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Cetin-Karayumak S, Zhang F, Zurrin R, Billah T, Zekelman L, Makris N, Pieper S, O'Donnell LJ, Rathi Y. Harmonized diffusion MRI data and white matter measures from the Adolescent Brain Cognitive Development Study. Sci Data 2024; 11:249. [PMID: 38413633 PMCID: PMC10899197 DOI: 10.1038/s41597-024-03058-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 02/12/2024] [Indexed: 02/29/2024] Open
Abstract
The Adolescent Brain Cognitive Development (ABCD) Study® has collected data from over 10,000 children across 21 sites, providing insights into adolescent brain development. However, site-specific scanner variability has made it challenging to use diffusion MRI (dMRI) data from this study. To address this, a dataset of harmonized and processed ABCD dMRI data (from release 3) has been created, comprising quality-controlled imaging data from 9,345 subjects, focusing exclusively on the baseline session, i.e., the first time point of the study. This resource required substantial computational time (approx. 50,000 CPU hours) for harmonization, whole-brain tractography, and white matter parcellation. The dataset includes harmonized dMRI data, 800 white matter clusters, 73 anatomically labeled white matter tracts in full and low resolution, and 804 different dMRI-derived measures per subject (72.3 TB total size). Accessible via the NIMH Data Archive, it offers a large-scale dMRI dataset for studying structural connectivity in child and adolescent neurodevelopment. Additionally, several post-harmonization experiments were conducted to demonstrate the success of the harmonization process on the ABCD dataset.
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Affiliation(s)
- Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ryan Zurrin
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Tashrif Billah
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Leo Zekelman
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Program in Speech and Hearing Bioscience and Technology, Division of Medical Sciences, Harvard University, Boston, Massachusetts, USA
| | - Nikos Makris
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Lauren J O'Donnell
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
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2
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Anderson J, Calhoun VD, Pearlson GD, Hawkins KA, Stevens MC. Age-related, multivariate associations between white matter microstructure and behavioral performance in three executive function domains. Dev Cogn Neurosci 2023; 64:101318. [PMID: 37875033 PMCID: PMC10618425 DOI: 10.1016/j.dcn.2023.101318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 10/04/2023] [Accepted: 10/20/2023] [Indexed: 10/26/2023] Open
Abstract
The executive function (EF) domains of working memory (WM), response inhibition (RI), and set shifting (SS) show maturational gains and are linked to neuroimaging-measured brain changes. This study explored ways in which maturation-linked differences in EF abilities are systematically associated with white matter microstructural differences from adolescence into young adulthood. Diffusion tensor imaging (DTI) and nine neurocognitive tests were collected from 120 healthy subjects ages 12-24. Analyses across the white matter skeleton were performed, focusing on fractional anisotropy (FA). Data were 'fused' using a multivariate technique (CCA+jICA), producing four independent components (ICs) depicting white matter FA values that covaried with test performance. Correlations between age and IC loading coefficients identified three EF-DTI profiles that may change developmentally. In one, SS performance was linked to greater reliance on the FA of ventral brain tracts, and less on dorsal tracts with age. In another, white matter microstructure was related to a pattern of strong WM and weak SS that became more pronounced with age. A final IC revealed that younger individuals with low RI and high WM/SS skills typically matured out of this cognitive imbalance, underscored by white matter changes with age. These novel multivariate results begin to emphasize the complexity of brain structure-cognition relationships in adolescents and young adults.
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Affiliation(s)
- Jacey Anderson
- Olin Neuropsychiatry Research Center, Institute of Living, 200 Retreat Ave, Hartford, CT 06106, USA.
