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Ayyash S, Davis AD, Alders GL, MacQueen G, Strother SC, Hassel S, Zamyadi M, Arnott SR, Harris JK, Lam RW, Milev R, Müller DJ, Kennedy SH, Rotzinger S, Frey BN, Minuzzi L, Hall GB. Assessing remission in major depressive disorder using a functional-structural data fusion pipeline: A CAN-BIND-1 study. IBRO Neurosci Rep 2024; 16:135-146. [PMID: 38293679 PMCID: PMC10826332 DOI: 10.1016/j.ibneur.2023.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 12/30/2023] [Indexed: 02/01/2024] Open
Abstract
Neural network-level changes underlying symptom remission in major depressive disorder (MDD) are often studied from a single perspective. Multimodal approaches to assess neuropsychiatric disorders are evolving, as they offer richer information about brain networks. A FATCAT-awFC pipeline was developed to integrate a computationally intense data fusion method with a toolbox, to produce a faster and more intuitive pipeline for combining functional connectivity with structural connectivity (denoted as anatomically weighted functional connectivity (awFC)). Ninety-three participants from the Canadian Biomarker Integration Network for Depression study (CAN-BIND-1) were included. Patients with MDD were treated with 8 weeks of escitalopram and adjunctive aripiprazole for another 8 weeks. Between-group connectivity (SC, FC, awFC) comparisons contrasted remitters (REM) with non-remitters (NREM) at baseline and 8 weeks. Additionally, a longitudinal study analysis was performed to compare connectivity changes across time for REM, from baseline to week-8. Association between cognitive variables and connectivity were also assessed. REM were distinguished from NREM by lower awFC within the default mode, frontoparietal, and ventral attention networks. Compared to REM at baseline, REM at week-8 revealed increased awFC within the dorsal attention network and decreased awFC within the frontoparietal network. A medium effect size was observed for most results. AwFC in the frontoparietal network was associated with neurocognitive index and cognitive flexibility for the NREM group at week-8. In conclusion, the FATCAT-awFC pipeline has the benefit of providing insight on the 'full picture' of connectivity changes for REMs and NREMs while making for an easy intuitive approach.
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Affiliation(s)
- Sondos Ayyash
- School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada
- Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, Ontario, Canada
| | - Andrew D Davis
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Gésine L Alders
- Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
| | - Glenda MacQueen
- Hotchkiss Brain Institute and Mathison Centre for Mental Health Research and Education, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Ontario, Canada
| | - Stefanie Hassel
- Hotchkiss Brain Institute and Mathison Centre for Mental Health Research and Education, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | | | - Jacqueline K Harris
- Department of Computer Science, University of Alberta, Edmonton, Alberta, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, Providence Care Hospital, Kingston, Ontario, Canada
| | - Daniel J Müller
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Sidney H Kennedy
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Centre for Mental Health, University Health Network, Toronto, Ontario, Canada
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
- Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Susan Rotzinger
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
- Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
- Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
- Mood Disorders Treatment and Research Centre and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, Ontario, Canada
| | - Luciano Minuzzi
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
- Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
- Mood Disorders Treatment and Research Centre and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, Ontario, Canada
| | - Geoffrey B Hall
- School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada
- Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, Ontario, Canada
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
- Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
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Nogovitsyn N, Ballester P, Lasby M, Dunlop K, Ceniti AK, Squires S, Rowe J, Ho K, Suh J, Hassel S, Souza R, Casseb RF, Harris JK, Zamyadi M, Arnott SR, Strother SC, Hall G, Lam RW, Poppenk J, Lebel C, Bray S, Metzak P, MacIntosh BJ, Goldstein BI, Wang J, Rizvi SJ, MacQueen G, Addington J, Harkness KL, Rotzinger S, Kennedy SH, Frey BN. An empirical analysis of structural neuroimaging profiles in a staging model of depression. J Affect Disord 2024; 351:631-640. [PMID: 38290583 DOI: 10.1016/j.jad.2024.01.246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/16/2024] [Accepted: 01/26/2024] [Indexed: 02/01/2024]
Abstract
We examine structural brain characteristics across three diagnostic categories: at risk for serious mental illness; first-presenting episode and recurrent major depressive disorder (MDD). We investigate whether the three diagnostic groups display a stepwise pattern of brain changes in the cortico-limbic regions. Integrated clinical and neuroimaging data from three large Canadian studies were pooled (total n = 622 participants, aged 12-66 years). Four clinical profiles were used in the classification of a clinical staging model: healthy comparison individuals with no history of depression (HC, n = 240), individuals at high risk for serious mental illness due to the presence of subclinical symptoms (SC, n = 80), first-episode depression (FD, n = 82), and participants with recurrent MDD in a current major depressive episode (RD, n = 220). Whole-brain volumetric measurements were extracted with FreeSurfer 7.1 and examined using three different types of analyses. Hippocampal volume decrease and cortico-limbic thinning were the most informative features for the RD vs HC comparisons. FD vs HC revealed that FD participants were characterized by a focal decrease in cortical thickness and global enlargement in amygdala volumes. Greater total amygdala volumes were significantly associated with earlier onset of illness in the FD but not the RD group. We did not confirm the construct validity of a tested clinical staging model, as a differential pattern of brain alterations was identified across the three diagnostic groups that did not parallel a stepwise clinical staging approach. The pathological processes during early stages of the illness may fundamentally differ from those that occur at later stages with clinical progression.
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Affiliation(s)
- Nikita Nogovitsyn
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, ON, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
| | - Pedro Ballester
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Mike Lasby
- Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Katharine Dunlop
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Amanda K Ceniti
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, ON, Canada; Arthur Sommer Rotenberg Suicide & Depression Studies Program, St. Michael's Hospital, Toronto, ON, Canada
| | - Scott Squires
- Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Jessie Rowe
- Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Keith Ho
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, ON, Canada
| | - JeeSu Suh
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Stefanie Hassel
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Roberto Souza
- Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Raphael F Casseb
- Neuroimaging Laboratory, University of Campinas, Campinas, SP, Brazil
| | | | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest, Toronto, ON, Canada
| | | | - Stephen C Strother
- Rotman Research Institute, Baycrest, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, ON, Canada
| | - Geoffrey Hall
- Department of Psychology, Neuroscience & Behaviour, McMaster University, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Jordan Poppenk
- Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Catherine Lebel
- Department of Radiology, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, Calgary, AB, Canada; Child & Adolescent Imaging Research (CAIR) Program, Calgary, AB, Canada
| | - Signe Bray
- Department of Radiology, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, Calgary, AB, Canada; Child & Adolescent Imaging Research (CAIR) Program, Calgary, AB, Canada
| | - Paul Metzak
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Bradley J MacIntosh
- Rotman Research Institute, Baycrest, Toronto, ON, Canada; Hurvitz Brain Sciences Program, Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada; Computational Radiology & Artificial Intelligence (CRAI) Unit, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Benjamin I Goldstein
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry and Pharmacology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - JianLi Wang
- Department of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada
| | - Sakina J Rizvi
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, ON, Canada; Arthur Sommer Rotenberg Suicide & Depression Studies Program, St. Michael's Hospital, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Glenda MacQueen
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Jean Addington
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Kate L Harkness
- Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Susan Rotzinger
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, ON, Canada; Arthur Sommer Rotenberg Suicide & Depression Studies Program, St. Michael's Hospital, Toronto, ON, Canada; Krembil Research Centre, University Health Network, Toronto, ON, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Sidney H Kennedy
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, ON, Canada; Arthur Sommer Rotenberg Suicide & Depression Studies Program, St. Michael's Hospital, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Krembil Research Centre, University Health Network, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
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Vaccarino SR, Wang S, Rizvi SJ, Lou W, Hassel S, MacQueen GM, Ho K, Frey BN, Lam RW, Milev RV, Rotzinger S, Ravindran AV, Strother SC, Kennedy SH. Functional neuroimaging biomarkers of anhedonia response to escitalopram plus adjunct aripiprazole treatment for major depressive disorder. BJPsych Open 2024; 10:e18. [PMID: 38179598 PMCID: PMC10790221 DOI: 10.1192/bjo.2023.588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/21/2023] [Accepted: 09/19/2023] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Identifying neuroimaging biomarkers of antidepressant response may help guide treatment decisions and advance precision medicine. AIMS To examine the relationship between anhedonia and functional neurocircuitry in key reward processing brain regions in people with major depressive disorder receiving aripiprazole adjunct therapy with escitalopram. METHOD Data were collected as part of the CAN-BIND-1 study. Participants experiencing a current major depressive episode received escitalopram for 8 weeks; escitalopram non-responders received adjunct aripiprazole for an additional 8 weeks. Functional magnetic resonance imaging (on weeks 0 and 8) and clinical assessment of anhedonia (on weeks 0, 8 and 16) were completed. Seed-based correlational analysis was employed to examine the relationship between baseline resting-state functional connectivity (rsFC), using the nucleus accumbens (NAc) and anterior cingulate cortex (ACC) as key regions of interest, and change in anhedonia severity after adjunct aripiprazole. RESULTS Anhedonia severity significantly improved after treatment with adjunct aripiprazole.There was a positive correlation between anhedonia improvement and rsFC between the ACC and posterior cingulate cortex, ACC and posterior praecuneus, and NAc and posterior praecuneus. There was a negative correlation between anhedonia improvement and rsFC between the ACC and anterior praecuneus and NAc and anterior praecuneus. CONCLUSIONS Eight weeks of aripiprazole, adjunct to escitalopram, was associated with improved anhedonia symptoms. Changes in functional connectivity between key reward regions were associated with anhedonia improvement, suggesting aripiprazole may be an effective treatment for individuals experiencing reward-related deficits. Future studies are required to replicate our findings and explore their generalisability, using other agents with partial dopamine (D2) agonism and/or serotonin (5-HT2A) antagonism.
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Affiliation(s)
- Sophie R. Vaccarino
- Institute of Medical Science, University of Toronto, Canada; Centre for Depression and Suicide Studies, Unity Health Toronto, Canada; and Cumming School of Medicine, University of Calgary, Canada
| | - Shijing Wang
- Institute of Medical Science, University of Toronto, Canada; and Centre for Depression and Suicide Studies, Unity Health Toronto, Canada
| | - Sakina J. Rizvi
- Institute of Medical Science, University of Toronto, Canada; Centre for Depression and Suicide Studies, Unity Health Toronto, Canada; Department of Psychiatry, University of Toronto, Canada; Department of Psychiatry, Unity Health Toronto, Canada; and Li Ka Shing Knowledge Institute, Unity Health Toronto, Canada
| | - Wendy Lou
- Dalla Lana School of Public Health, University of Toronto, Canada; and Department of Biostatistics, University of Toronto, Canada
| | - Stefanie Hassel
- Cumming School of Medicine, University of Calgary, Canada; and Department of Psychiatry, University of Calgary, Canada
| | - Glenda M. MacQueen
- Cumming School of Medicine, University of Calgary, Canada; and Department of Psychiatry, University of Calgary, Canada
| | - Keith Ho
- Centre for Depression and Suicide Studies, Unity Health Toronto, Canada; Department of Psychiatry, Unity Health Toronto, Canada; and Li Ka Shing Knowledge Institute, Unity Health Toronto, Canada
| | - Benicio N. Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Canada
| | - Raymond W. Lam
- Department of Psychiatry, University of British Columbia, Canada
| | - Roumen V. Milev
- Department of Psychiatry, Providence Care, Queen's University, Canada
| | - Susan Rotzinger
- Centre for Depression and Suicide Studies, Unity Health Toronto, Canada
| | | | - Stephen C. Strother
- Institute of Medical Science, University of Toronto, Canada; Rotman Research Institute, Baycrest Centre, Canada; and Department of Medical Biophysics, University of Toronto, Canada
| | - Sidney H. Kennedy
- Institute of Medical Science, University of Toronto, Canada; Centre for Depression and Suicide Studies, Unity Health Toronto, Canada; Department of Psychiatry, University of Toronto, Canada; Department of Psychiatry, Unity Health Toronto, Canada; Li Ka Shing Knowledge Institute, Unity Health Toronto, Canada; and Krembil Research Institute, University Health Network, Toronto, Canada
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4
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Mazurka R, Cunningham S, Hassel S, Foster JA, Nogovitsyn N, Fiori LM, Strother SC, Arnott SR, Frey BN, Lam RW, MacQueen GM, Milev RV, Rotzinger S, Turecki G, Kennedy SH, Harkness KL. Relation of hippocampal volume and SGK1 gene expression to treatment remission in major depression is moderated by childhood maltreatment: A CAN-BIND-1 report. Eur Neuropsychopharmacol 2024; 78:71-80. [PMID: 38128154 DOI: 10.1016/j.euroneuro.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 12/01/2023] [Accepted: 12/14/2023] [Indexed: 12/23/2023]
Abstract
Preclinical research implicates stress-induced upregulation of the enzyme, serum- and glucocorticoid-regulated kinase 1 (SGK1), in reduced hippocampal volume. In the current study, we tested the hypothesis that greater SGK1 mRNA expression in humans would be associated with lower hippocampal volume, but only among those with a history of prolonged stress exposure, operationalized as childhood maltreatment (physical, sexual, and/or emotional abuse). Further, we examined whether baseline levels of SGK1 and hippocampal volume, or changes in these markers over the course of antidepressant treatment, would predict treatment outcomes in adults with major depression [MDD]. We assessed SGK1 mRNA expression from peripheral blood, and left and right hippocampal volume at baseline, as well as change in these markers over the first 8 weeks of a 16-week open-label trial of escitalopram as part of the Canadian Biomarker Integration Network in Depression program (MDD [n = 161] and healthy comparison participants [n = 91]). Childhood maltreatment was assessed via contextual interview with standardized ratings. In the full sample at baseline, greater SGK1 expression was associated with lower hippocampal volume, but only among those with more severe childhood maltreatment. In individuals with MDD, decreases in SGK1 expression predicted lower remission rates at week 16, again only among those with more severe maltreatment. Decreases in hippocampal volume predicted lower week 16 remission for those with low childhood maltreatment. These results suggest that both glucocorticoid-related neurobiological mechanisms of the stress response and history of childhood stress exposure may be critical to understanding differential treatment outcomes in MDD. ClinicalTrials.gov: NCT01655706 Canadian Biomarker Integration Network for Depression Study.
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Affiliation(s)
- Raegan Mazurka
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.
| | | | - Stefanie Hassel
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Jane A Foster
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Nikita Nogovitsyn
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto ON, Canada
| | - Laura M Fiori
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Canada
| | | | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Mood Disorders Program, St. Joseph's Healthcare Hamilton, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Glenda M MacQueen
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Roumen V Milev
- Departments of Psychiatry and Psychology, And Providence Care Hospital, Queen's University, Kingston, ON, Canada
| | - Susan Rotzinger
- Department of Psychiatry, University of Toronto, Canada; Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto ON, Canada
| | - Gustavo Turecki
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Canada; Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto ON, Canada
| | - Kate L Harkness
- Department of Psychology, Queen's University, Kingston, ON, Canada
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5
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Sajjadian M, Uher R, Ho K, Hassel S, Milev R, Frey BN, Farzan F, Blier P, Foster JA, Parikh SV, Müller DJ, Rotzinger S, Soares CN, Turecki G, Taylor VH, Lam RW, Strother SC, Kennedy SH. Prediction of depression treatment outcome from multimodal data: a CAN-BIND-1 report. Psychol Med 2023; 53:5374-5384. [PMID: 36004538 PMCID: PMC10482706 DOI: 10.1017/s0033291722002124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 05/04/2022] [Accepted: 06/20/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Prediction of treatment outcomes is a key step in improving the treatment of major depressive disorder (MDD). The Canadian Biomarker Integration Network in Depression (CAN-BIND) aims to predict antidepressant treatment outcomes through analyses of clinical assessment, neuroimaging, and blood biomarkers. METHODS In the CAN-BIND-1 dataset of 192 adults with MDD and outcomes of treatment with escitalopram, we applied machine learning models in a nested cross-validation framework. Across 210 analyses, we examined combinations of predictive variables from three modalities, measured at baseline and after 2 weeks of treatment, and five machine learning methods with and without feature selection. To optimize the predictors-to-observations ratio, we followed a tiered approach with 134 and 1152 variables in tier 1 and tier 2 respectively. RESULTS A combination of baseline tier 1 clinical, neuroimaging, and molecular variables predicted response with a mean balanced accuracy of 0.57 (best model mean 0.62) compared to 0.54 (best model mean 0.61) in single modality models. Adding week 2 predictors improved the prediction of response to a mean balanced accuracy of 0.59 (best model mean 0.66). Adding tier 2 features did not improve prediction. CONCLUSIONS A combination of clinical, neuroimaging, and molecular data improves the prediction of treatment outcomes over single modality measurement. The addition of measurements from the early stages of treatment adds precision. Present results are limited by lack of external validation. To achieve clinically meaningful prediction, the multimodal measurement should be scaled up to larger samples and the robustness of prediction tested in an external validation dataset.
