Richard J Rose
- Department of Psychological & Brain Sciences, Indiana University Bloomington, Bloomington, IN, USA
| | - Vijay Sadashivaiah
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Claudia L Satizabal
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Peter W Schofield
- Neuropsychiatry Service, Hunter New England Local Health District, Charlestown, NSW, Australia
| | - Katharina E Schraut
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, Royal Infirmary of Edinburgh, University of Edinburgh, Edinburgh, UK
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Jeannette Simino
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Albert V Smith
- Icelandic Heart Assocation, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
- Institute of Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, USA
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Stella Trompet
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Sven J van der Lee
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Neurology and Alzheimer Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Arno Villringer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Day Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, Department Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Robert S Wilson
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases, Greifswald, Germany
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Rui Xia
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kristine Yaffe
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Habil Zare
- Department of Cell Systems & Anatomy, The University of Texas Health Science Center, San Antonio, TX, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas, San Antonio, TX, USA
- University of Texas Health Sciences Center, Houston, NA, US
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - David Ames
- National Ageing Research Institute, Parkville, Melbourne, VIC, Australia
- University of Melbourne, Academic Unit for Psychiatry of Old Age, St George's Hospital, Melbourne, VIC, Australia
| | - John Attia
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia
- Clinical Research Design, IT and Statistical Support Unit, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Henry Brodaty
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Dementia Collaborative Research Centre, University of New South Wales, Sydney, NSW, Australia
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Aaron L Goldman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Todd Lencz
- Hofstra Northwell School of Medicine, Hempstead, NY, USA
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Venkata S Mattay
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Food and Drug Administration, Washington, DC, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology and Department of Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Heath Research Institute, Seattle, WA, USA
| | - Alfredo Ramirez
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
- Department of Psychiatry, University of Cologne, Cologne, Germany
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Martin Scherer
- Institute of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Peter R Schofield
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Randwick, NSW, Australia
| | - Stephen Sidney
- Kaiser Permanente Northern California, Division of Research, Oakland, CA, USA
| | - John M Starr
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Julian Trollor
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Department of Developmental Disability Neuropsychiatry, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - William Ulrich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Michael Wagner
- German Center for Neurodegenerative Diseases, Bonn, Germany
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Stephanie Debette
- Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, University of Bordeaux, Bordeaux, France
- Bordeaux University Hospital (CHU Bordeaux), Department of Neurology, Bordeaux, France
| | - Johan G Eriksson
- Folkhälsan Research Center, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, and Helsinki University Hospital, University of Helsinki, Helsinki, Finland
- Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Helsinki, Singapore
| | - Thomas H Mosley
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Public Health, Oxford University, Oxford, UK
| | - Ian J Deary
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
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14
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Pergola G, Penzel N, Sportelli L, Bertolino A. Lessons Learned From Parsing Genetic Risk for Schizophrenia Into Biological Pathways. Biol Psychiatry 2022:S0006-3223(22)01701-2. [PMID: 36740470 DOI: 10.1016/j.biopsych.2022.10.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 09/10/2022] [Accepted: 10/06/2022] [Indexed: 02/07/2023]
Abstract
The clinically heterogeneous presentation of schizophrenia is compounded by the heterogeneity of risk factors and neurobiological correlates of the disorder. Genome-wide association studies in schizophrenia have uncovered a remarkably high number of genetic variants, but the biological pathways they impact upon remain largely unidentified. Among the diverse methodological approaches employed to provide a more granular understanding of genetic risk for schizophrenia, the use of biological labels, such as gene ontologies, regulome approaches, and gene coexpression have all provided novel perspectives into how genetic risk translates into the neurobiology of schizophrenia. Here, we review the salient aspects of parsing polygenic risk for schizophrenia into biological pathways. We argue that parsed scores, compared to standard polygenic risk scores, may afford a more biologically plausible and accurate physiological modeling of the different dimensions involved in translating genetic risk into brain mechanisms, including multiple brain regions, cell types, and maturation stages. We discuss caveats, opportunities, and pitfalls inherent in the parsed risk approach.
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Affiliation(s)
- Giulio Pergola
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.
| | - Nora Penzel
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Leonardo Sportelli
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Alessandro Bertolino
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
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15
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D'Ambrosio E, Pergola G, Pardiñas AF, Dahoun T, Veronese M, Sportelli L, Taurisano P, Griffiths K, Jauhar S, Rogdaki M, Bloomfield MAP, Froudist-Walsh S, Bonoldi I, Walters JTR, Blasi G, Bertolino A, Howes OD. A polygenic score indexing a DRD2-related co-expression network is associated with striatal dopamine function. Sci Rep 2022; 12:12610. [PMID: 35871219 PMCID: PMC9308811 DOI: 10.1038/s41598-022-16442-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 07/11/2022] [Indexed: 11/09/2022] Open
Abstract
The D2 dopamine receptor (D2R) is the primary site of the therapeutic action of antipsychotics and is involved in essential brain functions relevant to schizophrenia, such as attention, memory, motivation, and emotion processing. Moreover, the gene coding for D2R (DRD2) has been associated with schizophrenia at a genome-wide level. Recent studies have shown that a polygenic co-expression index (PCI) predicting the brain-specific expression of a network of genes co-expressed with DRD2 was associated with response to antipsychotics, brain function during working memory in patients with schizophrenia, and with the modulation of prefrontal cortex activity after pharmacological stimulation of D2 receptors. We aimed to investigate the relationship between the DRD2 gene network and in vivo striatal dopaminergic function, which is a phenotype robustly associated with psychosis and schizophrenia. To this aim, a sample of 92 healthy subjects underwent 18F-DOPA PET and was genotyped for genetic variations indexing the co-expression of the DRD2-related genetic network in order to calculate the PCI for each subject. The PCI was significantly associated with whole striatal dopamine synthesis capacity (p = 0.038). Exploratory analyses on the striatal subdivisions revealed a numerically larger effect size of the PCI on dopamine function for the associative striatum, although this was not significantly different than effects in other sub-divisions. These results are in line with a possible relationship between the DRD2-related co-expression network and schizophrenia and extend it by identifying a potential mechanism involving the regulation of dopamine synthesis. Future studies are needed to clarify the molecular mechanisms implicated in this relationship.
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Affiliation(s)
- Enrico D'Ambrosio
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.,Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Giulio Pergola
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy.,Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Tarik Dahoun
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Mattia Veronese
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Department of Information Engineering, University of Padua, Padua, Italy
| | - Leonardo Sportelli
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Paolo Taurisano
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Kira Griffiths
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Sameer Jauhar
- Centre for Affective Disorders, Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Maria Rogdaki
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Michael A P Bloomfield
- Division of Psychiatry, University College London, 6th Floor, Maple House, 149 Tottenham Court Road, London, W1T 7NF, UK
| | | | - Ilaria Bonoldi
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Giuseppe Blasi
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy.
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK. .,Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, Du Cane Road, London, UK. .,H. Lundbeck A/S, Ottiliavej 9, 2500, Valby, Denmark.
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16
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Yan W, Palaniyappan L, Liddle PF, Rangaprakash D, Wei W, Deshpande G. Characterization of Hemodynamic Alterations in Schizophrenia and Bipolar Disorder and Their Effect on Resting-State fMRI Functional Connectivity. Schizophr Bull 2022; 48:695-711. [PMID: 34951473 PMCID: PMC9077436 DOI: 10.1093/schbul/sbab140] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Common and distinct neural bases of Schizophrenia (SZ) and bipolar disorder (BP) have been explored using resting-state fMRI (rs-fMRI) functional connectivity (FC). However, fMRI is an indirect measure of neural activity, which is a convolution of the hemodynamic response function (HRF) and latent neural activity. The HRF, which models neurovascular coupling, varies across the brain within and across individuals, and is altered in many psychiatric disorders. Given this background, this study had three aims: quantifying HRF aberrations in SZ and BP, measuring the impact of such HRF aberrations on FC group differences, and exploring the genetic basis of HRF aberrations. We estimated voxel-level HRFs by deconvolving rs-fMRI data obtained from SZ (N = 38), BP (N = 19), and matched healthy controls (N = 35). We identified HRF group differences (P < .05, FDR corrected) in many regions previously implicated in SZ/BP, with mediodorsal, habenular, and central lateral nuclei of the thalamus exhibiting HRF differences in all pairwise group comparisons. Thalamus seed-based FC analysis revealed that ignoring HRF variability results in false-positive and false-negative FC group differences, especially in insula, superior frontal, and lingual gyri. HRF was associated with DRD2 gene expression (P < .05, 1.62 < |Z| < 2.0), as well as with medication dose (P < .05, 1.75 < |Z| < 3.25). In this first study to report HRF aberrations in SZ and BP, we report the possible modulatory effect of dopaminergic signalling on HRF, and the impact that HRF variability can have on FC studies in clinical samples. To mitigate the impact of HRF variability on FC group differences, we suggest deconvolution during data preprocessing.