| | - Vince D Calhoun
- Department of Psychology, Georgia State University, 33 Gilmer St SE , Atlanta, GA 30303, USA
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, 200 Retreat Ave, Hartford, CT 06106, USA; Yale University School of Medicine, 333 Cedar St, New Haven, CT 06510, USA
| | - Keith A Hawkins
- Yale University School of Medicine, 333 Cedar St, New Haven, CT 06510, USA
| | - Michael C Stevens
- Olin Neuropsychiatry Research Center, Institute of Living, 200 Retreat Ave, Hartford, CT 06106, USA; Yale University School of Medicine, 333 Cedar St, New Haven, CT 06510, USA
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3
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Clementz BA, Chattopadhyay I, Trotti RL, Parker DA, Gershon ES, Hill SK, Ivleva EI, Keedy SK, Keshavan MS, McDowell JE, Pearlson GD, Tamminga CA, Gibbons RD. Clinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1. Schizophr Res 2023; 260:143-151. [PMID: 37657281 PMCID: PMC10712427 DOI: 10.1016/j.schres.2023.08.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 09/03/2023]
Abstract
Clinically defined psychosis diagnoses are neurobiologically heterogeneous. The B-SNIP consortium identified and validated more neurobiologically homogeneous psychosis Biotypes using an extensive battery of neurocognitive and psychophysiological laboratory measures. However, typically the first step in any diagnostic evaluation is the clinical interview. In this project, we evaluated if psychosis Biotypes have clinical characteristics that can support their differentiation in addition to obtaining laboratory testing. Clinical interview data from 1907 individuals with a psychosis Biotype were used to create a diagnostic algorithm. The features were 58 ratings from standard clinical scales. Extremely randomized tree algorithms were used to evaluate sensitivity, specificity, and overall classification success. Biotype classification accuracy peaked at 91 % with the use of 57 items on average. A reduced feature set of 28 items, though, also showed 81 % classification accuracy. Using this reduced item set, we found that only 10-11 items achieved a one-vs-all (Biotype-1 or not, Biotype-2 or not, Biotype-3 or not) area under the sensitivity-specificity curve of .78 to .81. The top clinical characteristics for differentiating psychosis Biotypes, in order of importance, were (i) difficulty in abstract thinking, (ii) multiple indicators of social functioning, (iii) conceptual disorganization, (iv) severity of hallucinations, (v) stereotyped thinking, (vi) suspiciousness, (vii) unusual thought content, (viii) lack of spontaneous speech, and (ix) severity of delusions. These features were remarkably different from those that differentiated DSM psychosis diagnoses. This low-burden adaptive algorithm achieved reasonable classification accuracy and will support Biotype-specific etiological and treatment investigations even in under-resourced clinical and research environments.
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Affiliation(s)
- Brett A Clementz
- Department of Psychology, BioImaging Research Center, University of Georgia, Athens, GA 30602, United States of America.
| | - Ishanu Chattopadhyay
- Department of Medicine, Section of Hospital Medicine, University of Chicago, Chicago, IL, United States of America
| | - Rebekah L Trotti
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - David A Parker
- Department of Human Genetics, Emory University School of Medicine, Atlanta VA Medical Center, Atlanta, GA, United States of America
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States of America
| | - Elena I Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - Jennifer E McDowell
- Department of Psychology, Owens Institute for Behavioral Research, University of Georgia, Athens, GA 30602, United States of America
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University, School of Medicine, New Haven, CT, United States of America; Olin NeuroPsychiatry Research Center, Institute of Living, Hartford, CT, United States of America
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - Robert D Gibbons
- Center for Health Statistics, Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, IL, United States of America
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Lizano P, Pong S, Santarriaga S, Bannai D, Karmacharya R. Brain microvascular endothelial cells and blood-brain barrier dysfunction in psychotic disorders. Mol Psychiatry 2023; 28:3698-3708. [PMID: 37730841 DOI: 10.1038/s41380-023-02255-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/31/2023] [Accepted: 09/08/2023] [Indexed: 09/22/2023]
Abstract
Although there is convergent evidence for blood-brain barrier (BBB) dysfunction and peripheral inflammation in schizophrenia (SZ) and bipolar disorder (BD), it is unknown whether BBB deficits are intrinsic to brain microvascular endothelial cells (BMECs) or arise via effects of peripheral inflammatory cytokines. We examined BMEC function using stem cell-based models to identify cellular and molecular deficits associated with BBB dysfunction in SZ and BD. Induced pluripotent stem cells (iPSCs) from 4 SZ, 4 psychotic BD and 4 healthy control (HC) subjects were differentiated into BMEC-"like" cells. Gene expression and protein levels of tight junction proteins were assessed. Transendothelial electrical resistance (TEER) and permeability were assayed to evaluate BBB function. Cytokine levels were measured from conditioned media. BMECs derived from human iPSCs in SZ and BD did not show differences in BBB integrity or permeability compared to HC BMECs. Outlier analysis using TEER revealed a BBB-deficit (n = 3) and non-deficit (n = 5) group in SZ and BD lines. Stratification based on BBB function in SZ and BD patients identified a BBB-deficit subtype with reduced barrier function, tendency for increased permeability to smaller molecules, and decreased claudin-5 (CLDN5) levels. BMECs from the BBB-deficit group show increased matrix metallopeptidase 1 (MMP1) activity, which correlated with reduced CLDN5 and worse BBB function, and was improved by tumor necrosis factor α (TNFα) and MMP1 inhibition. These results show potential deficits in BMEC-like cells in psychotic disorders that result in BBB disruption and further identify TNFα and MMP1 as promising targets for ameliorating BBB deficits.