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Affiliation(s)
- Mehri Sajjadian
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Keith Ho
- University Health Network, 399 Bathurst Street, Toronto, ON, M5T 2S8, Canada
- Unity Health Toronto, St. Michael's Hospital, 193 Yonge Street, 6th floor, Toronto, ON, M5B 1M4, Canada
| | - Stefanie Hassel
- Department of Psychiatry and Mathison Centre for Mental Health Research and Education, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, AB, T2N 4N1, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, Providence Care Hospital, Kingston, ON, Canada
| | - Benicio N. Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
- Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - Faranak Farzan
- eBrain Lab, School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, BC, Canada
| | - Pierre Blier
- The Royal's Institute of Mental Health Research, 1145 Carling Avenue, Ottawa, ON, K1Z 7K4, Canada
- Department of Cellular and Molecular Medicine, University of Ottawa, 451 Smyth Road, Ottawa, ON, K1H 8M5, Canada
- Department of Psychiatry, University of Ottawa, 1145 Carling Avenue, Ottawa, ON, K1Z 7K4, Canada
| | - Jane A. Foster
- Department of Psychiatry & Behavioural Neurosciences, St Joseph's Healthcare, Hamilton, ON, Canada
| | - Sagar V. Parikh
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Daniel J. Müller
- Campbell Family Mental Health Research Institute, Center for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Susan Rotzinger
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Claudio N. Soares
- Department of Psychiatry, Queen's University School of Medicine, Kingston, ON, Canada
| | - Gustavo Turecki
- Department of Psychiatry, Douglas Institute, McGill University, Montreal, QC, Canada
| | - Valerie H. Taylor
- Department of Psychiatry, Foothills Medical Centre, University of Calgary, Calgary, AB, Canada
| | - Raymond W. Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Stephen C. Strother
- Rotman Research Center, Baycrest, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Sidney H. Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University Health Network, Toronto, Ontario, Canada
- Krembil Research Centre, University Health Network, University of Toronto, Toronto, Canada
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6
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Ozzoude M, Varriano B, Beaton D, Ramirez J, Adamo S, Holmes MF, Scott CJM, Gao F, Sunderland KM, McLaughlin P, Goubran M, Kwan D, Roberts A, Bartha R, Symons S, Tan B, Swartz RH, Abrahao A, Saposnik G, Masellis M, Lang AE, Marras C, Zinman L, Shoesmith C, Borrie M, Fischer CE, Frank A, Freedman M, Montero-Odasso M, Kumar S, Pasternak S, Strother SC, Pollock BG, Rajji TK, Seitz D, Tang-Wai DF, Turnbull J, Dowlatshahi D, Hassan A, Casaubon L, Mandzia J, Sahlas D, Breen DP, Grimes D, Jog M, Steeves TDL, Arnott SR, Black SE, Finger E, Rabin J, Tartaglia MC. White matter hyperintensities and smaller cortical thickness are associated with neuropsychiatric symptoms in neurodegenerative and cerebrovascular diseases. Alzheimers Res Ther 2023; 15:114. [PMID: 37340319 PMCID: PMC10280981 DOI: 10.1186/s13195-023-01257-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 06/01/2023] [Indexed: 06/22/2023]
Abstract
BACKGROUND Neuropsychiatric symptoms (NPS) are a core feature of most neurodegenerative and cerebrovascular diseases. White matter hyperintensities and brain atrophy have been implicated in NPS. We aimed to investigate the relative contribution of white matter hyperintensities and cortical thickness to NPS in participants across neurodegenerative and cerebrovascular diseases. METHODS Five hundred thirteen participants with one of these conditions, i.e. Alzheimer's Disease/Mild Cognitive Impairment, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, Parkinson's Disease, or Cerebrovascular Disease, were included in the study. NPS were assessed using the Neuropsychiatric Inventory - Questionnaire and grouped into hyperactivity, psychotic, affective, and apathy subsyndromes. White matter hyperintensities were quantified using a semi-automatic segmentation technique and FreeSurfer cortical thickness was used to measure regional grey matter loss. RESULTS Although NPS were frequent across the five disease groups, participants with frontotemporal dementia had the highest frequency of hyperactivity, apathy, and affective subsyndromes compared to other groups, whilst psychotic subsyndrome was high in both frontotemporal dementia and Parkinson's disease. Results from univariate and multivariate results showed that various predictors were associated with neuropsychiatric subsyndromes, especially cortical thickness in the inferior frontal, cingulate, and insula regions, sex(female), global cognition, and basal ganglia-thalamus white matter hyperintensities. CONCLUSIONS In participants with neurodegenerative and cerebrovascular diseases, our results suggest that smaller cortical thickness and white matter hyperintensity burden in several cortical-subcortical structures may contribute to the development of NPS. Further studies investigating the mechanisms that determine the progression of NPS in various neurodegenerative and cerebrovascular diseases are needed.
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Affiliation(s)
- Miracle Ozzoude
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 2S8, Canada
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Psychology, Faculty of Health, York University, Toronto, ON, Canada
| | - Brenda Varriano
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 2S8, Canada
- Central Michigan University College of Medicine, Mount Pleasant, MI, USA
| | - Derek Beaton
- Data Science & Advanced Analytic, St. Michael's Hospital, Toronto, ON, Canada
| | - Joel Ramirez
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Sabrina Adamo
- Graduate Department of Psychological Clinical Science, University of Toronto Scarborough, Scarborough, ON, Canada
| | - Melissa F Holmes
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher J M Scott
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Fuqiang Gao
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | | | | | - Maged Goubran
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
- Queen's University, Kingston, ON, Canada
| | - Angela Roberts
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA
- School of Communication Sciences and Disorders, Faculty of Health Sciences, Western University, London, ON, Canada
| | - Robert Bartha
- Robarts Research Institute, Western University, London, ON, Canada
| | - Sean Symons
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Brian Tan
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Richard H Swartz
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Agessandro Abrahao
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Gustavo Saposnik
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Mario Masellis
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Anthony E Lang
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Edmond J Safra Program for Parkinson Disease, Movement Disorder Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Connie Marras
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Edmond J Safra Program for Parkinson Disease, Movement Disorder Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Lorne Zinman
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Christen Shoesmith
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Michael Borrie
- Robarts Research Institute, Western University, London, ON, Canada
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Corinne E Fischer
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada
| | - Andrew Frank
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada
- Bruyère Research Institute, Ottawa, ON, Canada
| | - Morris Freedman
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Division of Neurology, Baycrest Health Sciences, Toronto, ON, Canada
| | - Manuel Montero-Odasso
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Lawsone Health Research Institute, London, ON, Canada
- Gait and Brain Lab, Parkwood Institute, London, ON, Canada
| | - Sanjeev Kumar
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Stephen Pasternak
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Stephen C Strother
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Bruce G Pollock
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tarek K Rajji
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada
| | - Dallas Seitz
- Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - David F Tang-Wai
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Memory Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - John Turnbull
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
- Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Dar Dowlatshahi
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada
| | - Ayman Hassan
- Thunder Bay Regional Health Research Institute, Thunder Bay, ON, Canada
| | - Leanne Casaubon
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Jennifer Mandzia
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- St. Joseph's Healthcare Centre, London, ON, Canada
| | - Demetrios Sahlas
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
- Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - David P Breen
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - David Grimes
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada
| | - Mandar Jog
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- London Health Sciences Centre, London, ON, Canada
| | - Thomas D L Steeves
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Stephen R Arnott
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Sandra E Black
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Jennifer Rabin
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 2S8, Canada.
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada.
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada.
- Memory Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.
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7
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Behan B, Jeanson F, Cheema H, Eng D, Khimji F, Vaccarino AL, Gee T, Evans SG, MacPhee FC, Dong F, Shahnazari S, Sparks A, Martens E, Lasalandra B, Arnott SR, Strother SC, Javadi M, Dharsee M, Evans KR, Nylen K, Mikkelsen T. FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research. Front Neuroinform 2023; 17:1158378. [PMID: 37274750 PMCID: PMC10233014 DOI: 10.3389/fninf.2023.1158378] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 04/10/2023] [Indexed: 06/06/2023] Open
Abstract
The effective sharing of health research data within the healthcare ecosystem can have tremendous impact on the advancement of disease understanding, prevention, treatment, and monitoring. By combining and reusing health research data, increasingly rich insights can be made about patients and populations that feed back into the health system resulting in more effective best practices and better patient outcomes. To achieve the promise of a learning health system, data needs to meet the FAIR principles of findability, accessibility, interoperability, and reusability. Since the inception of the Brain-CODE platform and services in 2012, the Ontario Brain Institute (OBI) has pioneered data sharing activities aligned with FAIR principles in neuroscience. Here, we describe how Brain-CODE has operationalized data sharing according to the FAIR principles. Findable-Brain-CODE offers an interactive and itemized approach for requesters to generate data cuts of interest that align with their research questions. Accessible-Brain-CODE offers multiple data access mechanisms. These mechanisms-that distinguish between metadata access, data access within a secure computing environment on Brain-CODE and data access via export will be discussed. Interoperable-Standardization happens at the data capture level and the data release stage to allow integration with similar data elements. Reusable - Brain-CODE implements several quality assurances measures and controls to maximize data value for reusability. We will highlight the successes and challenges of a FAIR-focused neuroinformatics platform that facilitates the widespread collection and sharing of neuroscience research data for learning health systems.
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Affiliation(s)
| | | | | | - Derek Eng
- Ontario Brain Institute, Toronto, ON, Canada
| | | | | | - Tom Gee
- Indoc Research, Toronto, ON, Canada
| | | | | | - Fan Dong
- Indoc Research, Toronto, ON, Canada
| | | | | | | | | | | | | | | | | | | | - Kirk Nylen
- Ontario Brain Institute, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
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8
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Riek HC, Brien DC, Coe BC, Huang J, Perkins JE, Yep R, McLaughlin PM, Orange JB, Peltsch AJ, Roberts AC, Binns MA, Lou W, Abrahao A, Arnott SR, Beaton D, Black SE, Dowlatshahi D, Finger E, Fischer CE, Frank AR, Grimes DA, Kumar S, Lang AE, Lawrence-Dewar JM, Mandzia JL, Marras C, Masellis M, Pasternak SH, Pollock BG, Rajji TK, Sahlas DJ, Saposnik G, Seitz DP, Shoesmith C, Steeves TDL, Strother SC, Sunderland KM, Swartz RH, Tan B, Tang-Wai DF, Tartaglia MC, Turnbull J, Zinman L, Munoz DP. Cognitive correlates of antisaccade behaviour across multiple neurodegenerative diseases. Brain Commun 2023; 5:fcad049. [PMID: 36970045 PMCID: PMC10036290 DOI: 10.1093/braincomms/fcad049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 12/01/2022] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
Abstract
Oculomotor tasks generate a potential wealth of behavioural biomarkers for neurodegenerative diseases. Overlap between oculomotor and disease-impaired circuitry reveals the location and severity of disease processes via saccade parameters measured from eye movement tasks such as prosaccade and antisaccade. Existing studies typically examine few saccade parameters in single diseases, using multiple separate neuropsychological test scores to relate oculomotor behaviour to cognition; however, this approach produces inconsistent, ungeneralizable results and fails to consider the cognitive heterogeneity of these diseases. Comprehensive cognitive assessment and direct inter-disease comparison are crucial to accurately reveal potential saccade biomarkers.
We remediate these issues by characterizing twelve behavioural parameters, selected to robustly describe saccade behaviour, derived from an interleaved pro- and antisaccade task in a large cross-sectional dataset comprising five disease cohorts (Alzheimer’s disease/mild cognitive impairment, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson’s disease, cerebrovascular disease; n=391, age 40-87) and healthy controls (n=149, age 42-87). These participants additionally completed an extensive neuropsychological test battery. We further subdivided each cohort by diagnostic subgroup (for Alzheimer’s disease/mild cognitive impairment and frontotemporal dementia) or degree of cognitive impairment based on neuropsychological testing (all other cohorts). We sought to understand links between oculomotor parameters, their relationships to robust cognitive measures, and their alterations in disease. We performed a factor analysis evaluating interrelationships among the twelve oculomotor parameters and examined correlations of the four resultant factors to five neuropsychology-based cognitive domain scores. We then compared behaviour between the abovementioned disease subgroups and controls at the individual parameter level.
We theorized that each underlying factor measured the integrity of a distinct task-relevant brain process. Notably, factor 3 (voluntary saccade generation) and factor 1 (task disengagements) significantly correlated with attention/working memory and executive function scores. Factor 3 also correlated with memory and visuospatial function scores. Factor 2 (preemptive global inhibition) correlated only with attention/working memory scores, and factor 4 (saccade metrics) correlated with no cognitive domain scores. Impairment on several mostly antisaccade-related individual parameters scaled with cognitive impairment across disease cohorts, while few subgroups differed from controls on prosaccade parameters.
The interleaved pro- and antisaccade task detects cognitive impairment, and subsets of parameters likely index disparate underlying processes related to different cognitive domains. This suggests that the task represents a sensitive paradigm that can simultaneously evaluate a variety of clinically relevant cognitive constructs in neurodegenerative and cerebrovascular diseases and could be developed into a screening tool applicable to multiple diagnoses.
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Affiliation(s)
- Heidi C Riek
- Correspondence to: Heidi C. Riek Centre for Neuroscience Studies, Queen’s University Botterell Hall, 18 Stuart Street Kingston, ON K7L 3N6, Canada E-mail:
| | - Donald C Brien
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario K7L 3N6Canada
| | - Brian C Coe
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario K7L 3N6Canada
| | - Jeff Huang
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario K7L 3N6Canada
| | - Julia E Perkins
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario K7L 3N6Canada
| | - Rachel Yep
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario K7L 3N6Canada
| | - Paula M McLaughlin
- Nova Scotia Health, Halifax, Nova Scotia B3S 0H6, Canada
- Department of Medicine (Geriatrics), Dalhousie University, Halifax, Nova Scotia B3H 2Y9, Canada
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada
| | - Joseph B Orange
- School of Communication Sciences and Disorders, Faculty of Health Sciences, Western University, London, Ontario N6G 1H1, Canada
- Canadian Centre for Activity and Aging, Faculty of Health Sciences, Western University, London, Ontario N6G 1H1, Canada
| | - Alicia J Peltsch
- Faculty of Engineering and Applied Science, Queen’s University, Kingston Ontario K7L 3N6, Canada
| | - Angela C Roberts
- School of Communication Sciences and Disorders, Faculty of Health Sciences, Western University, London, Ontario N6G 1H1, Canada
- Department of Computer Science, Western University, London, Ontario N6A 5B7, Canada
| | - Malcolm A Binns
- Rotman Research Institute, Baycrest Centre, North York, Ontario M6A 2E1, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario M5T 3M7, Canada
| | - Wendy Lou
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario M5T 3M7, Canada
| | - Agessandro Abrahao
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Ontario M5S 3H2, Canada
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario M4N 3M5, Canada
| | - Stephen R Arnott
- Rotman Research Institute, Baycrest Centre, North York, Ontario M6A 2E1, Canada
| | - Derek Beaton
- Present address: Data Science and Advanced Analytics, St. Michael’s Hospital, Unity Health Toronto, Toronto, Ontario M5B 1W8, Canada
| | - Sandra E Black
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Ontario M5S 3H2, Canada
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario M4N 3M5, Canada
| | - Dar Dowlatshahi
- Department of Medicine (Neurology), University of Ottawa, Ottawa, Ontario K1H 8M5, Canada
- Ottawa Hospital Research Institute, Ottawa, Ontario K1Y 4E9, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada
| | - Corinne E Fischer
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario M5B 1W8, Canada
| | - Andrew R Frank
- Department of Medicine (Neurology), University of Ottawa, Ottawa, Ontario K1H 8M5, Canada
- Bruyere Research Institute, Ottawa, Ontario K1R 6M1, Canada
| | - David A Grimes
- Department of Medicine (Neurology), University of Ottawa, Ottawa, Ontario K1H 8M5, Canada
- Ottawa Hospital Research Institute, Ottawa, Ontario K1Y 4E9, Canada
- University of Ottawa Brain and Mind Research Institute, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada
| | - Sanjeev Kumar
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario M6J 1H4, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Anthony E Lang
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario M5S 3H2, Canada
- Edmond J. Safra Program in Parkinson’s Disease, Toronto Western Hospital, Toronto, Ontario M5T 2S8, Canada
| | - Jane M Lawrence-Dewar
- Thunder Bay Regional Health Research Institute, Thunder Bay, Ontario P7B 7A5, Canada
| | - Jennifer L Mandzia
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada
- London Health Sciences Centre, London, Ontario N6A 5W9, Canada
| | - Connie Marras
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario M5S 3H2, Canada
- Edmond J. Safra Program in Parkinson’s Disease, Toronto Western Hospital, Toronto, Ontario M5T 2S8, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario M4N 3M5, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario M5S 3H2, Canada
- Cognitive and Movement Disorders Clinic, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5, Canada
| | - Stephen H Pasternak
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 5B7, Canada
- Cognitive Neurology and Alzheimer’s Disease Research Centre, Parkwood Institute, St. Joseph’s Health Care, London, Ontario N6A 4V2, Canada
| | - Bruce G Pollock
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario M6J 1H4, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Tarek K Rajji
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Demetrios J Sahlas
- Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, Ontario L8N 3Z5, Canada
| | - Gustavo Saposnik
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario M5S 3H2, Canada
| | - Dallas P Seitz
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Christen Shoesmith
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada
- London Health Sciences Centre, London, Ontario N6A 5W9, Canada
| | - Thomas D L Steeves
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario M5S 3H2, Canada
- Division of Neurology, St. Michael’s Hospital, Toronto, Ontario M5B 1W8, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Centre, North York, Ontario M6A 2E1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
| | - Kelly M Sunderland
- Rotman Research Institute, Baycrest Centre, North York, Ontario M6A 2E1, Canada
| | - Richard H Swartz
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Ontario M5S 3H2, Canada
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario M4N 3M5, Canada
| | - Brian Tan
- Rotman Research Institute, Baycrest Centre, North York, Ontario M6A 2E1, Canada
| | - David F Tang-Wai
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario M5S 3H2, Canada
- University Health Network Memory Clinic, Krembil Brain Institute, Toronto Western Hospital, Toronto, Ontario M5T 2S8, Canada
| | - Maria Carmela Tartaglia
- University Health Network Memory Clinic, Krembil Brain Institute, Toronto Western Hospital, Toronto, Ontario M5T 2S8, Canada
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - John Turnbull
- Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, Ontario L8N 3Z5, Canada
| | - Lorne Zinman
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Ontario M5S 3H2, Canada
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario M4N 3M5, Canada
| | - Douglas P Munoz
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario K7L 3N6Canada
- Department of Biomedical and Molecular Sciences, Queen’s University, Kingston, Ontario K7L 3N6, Canada
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9
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Dhami P, Quilty LC, Schwartzmann B, Uher R, Allen TA, Kloiber S, Lam RW, MacQueen G, Frey BN, Milev R, Müller DJ, Strother SC, Blier P, Soares CN, Parikh SV, Turecki G, Foster JA, Rotzinger S, Kennedy SH, Farzan F. Response Inhibition and Predicting Response to Pharmacological and Cognitive Behavioral Therapy Treatments for Major Depressive Disorder: A Canadian Biomarker Integration Network for Depression Study. Biol Psychiatry Cogn Neurosci Neuroimaging 2023; 8:162-170. [PMID: 35032682 DOI: 10.1016/j.bpsc.2021.12.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 12/11/2021] [Accepted: 12/28/2021] [Indexed: 11/20/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) is associated with various cognitive impairments, including response inhibition. Deficits in response inhibition may also underlie poor antidepressant treatment response. Recent studies revealed that the neurobiological correlates of response inhibition can predict response to pharmacological treatments. However, the generalizability of this finding to first-line nonpharmacological treatments, particularly cognitive behavioral therapy, remains to be investigated. METHODS Data from two independent treatment protocols were combined, one in which 65 patients with MDD underwent treatment with escitalopram, and the other in which 41 patients with MDD underwent a course of cognitive behavioral therapy. A total of 25 healthy control subjects were also recruited. Neural correlates of response inhibition were captured by participants completing a Go/NoGo task during electroencephalography recording. Response inhibition-related measures of interest included the amplitudes of the N2 and P3 event-related potentials. RESULTS Pretreatment P3 amplitude, which has been linked to both the motor and cognitive aspects of response inhibition, was a significant predictor of change in depressive symptoms following escitalopram and cognitive behavioral therapy treatment. A greater pretreatment P3 amplitude was associated with a greater reduction in depressive severity. In addition, the pretreatment P3 amplitude was found to be significantly greater at baseline in remitters than in nonremitters and healthy control subjects. CONCLUSIONS The integrity of response inhibition may be critical for a successful course of pharmacological or psychological treatment for MDD. Electrophysiological correlates of response inhibition may have utility as a general prognostic marker of treatment response in MDD. Future studies may investigate the benefit of preceding first-line treatments with interventions that improve response inhibition in MDD.
