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Wu D, Chang Z, Wang Y, Jiang Z, Wang R, Wu Y. High-order network degree revealed shared and distinct features among schizophrenia, bipolar disorder and ADHD. Neuroscience 2025:S0306-4522(24)00776-0. [PMID: 39755231 DOI: 10.1016/j.neuroscience.2024.12.063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 12/02/2024] [Accepted: 12/30/2024] [Indexed: 01/06/2025]
Abstract
Schizophrenia (SCHZ), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD) share clinical symptoms and risk genes, but the shared and distinct neural dynamic mechanisms remain inadequately understood. Degree is a fundamental and important graph measure in network neuroscience, and we here extended the degree to hierarchical levels based on eigenmodes and compared the resting-state brain networks of three disorders and healthy controls (HC). First, compared to HC, SCHZ and BD patients exhibited substantially overlapped abnormalities in brain networks, wherein BD patients displayed more significant alterations. In contrast, ADHD patients exhibited few alterations. Second, compared to the graph theory measure, hierarchical degree better predicted the clinical symptoms of three disorders, and distinguished them from HC. Furthermore, three disorders shared associations of brain network abnormalities with dopamine receptors/transporters. Finally, the alterations in SCHZ and BD patients were associated with cellular localization and transport, as well as abnormal social behavior and communication, while ADHD patients were associated with energy production and transport. These findings provided a deep understanding of the shared and distinct neuropathology of three disorders and facilitated a more precise differentiation for them.
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Affiliation(s)
- Dingjie Wu
- School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an, China; State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi'an, China
| | - Zhao Chang
- College of Science, Xi'an University of Science and Technology, Xi'an, China
| | - Yaozu Wang
- School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an, China; State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi'an, China
| | - Zhengchang Jiang
- School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an, China; State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi'an, China
| | - Rong Wang
- School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an, China; College of Science, Xi'an University of Science and Technology, Xi'an, China.
| | - Ying Wu
- School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an, China; State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi'an, China; National Demonstration Center for Experimental Mechanics Education, Xi'an Jiaotong University, Xi'an, China.
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2
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de Freitas MBL, Luna LP, Beatriz M, Pinto RK, Alves CHL, Bittencourt L, Nardi AE, Oertel V, Veras AB, de Lucena DF, Alves GS. Resting-state fMRI is associated with trauma experiences, mood and psychosis in Afro-descendants with bipolar disorder and schizophrenia. Psychiatry Res Neuroimaging 2024; 340:111766. [PMID: 38408419 DOI: 10.1016/j.pscychresns.2023.111766] [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: 07/31/2023] [Revised: 11/19/2023] [Accepted: 11/26/2023] [Indexed: 02/28/2024]
Abstract
BACKGROUND Bipolar disorder (BD) and schizophrenia (SCZ) may exhibit functional abnormalities in several brain areas, including the medial temporal and prefrontal cortex and hippocampus; however, a less explored topic is how brain connectivity is linked to premorbid trauma experiences and clinical features in non-Caucasian samples of SCZ and BD. METHODS Sixty-two individuals with SCZ (n = 20), BD (n = 21), and healthy controls (HC, n = 21) from indigenous and African ethnicity were submitted to clinical screening (Di-PAD), traumata experiences (ETISR-SF), cognitive and functional MRI assessment. The item psychosis/hallucinations in SCZ patients showed a negative correlation with the global efficiency (GE) in the right dorsal attention network. The items mania, irritable mood, and racing thoughts in the Di-PAD scale had a significant negative correlation with the GE in the parietal right default mode network. CONCLUSIONS Differences in the activation of specific networks were associated with earlier disease onset, history of physical abuse, and more severe psychotic and mood symptoms in SCZ and BD subjects of indigenous and black ethnicity. Findings provide further evidence on SZ and BD's brain connectivity disturbances, and their clinical significance, in non-Caucasian samples.
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Affiliation(s)
| | - Licia P Luna
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, MD, USA
| | - Márcia Beatriz
- Neuroradiology Service, São Domingos Hospital, São Luís, Brazil; Translational Psychiatry Research Group, Federal University of Maranhão, São Luís, Brazil
| | | | - Candida H Lopes Alves
- Translational Psychiatry Research Group, Federal University of Maranhão, São Luís, Brazil
| | - Lays Bittencourt
- Neuropsychiatry Service, Nina Rodrigues Hospital, São Luís, Brazil
| | - Antônio E Nardi
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Viola Oertel
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Frankfurt Goethe University, Germany
| | - André B Veras
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Gilberto Sousa Alves
- Translational Psychiatry Research Group, Federal University of Maranhão, São Luís, Brazil; Neuropsychiatry Service, Nina Rodrigues Hospital, São Luís, Brazil; Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
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3
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Jiang X, Zai CC, Sultan AA, Dimick MK, Nikolova YS, Felsky D, Young LT, MacIntosh BJ, Goldstein BI. Association of polygenic risk for bipolar disorder with resting-state network functional connectivity in youth with and without bipolar disorder. Eur Neuropsychopharmacol 2023; 77:38-52. [PMID: 37717349 DOI: 10.1016/j.euroneuro.2023.08.503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/24/2023] [Accepted: 08/29/2023] [Indexed: 09/19/2023]
Abstract
Little is known regarding the polygenic underpinnings of anomalous resting-state functional connectivity (rsFC) in youth bipolar disorder (BD). The current study examined the association of polygenic risk for BD (BD-PRS) with whole-brain rsFC at the large-scale network level in youth with and without BD. 99 youth of European ancestry (56 BD, 43 healthy controls [HC]), ages 13-20 years, completed resting-state fMRI scans. BD-PRS was calculated using summary statistics from the latest adult BD genome-wide association study. Data-driven independent component analyses of the resting-state fMRI data were implemented to examine the association of BD-PRS with rsFC in the overall sample, and separately in BD and HC. In the overall sample, higher BD-PRS was associated with lower rsFC of the salience network and higher rsFC of the frontoparietal network with frontal and parietal regions. Within the BD group, higher BD-PRS was associated with higher rsFC of the default mode network with orbitofrontal cortex, and altered rsFC of the visual network with frontal and occipital regions. Within the HC group, higher BD-PRS was associated with altered rsFC of the frontoparietal network with frontal, temporal and occipital regions. In conclusion, the current study found that BD-PRS generated based on adult genetic data was associated with altered rsFC patterns of brain networks in youth. Our findings support the usefulness of BD-PRS to investigate genetically influenced neuroimaging markers of vulnerability to BD, which can be observed in youth with BD early in their course of illness as well as in healthy youth.
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Affiliation(s)
- Xinyue Jiang
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Clement C Zai
- Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Alysha A Sultan
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Mikaela K Dimick
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Yuliya S Nikolova
- Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Daniel Felsky
- Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Totonto, ON, Canada
| | - L Trevor Young
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Bradley J MacIntosh
- Sandra E Black Centre for Brain Resilience and Recovery, Sunnybrook Research Institute, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Benjamin I Goldstein
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
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Luna LP, Sousa MB, Passinho JS, Nardi AE, Oertel V, Veras AB, Alves GS. Resting-state fMRI functional connectivity and clinical correlates in Afro-descendants with schizophrenia and bipolar disorder. Psychiatry Res Neuroimaging 2023; 331:111628. [PMID: 36924740 DOI: 10.1016/j.pscychresns.2023.111628] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 02/12/2023] [Accepted: 03/07/2023] [Indexed: 03/18/2023]
Abstract
Schizophrenia (SCZ) and bipolar disorder (BD) exhibited altered activation in several brain areas, including the prefrontal and temporal cortex; however, a less explored topic is how brain connectivity and functional disturbances occur in non-Caucasian samples of SCZ and BD. Individuals with SCZ (n=20), BD (n=21), and healthy controls (HC, n=21) from indigenous and African ethnicity were submitted to clinical screening and functional assessments. Mood, compulsive and psychotic symptoms were also correlated to network dysfunction in each group. Two distinct networks' subcomponents demonstrated significant lower global efficiency (GE) in SCZ versus HC, corresponding to left posterior dorsal attention and medial left ventral attention (VA) networks. Lower GE was found in BD versus controls in four subcomponents, including the left medial and right VA. Higher compulsion scores correlated in BD with lower GE in the left VA, whereas increased report of alcohol abuse was associated with higher GE in left default mode network. Although preliminary, differences in the activation of specific networks, notably the left hemisphere, in SCZ versus controls, and lower activation in VA areas, in BD versus controls. Results highlight default mode and salient network as relevant for the emotional processing of SCZ and BD of indigenous and black ethnicity. Abstract: schizophrenia, bipolar disorder, functional neuroimaging, ethnicity, default network.