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Affiliation(s)
- Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA.
- Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Sovannarath Pong
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Stephanie Santarriaga
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Chemical Biology and Therapeutic Science Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Deepthi Bannai
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Rakesh Karmacharya
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
- Chemical Biology and Therapeutic Science Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, USA.
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5
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Chen F, Mihaljevic M, Hou Z, Li Y, Lu H, Mori S, Sawa A, Faria AV. Relation between white matter integrity, perfusion, and processing speed in early-stage schizophrenia. J Psychiatr Res 2023; 163:166-171. [PMID: 37210835 DOI: 10.1016/j.jpsychires.2023.05.049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 05/10/2023] [Accepted: 05/15/2023] [Indexed: 05/23/2023]
Abstract
OBJECTIVE Cerebral blood flow (CBF) plays a critical role in the maintenance of neuronal integrity, and CBF alterations have been linked to deleterious white matter changes. Several studies report CBF and white matter structural alterations individually. However, whether and how these pathological changes relate to each other remains elusive. By using our cohort of individuals with early-stage schizophrenia, we investigated the relationship between CBF and white matter structure. METHOD We studied 51 early-stage schizophrenia patients and age- and sex-matched healthy controls. We investigated the relationship among tissue structure (assessed with diffusion weighted imaging), perfusion (accessed by pseudo-continuous arterial labeling imaging), and neuropsychological indices (focusing on processing speed). We focused on the corpus callosum, due to its major role in associative functions and directness on revealing the architecture of a major white matter bundle. We performed mediation analysis to identify the possible mechanism underlay the relationship among cognition and white matter integrity and perfusion. RESULTS The CBF and the fractional anisotropy (FA) were inversely correlated in the corpus callosum of early-stage schizophrenia patients. While CBF negatively correlated with processing speed, FA correlated positively with this cognitive measure. These results were not observed in controls. Mediation analysis revealed that the effect of FA on processing speed was mediated via the CBF. CONCLUSIONS We provide evidence of a relationship between brain perfusion and white matter integrity in the corpus callosum in early-stage schizophrenia. These findings may shed the light on underlying metabolic support for structural changes with cognitive impact in schizophrenia.
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Affiliation(s)
- Feng Chen
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, 570311, China
| | - Marina Mihaljevic
- Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zhipeng Hou
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Yang Li
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, 570311, China
| | - Hanzhang Lu
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Susumu Mori
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Akira Sawa
- Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Psychiatry, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, The Whiting School of Engineering, Baltimore, MD, USA; Department of Mental Health, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Andreia V Faria
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
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6
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Cetin-Karayumak S, Zhang F, Billah T, Zekelman L, Makris N, Pieper S, O’Donnell LJ, Rathi Y. Harmonized diffusion MRI data and white matter measures from the Adolescent Brain Cognitive Development Study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.04.535587. [PMID: 37066186 PMCID: PMC10104063 DOI: 10.1101/2023.04.04.535587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
The Adolescent Brain Cognitive Development (ABCD) study has collected data from over 10,000 children across 21 sites, providing valuable insights into adolescent brain development. However, site-specific scanner variability has made it challenging to use diffusion MRI (dMRI) data from this study. To address this, a database of harmonized and processed ABCD dMRI data has been created, comprising quality-controlled imaging data from 9345 subjects. This resource required significant computational effort, taking ~50,000 CPU hours to harmonize the data, perform white matter parcellation, and run whole brain tractography. The database includes harmonized dMRI data, 800 white matter clusters, 73 anatomically labeled white matter tracts both in full-resolution (for analysis) and low-resolution (for visualization), and 804 different dMRI-derived measures per subject. It is available via the NIMH Data Archive and offers tremendous potential for scientific discoveries in structural connectivity studies of neurodevelopment in children and adolescents. Additionally, several post-harmonization experiments were conducted to demonstrate the success of the harmonization process on the ABCD dataset.