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Affiliation(s)
- Prabhjot Dhami
- eBrain Lab, Simon Fraser University, Surrey, British Columbia, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Lena C Quilty
- Department of Psychology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | | | - Rudolf Uher
- Department of Psychiatry, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Timothy A Allen
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Stefan Kloiber
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Raymond W Lam
- Department of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Glenda MacQueen
- Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Benicio N Frey
- Mood Disorders Program and Women's Health Concerns Clinic, St Joseph's Healthcare, Hamilton, Ontario, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, Providence Care, Kingston, Ontario, Canada
| | - Daniel J Müller
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | | | - Pierre Blier
- Mood Disorders Research Unit, University of Ottawa Institute of Mental Health Research, Ottawa, Ontario, Canada
| | - Claudio N Soares
- Departments of Psychiatry and Psychology, Queen's University, Providence Care, Kingston, Ontario, Canada
| | - Sagar V Parikh
- University of Michigan Depression Center, Ann Arbor, Michigan
| | - Gustavo Turecki
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Jane A Foster
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Susan Rotzinger
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, Ontario, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, Ontario, Canada
| | - Faranak Farzan
- eBrain Lab, Simon Fraser University, Surrey, British Columbia, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
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10
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Fu CHY, Erus G, Fan Y, Antoniades M, Arnone D, Arnott SR, Chen T, Choi KS, Fatt CC, Frey BN, Frokjaer VG, Ganz M, Garcia J, Godlewska BR, Hassel S, Ho K, McIntosh AM, Qin K, Rotzinger S, Sacchet MD, Savitz J, Shou H, Singh A, Stolicyn A, Strigo I, Strother SC, Tosun D, Victor TA, Wei D, Wise T, Woodham RD, Zahn R, Anderson IM, Deakin JFW, Dunlop BW, Elliott R, Gong Q, Gotlib IH, Harmer CJ, Kennedy SH, Knudsen GM, Mayberg HS, Paulus MP, Qiu J, Trivedi MH, Whalley HC, Yan CG, Young AH, Davatzikos C. AI-based dimensional neuroimaging system for characterizing heterogeneity in brain structure and function in major depressive disorder: COORDINATE-MDD consortium design and rationale. BMC Psychiatry 2023; 23:59. [PMID: 36690972 PMCID: PMC9869598 DOI: 10.1186/s12888-022-04509-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 12/29/2022] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states. METHODS We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants. RESULTS We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites. CONCLUSION We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.
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Affiliation(s)
- Cynthia H Y Fu
- Department of Psychological Sciences, University of East London, London, UK.
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.
| | - Guray Erus
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Yong Fan
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Mathilde Antoniades
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Danilo Arnone
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- Department of Psychiatry and Behavioral Science, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | | | - Taolin Chen
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ki Sueng Choi
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Cherise Chin Fatt
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, USA
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada
- Mood Disorders Treatment and Research Centre and Women's Health Concerns Clinic, St Joseph's Healthcare Hamilton, Hamilton, Canada
| | - Vibe G Frokjaer
- Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Psychiatry, Psychiatric Centre Copenhagen, Copenhagen, Denmark
| | - Melanie Ganz
- Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Jose Garcia
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Beata R Godlewska
- Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Stefanie Hassel
- Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, Canada
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Keith Ho
- Department of Psychiatry, University Health Network, Toronto, Canada
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Kun Qin
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Susan Rotzinger
- Department of Psychiatry, University Health Network, Toronto, Canada
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, Canada
| | - Matthew D Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | | | - Haochang Shou
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE) Center, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, USA
| | - Ashish Singh
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Aleks Stolicyn
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Irina Strigo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Centre, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | | | - Dongtao Wei
- School of Psychology, Southwest University, Chongqing, China
| | - Toby Wise
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Rachel D Woodham
- Department of Psychological Sciences, University of East London, London, UK
| | - Roland Zahn
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Ian M Anderson
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - J F William Deakin
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Boadie W Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, USA
| | - Rebecca Elliott
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ian H Gotlib
- Department of Psychology, Stanford University, Stanford, USA
| | | | - Sidney H Kennedy
- Department of Psychiatry, University Health Network, Toronto, Canada
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, Canada
- Unity Health Toronto, Toronto, Canada
| | - Gitte M Knudsen
- Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Helen S Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, USA
| | | | - Jiang Qiu
- School of Psychology, Southwest University, Chongqing, China
| | - Madhukar H Trivedi
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, USA
| | - Heather C Whalley
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
| | - Allan H Young
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, London, UK
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
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11
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Magarbeh L, Hassel C, Choi M, Islam F, Marshe VS, Zai CC, Zuberi R, Gammal RS, Men X, Scherf-Clavel M, Enko D, Frey BN, Milev R, Soares CN, Parikh SV, Placenza F, Strother SC, Hassel S, Taylor VH, Leri F, Blier P, Farzan F, Lam RW, Turecki G, Foster JA, Rotzinger S, Kloiber S, Kennedy JL, Kennedy SH, Bousman CA, Müller DJ. ABCB1 Gene Variants and Antidepressant Treatment Outcomes: A Systematic Review and Meta-Analysis Including Results from the CAN-BIND-1 Study. Clin Pharmacol Ther 2023. [PMID: 36681895 DOI: 10.1002/cpt.2854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 01/06/2023] [Indexed: 01/23/2023]
Abstract
The P-glycoprotein efflux pump, encoded by the ABCB1 gene, has been shown to alter concentrations of various antidepressants in the brain. In this study, we conducted a systematic review and meta-analysis to investigate the association between six ABCB1 single-nucleotide polymorphisms (SNPs; rs1045642, rs2032582, rs1128503, rs2032583, rs2235015, and rs2235040) and antidepressant treatment outcomes in individuals with major depressive disorder (MDD), including new data from the Canadian Biomarker and Integration Network for Depression (CAN-BIND-1) cohort. For the CAN-BIND-1 sample, we applied regression models to investigate the association between ABCB1 SNPs and antidepressant treatment response, remission, tolerability, and antidepressant serum levels. For the meta-analysis, we systematically summarized pharmacogenetic evidence of the association between ABCB1 SNPs and antidepressant treatment outcomes. Studies were included in the meta-analysis if they investigated at least one ABCB1 SNP in individuals with MDD treated with at least one antidepressant. We did not find a significant association between ABCB1 SNPs and antidepressant treatment outcomes in the CAN-BIND-1 sample. A total of 39 studies were included in the systematic review. In the meta-analysis, we observed a significant association between rs1128503 and treatment response (T vs. C-allele, odds ratio = 1.30, 95% confidence interval = 1.15-1.48, P value (adjusted) = 0.024, n = 2,526). We did not find associations among the six SNPs and treatment remission nor tolerability. Our findings provide limited evidence for an association between common ABCB1 SNPs and antidepressant outcomes, which do not support the implementation of ABCB1 genotyping to inform antidepressant treatment at this time. Future research, especially on rs1128503, is recommended.
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Affiliation(s)
- Leen Magarbeh
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Claudia Hassel
- Department of Life Sciences, Queen's University, Kingston, Ontario, Canada.,Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada
| | - Maximilian Choi
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Farhana Islam
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Victoria S Marshe
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Center for Translational and Computational Neuroimmunology, Columbia University Medical Center, New York, New York, USA
| | - Clement C Zai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Rayyan Zuberi
- Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada
| | - Roseann S Gammal
- Massachusetts College of Pharmacy and Health Sciences, Boston, Massachusetts, USA
| | - Xiaoyu Men
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Maike Scherf-Clavel
- Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, Würzburg, Germany
| | - Dietmar Enko
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Mood Disorders Program, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
| | - Roumen Milev
- Department of Psychiatry, Queen's University, Providence Care, Kingston, Ontario, Canada
| | - Claudio N Soares
- Department of Psychiatry, Queen's University, Providence Care, Kingston, Ontario, Canada
| | - Sagar V Parikh
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Franca Placenza
- Centre for Mental Health, University Health Network, Toronto, Ontario, Canada
| | | | - Stefanie Hassel
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada.,Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Valerie H Taylor
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Francesco Leri
- Department of Psychology and Neuroscience, University of Guelph, Guelph, Ontario, Canada
| | - Pierre Blier
- The Royal Institute of Mental Health Research, Ottawa, Ontario, Canada
| | - Faranak Farzan
- Mechatronic Systems Engineering, Simon Fraser University, Surrey, British Columbia, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Gustavo Turecki
- McGill Group for Suicide Studies, Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada
| | - Jane A Foster
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Centre for Mental Health, University Health Network, Toronto, Ontario, Canada.,Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Susan Rotzinger
- Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Stefan Kloiber
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - James L Kennedy
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Sidney H Kennedy
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Centre for Mental Health, University Health Network, Toronto, Ontario, Canada.,Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.,Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Chad A Bousman
- Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada.,Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada.,Department of Physiology and Pharmacology, University of Calgary, Calgary, Alberta, Canada
| | - Daniel J Müller
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, Würzburg, Germany
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12
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Ballester PL, Suh JS, Ho NCW, Liang L, Hassel S, Strother SC, Arnott SR, Minuzzi L, Sassi RB, Lam RW, Milev R, Müller DJ, Taylor VH, Kennedy SH, Reilly JP, Palaniyappan L, Dunlop K, Frey BN. Gray matter volume drives the brain age gap in schizophrenia: a SHAP study. Schizophrenia (Heidelb) 2023; 9:3. [PMID: 36624107 PMCID: PMC9829754 DOI: 10.1038/s41537-022-00330-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 12/28/2022] [Indexed: 01/11/2023]
Abstract
Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term β = 1.71 [0.53; 3.23]; pcorr < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.
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Affiliation(s)
- Pedro L. Ballester
- grid.25073.330000 0004 1936 8227Neuroscience Graduate Program, McMaster University, Hamilton, ON Canada
| | - Jee Su Suh
- grid.25073.330000 0004 1936 8227Neuroscience Graduate Program, McMaster University, Hamilton, ON Canada
| | - Natalie C. W. Ho
- grid.17063.330000 0001 2157 2938Faculty of Arts & Science, University of Toronto, Toronto, ON Canada ,grid.415502.7Keenan Research Centre for Biomedical Science, Unity Health Toronto, Toronto, Canada
| | - Liangbing Liang
- grid.39381.300000 0004 1936 8884Graduate Program in Neuroscience, Western University, London, ON Canada ,grid.39381.300000 0004 1936 8884Robarts Research Institute, Western University, London, ON Canada
| | - Stefanie Hassel
- grid.22072.350000 0004 1936 7697Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB Canada
| | - Stephen C. Strother
- grid.17063.330000 0001 2157 2938Rotman Research Institute, Baycrest, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Medical Biophysics, University of Toronto, Toronto, ON Canada
| | - Stephen R. Arnott
- grid.17063.330000 0001 2157 2938Rotman Research Institute, Baycrest, Toronto, ON Canada
| | - Luciano Minuzzi
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, Hamilton, ON Canada ,grid.416721.70000 0001 0742 7355Women’s Health Concerns Clinic, St. Joseph’s Healthcare Hamilton, Hamilton, ON Canada
| | - Roberto B. Sassi
- grid.17091.3e0000 0001 2288 9830Department of Psychiatry, University of British Columbia, Vancouver, BC Canada
| | - Raymond W. Lam
- grid.17091.3e0000 0001 2288 9830Department of Psychiatry, University of British Columbia, Vancouver, BC Canada
| | - Roumen Milev
- grid.410356.50000 0004 1936 8331Departments of Psychiatry and Psychology, Queen’s University, and Providence Care, Kingston, ON Canada
| | - Daniel J. Müller
- grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada
| | - Valerie H. Taylor
- grid.22072.350000 0004 1936 7697Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB Canada
| | - Sidney H. Kennedy
- grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428Centre for Mental Health, University Health Network, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428Krembil Research Institute, University Health Network, Toronto, ON Canada ,grid.415502.7Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON Canada
| | - James P. Reilly
- grid.25073.330000 0004 1936 8227Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON Canada
| | - Lena Palaniyappan
- grid.39381.300000 0004 1936 8884Robarts Research Institute, Western University, London, ON Canada ,grid.39381.300000 0004 1936 8884Department of Medical Biophysics, Western University, London, ON Canada ,grid.415847.b0000 0001 0556 2414Lawson Health Research Institute, London, ON Canada ,grid.39381.300000 0004 1936 8884Department of Psychiatry, Western University, London, ON Canada ,grid.14709.3b0000 0004 1936 8649Department of Psychiatry, Douglas Mental Health University Institute, McGill, Douglas, QC Canada
| | - Katharine Dunlop
- grid.415502.7Keenan Research Centre for Biomedical Science, Unity Health Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,Centre for Depression & Suicide Studies, Unity Health Toronto, Toronto, ON Canada
| | - Benicio N. Frey
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, Hamilton, ON Canada ,grid.416721.70000 0001 0742 7355Women’s Health Concerns Clinic, St. Joseph’s Healthcare Hamilton, Hamilton, ON Canada ,grid.25073.330000 0004 1936 8227Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON Canada
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13
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Sunderland KM, Beaton D, Arnott SR, Kleinstiver P, Kwan D, Lawrence-Dewar JM, Ramirez J, Tan B, Bartha R, Black SE, Borrie M, Brien D, Casaubon LK, Coe BC, Cornish B, Dilliott AA, Dowlatshahi D, Finger E, Fischer C, Frank A, Fraser J, Freedman M, Greenberg B, Grimes DA, Hassan A, Hatch W, Hegele RA, Hudson C, Jog M, Kumar S, Lang A, Levine B, Lou W, Mandzia J, Marras C, McIlroy W, Montero-Odasso M, Munoz DG, Munoz DP, Orange JB, Park DS, Pasternak SH, Pieruccini-Faria F, Rajji TK, Roberts AC, Robinson JF, Rogaeva E, Sahlas DJ, Saposnik G, Scott CJM, Seitz D, Shoesmith C, Steeves TDL, Strong MJ, Strother SC, Swartz RH, Symons S, Tang-Wai DF, Tartaglia MC, Troyer AK, Turnbull J, Zinman L, McLaughlin PM, Masellis M, Binns MA, Adamo S, Berezuk C, Black A, Breen DP, Bulman D, Chen Y, El‐Defrawy S, Farhan S, Ghani M, Gonder J, Haddad SMH, Holmes M, Huang J, Leontieva E, Mandelcorn E, Margolin E, Nanayakkara N, Ozzoude M, Peltsch AJ, Pollock B, Raamana P, Rashkovan N, Yanina, Southwell A, Sujanthan S, Tayyari F, Van Ooteghem K, Woulfe J, Zamyadi M, Zou G. Characteristics of the Ontario Neurodegenerative Disease Research Initiative cohort. Alzheimers Dement 2023; 19:226-243. [PMID: 36318754 DOI: 10.1002/alz.12632] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 12/01/2021] [Accepted: 12/17/2021] [Indexed: 01/18/2023]
Abstract
INTRODUCTION Understanding synergies between neurodegenerative and cerebrovascular pathologies that modify dementia presentation represents an important knowledge gap. METHODS This multi-site, longitudinal, observational cohort study recruited participants across prevalent neurodegenerative diseases and cerebrovascular disease and assessed participants comprehensively across modalities. We describe univariate and multivariate baseline features of the cohort and summarize recruitment, data collection, and curation processes. RESULTS We enrolled 520 participants across five neurodegenerative and cerebrovascular diseases. Median age was 69 years, median Montreal Cognitive Assessment score was 25, median independence in activities of daily living was 100% for basic and 93% for instrumental activities. Spousal study partners predominated; participants were often male, White, and more educated. Milder disease stages predominated, yet cohorts reflect clinical presentation. DISCUSSION Data will be shared with the global scientific community. Within-disease and disease-agnostic approaches are expected to identify markers of severity, progression, and therapy targets. Sampling characteristics also provide guidance for future study design.