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Affiliation(s)
- Licia P Luna
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, MD, USA
| | | | - Jhule S Passinho
- Neuropsychology Laboratory, CEUMA University, São Luís, Maranhão, Brazil
| | - Antônio E Nardi
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Viola Oertel
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Frankfurt Goethe University, Germany
| | - André Barciela Veras
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; Translational Research Group on Mental Health (GPTranSMe), Dom Bosco Catholic University, Campo Grande, Mato Grosso do Sul, Brazil
| | - Gilberto Sousa Alves
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; Translational Psychiatry Research Group, Federal University of Maranhão, São Luís, Maranhão, Brazil.
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Duan J, Gong X, Womer FY, Sun K, Tang L, Liu J, Zheng J, Zhu Y, Tang Y, Zhang X, Wang F. Neurodevelopmental trajectories, polygenic risk, and lipometabolism in vulnerability and resilience to schizophrenia. BMC Psychiatry 2023; 23:153. [PMID: 36894907 PMCID: PMC9999573 DOI: 10.1186/s12888-023-04597-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 02/07/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND Schizophrenia (SZ) arises from a complex interplay involving genetic and molecular factors. Early intervention of SZ hinges upon understanding its vulnerability and resiliency factors in study of SZ and genetic high risk for SZ (GHR). METHODS Herein, using integrative and multimodal strategies, we first performed a longitudinal study of neural function as measured by amplitude of low frequency function (ALFF) in 21 SZ, 26 GHR, and 39 healthy controls to characterize neurodevelopmental trajectories of SZ and GHR. Then, we examined the relationship between polygenic risk score for SZ (SZ-PRS), lipid metabolism, and ALFF in 78 SZ, and 75 GHR in cross-sectional design to understand its genetic and molecular substrates. RESULTS Across time, SZ and GHR diverge in ALFF alterations of the left medial orbital frontal cortex (MOF). At baseline, both SZ and GHR had increased left MOF ALFF compared to HC (P < 0.05). At follow-up, increased ALFF persisted in SZ, yet normalized in GHR. Further, membrane genes and lipid species for cell membranes predicted left MOF ALFF in SZ; whereas in GHR, fatty acids best predicted and were negatively correlated (r = -0.302, P < 0.05) with left MOF. CONCLUSIONS Our findings implicate divergence in ALFF alteration in left MOF between SZ and GHR with disease progression, reflecting vulnerability and resiliency to SZ. They also indicate different influences of membrane genes and lipid metabolism on left MOF ALFF in SZ and GHR, which have important implications for understanding mechanisms underlying vulnerability and resiliency in SZ and contribute to translational efforts for early intervention.
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Affiliation(s)
- Jia Duan
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Xiaohong Gong
- State Key Laboratory of Genetic Engineering and Human Phenome Institute, School of Life Sciences, Fudan University, Shanghai, China
| | - Fay Y Womer
- Dept of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kaijin Sun
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China
| | - Lili Tang
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Juan Liu
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Junjie Zheng
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China
| | - Yue Zhu
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Yanqing Tang
- Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China.
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China.
| | - Fei Wang
- Department of Psychiatry. Early Intervention Unit, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, PR China. .,Department of Psychiatry and Gerontology, The First Affiliated Hospital, China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China.
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6
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Liu S, Smit DJA, Abdellaoui A, van Wingen GA, Verweij KJH. Brain Structure and Function Show Distinct Relations With Genetic Predispositions to Mental Health and Cognition. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:300-310. [PMID: 35961582 DOI: 10.1016/j.bpsc.2022.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 07/09/2022] [Accepted: 08/01/2022] [Indexed: 10/15/2022]
Abstract
BACKGROUND Mental health and cognitive achievement are partly heritable, highly polygenic, and associated with brain variations in structure and function. However, the underlying neural mechanisms remain unclear. METHODS We investigated the association between genetic predispositions to various mental health and cognitive traits and a large set of structural and functional brain measures from the UK Biobank (N = 36,799). We also applied linkage disequilibrium score regression to estimate the genetic correlations between various traits and brain measures based on genome-wide data. To decompose the complex association patterns, we performed a multivariate partial least squares model of the genetic and imaging modalities. RESULTS The univariate analyses showed that certain traits were related to brain structure (significant genetic correlations with total cortical surface area from rg = -0.101 for smoking initiation to rg = 0.230 for cognitive ability), while other traits were related to brain function (significant genetic correlations with functional connectivity from rg = -0.161 for educational attainment to rg = 0.318 for schizophrenia). The multivariate analysis showed that genetic predispositions to attention-deficit/hyperactivity disorder, smoking initiation, and cognitive traits had stronger associations with brain structure than with brain function, whereas genetic predispositions to most other psychiatric disorders had stronger associations with brain function than with brain structure. CONCLUSIONS These results reveal that genetic predispositions to mental health and cognitive traits have distinct brain profiles.