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Affiliation(s)
- Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Tashrif Billah
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Leo Zekelman
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Program in Speech and Hearing Bioscience and Technology, Division of Medical Sciences, Harvard University, Boston, Massachusetts, USA
| | - Nikos Makris
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Lauren J. O’Donnell
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
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7
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Cetin-Karayumak S, Lyall AE, Di Biase MA, Seitz-Holland J, Zhang F, Kelly S, Elad D, Pearlson G, Tamminga CA, Sweeney JA, Clementz BA, Schretlen D, Stegmayer K, Walther S, Lee J, Crow T, James A, Voineskos A, Buchanan RW, Szeszko PR, Malhotra AK, Keshavan M, Shenton ME, Rathi Y, Pasternak O, Kubicki M. Characterization of the extracellular free water signal in schizophrenia using multi-site diffusion MRI harmonization. Mol Psychiatry 2023; 28:2030-2038. [PMID: 37095352 PMCID: PMC11146151 DOI: 10.1038/s41380-023-02068-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 03/06/2023] [Accepted: 04/05/2023] [Indexed: 04/26/2023]
Abstract
Studies applying Free Water Imaging have consistently reported significant global increases in extracellular free water (FW) in populations of individuals with early psychosis. However, these published studies focused on homogenous clinical participant groups (e.g., only first episode or chronic), thereby limiting our understanding of the time course of free water elevations across illness stages. Moreover, the relationship between FW and duration of illness has yet to be directly tested. Leveraging our multi-site diffusion magnetic resonance imaging(dMRI) harmonization approach, we analyzed dMRI scans collected by 12 international sites from 441 healthy controls and 434 individuals diagnosed with schizophrenia-spectrum disorders at different illness stages and ages (15-58 years). We characterized the pattern of age-related FW changes by assessing whole brain white matter in individuals with schizophrenia and healthy controls. In individuals with schizophrenia, average whole brain FW was higher than in controls across all ages, with the greatest FW values observed from 15 to 23 years (effect size range = [0.70-0.87]). Following this peak, FW exhibited a monotonic decrease until reaching a minima at the age of 39 years. After 39 years, an attenuated monotonic increase in FW was observed, but with markedly smaller effect sizes when compared to younger patients (effect size range = [0.32-0.43]). Importantly, FW was found to be negatively associated with duration of illness in schizophrenia (p = 0.006), independent of the effects of other clinical and demographic data. In summary, our study finds in a large, age-diverse sample that participants with schizophrenia with a shorter duration of illness showed higher FW values compared to participants with more prolonged illness. Our findings provide further evidence that elevations in the FW are present in individuals with schizophrenia, with the greatest differences in the FW being observed in those at the early stages of the disorder, which might suggest acute extracellular processes.