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Affiliation(s)
- Kelly M Sunderland
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Stephen R Arnott
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Peter Kleinstiver
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada
| | | | - Joel Ramirez
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Brian Tan
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Robert Bartha
- Robarts Research Institute, Western University, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Sandra E Black
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada
| | - Michael Borrie
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,St. Joseph's Healthcare Centre, London, Ontario, Canada
| | - Donald Brien
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada
| | - Leanne K Casaubon
- Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada.,Toronto Western Hospital, Toronto, Ontario, Canada
| | - Brian C Coe
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada
| | - Benjamin Cornish
- Department of Kinesiology, University of Waterloo, Waterloo, Ontario, Canada
| | - Allison A Dilliott
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Robarts Research Institute, Western University, London, Ontario, Canada
| | - Dar Dowlatshahi
- Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Elizabeth Finger
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Lawson Health Research Institute, London, Ontario, Canada
| | - Corinne Fischer
- Keenan Research Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Andrew Frank
- Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada.,Bruyère Research Institute, Ottawa, Ontario, Canada
| | - Julia Fraser
- Department of Kinesiology, University of Waterloo, Waterloo, Ontario, Canada
| | - Morris Freedman
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada.,Division of Neurology, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Barry Greenberg
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - David A Grimes
- Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Ayman Hassan
- Thunder Bay Regional Health Research Institute, Thunder Bay, Ontario, Canada
| | - Wendy Hatch
- Kensington Eye Institute, Toronto, Ontario, Canada.,Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Robert A Hegele
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Robarts Research Institute, Western University, London, Ontario, Canada
| | - Christopher Hudson
- Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, Ontario, Canada.,School of Optometry and Vision Science, University of Waterloo, Waterloo, Ontario, Canada
| | - Mandar Jog
- London Health Sciences Centre, London, Ontario, Canada
| | - Sanjeev Kumar
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Anthony Lang
- Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Centre, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Brian Levine
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada.,Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Wendy Lou
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Jennifer Mandzia
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Department of Clinical Neurological Sciences, London Health Sciences Centre, London, Ontario, Canada
| | - Connie Marras
- Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Centre, Toronto Western Hospital, Toronto, Ontario, Canada
| | - William McIlroy
- Department of Kinesiology, University of Waterloo, Waterloo, Ontario, Canada
| | - Manuel Montero-Odasso
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Lawson Health Research Institute, London, Ontario, Canada.,Gait and Brain Lab, Parkwood Institute, London, Ontario, Canada
| | - David G Munoz
- Keenan Research Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Douglas P Munoz
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada
| | - Joseph B Orange
- School of Communication Sciences and Disorders, Elborn College, Western University, London, Ontario, Canada
| | - David S Park
- Hotchkiss Brain Institute, Calgary, Alberta, Canada.,Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Stephen H Pasternak
- St. Joseph's Healthcare Centre, London, Ontario, Canada.,Cognitive Neurology and Alzheimer's Disease Research Centre, Parkwood Institute, London, Ontario, Canada
| | - Frederico Pieruccini-Faria
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Lawson Health Research Institute, London, Ontario, Canada.,Gait and Brain Lab, Parkwood Institute, London, Ontario, Canada
| | - Tarek K Rajji
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Angela C Roberts
- School of Communication Sciences and Disorders, Elborn College, Western University, London, Ontario, Canada.,Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois, USA
| | - John F Robinson
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Robarts Research Institute, Western University, London, Ontario, Canada
| | - Ekaterina Rogaeva
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Ontario, Canada
| | | | - Gustavo Saposnik
- Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada.,Keenan Research Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Christopher J M Scott
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Dallas Seitz
- Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | | | | | - Michael J Strong
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Canadian Institutes for Health Research, Ottawa, Ontario, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Richard H Swartz
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada
| | - Sean Symons
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - David F Tang-Wai
- Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Angela K Troyer
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada.,Neuropsychology and Cognitive Health, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - John Turnbull
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Lorne Zinman
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada
| | - Paula M McLaughlin
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada.,Nova Scotia Health, Halifax, Nova Scotia, Canada
| | - Mario Masellis
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada
| | - Malcolm A Binns
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
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14
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Haddad SMH, Scott CJM, Ozzoude M, Berezuk C, Holmes M, Adamo S, Ramirez J, Arnott SR, Nanayakkara ND, Binns M, Beaton D, Lou W, Sunderland K, Sujanthan S, Lawrence J, Kwan D, Tan B, Casaubon L, Mandzia J, Sahlas D, Saposnik G, Hassan A, Levine B, McLaughlin P, Orange JB, Roberts A, Troyer A, Black SE, Dowlatshahi D, Strother SC, Swartz RH, Symons S, Montero-Odasso M, ONDRI Investigators, Bartha R. Comparison of Diffusion Tensor Imaging Metrics in Normal-Appearing White Matter to Cerebrovascular Lesions and Correlation with Cerebrovascular Disease Risk Factors and Severity. Int J Biomed Imaging 2022; 2022:5860364. [PMID: 36313789 PMCID: PMC9616672 DOI: 10.1155/2022/5860364] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 04/21/2022] [Accepted: 06/01/2022] [Indexed: 11/13/2023] Open
Abstract
Alterations in tissue microstructure in normal-appearing white matter (NAWM), specifically measured by diffusion tensor imaging (DTI) fractional anisotropy (FA), have been associated with cognitive outcomes following stroke. The purpose of this study was to comprehensively compare conventional DTI measures of tissue microstructure in NAWM to diverse vascular brain lesions in people with cerebrovascular disease (CVD) and to examine associations between FA in NAWM and cerebrovascular risk factors. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were measured in cerebral tissues and cerebrovascular anomalies from 152 people with CVD participating in the Ontario Neurodegenerative Disease Research Initiative (ONDRI). Ten cerebral tissue types were segmented including NAWM, and vascular lesions including stroke, periventricular and deep white matter hyperintensities, periventricular and deep lacunar infarcts, and perivascular spaces (PVS) using T1-weighted, proton density-weighted, T2-weighted, and fluid attenuated inversion recovery MRI scans. Mean DTI metrics were measured in each tissue region using a previously developed DTI processing pipeline and compared between tissues using multivariate analysis of covariance. Associations between FA in NAWM and several CVD risk factors were also examined. DTI metrics in vascular lesions differed significantly from healthy tissue. Specifically, all tissue types had significantly different MD values, while FA was also found to be different in most tissue types. FA in NAWM was inversely related to hypertension and modified Rankin scale (mRS). This study demonstrated the differences between conventional DTI metrics, FA, MD, AD, and RD, in cerebral vascular lesions and healthy tissue types. Therefore, incorporating DTI to characterize the integrity of the tissue microstructure could help to define the extent and severity of various brain vascular anomalies. The association between FA within NAWM and clinical evaluation of hypertension and disability provides further evidence that white matter microstructural integrity is impacted by cerebrovascular function.
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Affiliation(s)
- Seyyed M. H. Haddad
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Canada
| | - Christopher J. M. Scott
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | - Miracle Ozzoude
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | | | - Melissa Holmes
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | - Sabrina Adamo
- Clinical Neurosciences, University of Toronto, Toronto, Canada
| | - Joel Ramirez
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | - Stephen R. Arnott
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Nuwan D. Nanayakkara
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Canada
| | - Malcolm Binns
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Wendy Lou
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Kelly Sunderland
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | | | - Jane Lawrence
- Thunder Bay Regional Health Research Institute, Thunder Bay, Canada
| | | | - Brian Tan
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Leanne Casaubon
- Department of Medicine, University of Toronto, Toronto, Canada
| | - Jennifer Mandzia
- Department of Medicine, Division of Neurology, University of Western Ontario, London, Canada
| | - Demetrios Sahlas
- Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | | | - Ayman Hassan
- Thunder Bay Regional Research Institute, Thunder Bay, Canada
| | - Brian Levine
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | | | - J. B. Orange
- School of Communication Sciences and Disorders, Western University, London, Canada
| | - Angela Roberts
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorder, Northwestern University, Evanston, USA
| | - Angela Troyer
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Sandra E. Black
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
- Sunnybrook Health Sciences Centre, University of Toronto, Stroke Research Program, Toronto, Canada
| | | | - Stephen C. Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Richard H. Swartz
- Sunnybrook Health Sciences Centre, University of Toronto, Stroke Research Program, Toronto, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Manuel Montero-Odasso
- Department of Medicine, Division of Geriatric Medicine, Parkwood Hospital, St. Joseph's Health Care London, London, Canada
| | - ONDRI Investigators
- Ontario Neurodegenerative Disease Initiative, Ontario Brain Institute, Toronto, Canada
| | - Robert Bartha
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Canada
- Department of Medical Biophysics, University of Western Ontario, London, Canada
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15
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Ali M, Suh JS, Ramonas M, Hassel S, Arnott SR, Strother SC, Minuzzi L, Sassi RB, Lam RW, Milev R, Müller DJ, Taylor VH, Kennedy SH, Frey BN. A detailed manual segmentation procedure for the hypothalamus for 3T T1-weighted MRI. MethodsX 2022; 9:101864. [PMID: 36193115 PMCID: PMC9526169 DOI: 10.1016/j.mex.2022.101864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 09/13/2022] [Indexed: 10/31/2022] Open
Abstract
The hypothalamus is a small grey matter structure which plays a crucial role in many physiological functions. Some studies have found an association between hypothalamic volume and psychopathology, which stresses the need for a standardized method to maximize segmentation accuracy. Here, we provide a detailed step-by-step method outlining the procedures to manually segment the hypothalamus using anatomical T1w images from 3T scanners, which many neuroimaging studies collect as a standard anatomical reference image. We compared volumes generated by manual segmentation and those generated by an automatic algorithm, observing a significant difference between automatically and manually segmented hypothalamus volumes on both sides (left: U = 222842, p-value < 2.2e-16; right: U = 218520, p- value < 2.2e-16).•Significant difference exists between existing automatic segmentation methods and the manual segmentation procedure.•We discuss potential drift effects, segmentation quality issues, and suggestions on how to mitigate them.•We demonstrate that the present manual segmentation procedure using standard T1-weighted MRI may be significantly more accurate than automatic segmentation outputs.
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Affiliation(s)
- Mohammad Ali
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada
| | - Jee Su Suh
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Milita Ramonas
- Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, Hamilton, ON, Canada
| | - Stefanie Hassel
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | | | | | - Luciano Minuzzi
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.,Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
| | - Roberto B Sassi
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, and Providence Care Hospital, Kingston, ON, Canada
| | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Valerie H Taylor
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Sidney H Kennedy
- Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto ON, Canada
| | - Benicio N Frey
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.,Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
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16
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Islam F, Marshe VS, Magarbeh L, Frey BN, Milev RV, Soares CN, Parikh SV, Placenza F, Strother SC, Hassel S, Taylor VH, Leri F, Blier P, Uher R, Farzan F, Lam RW, Turecki G, Foster JA, Rotzinger S, Kennedy SH, Müller DJ. Effects of CYP2C19 and CYP2D6 gene variants on escitalopram and aripiprazole treatment outcome and serum levels: results from the CAN-BIND 1 study. Transl Psychiatry 2022; 12:366. [PMID: 36068210 PMCID: PMC9448818 DOI: 10.1038/s41398-022-02124-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 08/16/2022] [Accepted: 08/18/2022] [Indexed: 11/25/2022] Open
Abstract
Cytochrome P450 drug-metabolizing enzymes may contribute to interindividual differences in antidepressant outcomes. We investigated the effects of CYP2C19 and CYP2D6 gene variants on response, tolerability, and serum concentrations. Patients (N = 178) were treated with escitalopram (ESC) from weeks 0-8 (Phase I), and at week 8, either continued ESC if they were responders or were augmented with aripiprazole (ARI) if they were non-responders (<50% reduction in Montgomery-Åsberg Depression Rating Scale from baseline) for weeks 8-16 (Phase II). Our results showed that amongst patients on ESC-Only, CYP2C19 intermediate and poor metabolizers (IM + PMs), with reduced or null enzyme function, trended towards significantly lower symptom improvement during Phase II compared to normal metabolizers (NMs), which was not observed in ESC + ARI. We further showed that CYP2D6 NMs and IM + PMs had a higher likelihood of reporting a treatment-related central nervous system side effect in ESC-Only and ESC + ARI, respectively. The differences in the findings between ESC-Only and ESC + ARI may be due to the altered pharmacokinetics of ESC by ARI coadministration in ESC + ARI. We provided evidence for this postulation when we showed that in ESC-Only, CYP2C19 and CYP2D6 IM + PMs demonstrated significantly higher ESC concentrations at Weeks 10 and 16 compared to NMs. In contrast, ESC + ARI showed an association with CYP2C19 but not with CYP2D6 metabolizer group. Instead, ESC + ARI showed an association between CYP2D6 metabolizer group and ARI metabolite-to-drug ratio suggesting potential competition between ESC and ARI for CYP2D6. Our findings suggest that dosing based on CYP2C19 and CYP2D6 genotyping could improve safety and outcome in patients on ESC monotherapy.
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Affiliation(s)
- Farhana Islam
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON Canada
| | - Victoria S. Marshe
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada
| | - Leen Magarbeh
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON Canada
| | - Benicio N. Frey
- grid.25073.330000 0004 1936 8227Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON Canada ,grid.416721.70000 0001 0742 7355St. Joseph’s Healthcare Hamilton, Hamilton, ON Canada
| | - Roumen V. Milev
- grid.410356.50000 0004 1936 8331Department of Psychiatry, Queen’s University, Providence Care, Kingston, ON Canada
| | - Claudio N. Soares
- grid.410356.50000 0004 1936 8331Department of Psychiatry, Queen’s University, Providence Care, Kingston, ON Canada
| | - Sagar V. Parikh
- grid.214458.e0000000086837370Department of Psychiatry, University of Michigan, Ann Arbor, MI USA
| | - Franca Placenza
- grid.231844.80000 0004 0474 0428Centre for Mental Health, University Health Network, Toronto, ON Canada
| | - Stephen C. Strother
- grid.17063.330000 0001 2157 2938Rotman Research Institute, Baycrest Medical Centre, and Medical Biophysics, University of Toronto, Toronto, ON Canada
| | - Stefanie Hassel
- grid.22072.350000 0004 1936 7697Department of Psychiatry, University of Calgary, Calgary, AB Canada
| | - Valerie H. Taylor
- grid.22072.350000 0004 1936 7697Department of Psychiatry, University of Calgary, Calgary, AB Canada
| | - Francesco Leri
- grid.34429.380000 0004 1936 8198Department of Psychology and Neuroscience, University of Guelph, Guelph, ON Canada
| | - Pierre Blier
- grid.414622.70000 0001 1503 7525The Royal Institute of Mental Health Research, Ottawa, ON Canada
| | - Rudolf Uher
- grid.55602.340000 0004 1936 8200Department of Psychiatry, Dalhousie University, Halifax, NS Canada
| | - Faranak Farzan
- grid.61971.380000 0004 1936 7494Mechatronic Systems Engineering, Simon Fraser University, Surrey, BC Canada
| | - Raymond W. Lam
- grid.17091.3e0000 0001 2288 9830University of British Columbia and Vancouver Coastal Health Authority, Vancouver, BC Canada
| | - Gustavo Turecki
- grid.14709.3b0000 0004 1936 8649McGill Group for Suicide Studies, Douglas Mental Health University Institute, McGill University, Verdun, QC Canada
| | - Jane A. Foster
- grid.25073.330000 0004 1936 8227Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON Canada ,grid.416721.70000 0001 0742 7355St. Joseph’s Healthcare Hamilton, Hamilton, ON Canada ,grid.231844.80000 0004 0474 0428Centre for Mental Health, University Health Network, Toronto, ON Canada
| | - Susan Rotzinger
- grid.17063.330000 0001 2157 2938Department of Psychiatry, St Michael’s Hospital, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Sidney H. Kennedy
- grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428Centre for Mental Health, University Health Network, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, St Michael’s Hospital, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,grid.415502.7Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael’s Hospital, Toronto, ON Canada
| | - Daniel J. Müller
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,grid.411760.50000 0001 1378 7891Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Clinic of Würzburg, Würzburg, Germany
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Matthews DC, Lukic AS, Andrews RD, Wernick MN, Strother SC, Schmidt ME. Measurement of neurodegeneration using a multivariate early frame amyloid PET classifier. Alzheimers Dement (N Y) 2022; 8:e12325. [PMID: 35846158 PMCID: PMC9270637 DOI: 10.1002/trc2.12325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 03/28/2022] [Accepted: 06/01/2022] [Indexed: 11/18/2022]
Abstract
Introduction Amyloid measurement provides important confirmation of pathology for Alzheimer's disease (AD) clinical trials. However, many amyloid positive (Am+) early-stage subjects do not worsen clinically during a clinical trial, and a neurodegenerative measure predictive of decline could provide critical information. Studies have shown correspondence between perfusion measured by early amyloid frames post-tracer injection and fluorodeoxyglucose (FDG) positron emission tomography (PET), but with limitations in sensitivity. Multivariate machine learning approaches may offer a more sensitive means for detection of disease related changes as we have demonstrated with FDG. Methods Using summed dynamic florbetapir image frames acquired during the first 6 minutes post-injection for 107 Alzheimer's Disease Neuroimaging Initiative subjects, we applied optimized machine learning to develop and test image classifiers aimed at measuring AD progression. Early frame amyloid (EFA) classification was compared to that of an independently developed FDG PET AD progression classifier by scoring the FDG scans of the same subjects at the same time point. Score distributions and correlation with clinical endpoints were compared to those obtained from FDG. Region of interest measures were compared between EFA and FDG to further understand discrimination performance. Results The EFA classifier produced a primary pattern similar to that of the FDG classifier whose expression correlated highly with the FDG pattern (R-squared 0.71), discriminated cognitively normal (NL) amyloid negative (Am-) subjects from all Am+ groups, and that correlated in Am+ subjects with Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale-13-item Cognitive subscale (R = 0.59, 0.63, 0.73) and with subsequent 24-month changes in these measures (R = 0.67, 0.73, 0.50). Discussion Our results support the ability to use EFA with a multivariate machine learning-derived classifier to obtain a sensitive measure of AD-related loss in neuronal function that correlates with FDG PET in preclinical and early prodromal stages as well as in late mild cognitive impairment and dementia. Highlights The summed initial post-injection minutes of florbetapir positron emission tomography correlate with fluorodeoxyglucose.A machine learning classifier enabled sensitive detection of early prodromal Alzheimer's disease.Early frame amyloid (EFA) classifier scores correlate with subsequent change in Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale-13-item Cognitive subscale.EFA classifier effect sizes and clinical prediction outperformed region of interest standardized uptake value ratio.EFA classification may aid in stratifying patients to assess treatment effect.
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Affiliation(s)
| | | | | | | | - Stephen C. Strother
- Baycrest Hospitaland Department of Medical BiophysicsUniversity of TorontoNorth YorkOntarioCanada
| | - Mark E. Schmidt
- Janssen Research and DevelopmentDivision of Janssen PharmaceuticaBeerseBelgium
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18
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Nanayakkara ND, Arnott SR, Scott CJM, Solovey I, Liang S, Fonov VS, Gee T, Broberg DN, Haddad SMH, Ramirez J, Berezuk C, Holmes M, Adamo S, Ozzoude M, Theyers A, Sujanthan S, Zamyadi M, Casaubon L, Dowlatshahi D, Mandzia J, Sahlas D, Saposnik G, Hassan A, Swartz RH, Strother SC, Szilagyi GM, Black SE, Symons S, Investigators ONDRI, Bartha R. Increased brain volumetric measurement precision from multi-site 3D T1-weighted 3 T magnetic resonance imaging by correcting geometric distortions. Magn Reson Imaging 2022; 92:150-160. [PMID: 35753643 DOI: 10.1016/j.mri.2022.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Revised: 04/29/2022] [Accepted: 06/19/2022] [Indexed: 11/16/2022]
Abstract
PURPOSE Magnetic resonance imaging (MRI) scanner-specific geometric distortions may contribute to scanner induced variability and decrease volumetric measurement precision for multi-site studies. The purpose of this study was to determine whether geometric distortion correction increases the precision of brain volumetric measurements in a multi-site multi-scanner study. METHODS Geometric distortion variation was quantified over a one-year period at 10 sites using the distortion fields estimated from monthly 3D T1-weighted MRI geometrical phantom scans. The variability of volume and distance measurements were quantified using synthetic volumes and a standard quantitative MRI (qMRI) phantom. The effects of geometric distortion corrections on MRI derived volumetric measurements of the human brain were assessed in two subjects scanned on each of the 10 MRI scanners and in 150 subjects with cerebrovascaular disease (CVD) acquired across imaging sites. RESULTS Geometric distortions were found to vary substantially between different MRI scanners but were relatively stable on each scanner over a one-year interval. Geometric distortions varied spatially, increasing in severity with distance from the magnet isocenter. In measurements made with the qMRI phantom, the geometric distortion correction decreased the standard deviation of volumetric assessments by 35% and distance measurements by 42%. The average coefficient of variance decreased by 16% in gray matter and white matter volume estimates in the two subjects scanned on the 10 MRI scanners. CONCLUSION Geometric distortion correction using an up-to-date correction field is recommended to increase precision in volumetric measurements made from MRI images.