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Affiliation(s)
- Shu Liu
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| | - Dirk J A Smit
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Abdel Abdellaoui
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Guido A van Wingen
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| | - Karin J H Verweij
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
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7
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Cattarinussi G, Delvecchio G, Sambataro F, Brambilla P. The effect of polygenic risk scores for major depressive disorder, bipolar disorder and schizophrenia on morphological brain measures: A systematic review of the evidence. J Affect Disord 2022; 310:213-222. [PMID: 35533776 DOI: 10.1016/j.jad.2022.05.007] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 04/27/2022] [Accepted: 05/04/2022] [Indexed: 01/26/2023]
Abstract
BACKGROUND Major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SCZ) share clinical features and genetic bases. Magnetic Resonance Imaging (MRI) studies assessing the effect of polygenic risk score (PRS) for psychiatric disorders on brain structure show heterogeneous results. Therefore, we provided an overview of the existing evidence on the association between PRS for MDD, BD and SCZ and MRI abnormalities in clinical and healthy populations. METHODS A search on PubMed, Web of Science and Scopus was performed to identify the studies exploring the effect of PRS for MDD, BD and SCZ on MRI measures. A total of 25 studies were included (N = 13 on healthy individuals and N = 12 on clinical populations). RESULTS Both in affected and unaffected individuals, PRS for BD and SCZ showed either positive or negative correlations with cortical thickness (CT), mostly involving fronto-temporal areas, whereas PRS for MDD was associated with cortical alterations in prefrontal regions in healthy subjects. LIMITATIONS The heterogeneity in the methods limits the conclusions of this review. CONCLUSIONS Overall the evidence on the effect of PRS for MDD, BD and SCZ on brain is considerably heterogeneous and far to be conclusive. However, from the results emerged that PRS for MDD, BD and SCZ were associated with widespread cortical abnormalities in all the populations explored, suggesting that genetic risk for MDD, BD and SCZ might affect neurodevelopmental processes, resulting in cortical alterations that transcend diagnostic boundaries and seem to be independent from the clinical status.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
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8
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Sadeghi D, Shoeibi A, Ghassemi N, Moridian P, Khadem A, Alizadehsani R, Teshnehlab M, Gorriz JM, Khozeimeh F, Zhang YD, Nahavandi S, Acharya UR. An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future works. Comput Biol Med 2022; 146:105554. [DOI: 10.1016/j.compbiomed.2022.105554] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 04/11/2022] [Accepted: 04/11/2022] [Indexed: 12/21/2022]
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9
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Ulugut H, Trieu C, Groot C, van 't Hooft JJ, Tijms BM, Scheltens P, Ossenkoppele R, Barkhof F, van den Heuvel OA, Pijnenburg YAL. Overlap of Neuroanatomical Involvement in Frontotemporal Dementia and Primary Psychiatric Disorders: A Meta-analysis. Biol Psychiatry 2022; 93:820-828. [PMID: 35965106 DOI: 10.1016/j.biopsych.2022.05.028] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/05/2022] [Accepted: 05/31/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Despite significant symptomatic overlap between behavioral variant frontotemporal dementia (bvFTD) and primary psychiatric disorders (PPDs), a potential overlap in their structural anatomical changes has not been studied systematically. METHODS In this magnetic resonance imaging-based meta-analysis, we included studies on bvFTD, schizophrenia, bipolar disorder, and autism spectrum disorder that 1) used voxel-based morphometry analysis to assess regional gray matter volumes (GMVs) and 2) reported the coordinates of the regional GMV. Separate analyses were performed comparing clusters of coordinate-based changes in the GMVs (n = 24,183) between patients and control subjects, and overlapping brain regions between bvFTD and each PPD were examined. RESULTS We found that GMV alterations in the prefrontal and anterior cingulate cortices, temporal lobe, amygdala, and insula comprise the transdiagnostic brain alterations in bvFTD and PPD. CONCLUSIONS Our meta-analysis revealed significant anatomical overlap that paves the way for future investigations of shared pathophysiological pathways, and our cross-disorder approach would provide new insights to better understand the relationship between bvFTD and PPD.
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Affiliation(s)
- Hulya Ulugut
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Calvin Trieu
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Colin Groot
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jochum J van 't Hooft
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Betty M Tijms
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip Scheltens
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Clinical Memory Research Unit, Lunds Universitet, Lund, Sweden
| | - Frederik Barkhof
- Radiology and Nuclear Medicine, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; University College London, Institutes of Neurology and Healthcare Engineering, London, United Kingdom
| | - Odile A van den Heuvel
- Department of Psychiatry, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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10
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Koch E, Nyberg L, Lundquist A, Kauppi K. Polygenic Risk for Schizophrenia Has Sex-Specific Effects on Brain Activity during Memory Processing in Healthy Individuals. Genes (Basel) 2022; 13:genes13030412. [PMID: 35327966 PMCID: PMC8950000 DOI: 10.3390/genes13030412] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 02/10/2022] [Accepted: 02/23/2022] [Indexed: 12/28/2022] Open
Abstract
Genetic risk for schizophrenia has a negative impact on memory and other cognitive abilities in unaffected individuals, and it was recently shown that this effect is specific to males. Using functional MRI, we investigated the effect of a polygenic risk score (PRS) for schizophrenia on brain activation during working memory and episodic memory in 351 unaffected participants (167 males and 184 females, 25–95 years), and specifically tested if any effect of PRS on brain activation is sex-specific. Schizophrenia PRS was significantly associated with decreased brain activation in the left dorsolateral prefrontal cortex (DLPFC) during working-memory manipulation and in the bilateral superior parietal lobule (SPL) during episodic-memory encoding and retrieval. A significant interaction effect between sex and PRS was seen in the bilateral SPL during episodic-memory encoding and retrieval, and sex-stratified analyses showed that the effect of PRS on SPL activation was male-specific. These results confirm previous findings of DLPFC inefficiency in schizophrenia, and highlight the SPL as another important genetic intermediate phenotype of the disease. The observed sex differences suggest that the previously shown male-specific effect of schizophrenia PRS on cognition translates into an additional corresponding effect on brain functioning.
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Affiliation(s)
- Elise Koch
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden; (L.N.); (K.K.)
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden;
- Correspondence: ; Tel.: +46-90-786-50-00
| | - Lars Nyberg
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden; (L.N.); (K.K.)
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden;
- Department of Radiation Sciences, Diagnostic Radiology, University Hospital, Umeå University, 901 87 Umeå, Sweden
| | - Anders Lundquist
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden;
- Department of Statistics, School of Business, Economics and Statistics, Umeå University, 901 87 Umeå, Sweden
| | - Karolina Kauppi
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden; (L.N.); (K.K.)
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden;
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Nobels väg 12A, 171 65 Solna, Sweden
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11
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Saarinen A, Lyytikäinen LP, Hietala J, Dobewall H, Lavonius V, Raitakari O, Kähönen M, Sormunen E, Lehtimäki T, Keltikangas-Järvinen L. Magical thinking in individuals with high polygenic risk for schizophrenia but no non-affective psychoses-a general population study. Mol Psychiatry 2022; 27:3286-3293. [PMID: 35505089 PMCID: PMC9708578 DOI: 10.1038/s41380-022-01581-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/07/2022] [Accepted: 04/12/2022] [Indexed: 11/09/2022]
Abstract
A strong genetic background for psychoses is well-established. Most individuals with a high genetic risk for schizophrenia, however, do not develop the disorder. We investigated whether individuals, who have a high genetic risk for schizophrenia but no non-affective psychotic disorders, are predisposed to develop milder forms of deviant thinking in terms of magical thinking. Participants came from the population-based Young Finns Study (n = 1292). The polygenic risk score for schizophrenia (PRS) was calculated on the basis of the most recent genome-wide association study (GWAS). Psychiatric diagnoses over the lifespan were collected up to 2017 from the registry of hospital care. Magical thinking was evaluated with the Spiritual Acceptance Scale (e.g., beliefs in telepathy, miracles, mystical events, or sixth sense) of the Temperament and Character Inventory in 1997, 2001, and 2012 (participants were 20-50-year-olds). We found that, among those who did not develop non-affective psychotic disorders, high PRS predicted higher magical thinking in adulthood (p = 0.001). Further, PRS predicted different developmental courses: a low PRS predicted a steady decrease in magical thinking from age 20 to 50 years, while in individuals with high PRS the decrease in magical thinking ceased in middle age so that their level of magical thinking remained higher than expected for that age. These findings remained when controlling for sex, childhood family environment, and adulthood socioeconomic factors. In conclusion, if high PRS does not lead to a non-affective psychotic disorder, it predicts milder forms of deviant thinking such as elevated magical thinking in adulthood, especially in middle age. The finding enhances our understanding of different outcomes of high genetic psychosis risk.