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Affiliation(s)
- Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Amanda E Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Maria A Di Biase
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sinead Kelly
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Doron Elad
- Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | | | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - David Schretlen
- Department of Psychiatry and Behavioral Sciences, Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Katharina Stegmayer
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Sebastian Walther
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Jungsun Lee
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Tim Crow
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Anthony James
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | | | - Robert W Buchanan
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Philip R Szeszko
- Departments of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Anil K Malhotra
- The Feinstein Institutes for Medical Research and Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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8
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Zhang L, Lizano P, Xu Y, Rubin LH, Lee AM, Lencer R, Reilly JL, Keefe RSE, Keedy SK, Pearlson GD, Clementz BA, Keshavan MS, Gershon ES, Tamminga CA, Sweeney JA, Hill SK, Bishop JR. Peripheral inflammation is associated with impairments of inhibitory behavioral control and visual sensorimotor function in psychotic disorders. Schizophr Res 2023; 255:69-78. [PMID: 36965362 PMCID: PMC10175233 DOI: 10.1016/j.schres.2023.03.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 02/08/2023] [Accepted: 03/13/2023] [Indexed: 03/27/2023]
Abstract
Elevated markers of peripheral inflammation are common in psychosis spectrum disorders and have been associated with brain anatomy, pathology, and physiology as well as clinical outcomes. Preliminary evidence suggests a link between inflammatory cytokines and C-reactive protein (CRP) with generalized cognitive impairments in a subgroup of individuals with psychosis. Whether these patients with elevated peripheral inflammation demonstrate deficits in specific cognitive domains remains unclear. To examine this, seventeen neuropsychological and sensorimotor tasks and thirteen peripheral inflammatory and microvascular markers were quantified in a subset of B-SNIP consortium participants (129 psychosis, 55 healthy controls). Principal component analysis was conducted across the inflammatory markers, resulting in five inflammation factors. Three discrete latent cognitive domains (Visual Sensorimotor, General Cognitive Ability, and Inhibitory Behavioral Control) were characterized based on the neurobehavioral battery and examined in association with inflammation factors. Hierarchical clustering analysis identified cognition-sensitive high/low inflammation subgroups. Among persons with psychotic disorders but not healthy controls, higher inflammation scores had significant associations with impairments of Inhibitory Control (R2 = 0.100, p-value = 2.69e-4, q-value = 0.004) and suggestive associations with Visual Sensorimotor function (R2 = 0.039, p-value = 0.024, q-value = 0.180), but not with General Cognitive Ability (R2 = 0.015, p-value = 0.162). Greater deficits in Inhibitory Control were observed in the high inflammation patient subgroup, which represented 30.2 % of persons with psychotic disorders, as compared to the low inflammation psychosis subgroup. These findings indicate that inflammation dysregulation may differentially impact specific neurobehavioral domains across psychotic disorders, particularly performance on tasks requiring ongoing behavioral monitoring and control.
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Affiliation(s)
- Lusi Zhang
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Yanxun Xu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, United States
| | - Leah H Rubin
- Department of Neurology, Psychiatry, and Epidemiology, Johns Hopkins University, Baltimore, MD, United States
| | - Adam M Lee
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany; Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - James L Reilly
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Richard S E Keefe
- Departments of Psychiatry, Neuroscience, and Psychology, Duke University, Durham, NC, United States
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, School of Medicine, Yale University, New Haven, CT, United States
| | - Brett A Clementz
- Department of Psychology and Neuroscience, University of Georgia, Athens, GA, United States
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center Dallas, TX, United States
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, United States
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States; Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, United States.
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9
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Chien YL, Chen YJ, Tseng WL, Hsu YC, Wu CS, Tseng WYI, Gau SSF. Differences in white matter segments in autistic males, non-autistic siblings, and non-autistic participants: An intermediate phenotype approach. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2022; 27:1036-1052. [PMID: 36254873 DOI: 10.1177/13623613221125620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
LAY ABSTRACT White matter is the neural pathway that connects neurons in different brain regions. Although research has shown white matter differences between autistic and non-autistic people, little is known about the properties of white matter in non-autistic siblings. In addition, past studies often focused on the whole neural tracts; it is unclear where differences exist in specific segments of the tracts. This study identified neural segments that differed between autistic people, their non-autistic siblings, and the age- and non-autistic people. We found altered segments within the tracts connected to anterior brain regions corresponding to several higher cognitive functions (e.g. executive functions) in autistic people and non-autistic siblings. Segments connecting to regions for social cognition and Theory of Mind were altered only in autistic people, explaining a large portion of autistic traits and may serve as neuroimaging markers. Segments within the tracts associated with fewer autistic traits or connecting brain regions for diverse highly integrated functions showed compensatory increases in the microstructural properties in non-autistic siblings. Our findings suggest that differential white matter segments that are shared between autistic people and non-autistic siblings may serve as potential "intermediate phenotypes"-biological or neuropsychological characteristics in the causal link between genetics and symptoms-of autism. These findings shed light on a promising neuroimaging model to refine the intermediate phenotype of autism which may facilitate further identification of the genetic and biological bases of autism. Future research exploring links between compensatory segments and neurocognitive strengths in non-autistic siblings may help understand brain adaptation to autism.