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Affiliation(s)
- Wenjing Yan
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, USA
- Department of Information Management, School of E-business and Logistics, Beijing Technology and Business University, Beijing, China
| | - Lena Palaniyappan
- Department of Psychiatry, University of Western Ontario, London, ON, Canada
- Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
| | - Peter F Liddle
- Centre for Translational Neuroimaging, Division of Mental Health and Clinical Neuroscience, Institute of Mental Health, University of Nottingham, UK
| | - D Rangaprakash
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Wei Wei
- Department of Information Management, School of E-business and Logistics, Beijing Technology and Business University, Beijing, China
| | - Gopikrishna Deshpande
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, USA
- Department of Psychological Sciences, Auburn University, Auburn, AL
- Alabama Advanced Imaging Consortium, Birmingham, AL
- Center for Neuroscience, Auburn University, AL, USA
- School of Psychology, Capital Normal University, Beijing, China
- Key Laboratory for Learning and Cognition, Capital Normal University, Beijing, China
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
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17
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Lee GS, Graham DL, Noble BL, Trammell TS, McCarthy DM, Anderson LR, Rubinstein M, Bhide PG, Stanwood GD. Behavioral and Neuroanatomical Consequences of Cell-Type Specific Loss of Dopamine D2 Receptors in the Mouse Cerebral Cortex. Front Behav Neurosci 2022; 15:815713. [PMID: 35095443 PMCID: PMC8793809 DOI: 10.3389/fnbeh.2021.815713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 12/22/2021] [Indexed: 11/13/2022] Open
Abstract
Developmental dysregulation of dopamine D2 receptors (D2Rs) alters neuronal migration, differentiation, and behavior and contributes to the psychopathology of neurological and psychiatric disorders. The current study is aimed at identifying how cell-specific loss of D2Rs in the cerebral cortex may impact neurobehavioral and cellular development, in order to better understand the roles of this receptor in cortical circuit formation and brain disorders. We deleted D2R from developing cortical GABAergic interneurons (Nkx2.1-Cre) or from developing telencephalic glutamatergic neurons (Emx1-Cre). Conditional knockouts (cKO) from both lines, Drd2fl/fl, Nkx2.1-Cre+ (referred to as GABA-D2R-cKO mice) or Drd2fl/fl, Emx1-Cre+ (referred to as Glu-D2R-cKO mice), exhibited no differences in simple tests of anxiety-related or depression-related behaviors, or spatial or nonspatial working memory. Both GABA-D2R-cKO and Glu-D2R-cKO mice also had normal basal locomotor activity, but GABA-D2R-cKO mice expressed blunted locomotor responses to the psychotomimetic drug MK-801. GABA-D2R-cKO mice exhibited improved motor coordination on a rotarod whereas Glu-D2R-cKO mice were normal. GABA-D2R-cKO mice also exhibited spatial learning deficits without changes in reversal learning on a Barnes maze. At the cellular level, we observed an increase in PV+ cells in the frontal cortex of GABA-D2R-cKO mice and no noticeable changes in Glu-D2R-cKO mice. These data point toward unique and distinct roles for D2Rs within excitatory and inhibitory neurons in the regulation of behavior and interneuron development, and suggest that location-biased D2R pharmacology may be clinically advantageous to achieve higher efficacy and help avoid unwanted effects.
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Affiliation(s)
- Gloria S. Lee
- Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL, United States
| | - Devon L. Graham
- Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL, United States
- Center for Brain Repair, Florida State University College of Medicine, Tallahassee, FL, United States
| | - Brenda L. Noble
- Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL, United States
| | - Taylor S. Trammell
- Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL, United States
| | - Deirdre M. McCarthy
- Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL, United States
- Center for Brain Repair, Florida State University College of Medicine, Tallahassee, FL, United States
| | - Lisa R. Anderson
- Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL, United States
| | - Marcelo Rubinstein
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular, Consejo Nacional de Investigaciones Científicas y Técnicas and Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Pradeep G. Bhide
- Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL, United States
- Center for Brain Repair, Florida State University College of Medicine, Tallahassee, FL, United States
| | - Gregg D. Stanwood
- Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL, United States
- Center for Brain Repair, Florida State University College of Medicine, Tallahassee, FL, United States
- *Correspondence: Gregg D. Stanwood
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18
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Zhou J, Li J, Zhao Q, Ou P, Zhao W. Working memory deficits in children with schizophrenia and its mechanism, susceptibility genes, and improvement: A literature review. Front Psychiatry 2022; 13:899344. [PMID: 35990059 PMCID: PMC9389215 DOI: 10.3389/fpsyt.2022.899344] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 07/20/2022] [Indexed: 11/13/2022] Open
Abstract
The negative influence on the cognitive ability of schizophrenia is one of the issues widely discussed in recent years. Working memory deficits are thought to be a core cognitive symptom of schizophrenia and lead to poorer social functions and worse academic performance. Previous studies have confirmed that working memory deficits tend to appear in the prodromal phase of schizophrenia. Therefore, considering that children with schizophrenia have better brain plasticity, it is critical to explore the development of their working memory. Although the research in this field developed gradually in recent years, few researchers have summarized these findings. The current study aims to review the recent studies from both behavior and neuroimaging aspects to summarize the working memory deficits of children with schizophrenia and to discuss the pathogenic factors such as genetic susceptibility. In addition, this study put forward some practicable interventions to improve cognitive symptoms of schizophrenia from psychological and neural perspectives.
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Affiliation(s)
- Jintao Zhou
- School of Psychology, Nanjing Normal University, Nanjing, China.,Department of Psychology, Fudan University, Shanghai, China
| | - Jingfangzhou Li
- School of Psychology, Nanjing Normal University, Nanjing, China
| | - Qi Zhao
- Department of Psychology, Faculty of Social Sciences, University of Macau, Macao, Macao SAR, China
| | - Peixin Ou
- Department of Psychology, Faculty of Social Sciences, University of Macau, Macao, Macao SAR, China
| | - Wan Zhao
- School of Psychology, Nanjing Normal University, Nanjing, China
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19
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Elevated endogenous GDNF induces altered dopamine signalling in mice and correlates with clinical severity in schizophrenia. Mol Psychiatry 2022; 27:3247-3261. [PMID: 35618883 PMCID: PMC9708553 DOI: 10.1038/s41380-022-01554-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 03/24/2022] [Accepted: 03/25/2022] [Indexed: 11/08/2022]
Abstract
Presynaptic increase in striatal dopamine is the primary dopaminergic abnormality in schizophrenia, but the underlying mechanisms are not understood. Here, we hypothesized that increased expression of endogenous GDNF could induce dopaminergic abnormalities that resemble those seen in schizophrenia. To test the impact of GDNF elevation, without inducing adverse effects caused by ectopic overexpression, we developed a novel in vivo approach to conditionally increase endogenous GDNF expression. We found that a 2-3-fold increase in endogenous GDNF in the brain was sufficient to induce molecular, cellular, and functional changes in dopamine signalling in the striatum and prefrontal cortex, including increased striatal presynaptic dopamine levels and reduction of dopamine in prefrontal cortex. Mechanistically, we identified adenosine A2a receptor (A2AR), a G-protein coupled receptor that modulates dopaminergic signalling, as a possible mediator of GDNF-driven dopaminergic abnormalities. We further showed that pharmacological inhibition of A2AR with istradefylline partially normalised striatal GDNF and striatal and cortical dopamine levels in mice. Lastly, we found that GDNF levels are increased in the cerebrospinal fluid of first episode psychosis patients, and in post-mortem striatum of schizophrenia patients. Our results reveal a possible contributor for increased striatal dopamine signalling in a subgroup of schizophrenia patients and suggest that GDNF-A2AR crosstalk may regulate dopamine function in a therapeutically targetable manner.