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Affiliation(s)
- Aino Saarinen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland.
| | - Leo-Pekka Lyytikäinen
- grid.511163.10000 0004 0518 4910Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Finland ,grid.412330.70000 0004 0628 2985Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, Finland ,grid.502801.e0000 0001 2314 6254Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jarmo Hietala
- grid.1374.10000 0001 2097 1371Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland
| | - Henrik Dobewall
- grid.14758.3f0000 0001 1013 0499National Institute of Health and Welfare, Helsinki, Finland
| | - Veikka Lavonius
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Olli Raitakari
- grid.1374.10000 0001 2097 1371Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland ,grid.1374.10000 0001 2097 1371Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland ,grid.410552.70000 0004 0628 215XDepartment of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Mika Kähönen
- grid.502801.e0000 0001 2314 6254Department of Clinical Physiology, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Elina Sormunen
- grid.1374.10000 0001 2097 1371Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- grid.511163.10000 0004 0518 4910Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Finland ,grid.502801.e0000 0001 2314 6254Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Liisa Keltikangas-Järvinen
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
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12
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Johnson D, Wilke MA, Lyle SM, Kowalec K, Jorgensen A, Wright GE, Drögemöller BI. A systematic review and analysis of the use of polygenic scores in pharmacogenomics. Clin Pharmacol Ther 2021; 111:919-930. [PMID: 34953075 DOI: 10.1002/cpt.2520] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 12/18/2021] [Indexed: 11/09/2022]
Abstract
Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.
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Affiliation(s)
- Danielle Johnson
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - MacKenzie Ap Wilke
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Sarah M Lyle
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Kaarina Kowalec
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Andrea Jorgensen
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Galen Eb Wright
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre and Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada
| | - Britt I Drögemöller
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,CancerCare Manitoba Research Institute, Winnipeg, MB, Canada.,Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
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13
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Takeuchi H, Kimura R, Tomita H, Taki Y, Kikuchi Y, Ono C, Yu Z, Matsudaira I, Nouchi R, Yokoyama R, Kotozaki Y, Nakagawa S, Hanawa S, Iizuka K, Sekiguchi A, Araki T, Miyauchi CM, Ikeda S, Sakaki K, Dos S Kawata KH, Nozawa T, Yokota S, Magistro D, Imanishi T, Kawashima R. Polygenic risk score for bipolar disorder associates with divergent thinking and brain structures in the prefrontal cortex. Hum Brain Mapp 2021; 42:6028-6037. [PMID: 34587347 PMCID: PMC8596941 DOI: 10.1002/hbm.25667] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 08/26/2021] [Accepted: 09/13/2021] [Indexed: 11/11/2022] Open
Abstract
It has been hypothesized that a higher genetic risk of bipolar disorder (BD) is associated with greater creativity. Given the clinical importance of bipolar disorder and the importance of creativity to human society and cultural development, it is essential to reveal their associations and the neural basis of the genetic risk of bipolar disorder to gain insight into its etiology. However, despite the previous demonstration of the associations of polygenic risk score (PRS) of BD and creative jobs, the associations of BD‐PRS and creativity measured by the divergent thinking (CMDT) and regional gray matter volume (rGMV) as well as regional white matter volume (rWMV) have not been investigated. Using psychological analyses and whole‐brain voxel‐by‐voxel analyses, we examined these potential associations in 1558 young, typically developing adult students. After adjusting for confounding variables and multiple comparisons, a greater BD‐PRS was associated with a greater total CMDT fluency score, and a significant relationship was found in fluency subscores. A greater BD‐PRS was also associated with lower total mood disturbance. Neuroimaging analyses revealed that the BD‐PRS was associated with greater rGMV in the right inferior frontal gyrus, which is a consistently affected area in BD, as well as a greater rWMV in the left middle frontal gyrus, which has been suggested to play a central role in the increased creativity associated with the risk of BD with creativity. These findings suggest a relationship between the genetic risk of BD and CMDT and prefrontal cortical structures among young educated individuals.
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Affiliation(s)
- Hikaru Takeuchi
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Hiroaki Tomita
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan.,Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Yasuyuki Taki
- Division of Medical Neuroimaging Analysis, Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Radiology and Nuclear Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yoshie Kikuchi
- Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Chiaki Ono
- Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Zhiqian Yu
- Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | | | - Rui Nouchi
- Department of Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.,Creative Interdisciplinary Research Division, Frontier Research Institute for Interdisciplinary Science, Tohoku University, Sendai, Japan.,Human and Social Response Research Division, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | | | - Yuka Kotozaki
- Division of Clinical research, Medical-Industry Translational Research Center, Fukushima Medical University School of Medicine, Fukushima, Japan
| | - Seishu Nakagawa
- Department of Human Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.,Division of Psychiatry, Tohoku Medical and Pharmaceutical University, Sendai, Japan
| | - Sugiko Hanawa
- Department of Human Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Kunio Iizuka
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Atsushi Sekiguchi
- Division of Medical Neuroimaging Analysis, Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Behavioral Medicine, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | | | - Carlos Makoto Miyauchi
- Department of Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Shigeyuki Ikeda
- Department of Ubiquitous Sensing, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Kohei Sakaki
- Department of Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | | | - Takayuki Nozawa
- Research Center Institute for the Earth Inclusive Sensing Empathizing with Silent Voices, Tokyo Institute of Technology, Tokyo, Japan
| | - Susumu Yokota
- Faculty of Arts and Science, Kyushu University, Fukuoka, Japan
| | - Daniele Magistro
- Department of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham, UK
| | - Tadashi Imanishi
- Biomedical Informatics Laboratory, Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
| | - Ryuta Kawashima
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.,Department of Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.,Department of Ubiquitous Sensing, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
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14
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Dimitriadis SI, Lancaster TM, Perry G, Tansey KE, Jones DK, Singh KD, Zammit S, Smith GD, Hall J, O'Donovan MC, Owen MJ, Linden DE. Global Brain Flexibility During Working Memory Is Reduced in a High-Genetic-Risk Group for Schizophrenia. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2021; 6:1176-1184. [PMID: 33524599 PMCID: PMC7613444 DOI: 10.1016/j.bpsc.2021.01.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 01/07/2021] [Accepted: 01/09/2021] [Indexed: 10/22/2022]
Abstract
BACKGROUND Altered functional brain connectivity has been proposed as an intermediate phenotype between genetic risk loci and clinical expression of schizophrenia. Genetic high-risk groups of healthy subjects are particularly suited for the investigation of this proposition because they can be tested in the absence of medication or other secondary effects of schizophrenia. METHODS Here, we applied dynamic functional connectivity analysis to functional magnetic resonance imaging data to reveal the reconfiguration of brain networks during a cognitive task. We recruited healthy carriers of common risk variants using the recall-by-genotype design. We assessed 197 individuals: 99 individuals (52 female, 47 male) with low polygenic risk scores (schizophrenia risk profile scores [SCZ-PRSs]) and 98 individuals (52 female, 46 male) with high SCZ-PRSs from both tails of the SCZ-PRS distribution from a genotyped population cohort, the Avon Longitudinal Study of Parents and Children (N = 8169). We compared groups both on conventional brain activation profiles, using the general linear model of the experiment, and on the neural flexibility index, which quantifies how frequent a brain region's community affiliation changes over experimental time. RESULTS Behavioral performance and standard brain activation profiles did not differ significantly between groups. High SCZ-PRS was associated with reduced flexibility index and network modularity across n-back levels. The whole-brain flexibility index and that of the frontoparietal working memory network was associated with n-back performance. We identified a dynamic network phenotype related to high SCZ-PRS. CONCLUSIONS Such neurophysiological markers can become important for the elucidation of biological mechanisms of schizophrenia and, particularly, the associated cognitive deficit.