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Affiliation(s)
- Nuwan D Nanayakkara
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - Christopher J M Scott
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Igor Solovey
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Shuai Liang
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada
| | - Vladimir S Fonov
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Tom Gee
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada
| | - Dana N Broberg
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Seyyed M H Haddad
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Joel Ramirez
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Courtney Berezuk
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Melissa Holmes
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Sabrina Adamo
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Miracle Ozzoude
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Athena Theyers
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada
| | | | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada
| | - Leanne Casaubon
- Department of Medicine, University of Toronto, Toronto, ON, Canada
| | | | - Jennifer Mandzia
- Department of Medicine, Division of Neurology, Western University, London, ON, Canada
| | - Demetrios Sahlas
- Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
| | | | - Ayman Hassan
- Thunder Bay Regional Research Institute, Thunder Bay, ON, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Gregory M Szilagyi
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Sean Symons
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | | | - Robert Bartha
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada; Departments of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
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19
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Beaton D, McLaughlin PM, Orange JB, Munoz DP, Mandzia J, Abrahao A, Binns MA, Black SE, Borrie M, Dowlatshahi D, Freedman M, Fischer CE, Finger EC, Frank A, Grimes D, Hassan A, Kumar S, Lang AE, Levine B, Marras C, Masellis M, Pollock BG, Rajji TK, Ramirez J, Sahlas DJ, Saposnik G, Scott CJM, Seitz DP, Strother SC, Sunderland KM, Tan B, Tang-Wai DF, Troyer AK, Turnbull J, Zinman L, Swartz RH, Tartaglia MC, Breen DP, Kwan D, Roberts AC, The Ondri Investigators. Caregiving concerns and clinical characteristics across neurodegenerative and cerebrovascular disorders in the Ontario neurodegenerative disease research initiative. Int J Geriatr Psychiatry 2022; 37. [PMID: 35633037 DOI: 10.1002/gps.5727] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 04/20/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVES Caregiving burdens are a substantial concern in the clinical care of persons with neurodegenerative disorders. In the Ontario Neurodegenerative Disease Research Initiative, we used the Zarit's Burden Interview (ZBI) to examine: (1) the types of burdens captured by the ZBI in a cross-disorder sample of neurodegenerative conditions (2) whether there are categorical or disorder-specific effects on caregiving burdens, and (3) which demographic, clinical, and cognitive measures are related to burden(s) in neurodegenerative disorders? METHODS/DESIGN N = 504 participants and their study partners (e.g., family, friends) across: Alzheimer's disease/mild cognitive impairment (AD/MCI; n = 120), Parkinson's disease (PD; n = 136), amyotrophic lateral sclerosis (ALS; n = 38), frontotemporal dementia (FTD; n = 53), and cerebrovascular disease (CVD; n = 157). Study partners provided information about themselves, and information about the clinical participants (e.g., activities of daily living (ADL)). We used Correspondence Analysis to identify types of caregiving concerns in the ZBI. We then identified relationships between those concerns and demographic and clinical measures, and a cognitive battery. RESULTS We found three components in the ZBI. The first was "overall burden" and was (1) strongly related to increased neuropsychiatric symptoms (NPI severity r = 0.586, NPI distress r = 0.587) and decreased independence in ADL (instrumental ADLs r = -0.566, basic ADLs r = -0.43), (2) moderately related to cognition (MoCA r = -0.268), and (3) showed little-to-no differences between disorders. The second and third components together showed four types of caregiving concerns: current care of the person with the neurodegenerative disease, future care of the person with the neurodegenerative disease, personal concerns of study partners, and social concerns of study partners. CONCLUSIONS Our results suggest that the experience of caregiving in neurodegenerative and cerebrovascular diseases is individualized and is not defined by diagnostic categories. Our findings highlight the importance of targeting ADL and neuropsychiatric symptoms with caregiver-personalized solutions.
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Affiliation(s)
- Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Paula M McLaughlin
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.,Nova Scotia Health Authority, Halifax, NS, Canada.,Department of Medicine - Geriatrics, Dalhousie University, Halifax, NS, Canada
| | - Joseph B Orange
- School of Communication Sciences and Disorders, Western University, London, ON, Canada.,Canadian Centre for Activity and Aging, Western University, London, ON, Canada.,Faculty of Health Sciences, Western University, London, ON, Canada
| | - Douglas P Munoz
- Department of Biomedical and Molecular Sciences, Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Jennifer Mandzia
- Department of Clinical Neurological Sciences, London Health Sciences Center, Western University, London, ON, Canada
| | - Agessandro Abrahao
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada.,Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Malcolm A Binns
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Sandra E Black
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada.,Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Michael Borrie
- Department of Medicine, Division of Geriatric Medicine, Western University, Toronto, ON, Canada
| | - Dar Dowlatshahi
- Department of Medicine, University of Ottawa, Ottawa, ON, Canada.,Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Morris Freedman
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.,Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada
| | - Corinne E Fischer
- Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Elizabeth C Finger
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Andrew Frank
- Bruyere Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - David Grimes
- Department of Medicine, University of Ottawa, Ottawa, ON, Canada.,Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Ayman Hassan
- Northern Ontario School of Medicine, Clinical Science Division, Depart of Internal Medicine, Thunder Bay, ON, Canada
| | - Sanjeev Kumar
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Anthony Edward Lang
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada.,Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, ON, Canada
| | - Brian Levine
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.,Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada.,Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - Connie Marras
- Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, ON, Canada
| | - Mario Masellis
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada.,Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Bruce G Pollock
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Tarek K Rajji
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Joel Ramirez
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,LC Campbell Cognitive Neurology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Demetrios J Sahlas
- Department of Medicine (Division of Neurology), McMaster University, Hamilton, ON, Canada
| | - Gustavo Saposnik
- Outcomes and Decision Neuroscience Research Unit, Toronto, ON, Canada
| | - Christopher J M Scott
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,LC Campbell Cognitive Neurology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Dallas P Seitz
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Kelly M Sunderland
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Brian Tan
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - David F Tang-Wai
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada.,Department of Medicine (Geriatric Medicine), University of Toronto, Toronto, ON, Canada.,University Hospital Network Memory Clinic, Toronto, ON, Canada
| | - Angela K Troyer
- Department of Psychology, University of Toronto, Toronto, ON, Canada.,Neuropsychology & Cognitive Health Program, Baycrest Health Sciences, Toronto, ON, Canada
| | - John Turnbull
- Department of Medicine (Division of Neurology), McMaster University, Hamilton, ON, Canada
| | - Lorne Zinman
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada.,Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Richard H Swartz
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada.,Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada.,Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Krembil Neuroscience Centre Memory Clinic, Toronto, ON, Canada
| | - David P Breen
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK.,Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Donna Kwan
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Angela C Roberts
- School of Communication Sciences and Disorders, Western University, London, ON, Canada.,Roxelyn and Richard Pepper Department of Communication Sciences and Disorders and Department of Computer Science, Northwestern University, Evanston, Illinois, USA
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20
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Ozzoude M, Varriano B, Beaton D, Ramirez J, Holmes MF, Scott CJM, Gao F, Sunderland KM, McLaughlin P, Rabin J, Goubran M, Kwan D, Roberts A, Bartha R, Symons S, Tan B, Swartz RH, Abrahao A, Saposnik G, Masellis M, Lang AE, Marras C, Zinman L, Shoesmith C, Borrie M, Fischer CE, Frank A, Freedman M, Montero-Odasso M, Kumar S, Pasternak S, Strother SC, Pollock BG, Rajji TK, Seitz D, Tang-Wai DF, Turnbull J, Dowlatshahi D, Hassan A, Casaubon L, Mandzia J, Sahlas D, Breen DP, Grimes D, Jog M, Steeves TDL, Arnott SR, Black SE, Finger E, Tartaglia MC. Investigating the contribution of white matter hyperintensities and cortical thickness to empathy in neurodegenerative and cerebrovascular diseases. GeroScience 2022; 44:1575-1598. [PMID: 35294697 DOI: 10.1007/s11357-022-00539-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 02/22/2022] [Indexed: 11/24/2022] Open
Abstract
Change in empathy is an increasingly recognised symptom of neurodegenerative diseases and contributes to caregiver burden and patient distress. Empathy impairment has been associated with brain atrophy but its relationship to white matter hyperintensities (WMH) is unknown. We aimed to investigate the relationships amongst WMH, brain atrophy, and empathy deficits in neurodegenerative and cerebrovascular diseases. Five hundred thirteen participants with Alzheimer's disease/mild cognitive impairment, amyotrophic lateral sclerosis, frontotemporal dementia (FTD), Parkinson's disease, or cerebrovascular disease (CVD) were included. Empathy was assessed using the Interpersonal Reactivity Index. WMH were measured using a semi-automatic segmentation and FreeSurfer was used to measure cortical thickness. A heterogeneous pattern of cortical thinning was found between groups, with FTD showing thinning in frontotemporal regions and CVD in left superior parietal, left insula, and left postcentral. Results from both univariate and multivariate analyses revealed that several variables were associated with empathy, particularly cortical thickness in the fronto-insulo-temporal and cingulate regions, sex (female), global cognition, and right parietal and occipital WMH. Our results suggest that cortical atrophy and WMH may be associated with empathy deficits in neurodegenerative and cerebrovascular diseases. Future work should consider investigating the longitudinal effects of WMH and atrophy on empathy deficits in neurodegenerative and cerebrovascular diseases.
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Affiliation(s)
- Miracle Ozzoude
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 0S8, Canada.,L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Brenda Varriano
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 0S8, Canada
| | - Derek Beaton
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Joel Ramirez
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Melissa F Holmes
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Christopher J M Scott
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Fuqiang Gao
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | | | - Paula McLaughlin
- Nova Scotia Health and Dalhousie University, Halifax, NS, Canada
| | - Jennifer Rabin
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.,Queen's University, Kingston, ON, Canada
| | - Angela Roberts
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA.,School of Communication Sciences and Disorders, Faculty of Health Sciences, Western University, London, ON, Canada
| | - Robert Bartha
- Robarts Research Institute, Western University, London, ON, Canada
| | - Sean Symons
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Brian Tan
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Agessandro Abrahao
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Gustavo Saposnik
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Mario Masellis
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Anthony E Lang
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Edmond J Safra Program for Parkinson Disease, Movement Disorder Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Connie Marras
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Edmond J Safra Program for Parkinson Disease, Movement Disorder Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Lorne Zinman
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Christen Shoesmith
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Michael Borrie
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,St. Joseph's Healthcare Centre, London, ON, Canada
| | - Corinne E Fischer
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada
| | - Andrew Frank
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute and Ottawa Hospital Research Institute, Ottawa, ON, Canada.,Bruyère Research Institute, Ottawa, ON, Canada
| | - Morris Freedman
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Baycrest Health Sciences, Toronto, ON, Canada
| | - Manuel Montero-Odasso
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,Lawson Health Research Institute, London, ON, Canada.,Gait and Brain Lab, Parkwood Institute, London, ON, Canada
| | - Sanjeev Kumar
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Stephen Pasternak
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Stephen C Strother
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Bruce G Pollock
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tarek K Rajji
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada
| | - Dallas Seitz
- Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - David F Tang-Wai
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Memory Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - John Turnbull
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.,Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Dar Dowlatshahi
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute and Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Ayman Hassan
- Thunder Bay Regional Health Research Institute, Thunder Bay, ON, Canada
| | - Leanne Casaubon
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jennifer Mandzia
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Demetrios Sahlas
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.,Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - David P Breen
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK.,Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - David Grimes
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute and Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Mandar Jog
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,London Health Sciences Centre, London, ON, Canada
| | - Thomas D L Steeves
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Stephen R Arnott
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Sandra E Black
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 0S8, Canada. .,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada. .,Memory Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.
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21
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Abrams MB, Bjaalie JG, Das S, Egan GF, Ghosh SS, Goscinski WJ, Grethe JS, Kotaleski JH, Ho ETW, Kennedy DN, Lanyon LJ, Leergaard TB, Mayberg HS, Milanesi L, Mouček R, Poline JB, Roy PK, Strother SC, Tang TB, Tiesinga P, Wachtler T, Wójcik DK, Martone ME. A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility. Neuroinformatics 2022; 20:25-36. [PMID: 33506383 PMCID: PMC9036053 DOI: 10.1007/s12021-020-09509-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/28/2020] [Indexed: 01/07/2023]
Abstract
There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.
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Affiliation(s)
| | - Jan G. Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Samir Das
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, QC Canada
| | - Gary F. Egan
- Monash Biomedical Imaging, Monash University, Clayton, VIC Australia
| | - Satrajit S. Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA USA ,Department of Otolaryngology - Head and Neck Surgery Harvard Medical School Boston, Boston, MA USA
| | | | - Jeffrey S. Grethe
- Department of Neuroscience, School of Medicine, University of California, San Diego, La Jolla, CA USA
| | | | - Eric Tatt Wei Ho
- Centre for Intelligent Signal and Imaging Research, Institute of Health and Analytics, Universiti Teknologi PETRONAS, Perak, Malaysia
| | - David N. Kennedy
- Department of Psychiatry, University of Massachusetts Medical School, Worchester, MA USA
| | | | | | - Helen S. Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine, New York, NY USA
| | - Luciano Milanesi
- Institute of Biomedical Technologies, National Research Council (CNR), Milan, Italy
| | - Roman Mouček
- Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Pilsen, Czech Republic
| | - J. B. Poline
- Montreal Neurological Institute, Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
| | - Prasun K. Roy
- Computational Neuroscience & Neuroimaging Laboratory, School of Bio-Medical Engineering, Indian Institute of Technology (BHU), Varanasi, UP India
| | - Stephen C. Strother
- Rotman Research Institute, Baycrest Centre, Department of Medical Biophysics, University of Toronto, Ontario, ON Canada
| | - Tong Boon Tang
- Centre for Intelligent Signal and Imaging Research, Institute of Health and Analytics, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Malaysia
| | - Paul Tiesinga
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Thomas Wachtler
- Department of Biology II, Ludwig-Maximilians-Universität München, Martinsried, Planegg Germany
| | - Daniel K. Wójcik
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Maryann E. Martone
- Department of Neuroscience, School of Medicine, University of California, San Diego, La Jolla, CA USA
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22
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Ballester PL, Romano MT, de Azevedo Cardoso T, Hassel S, Strother SC, Kennedy SH, Frey BN. Brain age in mood and psychotic disorders: a systematic review and meta-analysis. Acta Psychiatr Scand 2022; 145:42-55. [PMID: 34510423 DOI: 10.1111/acps.13371] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 09/05/2021] [Accepted: 09/07/2021] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To evaluate whether accelerated brain aging occurs in individuals with mood or psychotic disorders. METHODS A systematic review following PRISMA guidelines was conducted. A meta-analysis was then performed to assess neuroimaging-derived brain age gap in three independent groups: (1) schizophrenia and first-episode psychosis, (2) major depressive disorder, and (3) bipolar disorder. RESULTS A total of 18 papers were included. The random-effects model meta-analysis showed a significantly increased neuroimaging-derived brain age gap relative to age-matched controls for the three major psychiatric disorders, with schizophrenia (3.08; 95%CI [2.32; 3.85]; p < 0.01) presenting the largest effect, followed by bipolar disorder (1.93; [0.53; 3.34]; p < 0.01) and major depressive disorder (1.12; [0.41; 1.83]; p < 0.01). The brain age gap was larger in older compared to younger individuals. CONCLUSION Individuals with mood and psychotic disorders may undergo a process of accelerated brain aging reflected in patterns captured by neuroimaging data. The brain age gap tends to be more pronounced in older individuals, indicating a possible cumulative biological effect of illness burden.
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Affiliation(s)
- Pedro L Ballester
- Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
| | - Maria T Romano
- Integrated Science Undergraduate Program, McMaster University, Hamilton, Ontario, Canada
| | - Taiane de Azevedo Cardoso
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Stefanie Hassel
- Mathison Centre for Mental Health Research and Education, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Sidney H Kennedy
- Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Mood Disorders Treatment and Research Centre, and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, Ontario, Canada
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23
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Harris JK, Hassel S, Davis AD, Zamyadi M, Arnott SR, Milev R, Lam RW, Frey BN, Hall GB, Müller DJ, Rotzinger S, Kennedy SH, Strother SC, MacQueen GM, Greiner R. Predicting escitalopram treatment response from pre-treatment and early response resting state fMRI in a multi-site sample: A CAN-BIND-1 report. NeuroImage: Clinical 2022; 35:103120. [PMID: 35908308 PMCID: PMC9421454 DOI: 10.1016/j.nicl.2022.103120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/17/2022] [Accepted: 07/14/2022] [Indexed: 11/22/2022] Open
Abstract
Baseline measures alone not able to predict escitalopram response above default. This poor baseline performance contradicts results from smaller studies. Accuracy improved using change in functional connectivity from baseline to week 2. Measures of early change following treatment may be crucial for accurate prediction.
Many previous intervention studies have used functional magnetic resonance imaging (fMRI) data to predict the antidepressant response of patients with major depressive disorder (MDD); however, practical constraints have limited many of those attempts to small, single centre studies which may not adequately reflect how these models will generalize when used in clinical practice. Not only does the act of collecting data at multiple sites generally increase sample sizes (a critical point in machine learning development) it also generates a more heterogeneous dataset due to systematic differences in scanners at different sites, and geographical differences in patient populations. As part of the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) study, 144 MDD patients from six sites underwent resting state fMRI prior to starting escitalopram treatment, and again two weeks after the start. Here, we consider ways to use machine learning techniques to produce models that can predict response (measured at eight weeks after initiation), based on various parcellations, functional connectivity (FC) metrics, dimensionality reduction algorithms, and base learners, and also whether to use scans from one or both time points. Models that use only baseline (pre-treatment) or only week 2 (early-response) whole-brain FC features consistently failed to perform significantly better than default models. Utilizing the change in FC between these two time points, however, yielded significant results, with the best performing analytical pipeline achieving 69.6% (SD 10.8) accuracy. These results appear contrary to findings from many smaller single-site studies, which report substantially higher predictive accuracies from models trained on only baseline resting state FC features, suggesting these models may not generalize well beyond data used for development. Further, these results indicate the potential value of collecting data both before and shortly after treatment initiation.
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24
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Vaccarino AL, Beaton D, Black SE, Blier P, Farzan F, Finger E, Foster JA, Freedman M, Frey BN, Gilbert Evans S, Ho K, Javadi M, Kennedy SH, Lam RW, Lang AE, Lasalandra B, Latour S, Masellis M, Milev RV, Müller DJ, Munoz DP, Parikh SV, Placenza F, Rotzinger S, Soares CN, Sparks A, Strother SC, Swartz RH, Tan B, Tartaglia MC, Taylor VH, Theriault E, Turecki G, Uher R, Zinman L, Evans KR. Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data: Assessment of Psychiatric Comorbidity Across Brain Disorders. Front Psychiatry 2022; 13:816465. [PMID: 35197877 PMCID: PMC8859302 DOI: 10.3389/fpsyt.2022.816465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 01/12/2022] [Indexed: 11/24/2022] Open
Abstract
The Ontario Brain Institute's "Brain-CODE" is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease).