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20
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Zhang Q, Zhang Y, Zhang J, Zhang D, Li M, Yan H, Zhang H, Song L, Wang J, Hou Z, Yang Y, Zou X. p66α Suppresses Breast Cancer Cell Growth and Migration by Acting as Co-Activator of p53. Cells 2021; 10:3593. [PMID: 34944103 PMCID: PMC8700327 DOI: 10.3390/cells10123593] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 12/03/2021] [Accepted: 12/16/2021] [Indexed: 01/31/2023] Open
Abstract
p66α is a GATA zinc finger domain-containing transcription factor that has been shown to be essential for gene silencing by participating in the NuRD complex. Several studies have suggested that p66α is a risk gene for a wide spectrum of diseases such as diabetes, schizophrenia, and breast cancer; however, its biological role has not been defined. Here, we report that p66α functions as a tumor suppressor to inhibit breast cancer cell growth and migration, evidenced by the fact that the depletion of p66α results in accelerated tumor growth and migration of breast cancer cells. Mechanistically, immunoprecipitation assays identify p66α as a p53-interacting protein that binds the DNA-binding domain of p53 molecule predominantly via its CR2 domain. Depletion of p66α in multiple breast cells results in decreased expression of p53 target genes, while over-expression of p66α results in increased expression of these target genes. Moreover, p66α promotes the transactivity of p53 by enhancing p53 binding at target promoters. Together, these findings demonstrate that p66α is a tumor suppressor by functioning as a co-activator of p53.
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Affiliation(s)
- Qun Zhang
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Yihong Zhang
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Jie Zhang
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Dan Zhang
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Mengying Li
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Han Yan
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Hui Zhang
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Liwei Song
- Shanghai Pulmonary Tumor Medical Center, Shanghai Chest Hospital, Shanghai 200025, China;
- Naruiboen Biomedical Technology Corporation Limited, Linyi 277700, China
| | - Jiamin Wang
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Zhaoyuan Hou
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Yunhai Yang
- Shanghai Pulmonary Tumor Medical Center, Shanghai Chest Hospital, Shanghai 200025, China;
| | - Xiuqun Zou
- Hongqiao International Institute of Medicine, Tongren Hospital/Faculty of Basic Medicine, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China; (Q.Z.); (Y.Z.); (J.Z.); (D.Z.); (M.L.); (H.Y.); (H.Z.); (J.W.); (Z.H.)
- Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cellular Biology, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
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21
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Braun U, Harneit A, Pergola G, Menara T, Schäfer A, Betzel RF, Zang Z, Schweiger JI, Zhang X, Schwarz K, Chen J, Blasi G, Bertolino A, Durstewitz D, Pasqualetti F, Schwarz E, Meyer-Lindenberg A, Bassett DS, Tost H. Brain network dynamics during working memory are modulated by dopamine and diminished in schizophrenia. Nat Commun 2021; 12:3478. [PMID: 34108456 PMCID: PMC8190281 DOI: 10.1038/s41467-021-23694-9] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2019] [Accepted: 04/27/2021] [Indexed: 02/06/2023] Open
Abstract
Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory performance entails brain-wide switching between activity states using a combination of functional magnetic resonance imaging in healthy controls and individuals with schizophrenia, pharmacological fMRI, genetic analyses and network control theory. The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expression and pharmacological modulation. Individuals with schizophrenia show altered network control properties, including a more diverse energy landscape and decreased stability of working memory representations. Our results demonstrate the relevance of dopamine signaling for the steering of whole-brain network dynamics during working memory and link these processes to schizophrenia pathophysiology. Working memory requires the brain to switch between cognitive states and activity patterns. Here, the authors show that the steering of these neural network dynamics is influenced by dopamine D1- and D2-receptor function and altered in schizophrenia.
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Affiliation(s)
- Urs Braun
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 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, Mannheim, Germany
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Tommaso Menara
- Mechanical Engineering Department, University of California at Riverside, Riverside, CA, USA
| | - Axel Schäfer
- Bender Institute of Neuroimaging, Justus Liebig University Giessen, Gießen, Germany.,Center for Mind, Brain and Behavior, University of Marburg and Justus Liebig University Giessen, Gießen, Germany
| | - Richard F Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Zhenxiang Zang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Janina I Schweiger
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Xiaolong Zhang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Kristina Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Junfang Chen
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Giuseppe Blasi
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Daniel Durstewitz
- Department of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Fabio Pasqualetti
- Mechanical Engineering Department, University of California at Riverside, Riverside, CA, USA
| | - Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Danielle S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, USA.,Department of Neurology, University of Pennsylvania, Philadelphia, USA.,Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, USA.,Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, USA.,The 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, Mannheim, Germany
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22
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The interaction between cannabis use and a CB1-related polygenic co-expression index modulates dorsolateral prefrontal activity during working memory processing. Brain Imaging Behav 2021; 15:288-299. [PMID: 32124274 DOI: 10.1007/s11682-020-00256-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Convergent findings indicate that cannabis use and variation in the cannabinoid CB1 receptor coding gene (CNR1) modulate prefrontal function during working memory (WM). Other results also suggest that cannabis modifies the physiological relationship between genetically induced expression of CNR1 and prefrontal WM processing. However, it is possible that cannabis exerts its modifying effect on prefrontal physiology by interacting with complex molecular ensembles co-regulated with CB1. Since co-regulated genes are likely co-expressed, we investigated how genetically predicted co-expression of a molecular network including CNR1 interacts with cannabis use in modulating WM processing in humans. Using post-mortem human prefrontal data, we first computed a polygenic score (CNR1-PCI), combining the effects of single nucleotide polymorphisms (SNPs) on co-expression of a cohesive gene set including CNR1, and positively correlated with such co-expression. Then, in an in vivo study, we computed CNR1-PCI in 88 cannabis users and 147 non-users and investigated its interaction with cannabis use on brain activity during WM. Results revealed an interaction between cannabis use and CNR1-PCI in the dorsolateral prefrontal cortex (DLPFC), with a positive relationship between CNR1-PCI and DLPFC activity in cannabis users and a negative relationship in non-users. Furthermore, DLPFC activity in cannabis users was positively correlated with the frequency of cannabis use. Taken together, our results suggest that co-expression of a CNR1-related network predicts WM-related prefrontal activation as a function of cannabis use. Furthermore, they offer novel insights into the biological mechanisms associated with the use of cannabis.
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23
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Rampino A, Torretta S, Gelao B, Veneziani F, Iacoviello M, Marakhovskaya A, Masellis R, Andriola I, Sportelli L, Pergola G, Minelli A, Magri C, Gennarelli M, Vita A, Beaulieu JM, Bertolino A, Blasi G. Evidence of an interaction between FXR1 and GSK3β polymorphisms on levels of Negative Symptoms of Schizophrenia and their response to antipsychotics. Eur Psychiatry 2021; 64:e39. [PMID: 33866994 PMCID: PMC8260562 DOI: 10.1192/j.eurpsy.2021.26] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Genome-Wide Association Studies (GWASs) have identified several genes associated with Schizophrenia (SCZ) and exponentially increased knowledge on the genetic basis of the disease. In addition, products of GWAS genes interact with neuronal factors coded by genes lacking association, such that this interaction may confer risk for specific phenotypes of this brain disorder. In this regard, fragile X mental retardation syndrome-related 1 (FXR1) gene has been GWAS associated with SCZ. FXR1 protein is regulated by glycogen synthase kinase-3β (GSK3β), which has been implicated in pathophysiology of SCZ and response to antipsychotics (APs). rs496250 and rs12630592, two eQTLs (Expression Quantitative Trait Loci) of FXR1 and GSK3β, respectively, interact on emotion stability and amygdala/prefrontal cortex activity during emotion processing. These two phenotypes are associated with Negative Symptoms (NSs) of SCZ suggesting that the interaction between these SNPs may also affect NS severity and responsiveness to medication. METHODS To test this hypothesis, in two independent samples of patients with SCZ, we investigated rs496250 by rs12630592 interaction on NS severity and response to APs. We also tested a putative link between APs administration and FXR1 expression, as already reported for GSK3β expression. RESULTS We found that rs496250 and rs12630592 interact on NS severity. We also found evidence suggesting interaction of these polymorphisms also on response to APs. This interaction was not present when looking at positive and general psychopathology scores. Furthermore, chronic olanzapine administration led to a reduction of FXR1 expression in mouse frontal cortex. DISCUSSION Our findings suggest that, like GSK3β, FXR1 is affected by APs while shedding new light on the role of the FXR1/GSK3β pathway for NSs of SCZ.