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Affiliation(s)
- Stavros I Dimitriadis
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom; Neuroinformatics Group, School of Psychology, Cardiff University, Cardiff, United Kingdom.
| | - Thomas M Lancaster
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom; School of Psychology, Bath University, Bath, United Kingdom
| | - Gavin Perry
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Katherine E Tansey
- MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Krish D Singh
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Stanley Zammit
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jeremy Hall
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michael C O'Donovan
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michael J Owen
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - David E Linden
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom; School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
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15
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Sex-specific effects of polygenic risk for schizophrenia on lifespan cognitive functioning in healthy individuals. Transl Psychiatry 2021; 11:520. [PMID: 34635642 PMCID: PMC8505489 DOI: 10.1038/s41398-021-01649-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/16/2021] [Accepted: 09/27/2021] [Indexed: 12/13/2022] Open
Abstract
Polygenic risk for schizophrenia has been associated with lower cognitive ability and age-related cognitive change in healthy individuals. Despite well-established neuropsychological sex differences in schizophrenia patients, genetic studies on sex differences in schizophrenia in relation to cognitive phenotypes are scarce. Here, we investigated whether the effect of a polygenic risk score (PRS) for schizophrenia on childhood, midlife, and late-life cognitive function in healthy individuals is modified by sex, and if PRS is linked to accelerated cognitive decline. Using a longitudinal data set from healthy individuals aged 25-100 years (N = 1459) spanning a 25-year period, we found that PRS was associated with lower cognitive ability (episodic memory, semantic memory, visuospatial ability), but not with accelerated cognitive decline. A significant interaction effect between sex and PRS was seen on cognitive task performance, and sex-stratified analyses showed that the effect of PRS was male-specific. In a sub-sample, we observed a male-specific effect of the PRS on school performance at age 12 (N = 496). Our findings of sex-specific effects of schizophrenia genetics on cognitive functioning across the lifespan indicate that the effects of underlying disease genetics on cognitive functioning is dependent on biological processes that differ between the sexes.
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16
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Abé C, Petrovic P, Ossler W, Thompson WH, Liberg B, Song J, Bergen SE, Sellgren CM, Fransson P, Ingvar M, Landén M. Genetic risk for bipolar disorder and schizophrenia predicts structure and function of the ventromedial prefrontal cortex. J Psychiatry Neurosci 2021; 46:E441-E450. [PMID: 34291628 PMCID: PMC8519489 DOI: 10.1503/jpn.200165] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Bipolar disorder is highly heritable and polygenic. The polygenic risk for bipolar disorder overlaps with that of schizophrenia, and polygenic scores are normally distributed in the population. Bipolar disorder has been associated with structural brain abnormalities, but it is unknown how these are linked to genetic risk factors for psychotic disorders. METHODS We tested whether polygenic risk scores for bipolar disorder and schizophrenia predict structural brain alterations in 98 patients with bipolar disorder and 81 healthy controls. We derived brain cortical thickness, surface area and volume from structural MRI scans. In post-hoc analyses, we correlated polygenic risk with functional hub strength, derived from resting-state functional MRI and brain connectomics. RESULTS Higher polygenic risk scores for both bipolar disorder and schizophrenia were associated with a thinner ventromedial prefrontal cortex (vmPFC). We found these associations in the combined group, and separately in patients and drug-naive controls. Polygenic risk for bipolar disorder was correlated with the functional hub strength of the vmPFC within the default mode network. LIMITATIONS Polygenic risk is a cumulative measure of genomic burden. Detailed genetic mechanisms underlying brain alterations and their cognitive consequences still need to be determined. CONCLUSION Our multimodal neuroimaging study linked genomic burden and brain endophenotype by demonstrating an association between polygenic risk scores for bipolar disorder and schizophrenia and the structure and function of the vmPFC. Our findings suggest that genetic factors might confer risk for psychotic disorders by influencing the integrity of the vmPFC, a brain region involved in self-referential processes and emotional regulation. Our study may also provide an imaging-genetics vulnerability marker that can be used to help identify individuals at risk for developing bipolar disorder.
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Affiliation(s)
- Christoph Abé
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - Predrag Petrovic
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - William Ossler
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - William H Thompson
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - Benny Liberg
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - Jie Song
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - Sarah E Bergen
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - Carl M Sellgren
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - Peter Fransson
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - Martin Ingvar
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
| | - Mikael Landén
- From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén)
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Yaple ZA, Tolomeo S, Yu R. Mapping working memory-specific dysfunction using a transdiagnostic approach. NEUROIMAGE-CLINICAL 2021; 31:102747. [PMID: 34256292 PMCID: PMC8278205 DOI: 10.1016/j.nicl.2021.102747] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 06/26/2021] [Indexed: 01/17/2023]
Abstract
Background Working memory (WM) is an executive ability that allows one to hold and manipulate information for a short period of time. Schizophrenia and mood disorders are severe psychiatric conditions with overlapping genetic and clinical symptoms. Whilst WM has been suggested as meeting the criteria for being an endophenotype for schizophrenia and mood disorders, it still unclear whether they share overlapping neural circuitry. Objective The n-back task has been widely used to measure WM capacity, such as maintenance, flexible updating, and interference control. Here we compiled studies that included psychiatric populations, i.e., schizophrenia, bipolar disorder and major depressive disorder. Methods We performed a coordinate-based meta-analysis that combined 34 BOLD-fMRI studies comparing activity associated with n-back working memory between psychiatric patients and healthy controls. We specifically focused our search using the n-back task to diminish study heterogeneity. Results All patient groups showed blunted activity in the striatum, anterior insula and frontal lobe. The same brain networks related to WM were compromised in schizophrenia, major depressive disorder and bipolar disorder. Conclusion Our findings support the suggestion of commonal functional abnormalities across schizophrenia and mood disorders related to WM.
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Affiliation(s)
| | - Serenella Tolomeo
- Department of Psychology, National University of Singapore, Singapore
| | - Rongjun Yu
- Department of Management, Hong Kong Baptist University, Hong Kong, China; Department of Sport, Physical Education and Health, Hong Kong Baptist University, Hong Kong, China; Department of Physics, Hong Kong Baptist University, Hong Kong, China.
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18
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Functional connectome-wide associations of schizophrenia polygenic risk. Mol Psychiatry 2021; 26:2553-2561. [PMID: 32127647 PMCID: PMC9557214 DOI: 10.1038/s41380-020-0699-3] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Revised: 02/15/2020] [Accepted: 02/20/2020] [Indexed: 01/29/2023]
Abstract
Schizophrenia is a highly heritable mental disorder characterized by functional dysconnectivity across the brain. However, the relationships between polygenic risk factors and connectome-wide neural mechanisms are unclear. Here, combining genetic and multiparadigm fMRI data of 623 healthy Caucasian adults drawn from the Human Connectome Project, we found that higher schizophrenia polygenic risk scores were significantly correlated with lower functional connectivity in a large-scale brain network primarily encompassing the visual system, default-mode system, and frontoparietal system. Such correlation was robustly observed across multiple fMRI paradigms, suggesting a brain-state-independent neural phenotype underlying individual genetic liability to schizophrenia. Moreover, using an independent clinical dataset acquired from the Consortium for Neuropsychiatric Phenomics, we further demonstrated that the connectivity of the identified network was reduced in patients with schizophrenia and significantly correlated with general cognitive ability. These findings provide the first evidence for connectome-wide associations of schizophrenia polygenic risk at the systems level and suggest that disrupted integration of sensori-cognitive information may be a hallmark of genetic effects on the brain that contributes to the pathogenesis of schizophrenia.
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19
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Radonjić NV, Hess JL, Rovira P, Andreassen O, Buitelaar JK, Ching CRK, Franke B, Hoogman M, Jahanshad N, McDonald C, Schmaal L, Sisodiya SM, Stein DJ, van den Heuvel OA, van Erp TGM, van Rooij D, Veltman DJ, Thompson P, Faraone SV. Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders. Mol Psychiatry 2021; 26:2101-2110. [PMID: 33456050 PMCID: PMC8440178 DOI: 10.1038/s41380-020-01002-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 12/07/2020] [Accepted: 12/11/2020] [Indexed: 02/06/2023]
Abstract
Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.