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Affiliation(s)
- Yi-Ling Chien
- National Taiwan University Hospital and College of Medicine, Taiwan.,National Taiwan University, Taiwan
| | | | | | | | - Chi-Shin Wu
- National Taiwan University Hospital and College of Medicine, Taiwan
| | | | - Susan Shur-Fen Gau
- National Taiwan University Hospital and College of Medicine, Taiwan.,National Taiwan University, Taiwan
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10
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Keshavan MS, Yassin W, Stone WS. Conceptualizing psychosis as an information processing disorder: Signal, bandwidth, noise, and bias. Schizophr Res 2022; 242:70-72. [PMID: 35177283 DOI: 10.1016/j.schres.2022.01.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/11/2022] [Accepted: 01/11/2022] [Indexed: 01/26/2023]
Affiliation(s)
- Matcheri S Keshavan
- Beth Israel Deaconess Medical Center, Boston, MA, United States of America; Massachusetts Mental Health Center, Boston, MA, United States of America; Harvard Medical School, Boston, MA, United States of America.
| | - Walid Yassin
- Beth Israel Deaconess Medical Center, Boston, MA, United States of America; Massachusetts Mental Health Center, Boston, MA, United States of America; Harvard Medical School, Boston, MA, United States of America; McLean Hospital, Belmont, MA, United States of America
| | - William S Stone
- Beth Israel Deaconess Medical Center, Boston, MA, United States of America; Massachusetts Mental Health Center, Boston, MA, United States of America; Harvard Medical School, Boston, MA, United States of America
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11
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Hoang D, Xu Y, Lutz O, Bannai D, Zeng V, Bishop JR, Keshavan M, Lizano P. Inflammatory Subtypes in Antipsychotic-Naïve First-Episode Schizophrenia are Associated with Altered Brain Morphology and Topological Organization. Brain Behav Immun 2022; 100:297-308. [PMID: 34875344 PMCID: PMC8767408 DOI: 10.1016/j.bbi.2021.11.019] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 11/01/2021] [Accepted: 11/26/2021] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Peripheral inflammation is implicated in schizophrenia, however, not all individuals demonstrate inflammatory alterations. Recent studies identified inflammatory subtypes in chronic psychosis with high inflammation having worse cognitive performance and displaying neuroanatomical enlargement compared to low inflammation subtypes. It is unclear if inflammatory subtypes exist earlier in the disease course, thus, we aim to identify inflammatory subtypes in antipsychotic naïve First-Episode Schizophrenia (FES). METHODS 12 peripheral inflammatory markers, clinical, cognitive, and neuroanatomical measures were collected from a naturalistic study of antipsychotic-naïve FES patients. A combination of unsupervised principal component analysis and hierarchical clustering was used to categorize inflammatory subtypes from their cytokine data (17 FES High, 30 FES Low, and 33 healthy controls (HCs)). Linear regression analysis was used to assess subtype differences. Neuroanatomical correlations with clinical and cognitive measures were performed using partial Spearman correlations. Graph theoretical analyses were performed to assess global and local network properties across inflammatory subtypes. RESULTS The FES High group made up 36% of the FES group and demonstrated significantly greater levels of IL1β, IL6, IL8, and TNFα compared to FES Low, and higher levels of IL1β and IL8 compared to HCs. FES High had greater right parahippocampal, caudal anterior cingulate, and bank superior sulcus thicknesses compared to FES Low. Compared to HCs, FES Low showed smaller bilateral amygdala volumes and widespread cortical thickness. FES High and FES Low groups demonstrated less efficient topological organization compared to HCs. Individual cytokines and/or inflammatory signatures were positively associated with cognition and symptom measures. CONCLUSIONS Inflammatory subtypes are present in antipsychotic-naïve FES and are associated with inflammation-mediated cortical expansion. These findings support our previous findings in chronic psychosis and point towards a connection between inflammation and blood-brain barrier disruption. Thus, identifying inflammatory subtypes may provide a novel therapeutic avenue for biomarker-guided treatment involving anti-inflammatory medications.