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Affiliation(s)
- Antonio Rampino
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Silvia Torretta
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Barbara Gelao
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Federica Veneziani
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Department of Pharmacology, University of Toronto, Toronto, Ontario, Canada
| | - Matteo Iacoviello
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | | | - Rita Masellis
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Ileana Andriola
- Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Leonardo Sportelli
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Giulio Pergola
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland, USA
| | - Alessandra Minelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.,Genetics Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Chiara Magri
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.,Genetics Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Antonio Vita
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.,Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Brescia, Italy
| | | | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
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24
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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: 15] [Impact Index Per Article: 5.0] [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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25
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Special Article: Translational Science Update. Pharmacological Implications of Emerging Schizophrenia Genetics: Can the Bridge From 'Genomics' to 'Therapeutics' be Defined and Traversed? J Clin Psychopharmacol 2021; 40:323-329. [PMID: 32433256 DOI: 10.1097/jcp.0000000000001215] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Recent schizophrenia genome-wide association studies (GWAS) have identified genomic variants of common and rare frequency, significantly associated with schizophrenia. While numerous functional genomics efforts are ongoing to elucidate the biological effects of schizophrenia risk variants, a consideration of their therapeutic implications is timely and imperative, for patients as well as for an iterative effect on elucidating the underlying biology and pathophysiology of illness. The current article reviews efforts to translate emerging schizophrenia genomics into novel approaches to target discovery and therapeutic intervention. Though the path from 'genetic risk to therapy' is far from straightforward, there are provocative early possibilities that harbor the promise of treatment based on causation rather than phenomenology, as well as 'precision psychiatry,' a basis for stratifying patients to enable more precise and effective, personalized therapy.
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26
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Chen J, Cao H, Kaufmann T, Westlye LT, Tost H, Meyer-Lindenberg A, Schwarz E. Identification of Reproducible BCL11A Alterations in Schizophrenia Through Individual-Level Prediction of Coexpression. Schizophr Bull 2020; 46:1165-1171. [PMID: 32232389 PMCID: PMC7505190 DOI: 10.1093/schbul/sbaa047] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Previous studies have provided evidence for an alteration of genetic coexpression in schizophrenia (SCZ). However, such analyses have thus far lacked biological specificity for individual genes, which may be critical for identifying illness-relevant effects. Therefore, we applied machine learning to identify gene-specific coexpression differences at the individual subject level and compared these between individuals with SCZ, bipolar disorder, major depressive disorder (MDD), autism spectrum disorder (ASD), and healthy controls. Utilizing transcriptome-wide gene expression data from 21 independent datasets, comprising a total of 9509 participants, we identified a reproducible decrease of BCL11A coexpression across 4 SCZ datasets that showed diagnostic specificity for SCZ when compared with ASD and MDD. We further demonstrate that individual-level coexpression differences can be combined in multivariate coexpression scores that show reproducible illness classification across independent datasets in SCZ and ASD. This study demonstrates that machine learning can capture gene-specific coexpression differences at the individual subject level for SCZ and identify novel biomarker candidates.
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Affiliation(s)
- Junfang Chen
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Han Cao
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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27
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A shared genetic contribution to breast cancer and schizophrenia. Nat Commun 2020; 11:4637. [PMID: 32934226 PMCID: PMC7492262 DOI: 10.1038/s41467-020-18492-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 08/21/2020] [Indexed: 01/12/2023] Open
Abstract
An association between schizophrenia and subsequent breast cancer has been suggested; however the risk of schizophrenia following a breast cancer is unknown. Moreover, the driving forces of the link are largely unclear. Here, we report the phenotypic and genetic positive associations of schizophrenia with breast cancer and vice versa, based on a Swedish population-based cohort and GWAS data from international consortia. We observe a genetic correlation of 0.14 (95% CI 0.09–0.19) and identify a shared locus at 19p13 (GATAD2A) associated with risks of breast cancer and schizophrenia. The epidemiological bidirectional association between breast cancer and schizophrenia may partly be explained by the genetic overlap between the two phenotypes and, hence, shared biological mechanisms. Schizophrenia has been associated with increased risk of breast cancer, yet the risk of schizophrenia following breast cancer is unclear. Here, the authors show a bidirectional association between breast cancer and schizophrenia in Sweden and a shared genetic contribution to both diseases.
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28
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Selvaggi P, Pergola G, Gelao B, Di Carlo P, Nettis MA, Amico G, Fazio L, Rampino A, Sambataro F, Blasi G, Bertolino A. Genetic Variation of a DRD2 Co-expression Network is Associated with Changes in Prefrontal Function After D2 Receptors Stimulation. Cereb Cortex 2020; 29:1162-1173. [PMID: 29415163 DOI: 10.1093/cercor/bhy022] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 01/15/2018] [Indexed: 01/26/2023] Open
Abstract
Dopamine D2 receptors (D2Rs) contribute to the inverted U-shaped relationship between dopamine signaling and prefrontal function. Genetic networks from post-mortem human brain revealed 84 partner genes co-expressed with DRD2. Moreover, eight functional single nucleotide polymorphisms combined into a polygenic co-expression index (PCI) predicted co-expression of this DRD2 network and were associated with prefrontal function in humans. Here, we investigated the non-linear association of the PCI with behavioral and Working Memory (WM) related brain response to pharmacological D2Rs stimulation. Fifty healthy volunteers took part in a double-blind, placebo-controlled, functional MRI (fMRI) study with bromocriptine and performed the N-Back task. The PCI by drug interaction was significant on both WM behavioral scores (P = 0.046) and related prefrontal activity (all corrected P < 0.05) using a polynomial PCI model. Non-linear responses under placebo were reversed by bromocriptine administration. fMRI results on placebo were replicated in an independent sample of 50 participants who did not receive drug administration (P = 0.034). These results match earlier evidence in non-human primates and confirm the physiological relevance of this DRD2 co-expression network. Results show that in healthy subjects, different alleles evaluated as an ensemble are associated with non-linear prefrontal responses. Therefore, brain response to a dopaminergic drug may depend on a complex system of allelic patterns associated with DRD2 co-expression.
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Affiliation(s)
- Pierluigi Selvaggi
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Giulio Pergola
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Barbara Gelao
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Pasquale Di Carlo
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Maria Antonietta Nettis
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Graziella Amico
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Leonardo Fazio
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Antonio Rampino
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Fabio Sambataro
- Department of Experimental and Clinical Medical Science, University of Udine, Udine, Italy
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy.,Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
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29
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Antonucci LA, Pergola G, Pigoni A, Dwyer D, Kambeitz-Ilankovic L, Penzel N, Romano R, Gelao B, Torretta S, Rampino A, Trojano M, Caforio G, Falkai P, Blasi G, Koutsouleris N, Bertolino A. A Pattern of Cognitive Deficits Stratified for Genetic and Environmental Risk Reliably Classifies Patients With Schizophrenia From Healthy Control Subjects. Biol Psychiatry 2020; 87:697-707. [PMID: 31948640 DOI: 10.1016/j.biopsych.2019.11.007] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 10/23/2019] [Accepted: 11/04/2019] [Indexed: 11/25/2022]
Abstract
BACKGROUND Schizophrenia risk is associated with both genetic and environmental risk factors. Furthermore, cognitive abnormalities are established core characteristics of schizophrenia. We aim to assess whether a classification approach encompassing risk factors, cognition, and their associations can discriminate patients with schizophrenia (SCZs) from healthy control subjects (HCs). We hypothesized that cognition would demonstrate greater HC-SCZ classification accuracy and that combined gene-environment stratification would improve the discrimination performance of cognition. METHODS Genome-wide association study-based genetic, environmental, and neurocognitive classifiers were trained to separate 337 HCs from 103 SCZs using support vector classification and repeated nested cross-validation. We validated classifiers on independent datasets using within-diagnostic (SCZ) and cross-diagnostic (clinically isolated syndrome for multiple sclerosis, another condition with cognitive abnormalities) approaches. Then, we tested whether gene-environment multivariate stratification modulated the discrimination performance of the cognitive classifier in iterative subsamples. RESULTS The cognitive classifier discriminated SCZs from HCs with a balanced accuracy (BAC) of 88.7%, followed by environmental (BAC = 65.1%) and genetic (BAC = 55.5%) classifiers. Similar classification performance was measured in the within-diagnosis validation sample (HC-SCZ BACs, cognition = 70.5%; environment = 65.8%; genetics = 49.9%). The cognitive classifier was relatively specific to schizophrenia (HC-clinically isolated syndrome for multiple sclerosis BAC = 56.7%). Combined gene-environment stratification allowed cognitive features to classify HCs from SCZs with 89.4% BAC. CONCLUSIONS Consistent with cognitive deficits being core features of the phenotype of SCZs, our results suggest that cognitive features alone bear the greatest amount of information for classification of SCZs. Consistent with genes and environment being risk factors, gene-environment stratification modulates HC-SCZ classification performance of cognition, perhaps providing another target for refining early identification and intervention strategies.