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Affiliation(s)
- Nevena V Radonjić
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Jonathan L Hess
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Paula Rovira
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Ole Andreassen
- NORMENT-Institute of Clinical Medicine, Division of Mental Health and Addiction, Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Jan K Buitelaar
- Radboudumc, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christopher R K Ching
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina Del Rey, CA, USA
| | - Barbara Franke
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Martine Hoogman
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Neda Jahanshad
- Imaging Genetics Center, Department of Neurology and Biomedical Engineering, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina Del Rey, CA, USA
| | - Carrie McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics (CMIG), University of California, San Diego, CA, USA
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, The National Centre of Excellence for Youth Mental Health, Parkville, VIC, Australia
| | - Sanjay M Sisodiya
- UCL Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, University College London, London, UK
- Chalfont Centre for Epilepsy, Epilepsy Society, Bucks, UK
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Odile A van den Heuvel
- Department of Psychiatry and Department of Anatomy & Neurosciences, Amsterdam UMC/VUmc, Amsterdam, The Netherlands
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA, USA
| | - Daan van Rooij
- Donders Centre for Cognitive Neuroimaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry and Department of Anatomy & Neurosciences, Amsterdam UMC/VUmc, Amsterdam, The Netherlands
| | - Paul Thompson
- Neuro Imaging Institute for Neuroimaging and Informatics, Keck School of Medicine of the University of Southern California, Marina Del Rey, CA, USA
| | - Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA.
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20
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Lawrence KE, Hernandez LM, Fuster E, Padgaonkar NT, Patterson G, Jung J, Okada NJ, Lowe JK, Hoekstra JN, Jack A, Aylward E, Gaab N, Van Horn JD, Bernier RA, McPartland JC, Webb SJ, Pelphrey KA, Green SA, Bookheimer SY, Geschwind DH, Dapretto M. Impact of autism genetic risk on brain connectivity: a mechanism for the female protective effect. Brain 2021; 145:378-387. [PMID: 34050743 PMCID: PMC8967090 DOI: 10.1093/brain/awab204] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 04/23/2021] [Accepted: 05/11/2021] [Indexed: 01/27/2023] Open
Abstract
The biological mechanisms underlying the greater prevalence of autism spectrum disorder in males than females remain poorly understood. One hypothesis posits that this female protective effect arises from genetic load for autism spectrum disorder differentially impacting male and female brains. To test this hypothesis, we investigated the impact of cumulative genetic risk for autism spectrum disorder on functional brain connectivity in a balanced sample of boys and girls with autism spectrum disorder and typically developing boys and girls (127 youth, ages 8-17). Brain connectivity analyses focused on the salience network, a core intrinsic functional connectivity network which has previously been implicated in autism spectrum disorder. The effects of polygenic risk on salience network functional connectivity were significantly modulated by participant sex, with genetic load for autism spectrum disorder influencing functional connectivity in boys with and without autism spectrum disorder but not girls. These findings support the hypothesis that autism spectrum disorder risk genes interact with sex differential processes, thereby contributing to the male bias in autism prevalence and proposing an underlying neurobiological mechanism for the female protective effect.
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Affiliation(s)
- Katherine E Lawrence
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA,Correspondence to: Mirella Dapretto Ahmanson-Lovelace Brain Mapping Center 660 Charles E. Young Drive South Los Angeles, CA 90095, USA E-mail:
| | - Leanna M Hernandez
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Emily Fuster
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Namita T Padgaonkar
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Genevieve Patterson
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Jiwon Jung
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Nana J Okada
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Jennifer K Lowe
- Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Jackson N Hoekstra
- Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Allison Jack
- Department of Psychology, George Mason University, Fairfax, VA 22030, USA
| | - Elizabeth Aylward
- Center for Integrative Brain Research, Seattle Children’s Research Institute, Seattle, WA 98101, USA
| | - Nadine Gaab
- Harvard Graduate School of Education, Cambridge, MA 02138, USA
| | - John D Van Horn
- Department of Psychology and School of Data Science, University of Virginia, Charlottesville, VA 22904, USA
| | - Raphael A Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA
| | | | - Sara J Webb
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA,Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA 98101, USA
| | - Kevin A Pelphrey
- Department of Neurology, University of Virginia, Charlottesville, VA 22904, USA
| | - Shulamite A Green
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Daniel H Geschwind
- Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA,Center for Neurobehavioral Genetics, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
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21
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Sato J, Hirano Y, Hirakawa N, Takahashi J, Oribe N, Kuga H, Nakamura I, Hirano S, Ueno T, Togao O, Hiwatashi A, Nakao T, Onitsuka T. Lower Hippocampal Volume in Patients with Schizophrenia and Bipolar Disorder: A Quantitative MRI Study. J Pers Med 2021; 11:jpm11020121. [PMID: 33668432 PMCID: PMC7918861 DOI: 10.3390/jpm11020121] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 02/06/2021] [Accepted: 02/09/2021] [Indexed: 01/02/2023] Open
Abstract
Since patients with schizophrenia (SZ) and bipolar disorder (BD) share many biological features, detecting biomarkers that differentiate SZ and BD patients is crucial for optimized treatments. High-resolution magnetic resonance imaging (MRI) is suitable for detecting subtle brain structural differences in patients with psychiatric disorders. In the present study, we adopted a neuroanatomically defined and manually delineated region of interest (ROI) method to evaluate the amygdalae, hippocampi, Heschl’s gyrus (HG), and planum temporale (PT), because these regions are crucial in the development of SZ and BD. ROI volumes were measured using high resolution MRI in 31 healthy subjects (HS), 23 SZ patients, and 21 BD patients. Right hippocampal volumes differed significantly among groups (HS > BD > SZ), whereas left hippocampal volumes were lower in SZ patients than in HS and BD patients (HS = BD > SZ). Volumes of the amygdalae, HG, and PT did not differ among the three groups. For clinical correlations, there were no significant associations between ROI volumes and demographics/clinical symptoms. Our study revealed significant lower hippocampal volume in patients with SZ and BD, and we suggest that the right hippocampal volume is a potential biomarker for differentiation between SZ and BD.
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Affiliation(s)
- Jinya Sato
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Yoji Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
- Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan
- Correspondence: (Y.H.); (T.O.); Tel.: +81-92-642-5627 (Y.H. & T.O.)
| | - Noriaki Hirakawa
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Junichi Takahashi
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Naoya Oribe
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
- Hizen Psychiatric Medical Center, Division of Clinical Research, National Hospital Organization, Saga 842-0192, Japan;
| | - Hironori Kuga
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
- Hizen Psychiatric Medical Center, Division of Clinical Research, National Hospital Organization, Saga 842-0192, Japan;
| | - Itta Nakamura
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Shogo Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Takefumi Ueno
- Hizen Psychiatric Medical Center, Division of Clinical Research, National Hospital Organization, Saga 842-0192, Japan;
| | - Osamu Togao
- Department of Molecular Imaging and Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan;
| | - Akio Hiwatashi
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan;
| | - Tomohiro Nakao
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
| | - Toshiaki Onitsuka
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan; (J.S.); (N.H.); (J.T.); (N.O.); (H.K.); (I.N.); (S.H.); (T.N.)
- Correspondence: (Y.H.); (T.O.); Tel.: +81-92-642-5627 (Y.H. & T.O.)