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Affiliation(s)
| | - Derek Beaton
- Data Science and Advanced Analytics, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Research Program, Dr. Sandra Black Centre for Brain Resilience and Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Pierre Blier
- Mood Disorders Research Unit, University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada
| | - Farnak Farzan
- School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, BC, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Jane A Foster
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Morris Freedman
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.,Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, ON, Canada
| | | | - Keith Ho
- Department of Psychiatry, University Health Network, Toronto, ON, Canada
| | | | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Anthony E Lang
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Edmond J. Safra Program in Parkinson's Disease, University Health Network, Toronto, ON, Canada
| | | | | | - Mario Masellis
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Roumen V Milev
- Departments of Psychiatry and Psychology, Queen's University, Providence Care, Kingston, ON, Canada
| | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
| | - Douglas P Munoz
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Sagar V Parikh
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Franca Placenza
- Department of Psychiatry, University Health Network, Toronto, ON, Canada
| | - Susan Rotzinger
- Department of Psychiatry, University Health Network, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Claudio N Soares
- Department of Psychiatry, Queen's University, Kingston, ON, Canada
| | | | - Stephen C Strother
- Indoc Research, Toronto, ON, Canada.,Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Research Program, Dr. Sandra Black Centre for Brain Resilience and Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Brian Tan
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases University of Toronto, Toronto, ON, Canada
| | - Valerie H Taylor
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | | | - Gustavo Turecki
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Lorne Zinman
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
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25
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Davis AD, Hassel S, Arnott SR, Hall GB, Harris JK, Zamyadi M, Downar J, Frey BN, Lam RW, Kennedy SH, Strother SC. Biophysical compartment models for single-shell diffusion MRI in the human brain: a model fitting comparison. Phys Med Biol 2021; 67. [PMID: 34965517 DOI: 10.1088/1361-6560/ac46de] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Accepted: 12/29/2021] [Indexed: 11/11/2022]
Abstract
Clinically oriented studies commonly acquire diffusion MRI (dMRI) data with a single non-zero b-value (i.e. single-shell) and diffusion weighting ofb=1000 s/mm2. To produce microstructural parameter maps, the tensor model is usually used, despite known limitations. Although compartment models have demonstrated improved fits in multi-shell dMRI data, they are rarely used for single-shell parameter maps, where their effectiveness is unclear from the literature. Here, various compartment models combining isotropic balls and symmetric tensors were fitted to single-shell dMRI data to investigate model fitting optimization and extract the most information possible. Full testing was performed in 5 subjects, and 3 subjects with multi-shell data were included for comparison. The results were tested and confirmed in a further 50 subjects. The Markov chain Monte Carlo (MCMC) model fitting technique outperformed non-linear least squares. Using MCMC, the 2-fibre-orientation mono-exponential ball & stick model (BSME2) provided artifact-free, stable results, in little processing time. The analogous ball & zeppelin model (BZ2) also produced stable, low-noise parameter maps, though it required much greater computing resources (50 000 burn-in steps). In single-shell data, the gamma-distributed diffusivity ball & stick model (BSGD2) underperformed relative to other models, despite being an often-used software default. It produced artifacts in the diffusivity maps even with extremely long processing times. Neither increased diffusion weighting nor a greater number of gradient orientations improved BSGD2fits. In white matter (WM), the tensor produced the best fit as measured by Bayesian information criterion. This result contrasts with studies using multi-shell data. However, in crossing fibre regions the tensor confounded geometric effects with fractional anisotropy (FA): the planar/linear WM FA ratio was 49%, while BZ2and BSME2retained 76% and 83% of restricted fraction, respectively. As a result, the BZ2and BSME2models are strong candidates to optimize information extraction from single-shell dMRI studies.
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Affiliation(s)
- Andrew D Davis
- Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst St, Toronto, Ontario, M6A 2E1, CANADA
| | - Stefanie Hassel
- University of Calgary Cumming School of Medicine, 3330 Hospital Dr NW, Calgary, Alberta, T2N 4N1, CANADA
| | - Stephen R Arnott
- Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst St, Toronto, Ontario, M6A 2E1, CANADA
| | - Geoffrey B Hall
- Department of Psychology, Neuroscience & Behaviour, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4K1, CANADA
| | - Jacqueline K Harris
- Department of Computing Science, University of Alberta, 8900 114 St NW, Edmonton, Alberta, T6G 2E8, CANADA
| | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst St, Toronto, Ontario, M6A 2E1, CANADA
| | - Jonathan Downar
- Institute of Medical Science, University of Toronto, 1 King's College Cir, Toronto, Ontario, M5S 1A8, CANADA
| | - Benicio N Frey
- McMaster University Department of Psychiatry and Behavioural Neurosciences, 100 West 5th Street, Hamilton, Ontario, L8N 3K7, CANADA
| | - Raymond W Lam
- Psychiatry, The University of British Columbia, 2255 Wesbrook Mall, Vancouver, British Columbia, V6T 2A1, CANADA
| | - Sidney H Kennedy
- University of Toronto Department of Psychiatry, 250 College Street, Toronto, Ontario, M5T 1R8, CANADA
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst St, Toronto, Ontario, M6A 2E1, CANADA
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26
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Ge R, Hassel S, Arnott SR, Davis AD, Harris JK, Zamyadi M, Milev R, Frey BN, Strother SC, Müller DJ, Rotzinger S, MacQueen GM, Kennedy SH, Lam RW, Vila-Rodriguez F. Structural covariance pattern abnormalities of insula in major depressive disorder: A CAN-BIND study report. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110194. [PMID: 33296696 DOI: 10.1016/j.pnpbp.2020.110194] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 09/25/2020] [Accepted: 11/30/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND AND METHODS Investigation of the insula may inform understanding of the etiopathogenesis of major depressive disorder (MDD). In the present study, we introduced a novel gray matter volume (GMV) based structural covariance technique, and applied it to a multi-centre study of insular subregions of 157 patients with MDD and 93 healthy controls from the Canadian Biomarker Integration Network in Depression (CAN-BIND, https://www.canbind.ca/). Specifically, we divided the unilateral insula into three subregions, and investigated their coupling with whole-brain GMV-based structural brain networks (SBNs). We compared between-group difference of the structural coupling patterns between the insular subregions and SBNs. RESULTS The insula was divided into three subregions, including an anterior one, a superior-posterior one and an inferior-posterior one. In the comparison between MDD patients and controls we found that patients' right anterior insula showed increased inter-network coupling with the default mode network, and it showed decreased inter-network coupling with the central executive network; whereas patients' right ventral-posterior insula showed decreased inter-network coupling with the default mode network, and it showed increased inter-network coupling with the central executive network. We also demonstrated that patients' loading parameters of the right ventral-posterior insular structural covariance negatively correlated with their suicidal ideation scores; and controls' loading parameters of the right ventral-posterior insular structural covariance positively correlated with their motor and psychomotor speed scores, whereas these phenomena were not found in patients. Additionally, we did not find significant inter-network coupling between the whole-brain SBNs, including salience network, default mode network, and central executive network. CONCLUSIONS Our work proposed a novel technique to investigate the structural covariance coupling between large-scale structural covariance networks, and provided further evidence that MDD is a system-level disorder that shows disrupted structural coupling between brain networks.
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Affiliation(s)
- Ruiyang Ge
- Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Stefanie Hassel
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada
| | | | - Andrew D Davis
- Department of Psychology, Neuroscience & Behaviour, McMaster University, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | | | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest, Toronto, ON, Canada
| | - Roumen Milev
- Department of Psychiatry, Queen's University and Providence Care Hospital, Kingston, ON, Canada; Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, ON, Canada
| | | | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Susan Rotzinger
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, Krembil Research Centre, University Health Network, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Glenda M MacQueen
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, Krembil Research Centre, University Health Network, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada; Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Fidel Vila-Rodriguez
- Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.
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27
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Ottoy J, Ozzoude M, Zukotynski K, Adamo SM, Scott CJM, Gaudet V, Ramirez J, Swardfager W, Lam B, Bhan A, Kiss A, Strother SC, Bocti C, Borrie M, Chertkow H, Frayne R, Hsiung GR, Laforce R, Noseworthy MD, Prato FS, Sahlas DJ, Smith EE, Sossi V, Thiel A, Soucy J, Tardif J, Goubran M, Black SE. Amyloid‐independent vascular contributions to cortical atrophy and cognition in a multi‐center mixed cohort with low to severe small vessel disease. Alzheimers Dement 2021. [DOI: 10.1002/alz.056326] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Julie Ottoy
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
| | - Miracle Ozzoude
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
| | - Katherine Zukotynski
- Departments of Medicine and Radiology, McMaster University Hamilton ON Canada
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute Toronto ON Canada
| | - Sabrina M. Adamo
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
| | - Christopher J. M. Scott
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute Toronto ON Canada
| | - Vincent Gaudet
- Department of Electrical and Computer Engineering, University of Waterloo Waterloo ON Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
| | - Walter Swardfager
- Department of Pharmacology & Toxicology, University of Toronto Toronto ON Canada
| | - Benjamin Lam
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute Toronto ON Canada
| | - Aparna Bhan
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute Toronto ON Canada
| | - Alex Kiss
- Department of Research Design and Biostatistics, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
| | | | - Christian Bocti
- Département de Médecine, Université de Sherbrooke Sherbrooke QC Canada
| | - Michael Borrie
- Lawson Health Research Institute, Western University London ON Canada
| | | | - Richard Frayne
- Departments of Radiology and Clinical Neuroscience, University of Calgary Calgary AB Canada
| | - Ging‐Yuek Robin Hsiung
- Djavad Mowafaghian Centre for Brain Health, University of British Colombia Vancouver BC Canada
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, CHU de Québec/Université Laval/Hôpital de l’Enfant‐Jésus Quebec City QC Canada
| | - Michael D. Noseworthy
- Department of Electrical and Computer Engineering, McMaster University Hamilton ON Canada
| | - Frank S. Prato
- Lawson Health Research Institute, Western University London ON Canada
| | | | - Eric E. Smith
- Hotchkiss Brain Institute, University of Calgary Calgary AB Canada
| | - Vesna Sossi
- Physics and Astronomy Department and DM Center for Brain Health, University of British Columbia Vancouver BC Canada
| | - Alexander Thiel
- Jewish General Hospital, McGill University Montreal QC Canada
| | - Jean‐Paul Soucy
- Montreal Neurological Institute, McGill University Montreal QC Canada
| | | | - Maged Goubran
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
| | - Sandra E. Black
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
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28
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Haddad SMH, Scott CJ, Arnott SR, Ozzoude M, Strother SC, Black SE, Borrie M, Finger E, Trataglia MC, Kwan D, Beaton D, Symons S, Soddu A, Menon RS, Montero‐Odasso M, Bartha R. Comparison of neuronal activity profiles in Alzheimer’s disease and frontotemporal dementia measured by resting‐state fMRI. Alzheimers Dement 2021. [DOI: 10.1002/alz.054549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | - Christopher J.M. Scott
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute Toronto ON Canada
| | | | - Miracle Ozzoude
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
| | | | | | - Michael Borrie
- Lawson Health Research Institute, Western University London ON Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario London ON Canada
| | | | - Donna Kwan
- Ontario Neurodegenerative Disease Research Initiative Toronto ON Canada
| | | | - Sean Symons
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute Toronto ON Canada
| | | | - Ravi S. Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute London ON Canada
| | - Manuel Montero‐Odasso
- Schulich School of Medicine& Dentistry, Division of Geriatric Medicine, Western University London ON Canada
| | - Robert Bartha
- Centre for Functional and Metabolic Mapping, Robarts Research Institute London ON Canada
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Haddad SMH, Scott CJ, Ozzoude M, Holmes MF, Arnott SR, Nanayakkara ND, Kwan D, Tan B, Casaubon L, Mandzia J, Sahlas DJ, Saposnik G, Hassan A, Black SE, Dowlatshahi D, Strother SC, Swartz RH, Symons S, Montero‐Odasso M, Bartha R. Disintegration of anterior thalamic radiation fibers in cerebrovascular disease subjects with periventricular white matter hyperintensities leads to lower executive function performance. Alzheimers Dement 2021. [DOI: 10.1002/alz.056596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
| | - Christopher J.M. Scott
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute Toronto ON Canada
| | - Miracle Ozzoude
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
| | - Melissa F. Holmes
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute Toronto ON Canada
| | | | | | | | - Brian Tan
- Rotman Research Institute Toronto ON Canada
| | | | | | | | | | - Ayman Hassan
- Thunder Bay Regional Health Sciences Centre Thunder Bay ON Canada
| | - Sandra E. Black
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto Toronto ON Canada
| | | | | | - Richard H. Swartz
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute Toronto ON Canada
| | - Sean Symons
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | - Manuel Montero‐Odasso
- Schulich School of Medicine& Dentistry, Division of Geriatric Medicine, Western University London ON Canada
| | - Robert Bartha
- Robarts Research Institute, Western University London ON Canada
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30
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Sajjadian M, Lam RW, Milev R, Rotzinger S, Frey BN, Soares CN, Parikh SV, Foster JA, Turecki G, Müller DJ, Strother SC, Farzan F, Kennedy SH, Uher R. Machine learning in the prediction of depression treatment outcomes: a systematic review and meta-analysis. Psychol Med 2021; 51:2742-2751. [PMID: 35575607 DOI: 10.1017/s0033291721003871] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Multiple treatments are effective for major depressive disorder (MDD), but the outcomes of each treatment vary broadly among individuals. Accurate prediction of outcomes is needed to help select a treatment that is likely to work for a given person. We aim to examine the performance of machine learning methods in delivering replicable predictions of treatment outcomes. METHODS Of 7732 non-duplicate records identified through literature search, we retained 59 eligible reports and extracted data on sample, treatment, predictors, machine learning method, and treatment outcome prediction. A minimum sample size of 100 and an adequate validation method were used to identify adequate-quality studies. The effects of study features on prediction accuracy were tested with mixed-effects models. Fifty-four of the studies provided accuracy estimates or other estimates that allowed calculation of balanced accuracy of predicting outcomes of treatment. RESULTS Eight adequate-quality studies reported a mean accuracy of 0.63 [95% confidence interval (CI) 0.56-0.71], which was significantly lower than a mean accuracy of 0.75 (95% CI 0.72-0.78) in the other 46 studies. Among the adequate-quality studies, accuracies were higher when predicting treatment resistance (0.69) and lower when predicting remission (0.60) or response (0.56). The choice of machine learning method, feature selection, and the ratio of features to individuals were not associated with reported accuracy. CONCLUSIONS The negative relationship between study quality and prediction accuracy, combined with a lack of independent replication, invites caution when evaluating the potential of machine learning applications for personalizing the treatment of depression.
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Affiliation(s)
- Mehri Sajjadian
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Roumen Milev
- Department of Psychiatry and Psychology, Queen's University, Providence Care Hospital, Kingston, ON, Canada
| | - Susan Rotzinger
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
- Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - Claudio N Soares
- Department of Psychiatry, Queen's University School of Medicine, Kingston, ON, Canada
| | - Sagar V Parikh
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Jane A Foster
- Department of Psychiatry & Behavioural Neurosciences, St. Joseph's Healthcare, Hamilton, ON, Canada
| | - Gustavo Turecki
- Department of Psychiatry, Douglas Institute, McGill University, Montreal, QC, Canada
| | - Daniel J Müller
- Campbell Family Mental Health Research Institute, Center for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Stephen C Strother
- Baycrest and Department of Medical Biophysics, Rotman Research Center, University of Toronto, Toronto, ON, Canada
| | - Faranak Farzan
- eBrain Lab, School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, BC, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, University Health Network, Toronto, ON, Canada
- Krembil Research Centre, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
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31
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Liang S, Beaton D, Arnott SR, Gee T, Zamyadi M, Bartha R, Symons S, MacQueen GM, Hassel S, Lerch JP, Anagnostou E, Lam RW, Frey BN, Milev R, Müller DJ, Kennedy SH, Scott CJM, Strother SC. Magnetic Resonance Imaging Sequence Identification Using a Metadata Learning Approach. Front Neuroinform 2021; 15:622951. [PMID: 34867254 PMCID: PMC8635782 DOI: 10.3389/fninf.2021.622951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 10/21/2021] [Indexed: 11/29/2022] Open
Abstract
Despite the wide application of the magnetic resonance imaging (MRI) technique, there are no widely used standards on naming and describing MRI sequences. The absence of consistent naming conventions presents a major challenge in automating image processing since most MRI software require a priori knowledge of the type of the MRI sequences to be processed. This issue becomes increasingly critical with the current efforts toward open-sharing of MRI data in the neuroscience community. This manuscript reports an MRI sequence detection method using imaging metadata and a supervised machine learning technique. Three datasets from the Brain Center for Ontario Data Exploration (Brain-CODE) data platform, each involving MRI data from multiple research institutes, are used to build and test our model. The preliminary results show that a random forest model can be trained to accurately identify MRI sequence types, and to recognize MRI scans that do not belong to any of the known sequence types. Therefore the proposed approach can be used to automate processing of MRI data that involves a large number of variations in sequence names, and to help standardize sequence naming in ongoing data collections. This study highlights the potential of the machine learning approaches in helping manage health data.