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Affiliation(s)
- Linda A Antonucci
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany; Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Department of Education, Psychology and Communication, University of Bari Aldo Moro, Bari, Italy.
| | - Giulio Pergola
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Alessandro Pigoni
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Dominic Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | | | - Nora Penzel
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - Raffaella Romano
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Barbara Gelao
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Silvia Torretta
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Antonio Rampino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Bari University Hospital, Bari, Italy
| | - Maria Trojano
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Bari University Hospital, Bari, Italy
| | - Grazia Caforio
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Bari University Hospital, Bari, Italy
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - Giuseppe Blasi
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Bari University Hospital, Bari, Italy
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - Alessandro Bertolino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Bari University Hospital, Bari, Italy.
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30
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Identification and prioritization of gene sets associated with schizophrenia risk by co-expression network analysis in human brain. Mol Psychiatry 2020; 25:791-804. [PMID: 30478419 DOI: 10.1038/s41380-018-0304-1] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2018] [Revised: 08/07/2018] [Accepted: 10/29/2018] [Indexed: 12/13/2022]
Abstract
Schizophrenia polygenic risk is plausibly manifested by complex transcriptional dysregulation in the brain, involving networks of co-expressed and functionally related genes. The main purpose of this study was to identify and prioritize co-expressed gene sets in a hierarchical manner, based on the strength of the relationships with clinical diagnosis and with polygenic risk for schizophrenia. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to RNA-quality-adjusted DLPFC RNA-Seq data from the LIBD Postmortem Human Brain Repository (90 controls, 74 schizophrenia cases; all Caucasians) to construct co-expression networks and detect "modules" of co-expressed genes. After multiple internal and external validation procedures, modules of selected interest were tested for enrichment in biological ontologies, for association with schizophrenia polygenic risk scores (PRSs) and with diagnosis, and also for enrichment in genes within the significant GWAS loci reported by the Psychiatric Genomic Consortium (PGC2). The association between schizophrenia genetic signals and modules of co-expression converged on one module showing not only a significant association with both diagnosis and PRS but also significant overlap with 36 PGC2 loci genes, deemed the strongest candidates for drug targets. This module contained many genes involved in synaptic signaling and neuroplasticity. Fifty-three PGC2 genes were in modules associated only with diagnosis and 59 in modules unrelated to diagnosis or PRS. Our study highlights complex relationships between gene co-expression networks in the brain and clinical state and polygenic risk for SCZ and provides a strategy for using this information in selecting and prioritizing potentially targetable gene sets for therapeutic drug development.
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31
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Torretta S, Rampino A, Basso M, Pergola G, Di Carlo P, Shin JH, Kleinman JE, Hyde TM, Weinberger DR, Masellis R, Blasi G, Pennuto M, Bertolino A. NURR1 and ERR1 Modulate the Expression of Genes of a DRD2 Coexpression Network Enriched for Schizophrenia Risk. J Neurosci 2020; 40:932-941. [PMID: 31811028 PMCID: PMC6975285 DOI: 10.1523/jneurosci.0786-19.2019] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Revised: 10/09/2019] [Accepted: 10/17/2019] [Indexed: 12/11/2022] Open
Abstract
Multiple schizophrenia (SCZ) risk loci may be involved in gene co-regulation mechanisms, and analysis of coexpressed gene networks may help to clarify SCZ molecular basis. We have previously identified a dopamine D2 receptor (DRD2) coexpression module enriched for SCZ risk genes and associated with cognitive and neuroimaging phenotypes of SCZ, as well as with response to treatment with antipsychotics. Here we aimed to identify regulatory factors modulating this coexpression module and their relevance to SCZ. We performed motif enrichment analysis to identify transcription factor (TF) binding sites in human promoters of genes coexpressed with DRD2. Then, we measured transcript levels of a group of these genes in primary mouse cortical neurons in basal conditions and upon overexpression and knockdown of predicted TFs. Finally, we analyzed expression levels of these TFs in dorsolateral prefrontal cortex (DLPFC) of SCZ patients. Our in silico analysis revealed enrichment for NURR1 and ERR1 binding sites. In neuronal cultures, the expression of genes either relevant to SCZ risk (Drd2, Gatad2a, Slc28a1, Cnr1) or indexing coexpression in our module (Btg4, Chit1, Osr1, Gpld1) was significantly modified by gain and loss of Nurr1 and Err1. Postmortem DLPFC expression data analysis showed decreased expression levels of NURR1 and ERR1 in patients with SCZ. For NURR1 such decreased expression is associated with treatment with antipsychotics. Our results show that NURR1 and ERR1 modulate the transcription of DRD2 coexpression partners and support the hypothesis that NURR1 is involved in the response to SCZ treatment.SIGNIFICANCE STATEMENT In the present study, we provide in silico and experimental evidence for a role of the TFs NURR1 and ERR1 in modulating the expression pattern of genes coexpressed with DRD2 in human DLPFC. Notably, genetic variations in these genes is associated with SCZ risk and behavioral and neuroimaging phenotypes of the disease, as well as with response to treatment. Furthermore, this study presents novel findings on a possible interplay between D2 receptor-mediated dopamine signaling involved in treatment with antipsychotics and the transcriptional regulation mechanisms exerted by NURR1. Our results suggest that coexpression and co-regulation mechanisms may help to explain some of the complex biology of genetic associations with SCZ.
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Affiliation(s)
- Silvia Torretta
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari 70124, Italy
| | - Antonio Rampino
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari 70124, Italy
- Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, 70124, Italy
| | - Manuela Basso
- Laboratory of Transcriptional Neurobiology, Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento 38123, Italy
| | - Giulio Pergola
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari 70124, Italy
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
| | - Pasquale Di Carlo
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari 70124, Italy
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
| | - Joo H Shin
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
- Departments of Neurology
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
- Neuroscience
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, 21205
| | - Rita Masellis
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari 70124, Italy
- Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, 70124, Italy
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari 70124, Italy
- Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, 70124, Italy
| | - Maria Pennuto
- Department of Biomedical Sciences, University of Padova, Padova 35131, Italy
- Veneto Institute of Molecular Medicine (VIMM), Padova 35129, Italy
- Dulbecco Telethon Institute, CIBIO, University of Trento, 38123, Italy
- Padova Neuroscience Center, 35131 Padova, Italy, and
| | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari 70124, Italy,
- Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, 70124, Italy
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Ramos PIP, Arge LWP, Lima NCB, Fukutani KF, de Queiroz ATL. Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets. Front Genet 2019; 10:1120. [PMID: 31798629 PMCID: PMC6863976 DOI: 10.3389/fgene.2019.01120] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 10/16/2019] [Indexed: 11/13/2022] Open
Abstract
Recent technological advances for the acquisition of multi-omics data have allowed an unprecedented understanding of the complex intricacies of biological systems. In parallel, a myriad of computational analysis techniques and bioinformatics tools have been developed, with many efforts directed towards the creation and interpretation of networks from this data. In this review, we begin by examining key network concepts and terminology. Then, computational tools that allow for their construction and analysis from high-throughput omics datasets are presented. We focus on the study of functional relationships such as co-expression, protein-protein interactions, and regulatory interactions that are particularly amenable to modeling using the framework of networks. We envisage that many potential users of these analytical strategies may not be completely literate in programming languages and code adaptation, and for this reason, emphasis is given to tools' user-friendliness, including plugins for the widely adopted Cytoscape software, an open-source, cross-platform tool for network analysis, visualization, and data integration.