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Affiliation(s)
- Dung Hoang
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yanxun Xu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Olivia Lutz
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Deepthi Bannai
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Victor Zeng
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology and Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
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12
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Bannai D, Adhan I, Katz R, Kim LA, Keshavan M, Miller JB, Lizano P. Quantifying Retinal Microvascular Morphology in Schizophrenia Using Swept-Source Optical Coherence Tomography Angiography. Schizophr Bull 2022; 48:80-89. [PMID: 34554256 PMCID: PMC8781445 DOI: 10.1093/schbul/sbab111] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Retinovascular changes are reported on fundus imaging in schizophrenia (SZ). This is the first study to use swept-source optical coherence tomography angiography (OCT-A) to comprehensively examine retinal microvascular changes in SZ. METHODS This study included 30 patients with SZ/schizoaffective disorder (8 early and 15 chronic) and 22 healthy controls (HCs). All assessments were performed at Beth Israel Deaconess Medical Center and Massachusetts Eye and Ear. All participants underwent swept-source OCT-A of right (oculus dextrus [OD]) and left (oculus sinister [OS]) eye, clinical, and cognitive assessments. Macular OCT-A images (6 × 6 mm) were collected with the DRI Topcon Triton for superficial, deep, and choriocapillaris vascular regions. Microvasculature was quantified using vessel density (VD), skeletonized vessel density (SVD), fractal dimension (FD), and vessel diameter index (VDI). RESULTS Twenty-one HCs and 26 SZ subjects were included. Compared to HCs, SZ patients demonstrated higher overall OD superficial SVD, OD choriocapillaris VD, and OD choriocapillaris SVD, which were primarily observed in the central, central and outer superior, and central and outer inferior/superior, respectively. Early-course SZ subjects had significantly higher OD superficial VD, OD choriocapillaris SVD, and OD choriocapillaris FD compared to matched HCs. Higher bilateral (OU) superficial VD correlated with lower Positive and Negative Syndrome Scale (PANSS) positive scores, and higher OU deep VDI was associated with higher PANSS negative scores. CONCLUSIONS AND RELEVANCE These results suggest the presence of microvascular dysfunction associated with early-stage SZ. Clinical associations with microvascular alterations further implicate this hypothesis, with higher measures being associated with worse symptom severity and functioning in early stages and with lower symptom severity and better functioning in later stages.
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Affiliation(s)
- Deepthi Bannai
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Iniya Adhan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Raviv Katz
- Harvard Retinal Imaging Lab, Massachusetts Eye and Ear, Boston, MA, USA
| | - Leo A Kim
- Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - John B Miller
- Harvard Retinal Imaging Lab, Massachusetts Eye and Ear, Boston, MA, USA
- Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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13
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Li F, Sun H, Biswal BB, Sweeney JA, Gong Q. Artificial intelligence applications in psychoradiology. PSYCHORADIOLOGY 2021; 1:94-107. [PMID: 37881257 PMCID: PMC10594695 DOI: 10.1093/psyrad/kkab009] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 05/10/2021] [Accepted: 06/04/2021] [Indexed: 02/05/2023]
Abstract
One important challenge in psychiatric research is to translate findings from brain imaging research studies that identified brain alterations in patient groups into an accurate diagnosis at an early stage of illness, prediction of prognosis before treatment, and guidance for selection of effective treatments that target patient-relevant pathophysiological features. This is the primary aim of the field of Psychoradiology. Using databases collected from large samples at multiple centers, sophisticated artificial intelligence (AI) algorithms may be used to develop clinically useful image analysis pipelines that can help physicians diagnose, predict, and make treatment decisions. In this review, we selectively summarize psychoradiological research using magnetic resonance imaging of the brain to explore the neural mechanism of psychiatric disorders, and outline progress and the path forward for the combination of psychoradiology and AI for complementing clinical examinations in patients with psychiatric disorders, as well as limitations in the application of AI that should be considered in future translational research.
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Affiliation(s)
- Fei Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, P.R. China
- Functional and Molecular Imaging Key Laboratory of Sichuan Provience, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
| | - Huaiqiang Sun
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, P.R. China
- Functional and Molecular Imaging Key Laboratory of Sichuan Provience, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, P.R. China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH 45219, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, P.R. China
- Functional and Molecular Imaging Key Laboratory of Sichuan Provience, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, P.R. China
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