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Affiliation(s)
- Shuai Liang
- Rotman Research Institute, Baycrest Health Center, Toronto, ON, Canada
- Indoc Research, Toronto, ON, Canada
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Center, Toronto, ON, Canada
| | - Stephen R. Arnott
- Rotman Research Institute, Baycrest Health Center, Toronto, ON, Canada
| | - Tom Gee
- Indoc Research, Toronto, ON, Canada
| | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest Health Center, Toronto, ON, Canada
| | - Robert Bartha
- Robarts Research Institute, Western University, London, ON, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Glenda M. MacQueen
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Stefanie Hassel
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Jason P. Lerch
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
- Department of Pediatrics, University of Toronto, Toronto, ON, Canada
| | - Raymond W. Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Benicio N. Frey
- Department of Psychiatry and Behavioral Neurosciences, McMaster University, Hamilton, ON, Canada
- Mood Disorders Program, St. Joseph’s Healthcare, Hamilton, ON, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Providence Care Hospital, Queen’s University, Kingston, ON, Canada
| | - Daniel J. Müller
- Molecular Brain Science, Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Sidney H. Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, Krembil Research Centre, University Health Network, Toronto, ON, Canada
- Department of Psychiatry, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Li Ka Shing Knowledge Institute, Toronto, ON, Canada
| | - Christopher J. M. Scott
- L.C. Campbell Cognitive Neurology Research Unit, Toronto, ON, Canada
- Heart & Stroke Foundation Centre for Stroke Recovery, Toronto, ON, Canada
- Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Stephen C. Strother
- Rotman Research Institute, Baycrest Health Center, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
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32
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Godkin FE, Turner E, Demnati Y, Vert A, Roberts A, Swartz RH, McLaughlin PM, Weber KS, Thai V, Beyer KB, Cornish B, Abrahao A, Black SE, Masellis M, Zinman L, Beaton D, Binns MA, Chau V, Kwan D, Lim A, Munoz DP, Strother SC, Sunderland KM, Tan B, McIlroy WE, Van Ooteghem K. Feasibility of a continuous, multi-sensor remote health monitoring approach in persons living with neurodegenerative disease. J Neurol 2021; 269:2673-2686. [PMID: 34705114 PMCID: PMC8548705 DOI: 10.1007/s00415-021-10831-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 01/02/2023]
Abstract
BACKGROUND Remote health monitoring with wearable sensor technology may positively impact patient self-management and clinical care. In individuals with complex health conditions, multi-sensor wear may yield meaningful information about health-related behaviors. Despite available technology, feasibility of device-wearing in daily life has received little attention in persons with physical or cognitive limitations. This mixed methods study assessed the feasibility of continuous, multi-sensor wear in persons with cerebrovascular (CVD) or neurodegenerative disease (NDD). METHODS Thirty-nine participants with CVD, Alzheimer's disease/amnestic mild cognitive impairment, frontotemporal dementia, Parkinson's disease, or amyotrophic lateral sclerosis (median age 68 (45-83) years, 36% female) wore five devices (bilateral ankles and wrists, chest) continuously for a 7-day period. Adherence to device wearing was quantified by examining volume and pattern of device removal (non-wear). A thematic analysis of semi-structured de-brief interviews with participants and study partners was used to examine user acceptance. RESULTS Adherence to multi-sensor wear, defined as a minimum of three devices worn concurrently, was high (median 98.2% of the study period). Non-wear rates were low across all sensor locations (median 17-22 min/day), with significant differences between some locations (p = 0.006). Multi-sensor non-wear was higher for daytime versus nighttime wear (p < 0.001) and there was a small but significant increase in non-wear over the collection period (p = 0.04). Feedback from de-brief interviews suggested that multi-sensor wear was generally well accepted by both participants and study partners. CONCLUSION A continuous, multi-sensor remote health monitoring approach is feasible in a cohort of persons with CVD or NDD.
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Affiliation(s)
- F Elizabeth Godkin
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Erin Turner
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Youness Demnati
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Adam Vert
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Angela Roberts
- School of Communication Sciences and Disorders, Elborn College, Western University, London, ON, Canada.,Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA
| | - Richard H Swartz
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | | | - Kyle S Weber
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Vanessa Thai
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Kit B Beyer
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Benjamin Cornish
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Agessandro Abrahao
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Sandra E Black
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Mario Masellis
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Lorne Zinman
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Malcolm A Binns
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Vivian Chau
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Andrew Lim
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Douglas P Munoz
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Kelly M Sunderland
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Brian Tan
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - William E McIlroy
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Karen Van Ooteghem
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.
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33
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Ballester PL, Suh JS, Nogovitsyn N, Hassel S, Strother SC, Arnott SR, Minuzzi L, Sassi RB, Lam RW, Milev R, Müller DJ, Taylor VH, Kennedy SH, Frey BN. Accelerated brain aging in major depressive disorder and antidepressant treatment response: A CAN-BIND report. Neuroimage Clin 2021; 32:102864. [PMID: 34710675 PMCID: PMC8556529 DOI: 10.1016/j.nicl.2021.102864] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 10/08/2021] [Accepted: 10/18/2021] [Indexed: 10/24/2022]
Abstract
OBJECTIVES Previous studies suggest that major depressive disorder (MDD) may be associated with volumetric indications of accelerated brain aging. This study investigated neuroanatomical signs of accelerated aging in MDD and evaluated whether a brain age gap is associated with antidepressant response. METHODS Individuals in a major depressive episode received escitalopram treatment (10-20 mg/d) for 8 weeks. Depression severity was assessed at baseline and at weeks 8 and 16 using the Montgomery-Asberg Depression Rating Scale (MADRS). Response to treatment was characterized by a significant reduction in the MADRS (≥50%). Nonresponders received adjunctive aripiprazole treatment (2-10 mg/d) for a further 8 weeks. The brain-predicted age difference (brain-PAD) at baseline was determined using machine learning methods trained on 3377 healthy individuals from seven publicly available datasets. The model used features from all brain regions extracted from structural magnetic resonance imaging data. RESULTS Brain-PAD was significantly higher in older MDD participants compared to younger MDD participants [t(147.35) = -2.35, p < 0.03]. BMI was significantly associated with brain-PAD in the MDD group [r(155) = 0.19, p < 0.03]. Response to treatment was not significantly associated with brain-PAD. CONCLUSION We found an elevated brain age gap in older individuals with MDD. Brain-PAD was not associated with overall treatment response to escitalopram monotherapy or escitalopram plus adjunctive aripiprazole.
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Affiliation(s)
- Pedro L Ballester
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada
| | - Jee Su Suh
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada
| | - Nikita Nogovitsyn
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Stefanie Hassel
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, ON, Canada
| | | | - Luciano Minuzzi
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - Roberto B Sassi
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, and Providence Care, Kingston, ON, Canada
| | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Valerie H Taylor
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Sidney H Kennedy
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Mental Health, University Health Network, Toronto, ON, Canada; Krembil Research Institute, University Health Network, Toronto, ON, Canada; Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Benicio N Frey
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
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34
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Suh JS, Fiori LM, Ali M, Harkness KL, Ramonas M, Minuzzi L, Hassel S, Strother SC, Zamyadi M, Arnott SR, Farzan F, Foster JA, Lam RW, MacQueen GM, Milev R, Müller DJ, Parikh SV, Rotzinger S, Sassi RB, Soares CN, Uher R, Kennedy SH, Turecki G, Frey BN. Hypothalamus volume and DNA methylation of stress axis genes in major depressive disorder: A CAN-BIND study report. Psychoneuroendocrinology 2021; 132:105348. [PMID: 34229186 DOI: 10.1016/j.psyneuen.2021.105348] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 06/14/2021] [Accepted: 06/25/2021] [Indexed: 11/28/2022]
Abstract
Dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis is considered one of the mechanisms underlying the development of major depressive disorder (MDD), but the exact nature of this dysfunction is unknown. We investigated the relationship between hypothalamus volume (HV) and blood-derived DNA methylation in MDD. We obtained brain MRI, clinical and molecular data from 181 unmedicated MDD and 90 healthy control (HC) participants. MDD participants received a 16-week standardized antidepressant treatment protocol, as part of the first Canadian Biomarker Integration Network in Depression (CAN-BIND) study. We collected bilateral HV measures via manual segmentation by two independent raters. DNA methylation and RNA sequencing were performed for three key HPA axis-regulating genes coding for the corticotropin-binding protein (CRHBP), glucocorticoid receptor (NR3C1) and FK506 binding protein 5 (FKBP5). We used elastic net regression to perform variable selection and assess predictive ability of methylation variables on HV. Left HV was negatively associated with duration of current episode (ρ = -0.17, p = 0.035). We did not observe significant differences in HV between MDD and HC or any associations between HV and treatment response at weeks 8 or 16, overall depression severity, illness duration or childhood maltreatment. We also did not observe any differentially methylated CpG sites between MDD and HC groups. After assessing functionality by correlating methylation levels with RNA expression of the respective genes, we observed that the number of functionally relevant CpG sites differed between MDD and HC groups in FKBP5 (χ2 = 77.25, p < 0.0001) and NR3C1 (χ2 = 7.29, p = 0.007). Cross-referencing functionally relevant CpG sites to those that were highly ranked in predicting HV in elastic net modeling identified one site from FKBP5 (cg03591753) and one from NR3C1 (cg20728768) within the MDD group. Stronger associations between DNA methylation, gene expression and HV in MDD suggest a novel putative molecular pathway of stress-related sensitivity in depression. Future studies should consider utilizing the epigenome and ultra-high field MR data which would allow the investigation of HV sub-fields.
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Affiliation(s)
- Jee Su Suh
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, ON, Canada
| | - Laura M Fiori
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Mohammad Ali
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, ON, Canada
| | - Kate L Harkness
- Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Milita Ramonas
- Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, Hamilton, ON, Canada
| | - Luciano Minuzzi
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, ON, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Stefanie Hassel
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | | | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest, Toronto, ON, Canada
| | | | - Faranak Farzan
- eBrain Lab, School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, BC, Canada
| | - Jane A Foster
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Glenda M MacQueen
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, and Providence Care Hospital, Kingston, ON, Canada
| | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Pharmacogenetics Research Clinic, Toronto, ON, Canada
| | - Sagar V Parikh
- University of Michigan Depression Center, Ann Arbor, MI, United States
| | - Susan Rotzinger
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Roberto B Sassi
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Claudio N Soares
- Departments of Psychiatry and Psychology, Queen's University, and Providence Care Hospital, Kingston, ON, Canada
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto, ON, Canada
| | - Gustavo Turecki
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Benicio N Frey
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, ON, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
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35
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van der Wijk G, Harris JK, Hassel S, Davis AD, Zamyadi M, Arnott SR, Milev R, Lam RW, Frey BN, Hall GB, Müller DJ, Rotzinger S, Kennedy SH, Strother SC, MacQueen GM, Protzner AB. Baseline Functional Connectivity in Resting State Networks Associated with Depression and Remission Status after 16 Weeks of Pharmacotherapy: A CAN-BIND Report. Cereb Cortex 2021; 32:1223-1243. [PMID: 34416758 DOI: 10.1093/cercor/bhab286] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 02/07/2023] Open
Abstract
Understanding the neural underpinnings of major depressive disorder (MDD) and its treatment could improve treatment outcomes. So far, findings are variable and large sample replications scarce. We aimed to replicate and extend altered functional connectivity associated with MDD and pharmacotherapy outcomes in a large, multisite sample. Resting-state fMRI data were collected from 129 patients and 99 controls through the Canadian Biomarker Integration Network in Depression. Symptoms were assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS). Connectivity was measured as correlations between four seeds (anterior and posterior cingulate cortex, insula and dorsolateral prefrontal cortex) and all other brain voxels. Partial least squares was used to compare connectivity prior to treatment between patients and controls, and between patients reaching remission (MADRS ≤ 10) early (within 8 weeks), late (within 16 weeks), or not at all. We replicated previous findings of altered connectivity in patients. In addition, baseline connectivity of the anterior/posterior cingulate and insula seeds differentiated patients with different treatment outcomes. The stability of these differences was established in the largest single-site subsample. Our replication and extension of altered connectivity highlighted previously reported and new differences between patients and controls, and revealed features that might predict remission prior to pharmacotherapy. Trial registration: ClinicalTrials.gov: NCT01655706.
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Affiliation(s)
- Gwen van der Wijk
- Department of Psychology, University of Calgary, Calgary AB T2N 1N4, Canada
| | - Jacqueline K Harris
- Department of Computing Science, University of Alberta, Edmonton AB T6G 2S4, Canada.,Alberta Machine Intelligence Institute, Edmonton AB T5J 3B1, Canada
| | - Stefanie Hassel
- Cumming School of Medicine, Department of Psychiatry, University of Calgary, Calgary AB T2N 4N1, Canada.,Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary AB T2N 4Z6, Canada
| | - Andrew D Davis
- Rotman Research Institute, Baycrest Health Sciences, Toronto ON M6A 2E1, Canada.,Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton ON L8S 4L6, Canada
| | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest Health Sciences, Toronto ON M6A 2E1, Canada
| | - Stephen R Arnott
- Rotman Research Institute, Baycrest Health Sciences, Toronto ON M6A 2E1, Canada
| | - Roumen Milev
- Queen's University, Departments of Psychiatry and Psychology, and Providence Care Hospital, Kingston ON K7L 3N6, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver BC V6T 2A1, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton ON L8S 4L8, Canada.,Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton ON L8N 4N6, Canada
| | - Geoffrey B Hall
- Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton ON L8S 4L6, Canada.,Imaging Research Centre, St. Joseph's Healthcare Hamilton, Hamilton ON L8N 4N6, Canada
| | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto ON M5T 1R8, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto ON M5T 1R8, Canada.,Department of Pharmacology and Toxicology, University of Toronto, Toronto ON M5S 1A8, Canada.,Institute of Medical Sciences, University of Toronto, Toronto ON M5S 1A8, Canada
| | - Susan Rotzinger
- Centre for Mental Health, University Health Network, Toronto ON M5G 1L7, Canada.,Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto ON M5B 1T8, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Toronto ON M5T 1R8, Canada.,Institute of Medical Sciences, University of Toronto, Toronto ON M5S 1A8, Canada.,Centre for Mental Health, University Health Network, Toronto ON M5G 1L7, Canada.,Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto ON M5B 1W8, Canada.,Krembil Research Institute, Toronto Western Hospital, Toronto ON M5T 0S8, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto ON M6A 2E1, Canada.,Department of Medical Biophysics, University of Toronto, Toronto ON M5G 1L7, Canada
| | - Glenda M MacQueen
- Cumming School of Medicine, Department of Psychiatry, University of Calgary, Calgary AB T2N 4N1, Canada.,Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary AB T2N 4Z6, Canada
| | - Andrea B Protzner
- Department of Psychology, University of Calgary, Calgary AB T2N 1N4, Canada.,Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary AB T2N 4Z6, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary AB T2N 4N1, Canada
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36
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Ayyash S, Davis AD, Alders GL, MacQueen G, Strother SC, Hassel S, Zamyadi M, Arnott SR, Harris JK, Lam RW, Milev R, Müller DJ, Kennedy SH, Rotzinger S, Frey BN, Minuzzi L, Hall GB. Exploring brain connectivity changes in major depressive disorder using functional-structural data fusion: A CAN-BIND-1 study. Hum Brain Mapp 2021; 42:4940-4957. [PMID: 34296501 PMCID: PMC8449113 DOI: 10.1002/hbm.25590] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/14/2021] [Accepted: 07/01/2021] [Indexed: 01/23/2023] Open
Abstract
There is a growing interest in examining the wealth of data generated by fusing functional and structural imaging information sources. These approaches may have clinical utility in identifying disruptions in the brain networks that underlie major depressive disorder (MDD). We combined an existing software toolbox with a mathematically dense statistical method to produce a novel processing pipeline for the fast and easy implementation of data fusion analysis (FATCAT‐awFC). The novel FATCAT‐awFC pipeline was then utilized to identify connectivity (conventional functional, conventional structural and anatomically weighted functional connectivy) changes in MDD patients compared to healthy comparison participants (HC). Data were acquired from the Canadian Biomarker Integration Network for Depression (CAN‐BIND‐1) study. Large‐scale resting‐state networks were assessed. We found statistically significant anatomically‐weighted functional connectivity (awFC) group differences in the default mode network and the ventral attention network, with a modest effect size (d < 0.4). Functional and structural connectivity seemed to overlap in significance between one region‐pair within the default mode network. By combining structural and functional data, awFC served to heighten or reduce the magnitude of connectivity differences in various regions distinguishing MDD from HC. This method can help us more fully understand the interconnected nature of structural and functional connectivity as it relates to depression.
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Affiliation(s)
- Sondos Ayyash
- School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.,Department of Psychology Neuroscience & Behaviour, McMaster University, Hamilton, Ontario, Canada
| | - Andrew D Davis
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Gésine L Alders
- Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
| | - Glenda MacQueen
- Mathison Centre for Mental Health Research and Education, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Ontario, Canada
| | - Stefanie Hassel
- Mathison Centre for Mental Health Research and Education, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | | | - Jacqueline K Harris
- Department of Computer Science, University of Alberta, Edmonton, Alberta, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, Providence Care Hospital, Kingston, Ontario, Canada
| | - Daniel J Müller
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Sidney H Kennedy
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Centre for Mental Health, University Health Network, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Susan Rotzinger
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada.,Mood Disorders Treatment and Research Centre and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, Ontario, Canada
| | - Luciano Minuzzi
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada.,Mood Disorders Treatment and Research Centre and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, Ontario, Canada
| | - Geoffrey B Hall
- School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.,Department of Psychology Neuroscience & Behaviour, McMaster University, Hamilton, Ontario, Canada.,Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
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37
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Shakeel MK, Hassel S, Davis AD, Metzak PD, MacQueen GM, Arnott SR, Bray S, Frey BN, Goldstein BI, Hall GB, Harris J, Lam RW, MacIntosh BJ, Milev R, Mueller DJ, Rotzinger S, Strother SC, Wang J, Zamyadi M, Kennedy SH, Addington J, Lebel C. White matter microstructure in youth at risk for serious mental illness: A comparative analysis. Psychiatry Res Neuroimaging 2021; 312:111289. [PMID: 33910139 DOI: 10.1016/j.pscychresns.2021.111289] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 12/01/2020] [Accepted: 04/08/2021] [Indexed: 10/21/2022]
Abstract
Identifying biomarkers of serious mental illness, such as altered white matter microstructure, can aid in early diagnosis and treatment. White matter microstructure was assessed using constrained spherical deconvolution of diffusion imaging data in a sample of 219 youth (age 12-25 years, 64.84% female) across 8 sites. Participants were classified as healthy controls (HC; n = 47), familial risk for serious mental illness (n = 31), mild-symptoms (n = 37), attenuated syndromes (n = 66), or discrete disorder (n = 38) based on clinical assessments. Fractional anisotropy (FA) and mean diffusivity (MD) values were derived for the whole brain white matter, forceps minor, anterior cingulate, anterior thalamic radiations (ATR), inferior fronto-occipital fasciculus, superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF). Linear mixed effects models showed a significant effect of age on MD of the left ATR, left SLF, and left UF, and a significant effect of group on FA for all tracts examined. For most tracts, the discrete disorder group had significantly lower FA than other groups, and the attenuated syndromes group had higher FA compared to HC, with few differences between the remaining groups. White matter differences in MDD are most evident in individuals following illness onset, as few significant differences were observed in the risk phase.