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Affiliation(s)
- Pablo Ivan Pereira Ramos
- Center for Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Luis Willian Pacheco Arge
- Laboratório de Genética Molecular e Biotecnologia Vegetal, Centro de Ciências da Saúde, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Kiyoshi F. Fukutani
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Fundação José Silveira, Salvador, Brazil
| | - Artur Trancoso L. de Queiroz
- Center for Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
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Molent C, Olivo D, Wolf RC, Balestrieri M, Sambataro F. Functional neuroimaging in treatment resistant schizophrenia: A systematic review. Neurosci Biobehav Rev 2019; 104:178-190. [PMID: 31276716 DOI: 10.1016/j.neubiorev.2019.07.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 06/25/2019] [Accepted: 07/01/2019] [Indexed: 01/06/2023]
Abstract
Despite the availability of several drugs, about 30% of patients with schizophrenia still fail to respond properly to a course of appropriate antipsychotic treatment. Functional neuroimaging studies have shown widespread patterns of altered activation and functional connectivity in treatment-resistant schizophrenia (TRS). The aim of the present study was to examine the available functional magnetic resonance imaging studies investigating TRS and to identify common patterns of altered brain function that could predict the lack of response to antipsychotic treatment in this disorder. Alterations of activation and functional connectivity in fronto-temporal, cortico-striatal, default mode network and salience networks, and of their interplay, were associated with TRS. Our findings support the notion that large-scale network alterations present in schizophrenia lie in a continuum within treatment response with the most severe dysfunction in TRS. Few studies with small sample size and without adequate control group limit the generalizability of current literature. Future controlled longitudinal studies are needed to identify neuroimaging biomarkers of pharmacotherapy response to inform individual treatment selection and facilitate early clinical response.
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Affiliation(s)
- Cinzia Molent
- Department of Medicine (DAME), University of Udine, Udine, Italy
| | - Daniele Olivo
- Department of Medicine (DAME), University of Udine, Udine, Italy; Department of Neuroscience (DNS), University of Padova, Padua, Italy
| | - Robert Christian Wolf
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Germany
| | | | - Fabio Sambataro
- Department of Medicine (DAME), University of Udine, Udine, Italy; Department of Neuroscience (DNS), University of Padova, Padua, Italy.
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Patania A, Selvaggi P, Veronese M, Dipasquale O, Expert P, Petri G. Topological gene expression networks recapitulate brain anatomy and function. Netw Neurosci 2019; 3:744-762. [PMID: 31410377 PMCID: PMC6663211 DOI: 10.1162/netn_a_00094] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 04/30/2019] [Indexed: 12/20/2022] Open
Abstract
Understanding how gene expression translates to and affects human behavior is one of the ultimate goals of neuroscience. In this paper, we present a pipeline based on Mapper, a topological simplification tool, to analyze gene co-expression data. We first validate the method by reproducing key results from the literature on the Allen Human Brain Atlas and the correlations between resting-state fMRI and gene co-expression maps. We then analyze a dopamine-related gene set and find that co-expression networks produced by Mapper return a structure that matches the well-known anatomy of the dopaminergic pathway. Our results suggest that network based descriptions can be a powerful tool to explore the relationships between genetic pathways and their association with brain function and its perturbation due to illness and/or pharmacological challenges.
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Affiliation(s)
- Alice Patania
- Network Science Institute, Indiana University, Bloomington, IN, USA
| | - Pierluigi Selvaggi
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Mattia Veronese
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Paul Expert
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
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Pergola G, Di Carlo P, Jaffe AE, Papalino M, Chen Q, Hyde TM, Kleinman JE, Shin JH, Rampino A, Blasi G, Weinberger DR, Bertolino A. Prefrontal Coexpression of Schizophrenia Risk Genes Is Associated With Treatment Response in Patients. Biol Psychiatry 2019; 86:45-55. [PMID: 31126695 DOI: 10.1016/j.biopsych.2019.03.981] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 03/13/2019] [Accepted: 03/14/2019] [Indexed: 10/27/2022]
Abstract
BACKGROUND Gene coexpression networks are relevant to functional and clinical translation of schizophrenia risk genes. We hypothesized that schizophrenia risk genes converge into coexpression pathways that may be associated with gene regulation mechanisms and with response to treatment in patients with schizophrenia. METHODS We identified gene coexpression networks in two prefrontal cortex postmortem RNA sequencing datasets (n = 688) and replicated them in four more datasets (n = 1295). We identified and replicated (p values < .001) a single module enriched for schizophrenia risk loci (13 risk genes in 10 loci). In silico screening of potential regulators of the schizophrenia risk module via bioinformatic analyses identified two transcription factors and three microRNAs associated with the risk module. To translate postmortem information into clinical phenotypes, we identified polymorphisms predicting coexpression and combined them to obtain an index approximating module coexpression (Polygenic Coexpression Index [PCI]). RESULTS The PCI-coexpression association was successfully replicated in two independent brain transcriptome datasets (n = 131; p values < .05). Finally, we tested the association between the PCI and short-term treatment response in two independent samples of patients with schizophrenia treated with olanzapine (n = 167). The PCI was associated with treatment response in the positive symptom domain in both clinical cohorts (p values < .05). CONCLUSIONS In summary, our findings in 1983 samples of human postmortem prefrontal cortex show that coexpression of a set of genes enriched for schizophrenia risk genes is relevant to treatment response. This coexpression pathway may be coregulated by transcription factors and microRNA associated with it.
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Affiliation(s)
- Giulio Pergola
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland.
| | - Pasquale Di Carlo
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Andrew E Jaffe
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Center for Computational Biology, Johns Hopkins University, Baltimore, Maryland
| | - Marco Papalino
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Joo Heon Shin
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
| | - Antonio Rampino
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland; McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy.
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Vita A, Minelli A, Barlati S, Deste G, Giacopuzzi E, Valsecchi P, Turrina C, Gennarelli M. Treatment-Resistant Schizophrenia: Genetic and Neuroimaging Correlates. Front Pharmacol 2019; 10:402. [PMID: 31040787 PMCID: PMC6476957 DOI: 10.3389/fphar.2019.00402] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Accepted: 04/01/2019] [Indexed: 12/11/2022] Open
Abstract
Schizophrenia is a severe neuropsychiatric disorder that affects approximately 0.5–1% of the population. Response to antipsychotic therapy is highly variable, and it is not currently possible to predict those patients who will or will not respond to antipsychotic medication. Furthermore, a high percentage of patients, approximately 30%, are classified as treatment-resistant (treatment-resistant schizophrenia; TRS). TRS is defined as a non-response to at least two trials of antipsychotic medication of adequate dose and duration. These patients are usually treated with clozapine, the only evidence-based pharmacotherapy for TRS. However, clozapine is associated with severe adverse events. For these reasons, there is an increasing interest to identify better targets for drug development of new compounds and to establish better biomarkers for existing medications. The ability of antipsychotics to improve psychotic symptoms is dependent on their antagonist and reverse agonist activities at different neuroreceptors, and some genetic association studies of TRS have focused on different pharmacodynamic factors. Some genetic studies have shown an association between antipsychotic response or TRS and neurodevelopment candidate genes, antipsychotic mechanisms of action (such as dopaminergic, serotonergic, GABAergic, and glutamatergic) or pharmacokinetic factors (i.e., differences in the cytochrome families). Moreover, there is a growing body of literature on the structural and functional neuroimaging research into TRS. Neuroimaging studies can help to uncover the underlying neurobiological reasons for such resistance and identify resistant patients earlier. Studies examining the neuropharmacological mechanisms of antipsychotics, including clozapine, can help to improve our knowledge of their action on the central nervous system, with further implications for the discovery of biomarkers and the development of new treatments. The identification of the underlying mechanisms of TRS is a major challenge for developing personalized medicine in the psychiatric field for schizophrenia treatment. The main goal of precision medicine is to use genetic and brain-imaging information to improve the safety, effectiveness, and health outcomes of patients via more efficiently targeted risk stratification, prevention, and tailored medication and treatment management approaches. The aim of this review is to summarize the state of art of pharmacogenetic, pharmacogenomic and neuroimaging studies in TRS.