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22
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Associations between Alzheimer's disease polygenic risk scores and hippocampal subfield volumes in 17,161 UK Biobank participants. Neurobiol Aging 2020; 98:108-115. [PMID: 33259984 DOI: 10.1016/j.neurobiolaging.2020.11.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 09/20/2020] [Accepted: 11/01/2020] [Indexed: 11/23/2022]
Abstract
Hippocampal volume is an important biomarker of Alzheimer's disease (AD), and genetic risk of AD is associated with hippocampal atrophy. However, the hippocampus is not a uniform structure and has a number of subfields, the associations of which with age, sex, and polygenic risk score for AD (PRSAD) have been inadequately investigated. We examined these associations in 17,161 cognitively normal UK Biobank participants (44-80 years). Age was negatively associated with all the hippocampal subfield volumes and females had smaller volumes than men. Higher PRSAD was associated with lower volumes in the bilateral whole hippocampus, hippocampal-amygdala-transition-area, and hippocampal tail; right subiculum; left cornu ammonis 1, cornu ammonis 4, molecular layer, and granule cell layer of dentate gyrus. Older individuals (median age 63 years, n = 8984) showed greater subfield vulnerability to high PRSAD compared to the younger group (n = 8177), but the effect did not differ by sex. The pattern of subfield involvement in relation to the PRSAD in community dwelling healthy individuals sheds additional light on the pathogenesis of AD.
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23
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Passchier RV, Stein DJ, Uhlmann A, van der Merwe C, Dalvie S. Schizophrenia Polygenic Risk and Brain Structural Changes in Methamphetamine-Associated Psychosis in a South African Population. Front Genet 2020; 11:1018. [PMID: 33133134 PMCID: PMC7566162 DOI: 10.3389/fgene.2020.01018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Accepted: 08/10/2020] [Indexed: 11/13/2022] Open
Abstract
Background The genetic architecture of psychotic disorders is complex, with hundreds of genetic risk loci contributing to a polygenic model of disease. Overlap in the genetics of psychotic disorders and brain measures has been found in European populations, but has not been explored in populations of African ancestry. The aim of this study was to determine whether a relationship exists between a schizophrenia-derived PRS and (i) methamphetamine associated psychosis (MAP), and (ii) brain structural measures, in a South African population. Methods The study sample consisted of three participant groups: 31 individuals with MAP, 48 with apsychotic methamphetamine dependence, and 49 healthy controls. Using PRSice, PRS was generated for each of the participants with GWAS summary statistics from the Psychiatric Genomics Consortium Schizophrenia working group (PGC-SCZ2) as the discovery dataset. Regression analyses were performed to determine associations of PRS, with diagnosis, whole brain, and regional gray and white matter measures. Results Schizophrenia-derived PRS did not significantly predict MAP diagnosis. After correction for multiple testing, no significant associations were found between PRS and brain measures across all groups. Discussion The lack of significant associations here may indicate that the study is underpowered, that brain volumes in MAP are due to factors other than polygenic risk for schizophrenia, or that PRS derived from a largely European discovery set has limited utility in individuals of African ancestry. Larger studies, that include diverse populations, and more nuanced brain measures, may help elucidate the relationship between schizophrenia-PRS, brain structural changes, and psychosis. Conclusion This research presents the first PRS study to investigate shared genetic effects across psychotic disorders and brain structural measures in an African population. Ancestrally comparable discovery datasets may be useful for future African genetic research.
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Affiliation(s)
- Ruth V Passchier
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Anne Uhlmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, TU Dresden, Dresden, Germany
| | - Celia van der Merwe
- The Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, United States
| | - Shareefa Dalvie
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
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24
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Long Y, Liu Z, Chan CKY, Wu G, Xue Z, Pan Y, Chen X, Huang X, Li D, Pu W. Altered Temporal Variability of Local and Large-Scale Resting-State Brain Functional Connectivity Patterns in Schizophrenia and Bipolar Disorder. Front Psychiatry 2020; 11:422. [PMID: 32477194 PMCID: PMC7235354 DOI: 10.3389/fpsyt.2020.00422] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Accepted: 04/24/2020] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia and bipolar disorder share some common clinical features and are both characterized by aberrant resting-state functional connectivity (FC). However, little is known about the common and specific aberrant features of the dynamic FC patterns in these two disorders. In this study, we explored the differences in dynamic FC among schizophrenia patients (n = 66), type I bipolar disorder patients (n = 53), and healthy controls (n = 66), by comparing temporal variabilities of FC patterns involved in specific brain regions and large-scale brain networks. Compared with healthy controls, both patient groups showed significantly increased regional FC variabilities in subcortical areas including the thalamus and basal ganglia, as well as increased inter-network FC variability between the thalamus and sensorimotor areas. Specifically, more widespread changes were found in the schizophrenia group, involving increased FC variabilities in sensorimotor, visual, attention, limbic and subcortical areas at both regional and network levels, as well as decreased regional FC variabilities in the default-mode areas. The observed alterations shared by schizophrenia and bipolar disorder may help to explain their overlapped clinical features; meanwhile, the schizophrenia-specific abnormalities in a wider range may support that schizophrenia is associated with more severe functional brain deficits than bipolar disorder. Together, these findings highlight the potentials of using dynamic FC as an objective biomarker for the monitoring and diagnosis of either schizophrenia or bipolar disorder.
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Affiliation(s)
- Yicheng Long
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- Mental Health Institute of Central South University, Changsha, China
| | - Zhening Liu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- Mental Health Institute of Central South University, Changsha, China
| | | | - Guowei Wu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- Mental Health Institute of Central South University, Changsha, China
| | - Zhimin Xue
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- Mental Health Institute of Central South University, Changsha, China
| | - Yunzhi Pan
- Mental Health Institute of Central South University, Changsha, China
| | - Xudong Chen
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- Mental Health Institute of Central South University, Changsha, China
| | - Xiaojun Huang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- Mental Health Institute of Central South University, Changsha, China
| | - Dan Li
- Department of Geriatrics, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Weidan Pu
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
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25
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Levchenko A, Nurgaliev T, Kanapin A, Samsonova A, Gainetdinov RR. Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders. Heliyon 2020; 6:e03990. [PMID: 32462093 PMCID: PMC7240336 DOI: 10.1016/j.heliyon.2020.e03990] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Revised: 10/31/2019] [Accepted: 05/12/2020] [Indexed: 12/13/2022] Open
Abstract
A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.
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Affiliation(s)
- Anastasia Levchenko
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
| | - Timur Nurgaliev
- Institute of Translational Biomedicine, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
| | - Alexander Kanapin
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
| | - Anastasia Samsonova
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
| | - Raul R. Gainetdinov
- Institute of Translational Biomedicine, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
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Zhuo C, Lin X, Tian H, Liu S, Bian H, Chen C. Adjunct ketamine treatment of depression in treatment-resistant schizophrenia patients is unsatisfactory in pilot and secondary follow-up studies. Brain Behav 2020; 10:e01600. [PMID: 32174025 PMCID: PMC7218248 DOI: 10.1002/brb3.1600] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 02/07/2020] [Accepted: 02/25/2020] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE To investigate the effects of adjunct ketamine treatment on chronic treatment-resistant schizophrenia patients with treatment-resistant depressive symptoms (CTRS-TRD patients), including alterations in brain function. METHODS Intravenous ketamine (0.5 mg/kg body weight) was administered to CTRS-TRD patients over a 1-hr period on days 1, 4, 7, 10, 13, 16, 19, 22, and 25 of our initial pilot study. This treatment method was subsequently repeated 58 days after the start of the pilot study for a secondary follow-up study. Calgary Depression Scale for Schizophrenia (CDSS), Positive and Negative Syndrome Scale (PANSS), and regional homogeneity (ReHo) results were used to assess treatment effects and alterations in brain function throughout the entire duration of our studies. RESULTS Between day 7 and day 14 of the first treatment, CDSS scores were reduced by 63.8% and PANSS scores were reduced by 30.04%. In addition, ReHo values increased in the frontal, temporal, and parietal lobes. However, by day 21, depressive symptoms relapsed. During the second treatment period, CDSS and PANSS scores exhibited no significant differences compared to baseline between day 58 and day 86. On day 65, ReHo values were higher in the temporal, frontal, and parietal lobes. However, on day 79, the increase in ReHo values completely disappeared. CONCLUSIONS Depressive symptoms in CTRS-TRD patients were alleviated with adjunct ketamine treatment for only 1 week during the first treatment period. Moreover, after 1 month, the antidepressant effects of ketamine on CTRS-TRD patients completely disappeared. Correspondingly, ReHo alterations induced by ketamine in the CTRS-TRD patients were not maintained for more than 3 weeks. These pilot findings indicate that adjunct ketamine treatment is not satisfactory for CTRS-TRD patients.