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Affiliation(s)
- Antonio Vita
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Alessandra Minelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Stefano Barlati
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Giacomo Deste
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy
| | - Edoardo Giacopuzzi
- Genetic Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Paolo Valsecchi
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Cesare Turrina
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.,Genetic Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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Trotta A, Iyegbe C, Yiend J, Dazzan P, David AS, Pariante C, Mondelli V, Colizzi M, Murray RM, Di Forti M, Fisher HL. Interaction between childhood adversity and functional polymorphisms in the dopamine pathway on first-episode psychosis. Schizophr Res 2019; 205:51-57. [PMID: 29653893 DOI: 10.1016/j.schres.2018.04.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 03/30/2018] [Accepted: 04/04/2018] [Indexed: 01/13/2023]
Abstract
BACKGROUND There is consistent evidence of a cumulative relationship between childhood adversity and psychosis, with number of adversities experienced increasing the probability of psychosis onset. It is possible that genetic factors moderate the association between childhood adversity and psychosis, potentially by influencing how an individual reacts biologically and/or psychologically following exposure to adversity, in such a way as to set them off on the path to psychosis. However, identifying the specific genetic variants involved and how they interact with childhood adversity remains challenging. We examined whether the association between cumulative exposure to childhood adversity and development of psychotic disorder was moderated by the COMT Val158Met, AKT1 rs2494732 or DRD2 rs1076560 polymorphisms, known to affect dopamine levels. METHODS Participants were 285 first-presentation psychosis cases and 256 geographically-matched controls drawn from the Genetics and Psychosis (GAP) study. Childhood adversity was assessed using the Childhood Experience of Care and Abuse Questionnaire (CECA.Q) and blood- and cheek-derived genotype data were collected. RESULTS Our findings revealed no main effect of COMT Val158Met, AKT1 rs2494732 and DRD2 rs1076560 polymorphisms on psychosis case status or reports of childhood adversity. Individuals reporting a history of multiple adversities were more likely to be psychosis patients than controls, regardless of their genetic risk. There was no evidence of candidate genotype by childhood adversity interactions in relation to psychosis onset. CONCLUSION These findings did not provide evidence of a possible role of COMT Val158Met, AKT1 rs2494732 or DRD2 rs1076560 genotypes in modifying the association between childhood adversity and onset of psychosis.
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Affiliation(s)
- Antonella Trotta
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Heather Close Rehabilitation Service, South London and Maudsley NHS Foundation Trust, London, UK
| | - Conrad Iyegbe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Jenny Yiend
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Paola Dazzan
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Anthony S David
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Carmine Pariante
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Valeria Mondelli
- National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Marco Colizzi
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Marta Di Forti
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Helen L Fisher
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
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Thalamic connectivity measured with fMRI is associated with a polygenic index predicting thalamo-prefrontal gene co-expression. Brain Struct Funct 2019; 224:1331-1344. [DOI: 10.1007/s00429-019-01843-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 01/31/2019] [Indexed: 01/11/2023]
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Whitton L, Apostolova G, Rieder D, Dechant G, Rea S, Donohoe G, Morris DW. Genes regulated by SATB2 during neurodevelopment contribute to schizophrenia and educational attainment. PLoS Genet 2018; 14:e1007515. [PMID: 30040823 PMCID: PMC6097700 DOI: 10.1371/journal.pgen.1007515] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Revised: 08/17/2018] [Accepted: 06/26/2018] [Indexed: 12/20/2022] Open
Abstract
SATB2 is associated with schizophrenia and is an important transcription factor regulating neocortical organization and circuitry. Rare mutations in SATB2 cause a syndrome that includes developmental delay, and mouse studies identify an important role for SATB2 in learning and memory. Interacting partners BCL11B and GATAD2A are also schizophrenia risk genes indicating that other genes interacting with or are regulated by SATB2 are making a contribution to schizophrenia and cognition. We used data from Satb2 mouse models to generate three gene-sets that contain genes either functionally related to SATB2 or targeted by SATB2 at different stages of development. Each was tested for enrichment using the largest available genome-wide association studies (GWAS) datasets for schizophrenia and educational attainment (EA) and enrichment analysis was also performed for schizophrenia and other neurodevelopmental disorders using data from rare variant sequencing studies. These SATB2 gene-sets were enriched for genes containing common variants associated with schizophrenia and EA, and were enriched for genes containing rare variants reported in studies of schizophrenia, autism and intellectual disability. In the developing cortex, genes targeted by SATB2 based on ChIP-seq data, and functionally affected when SATB2 is not expressed based on differential expression analysis using RNA-seq data, show strong enrichment for genes associated with EA. For genes expressed in the hippocampus or at the synapse, those targeted by SATB2 are more strongly enriched for genes associated EA than gene-sets not targeted by SATB2. This study demonstrates that single gene findings from GWAS can provide important insights to pathobiological processes. In this case we find evidence that genes influenced by SATB2 and involved in synaptic transmission, axon guidance and formation of the corpus callosum are contributing to schizophrenia and cognition. Schizophrenia is a complex disorder caused by many genes. Using new gene discoveries to understand pathobiology is a foundation for development of new treatments. Current drugs for schizophrenia are only partially effective and do not treat cognitive deficits, which are key factors for explaining disability, leading to unemployment, homelessness and social isolation. Genome-wide association studies (GWAS) of schizophrenia have been effective at identifying individual SNPs and genes that contribute to risk but have struggled to immediately uncover the bigger picture of the underlying biology of the disorder. Here we take an individual gene identified in a schizophrenia GWAS called SATB2, which on its own is a very important regulator of brain development. We use functional genomics data from mouse studies to identify sets of others genes that are influenced by SATB2 during development. We show that these gene sets are enriched for common variants associated with schizophrenia and educational attainment (used as a proxy for cognition), and for rare variants that increase risk of various neurodevelopmental disorders. This study provides evidence that the molecular mechanisms that underpin schizophrenia and cognitive function include disruption of biological processes influenced by SATB2 as the brain is being organized and wired during development.
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Affiliation(s)
- Laura Whitton
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition and Genomics (NICOG) Centre and NCBES Galway Neuroscience Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Galina Apostolova
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck, Austria
| | - Dietmar Rieder
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck, Austria
| | - Georg Dechant
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck, Austria
| | - Stephen Rea
- Centre for Chromosome Biology, Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Gary Donohoe
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition and Genomics (NICOG) Centre and NCBES Galway Neuroscience Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Derek W. Morris
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition and Genomics (NICOG) Centre and NCBES Galway Neuroscience Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
- * E-mail:
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Fazio L, Pergola G, Papalino M, Di Carlo P, Monda A, Gelao B, Amoroso N, Tangaro S, Rampino A, Popolizio T, Bertolino A, Blasi G. Transcriptomic context of DRD1 is associated with prefrontal activity and behavior during working memory. Proc Natl Acad Sci U S A 2018; 115:5582-5587. [PMID: 29735686 PMCID: PMC6003490 DOI: 10.1073/pnas.1717135115] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Dopamine D1 receptor (D1R) signaling shapes prefrontal cortex (PFC) activity during working memory (WM). Previous reports found higher WM performance associated with alleles linked to greater expression of the gene coding for D1Rs (DRD1). However, there is no evidence on the relationship between genetic modulation of DRD1 expression in PFC and patterns of prefrontal activity during WM. Furthermore, previous studies have not considered that D1Rs are part of a coregulated molecular environment, which may contribute to D1R-related prefrontal WM processing. Thus, we hypothesized a reciprocal link between a coregulated (i.e., coexpressed) molecular network including DRD1 and PFC activity. To explore this relationship, we used three independent postmortem prefrontal mRNA datasets (total n = 404) to characterize a coexpression network including DRD1 Then, we indexed network coexpression using a measure (polygenic coexpression index-DRD1-PCI) combining the effect of single nucleotide polymorphisms (SNPs) on coexpression. Finally, we associated the DRD1-PCI with WM performance and related brain activity in independent samples of healthy participants (total n = 371). We identified and replicated a coexpression network including DRD1, whose coexpression was correlated with DRD1-PCI. We also found that DRD1-PCI was associated with lower PFC activity and higher WM performance. Behavioral and imaging results were replicated in independent samples. These findings suggest that genetically predicted expression of DRD1 and of its coexpression partners stratifies healthy individuals in terms of WM performance and related prefrontal activity. They also highlight genes and SNPs potentially relevant to pharmacological trials aimed to test cognitive enhancers modulating DRD1 signaling.
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Affiliation(s)
- Leonardo Fazio
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, 70124 Bari, Italy
- Sezione di Neuroradiologia, Istituto di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza," 71013 San Giovanni Rotondo, Italy
- Contributed Equally
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, 70124 Bari, Italy
- Contributed Equally
| | - Marco Papalino
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, 70124 Bari, Italy
| | - Pasquale Di Carlo
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, 70124 Bari, Italy
| | - Anna Monda
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, 70124 Bari, Italy
| | - Barbara Gelao
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, 70124 Bari, Italy
| | - Nicola Amoroso
- Dipartimento Interateneo di Fisica "M. Merlin," Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy
- Sezione di Bari, Istituto Nazionale di Fisica Nucleare, 70125 Bari, Italy
| | - Sabina Tangaro
- Sezione di Bari, Istituto Nazionale di Fisica Nucleare, 70125 Bari, Italy
| | - Antonio Rampino
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, 70124 Bari, Italy
- Institute of Psychiatry, Bari University Hospital, 70124 Bari, Italy
| | - Teresa Popolizio
- Sezione di Neuroradiologia, Istituto di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza," 71013 San Giovanni Rotondo, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, 70124 Bari, Italy
- Institute of Psychiatry, Bari University Hospital, 70124 Bari, Italy
| | - Giuseppe Blasi
- Institute of Psychiatry, Bari University Hospital, 70124 Bari, Italy
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, 70124 Bari, Italy;
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41
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A complex network approach reveals a pivotal substructure of genes linked to schizophrenia. PLoS One 2018; 13:e0190110. [PMID: 29304112 PMCID: PMC5755767 DOI: 10.1371/journal.pone.0190110] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Accepted: 12/10/2017] [Indexed: 12/22/2022] Open
Abstract
Research on brain disorders with a strong genetic component and complex heritability, such as schizophrenia, has led to the development of brain transcriptomics. This field seeks to gain a deeper understanding of gene expression, a key factor in exploring further research issues. Our study focused on how genes are associated amongst each other. In this perspective, we have developed a novel data-driven strategy for characterizing genetic modules, i.e., clusters of strongly interacting genes. The aim was to uncover a pivotal community of genes linked to a target gene for schizophrenia. Our approach combined network topological properties with information theory to highlight the presence of a pivotal community, for a specific gene, and to simultaneously assess the information content of partitions with the Shannon’s entropy based on betweenness. We analyzed the publicly available BrainCloud dataset containing post-mortem gene expression data and focused on the Dopamine D2 receptor, encoded by the DRD2 gene. We used four different community detection algorithms to evaluate the consistence of our approach. A pivotal DRD2 community emerged for all the procedures applied, with a considerable reduction in size, compared to the initial network. The stability of the results was confirmed by a Dice index ≥80% within a range of tested parameters. The detected community was also the most informative, as it represented an optimization of the Shannon entropy. Lastly, we verified the strength of connection of the DRD2 community, which was stronger than any other randomly selected community and even more so than the Weighted Gene Co-expression Network Analysis module, commonly considered the standard approach for such studies. This finding substantiates the conclusion that the detected community represents a more connected and informative cluster of genes for the DRD2 community, and therefore better elucidates the behavior of this module of strongly related DRD2 genes. Because this gene plays a relevant role in Schizophrenia, this finding of a more specific DRD2 community will improve the understanding of the genetic factors related with this disorder.
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Abstract
Recent large-scale genomic studies have confirmed that schizophrenia is a polygenic syndrome and have implicated a number of biological pathways in its aetiology. Both common variants individually of small effect and rarer but more penetrant genetic variants have been shown to play a role in the pathogenesis of the disorder. No simple Mendelian forms of the condition have been identified, but progress has been made in stratifying risk on the basis of the polygenic burden of common variants individually of small effect, and the contribution of rarer variants of larger effect such as Copy Number Variants (CNVs). Pathway analysis of risk-associated variants has begun to identify specific biological processes implicated in risk for the disorder, including elements of the glutamatergic NMDA receptor complex and post synaptic density, voltage-gated calcium channels, targets of the Fragile X Mental Retardation Protein (FMRP targets) and immune pathways. Genetic studies have also been used to drive genomic imaging approaches to the investigation of brain markers associated with risk for the disorder. Genomic imaging approaches have been applied both to investigate the effect of polygenic risk and to study the impact of individual higher-penetrance variants such as CNVs. Both genomic and genomic imaging approaches offer potential for the stratification of patients and at-risk groups and the development of better biomarkers of risk and treatment response; however, further research is needed to integrate this work and realise the full potential of these approaches.
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Chen J, Schwarz E. The role of blood-based biomarkers in advancing personalized therapy of schizophrenia. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2017. [DOI: 10.1080/23808993.2017.1400906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Junfang Chen
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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Rampino A, Taurisano P, Fanelli G, Attrotto M, Torretta S, Antonucci LA, Miccolis G, Pergola G, Ursini G, Maddalena G, Romano R, Masellis R, Di Carlo P, Pignataro P, Blasi G, Bertolino A. A Polygenic Risk Score of glutamatergic SNPs associated with schizophrenia predicts attentional behavior and related brain activity in healthy humans. Eur Neuropsychopharmacol 2017; 27:928-939. [PMID: 28651857 DOI: 10.1016/j.euroneuro.2017.06.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Revised: 04/13/2017] [Accepted: 06/10/2017] [Indexed: 11/17/2022]
Abstract
Multiple genetic variations impact on risk for schizophrenia. Recent analyses by the Psychiatric Genomics Consortium (PGC2) identified 128 SNPs genome-wide associated with the disorder. Furthermore, attention and working memory deficits are core features of schizophrenia, are heritable and have been associated with variation in glutamatergic neurotransmission. Based on this evidence, in a sample of healthy volunteers, we used SNPs associated with schizophrenia in PGC2 to construct a Polygenic-Risk-Score (PRS) reflecting the cumulative risk for schizophrenia, along with a Polygenic-Risk-Score including only SNPs related to genes implicated in glutamatergic signaling (Glu-PRS). We performed Factor Analysis for dimension reduction of indices of cognitive performance. Furthermore, both PRS and Glu-PRS were used as predictors of cognitive functioning in the domains of Attention, Speed of Processing and Working Memory. The association of the Glu-PRS on brain activity during the Variable Attention Control (VAC) task was also explored. Finally, in a second independent sample of healthy volunteers we sought to confirm the association between the Glu-PRS and both performance in the domain of Attention and brain activity during the VAC.We found that performance in Speed of Processing and Working Memory was not associated with any of the Polygenic-Risk-Scores. The Glu-PRS, but not the PRS was associated with Attention and brain activity during the VAC. The specific effects of Glu-PRS on Attention and brain activity during the VAC were also confirmed in the replication sample.Our results suggest a pathway specificity in the relationship between genetic risk for schizophrenia, the associated cognitive dysfunction and related brain processing.
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Affiliation(s)
- Antonio Rampino
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Paolo Taurisano
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Giuseppe Fanelli
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Mariateresa Attrotto
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy; Psychiatry Unit - Bari University Hospital, Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Silvia Torretta
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Linda Antonella Antonucci
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Grazia Miccolis
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Gianluca Ursini
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, 21205 Baltimore, MD, USA
| | - Giancarlo Maddalena
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy; Psychiatry Unit - Bari University Hospital, Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Raffaella Romano
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Rita Masellis
- Psychiatry Unit - Bari University Hospital, Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Pasquale Di Carlo
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Patrizia Pignataro
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Giuseppe Blasi
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy; Psychiatry Unit - Bari University Hospital, Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs - University of Bari "Aldo Moro", Piazza Giulio Cesare 11, 70124 Bari, Italy; Psychiatry Unit - Bari University Hospital, Piazza Giulio Cesare 11, 70124 Bari, Italy.
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Peñagarikano O. Your genes are conspiring against you. Sci Transl Med 2017; 9:9/376/eaam6059. [DOI: 10.1126/scitranslmed.aam6059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Gene variants in the dopamine receptor D2 expression network predict physiological and clinical features as well as treatment responses in schizophrenia.
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Affiliation(s)
- Olga Peñagarikano
- Department of Pharmacology, School of Medicine, University of the Basque Country, Leioa 48940, Spain.
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