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Affiliation(s)
- Chuanjun Zhuo
- Department of Psychiatry, School of Mental Health, Jining Medical University, Jining, China.,Department of Psychiatric-Neuroimaging-Genetics Laboratory (PNG_Lab), Wenzhou Seventh People's Hospital, Wenzhou, China.,PNGC-Lab, Tianjin Mental Health Centre, Tianjin Anding Hospital, Tianjin, China
| | - Xiaodong Lin
- Department of Psychiatric-Neuroimaging-Genetics Laboratory (PNG_Lab), Wenzhou Seventh People's Hospital, Wenzhou, China
| | - Hongjun Tian
- PNGC-Lab, Tianjin Mental Health Centre, Tianjin Anding Hospital, Tianjin, China
| | - Sha Liu
- Department of Psychiatry, First Hospital of Shanxi Medical University, Tainyuan, China
| | - Haiman Bian
- Department of Radiology, The Fourth Centre Hospital of Tianjin, Tianjin Medical University Affiliated Fourth Centre Hospital, Tianijn, China
| | - Ce Chen
- Department of Psychiatric-Neuroimaging-Genetics Laboratory (PNG_Lab), Wenzhou Seventh People's Hospital, Wenzhou, China
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Chen J, Liu J, Calhoun VD. The Translational Potential of Neuroimaging Genomic Analyses To Diagnosis And Treatment In The Mental Disorders. PROCEEDINGS OF THE IEEE. INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS 2019; 107:912-927. [PMID: 32051642 PMCID: PMC7015534 DOI: 10.1109/jproc.2019.2913145] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Imaging genomics focuses on characterizing genomic influence on the variation of neurobiological traits, holding promise for illuminating the pathogenesis, reforming the diagnostic system, and precision medicine of mental disorders. This paper aims to provide an overall picture of the current status of neuroimaging-genomic analyses in mental disorders, and how we can increase their translational potential into clinical practice. The review is organized around three perspectives. (a) Towards reliability, generalizability and interpretability, where we summarize the multivariate models and discuss the considerations and trade-offs of using these methods and how reliable findings may be reached, to serve as ground for further delineation. (b) Towards improved diagnosis, where we outline the advantages and challenges of constructing a dimensional transdiagnostic model and how imaging genomic analyses map into this framework to aid in deconstructing heterogeneity and achieving an optimal stratification of patients that better inform treatment planning. (c) Towards improved treatment. Here we highlight recent efforts and progress in elucidating the functional annotations that bridge between genomic risk and neurobiological abnormalities, in detecting genomic predisposition and prodromal neurodevelopmental changes, as well as in identifying imaging genomic biomarkers for predicting treatment response. Providing an overview of the challenges and promises, this review hopefully motivates imaging genomic studies with multivariate, dimensional and transdiagnostic designs for generalizable and interpretable findings that facilitate development of personalized treatment.
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Affiliation(s)
- Jiayu Chen
- The Mind Research Network, Albuquerque, NM 87106 USA
| | - Jingyu Liu
- The Mind Research Network, Albuquerque, NM 87106 USA, and also with the Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131 USA
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, NM 87106 USA, and also with the Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131 USA
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Perry A, Roberts G, Mitchell PB, Breakspear M. Connectomics of bipolar disorder: a critical review, and evidence for dynamic instabilities within interoceptive networks. Mol Psychiatry 2019; 24:1296-1318. [PMID: 30279458 PMCID: PMC6756092 DOI: 10.1038/s41380-018-0267-2] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 08/14/2018] [Accepted: 09/07/2018] [Indexed: 12/31/2022]
Abstract
The notion that specific cognitive and emotional processes arise from functionally distinct brain regions has lately shifted toward a connectivity-based approach that emphasizes the role of network-mediated integration across regions. The clinical neurosciences have likewise shifted from a predominantly lesion-based approach to a connectomic paradigm-framing disorders as diverse as stroke, schizophrenia (SCZ), and dementia as "dysconnection syndromes". Here we position bipolar disorder (BD) within this paradigm. We first summarise the disruptions in structural, functional and effective connectivity that have been documented in BD. Not surprisingly, these disturbances show a preferential impact on circuits that support emotional processes, cognitive control and executive functions. Those at high risk (HR) for BD also show patterns of connectivity that differ from both matched control populations and those with BD, and which may thus speak to neurobiological markers of both risk and resilience. We highlight research fields that aim to link brain network disturbances to the phenotype of BD, including the study of large-scale brain dynamics, the principles of network stability and control, and the study of interoception (the perception of physiological states). Together, these findings suggest that the affective dysregulation of BD arises from dynamic instabilities in interoceptive circuits which subsequently impact on fear circuitry and cognitive control systems. We describe the resulting disturbance as a "psychosis of interoception".
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Affiliation(s)
- Alistair Perry
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. .,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin/London, Germany. .,Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195, Berlin, Germany.
| | - Gloria Roberts
- 0000 0004 4902 0432grid.1005.4School of Psychiatry, University of New South Wales, Randwick, NSW Australia ,grid.415193.bBlack Dog Institute, Prince of Wales Hospital, Randwick, NSW Australia
| | - Philip B. Mitchell
- 0000 0004 4902 0432grid.1005.4School of Psychiatry, University of New South Wales, Randwick, NSW Australia ,grid.415193.bBlack Dog Institute, Prince of Wales Hospital, Randwick, NSW Australia
| | - Michael Breakspear
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. .,Metro North Mental Health Service, Brisbane, QLD, Australia.
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Teixeira AL, Colpo GD, Fries GR, Bauer IE, Selvaraj S. Biomarkers for bipolar disorder: current status and challenges ahead. Expert Rev Neurother 2018; 19:67-81. [PMID: 30451546 DOI: 10.1080/14737175.2019.1550361] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Bipolar disorder (BD) is a chronic psychiatric disorder marked by clinical and pathophysiological heterogeneity. There is a high expectation that personalized approaches can improve the management of patients with BD. For that, identification and validation of potential biomarkers are fundamental. Areas covered: This manuscript will critically review the current status of different biomarkers for BD, including peripheral, genetic, neuroimaging, and neurophysiological candidates, discussing the challenges to move the field forward. Expert commentary: There are no lab or complementary tests currently recommended for the diagnosis or management of patients with BD. Panels composed by multiple biomarkers will probably contribute to stratifying patients according to their clinical stage, therapeutic response, and prognosis.
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Affiliation(s)
- Antonio L Teixeira
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA.,b Laboratório Interdisciplinar de Investigação Médica, Faculdade de Medicina , Universidade Federal de Minas Gerais (UFMG) , Belo Horizonte , Brazil
| | - Gabriela D Colpo
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA
| | - Gabriel R Fries
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA
| | - Isabelle E Bauer
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA
| | - Sudhakar Selvaraj
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA
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