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Affiliation(s)
| | | | - Andrew D Davis
- Department of Psychology, Neuroscience & Behavior, Canada; Imaging Research Center, Canada; Rotman Research Institute, Baycrest Centre, Toronto
| | - Paul D Metzak
- Department of Psychiatry, Hotchkiss Brain Institute, Canada
| | | | | | - Signe Bray
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Department of Radiology, Alberta Children's Hospital Research Institute,; Department of Radiology, Child and Adolescent Imaging Research Program, Calgary, Alberta, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioral Neurosciences, McMaster University, Hamilton, Ontario, Canada; Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton
| | - Benjamin I Goldstein
- Centre for Youth Bipolar Disorder, Sunnybrook Health Sciences Centre, Department of Psychiatry and Department of Pharmacology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Geoffrey B Hall
- Department of Psychology, Neuroscience & Behavior, Canada; Imaging Research Center, Canada
| | - Jacqueline Harris
- Department of Computer Science, University of Alberta, Edmonton, Alberta
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Bradley J MacIntosh
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, and Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Roumen Milev
- Department of Psychology, and Department of Psychiatry (RM), Queen's University and Providence Care Hospital, Kingston
| | - Daniel J Mueller
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Canada
| | - Susan Rotzinger
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Canada; Department of Psychiatry, St. Michael's Hospital, Canada; Department of Psychiatry, Krembil Research Centre, University Health Network, Canada; Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Centre, Toronto; Department of Medical Biophysics, University of Toronto, Canada
| | - JianLi Wang
- Work and Mental Health Research Unit, Institute of Mental Health Research, and School of Epidemiology and Public Health (JW), Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | | | - Sidney H Kennedy
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Canada; Department of Psychiatry, St. Michael's Hospital, Canada; Department of Psychiatry, Krembil Research Centre, University Health Network, Canada; Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario
| | - Jean Addington
- Department of Psychiatry, Hotchkiss Brain Institute, Canada
| | - Catherine Lebel
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Department of Radiology, Alberta Children's Hospital Research Institute,; Department of Radiology, Child and Adolescent Imaging Research Program, Calgary, Alberta, Canada
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38
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Fishman KN, Roberts AC, Orange JB, Sunderland KM, Marras C, Tan B, Steeves T, Kwan D, Lang AE, Grimes D, Levine B, Masellis M, Binns MA, Jog M, Strother SC, Investigators O, McLaughlin PM, Troyer AK. Bilingualism in Parkinson's disease: Relationship to cognition and quality of life. J Clin Exp Neuropsychol 2021; 43:199-212. [PMID: 33827353 DOI: 10.1080/13803395.2021.1902946] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Some studies have found that bilingualism promotes cognitive reserve. OBJECTIVE We aimed to determine whether bilingualism, defined as regularly (i.e. daily) using at least two languages at least since early adulthood, is associated with cognitive advantages in Parkinson's disease (PD) or whether the possible benefits of bilingualism are lost in the context of PD, possibly affecting quality of life (QoL) and independence. METHOD Participants with idiopathic PD (n = 140, mean age = 67.9 [SD = 6.4], 78% men) completed standard neuropsychological tasks evaluating attention/working memory, language, executive function, memory, and visuospatial ability, as well as measures of wellbeing and functional independence. RESULTS Bilinguals with PD (n = 21) performed worse than monolinguals with PD (n = 92) on attention/working memory and language measures. The between-group differences in attention/working memory were restricted to verbally-based measures. When measured along a continuum, a higher degree of bilingualism was correlated with lower scores on measures of attention/working memory and language. There were no group differences in self- or informant-reported cognitive decline, PD health-related QoL, or functional independence. CONCLUSIONS Bilingualism in PD was not associated with better cognitive performance. Lower scores on language-based measures may reflect a distributed fund of linguistic information across more than one language, lower language proficiency in English, and/or other cultural artifacts. Furthermore, using normative data specific to the dominant language spoken or conducting neuropsychological testing in participants' self-reported most proficient language may enhance additional studies addressing this topic. Future research may also examine the roles of bilingualism over time and across other neurodegenerative diseases with and without EF impairment to illuminate further the impact of bilingualism on cognition and QoL, and shape culturally and linguistically diverse research and clinical care.
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Affiliation(s)
- Keera N Fishman
- University of Ottawa, Ottawa, Ontario, Canada.,Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Angela C Roberts
- Northwestern University, Evanston, Illinois, USA.,, Western University, London, Ontario, Canada
| | - J B Orange
- , Western University, London, Ontario, Canada
| | | | - Connie Marras
- , University of Toronto, Toronto, Ontario, Canada.,Toronto Western Hospital, Toronto, Ontario, Canada
| | - Brian Tan
- Baycrest Health Sciences, Toronto, Ontario, Canada
| | | | - Donna Kwan
- Queen's University, Toronto, Ontario, Canada
| | - Anthony E Lang
- , University of Toronto, Toronto, Ontario, Canada.,Toronto Western Hospital, Toronto, Ontario, Canada
| | - David Grimes
- University of Ottawa, Ottawa, Ontario, Canada.,The Ottawa Hospital, Ottawa, Ontario, Canada
| | - Brian Levine
- Baycrest Health Sciences, Toronto, Ontario, Canada.,, University of Toronto, Toronto, Ontario, Canada
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Malcolm A Binns
- Baycrest Health Sciences, Toronto, Ontario, Canada.,, University of Toronto, Toronto, Ontario, Canada
| | - Mandar Jog
- , Western University, London, Ontario, Canada
| | - Stephen C Strother
- Baycrest Health Sciences, Toronto, Ontario, Canada.,, University of Toronto, Toronto, Ontario, Canada
| | | | - Paula M McLaughlin
- Queen's University, Toronto, Ontario, Canada.,Nova Scotia Health Authority, Halifax, Nova Scotia, Canada
| | - Angela K Troyer
- Baycrest Health Sciences, Toronto, Ontario, Canada.,, University of Toronto, Toronto, Ontario, Canada
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39
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Theyers AE, Zamyadi M, O'Reilly M, Bartha R, Symons S, MacQueen GM, Hassel S, Lerch JP, Anagnostou E, Lam RW, Frey BN, Milev R, Müller DJ, Kennedy SH, Scott CJM, Strother SC, Arnott SR. Multisite Comparison of MRI Defacing Software Across Multiple Cohorts. Front Psychiatry 2021; 12:617997. [PMID: 33716819 PMCID: PMC7943842 DOI: 10.3389/fpsyt.2021.617997] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 02/03/2021] [Indexed: 01/26/2023] Open
Abstract
With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3-85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3-20 years) for afni_refacer and the oldest (44-85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files.
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Affiliation(s)
- Athena E Theyers
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, ON, Canada
| | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, ON, Canada
| | | | - Robert Bartha
- Department of Medical Biophysics, Robarts Research Institute, Western University, London, ON, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Glenda M MacQueen
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Stefanie Hassel
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Jason P Lerch
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.,Mood Disorders Program, St. Joseph's Healthcare, Hamilton, ON, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, Providence Care Hospital, Kingston, ON, Canada
| | - Daniel J Müller
- Molecular Brain Science, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Department of Psychiatry, Krembil Research Centre, University Health Network, Toronto, ON, Canada.,Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada.,Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Christopher J M Scott
- LC Campbell Cognitive Neurology Research Unit, Toronto, ON, Canada.,Heart & Stroke Foundation Centre for Stroke Recovery, Toronto, ON, Canada.,Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Stephen R Arnott
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, ON, Canada
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40
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Ozzoude M, Ramirez J, Raamana PR, Holmes MF, Walker K, Scott CJM, Gao F, Goubran M, Kwan D, Tartaglia MC, Beaton D, Saposnik G, Hassan A, Lawrence-Dewar J, Dowlatshahi D, Strother SC, Symons S, Bartha R, Swartz RH, Black SE. Cortical Thickness Estimation in Individuals With Cerebral Small Vessel Disease, Focal Atrophy, and Chronic Stroke Lesions. Front Neurosci 2020; 14:598868. [PMID: 33381009 PMCID: PMC7768006 DOI: 10.3389/fnins.2020.598868] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 11/24/2020] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Regional changes to cortical thickness in individuals with neurodegenerative and cerebrovascular diseases (CVD) can be estimated using specialized neuroimaging software. However, the presence of cerebral small vessel disease, focal atrophy, and cortico-subcortical stroke lesions, pose significant challenges that increase the likelihood of misclassification errors and segmentation failures. PURPOSE The main goal of this study was to examine a correction procedure developed for enhancing FreeSurfer's (FS's) cortical thickness estimation tool, particularly when applied to the most challenging MRI obtained from participants with chronic stroke and CVD, with varying degrees of neurovascular lesions and brain atrophy. METHODS In 155 CVD participants enrolled in the Ontario Neurodegenerative Disease Research Initiative (ONDRI), FS outputs were compared between a fully automated, unmodified procedure and a corrected procedure that accounted for potential sources of error due to atrophy and neurovascular lesions. Quality control (QC) measures were obtained from both procedures. Association between cortical thickness and global cognitive status as assessed by the Montreal Cognitive Assessment (MoCA) score was also investigated from both procedures. RESULTS Corrected procedures increased "Acceptable" QC ratings from 18 to 76% for the cortical ribbon and from 38 to 92% for tissue segmentation. Corrected procedures reduced "Fail" ratings from 11 to 0% for the cortical ribbon and 62 to 8% for tissue segmentation. FS-based segmentation of T1-weighted white matter hypointensities were significantly greater in the corrected procedure (5.8 mL vs. 15.9 mL, p < 0.001). The unmodified procedure yielded no significant associations with global cognitive status, whereas the corrected procedure yielded positive associations between MoCA total score and clusters of cortical thickness in the left superior parietal (p = 0.018) and left insula (p = 0.04) regions. Further analyses with the corrected cortical thickness results and MoCA subscores showed a positive association between left superior parietal cortical thickness and Attention (p < 0.001). CONCLUSION These findings suggest that correction procedures which account for brain atrophy and neurovascular lesions can significantly improve FS's segmentation results and reduce failure rates, thus maximizing power by preventing the loss of our important study participants. Future work will examine relationships between cortical thickness, cerebral small vessel disease, and cognitive dysfunction due to neurodegenerative disease in the ONDRI study.
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Affiliation(s)
- Miracle Ozzoude
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | | | - Melissa F. Holmes
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Kirstin Walker
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher J. M. Scott
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Fuqiang Gao
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queens University, Kingston, ON, Canada
| | - Maria C. Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
- Division of Neurology, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Gustavo Saposnik
- Stroke Outcomes and Decision Neuroscience Research Unit, Division of Neurology, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada
| | - Ayman Hassan
- Thunder Bay Regional Health Research Institute, Thunder Bay, ON, Canada
| | | | - Dariush Dowlatshahi
- Department of Medicine (Neurology), Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Stephen C. Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Robert Bartha
- Centre for Functional and Metabolic Mapping, Department of Medical Biophysics, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Richard H. Swartz
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Sandra E. Black
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
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41
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Sakurai R, Faria‐Pieruccini F, Dilliott AA, Hegele R, Tartaglia C, McLaughlin P, Binns M, Blue K, Cornish B, Sunderland KM, Beaton D, Haddad SM, Tan B, Swartz RH, Kwan D, Masellis M, Ramirez J, Roberts AC, Black SE, Symons S, Strother SC, Borrie M, Pasternak SH, Freedman M, Bartha R, Lang A, Munoz D, McIlroy B, Montero‐Odasso M. Abnormal brain structure mediates the association between ApoE4 and slow gait among patients with pathological cognitive impairment: Results from the Ontario Neurodegenerative Research Initiative. Alzheimers Dement 2020. [DOI: 10.1002/alz.044540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Ryota Sakurai
- Tokyo Metropolitan Institute of Gerontology Tokyo Japan
| | | | | | | | | | - Paula McLaughlin
- Ontario Neurodegenerative Disease Research Initiative Toronto ON Canada
| | | | - Korbin Blue
- Gait and Brain Laboratory, Parkwood Institute London ON Canada
| | | | | | | | | | - Brian Tan
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | | | - Donna Kwan
- Ontario Neurodegenerative Disease Research Initiative Toronto ON Canada
| | | | - Joel Ramirez
- LC Campbell Cognitive Neurology Research Unit Toronto ON Canada
| | | | - Sandra E. Black
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program Sunnybrook Health Sciences Centre Toronto ON Canada
| | - Sean Symons
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | | | | | | | | | | | - Anthony Lang
- Movement Disorder Clinic, Toronto Western Hospital University Health Network Toronto ON Canada
| | | | | | - Manuel Montero‐Odasso
- Schulich School of Medicine & Dentistry, Division of Geriatric Medicine Western University London ON Canada
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42
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Haddad SMH, Scott CJ, Arnott SR, Ozzoude M, Strother SC, Black SE, Borrie M, Finger E, Tartaglia MC, Kwan D, Beaton D, Symons S, Soddu A, Menon RS, Montero‐Odasso M, Bartha R. Reduced neuronal activity in Alzheimer’s disease and mild cognitive impairment measured by resting state fMRI. Alzheimers Dement 2020. [DOI: 10.1002/alz.046067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | | | - Miracle Ozzoude
- Sunnybrook Research Institute University of Toronto Toronto ON Canada
| | | | - Sandra E. Black
- L.C.Campbell Cognitive Neurology Research Unit Hurvitz Brain Sciences Research Program Sunnybrook Health Sciences Centre Toronto ON Canada
| | | | | | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases University of Toronto Toronto ON Canada
| | - Donna Kwan
- Ontario Neurodegenerative Disease Research Initiative Toronto ON Canada
| | | | - Sean Symons
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | | | - Ravi S. Menon
- Centre for Functional and Metabolic Mapping Robarts Research Institute London ON Canada
| | - Manuel Montero‐Odasso
- Schulich School of Medicine& Dentistry Division of Geriatric Medicine Western University London ON Canada
| | - Robert Bartha
- Robarts Research Institute Western University London ON Canada
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43
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Tang‐Wai DF, Strother SC, Pugh B, Spring R, Vica C, Nourhaghighi N, Gee T, Pisterzi L, Greenberg B, Coahran M, Apatsidou A, Ding J, Kumar S, Black SE, Freedman M. Toronto dementia research alliance (TDRA) dementia clinical‐research platform: An example of research embedded into clinical care. Alzheimers Dement 2020. [DOI: 10.1002/alz.041756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- David F. Tang‐Wai
- University of Toronto Toronto ON Canada
- University Health Network Toronto ON Canada
- Toronto Dementia Research Alliance Toronto ON Canada
| | - Stephen C. Strother
- Toronto Dementia Research Alliance Toronto ON Canada
- Baycrest Health Sciences Toronto ON Canada
- Rotman Research Institute Baycrest Toronto ON Canada
| | - Bradley Pugh
- Toronto Dementia Research Alliance Toronto ON Canada
- Baycrest Health Sciences Toronto ON Canada
- Rotman Research Institute Baycrest Toronto ON Canada
| | - Robyn Spring
- Toronto Dementia Research Alliance Toronto ON Canada
- Baycrest Health Sciences Toronto ON Canada
| | - Carmina Vica
- Toronto Dementia Research Alliance Toronto ON Canada
- Rotman Research Institute Baycrest Toronto ON Canada
| | - Nima Nourhaghighi
- Toronto Dementia Research Alliance Toronto ON Canada
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | - Tom Gee
- Toronto Dementia Research Alliance Toronto ON Canada
- Indoc Research Toronto ON Canada
| | - Luca Pisterzi
- Toronto Dementia Research Alliance Toronto ON Canada
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | | | - Margaret Coahran
- Toronto Dementia Research Alliance Toronto ON Canada
- Centre for Addictions and Mental Health Toronto ON Canada
| | - Areti Apatsidou
- University Health Network Toronto ON Canada
- Toronto Dementia Research Alliance Toronto ON Canada
| | - Jane Ding
- Toronto Dementia Research Alliance Toronto ON Canada
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | - Sanjeev Kumar
- University of Toronto Toronto ON Canada
- Toronto Dementia Research Alliance Toronto ON Canada
- Centre for Addiction and Mental Health Toronto ON Canada
| | - Sandra E. Black
- University of Toronto Toronto ON Canada
- Toronto Dementia Research Alliance Toronto ON Canada
- Sunnybrook Health Sciences Centre Toronto ON Canada
- Sunnybrook Research Institute Toronto ON Canada
| | - Morris Freedman
- University of Toronto Toronto ON Canada
- Toronto Dementia Research Alliance Toronto ON Canada
- Baycrest Health Sciences Toronto ON Canada
- Rotman Research Institute Baycrest Toronto ON Canada
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44
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Haddad SMH, Scott CJ, Ozzoude M, Holmes MF, Arnott SR, Nanayakkara ND, Kwan D, Tan B, Casaubon L, Mandzia J, Sahlas DJ, Saposnik G, Hassan A, Black SE, Dowlatshahi D, Strother SC, Swartz RH, Symons S, Montero‐Odasso M, Bartha R. Fractional anisotropy in white matter hyperintensities is linked to associative memory performance. Alzheimers Dement 2020. [DOI: 10.1002/alz.045489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | - Miracle Ozzoude
- Sunnybrook Research Institute University of Toronto Toronto ON Canada
| | | | | | | | - Donna Kwan
- Ontario Neurodegenerative Disease Research Initiative Toronto ON Canada
| | - Brian Tan
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | | | | | | | | | - Ayman Hassan
- Thunder Bay Regional Health Sciences Centre Thunder Bay ON Canada
| | - Sandra E. Black
- L.C.Campbell Cognitive Neurology Research Unit Hurvitz Brain Sciences Research Program Sunnybrook Health Sciences Centre Toronto ON Canada
| | | | | | | | - Sean Symons
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | - Manuel Montero‐Odasso
- Schulich School of Medicine& Dentistry Division of Geriatric Medicine Western University London ON Canada
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45
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Kapustin D, Zarei S, Wang W, Black SE, Finger E, Freedman M, Hink H, Kwan D, Lang A, Masellis M, McLaughlin P, Pollock BG, Saposnik G, Strother SC, Sunderland KM, Swartz RH, Tan B, Tang‐Wai DF, Tartaglia C, Turnbull J, Zinman L, Rajji TK, Fischer CE, Kumar S. Neuropsychiatric symptom burden across neurodegenerative disorders and its association with function. Alzheimers Dement 2020. [DOI: 10.1002/alz.047279] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Daniel Kapustin
- University of Toronto ‐ Faculty of Medicine Toronto ON Canada
| | - Shadi Zarei
- Centre for Addiction and Mental Health Toronto ON Canada
| | - Wei Wang
- Centre for Addiction and Mental Health Toronto ON Canada
| | - Sandra E. Black
- L.C.Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program Sunnybrook Health Sciences Centre Toronto ON Canada
| | | | | | | | - Donna Kwan
- Ontario Neurodegenerative Disease Research Initiative Toronto ON Canada
| | | | | | - Paula McLaughlin
- Ontario Neurodegenerative Disease Research Initiative Toronto ON Canada
| | - Bruce G. Pollock
- Campbell Family Mental Health Research Institute, Division of Geriatric Psychiatry Centre for Addiction and Mental Health Toronto ON Canada
| | | | | | | | | | - Brian Tan
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | | | | | | | - Lorne Zinman
- Sunnybrook Health Sciences Centre Toronto ON Canada
| | - Tarek K. Rajji
- Centre for Addiction and Mental Health Toronto ON Canada
| | - Corinne E. Fischer
- Keenan Research Centre for Biomedical Research St. Michael’s Hospital Toronto ON Canada
| | - Sanjeev Kumar
- Centre for Addiction and Mental Health Toronto ON Canada
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46
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Raamana PR, Strother SC. Does size matter? The relationship between predictive power of single-subject morphometric networks to spatial scale and edge weight. Brain Struct Funct 2020; 225:2475-2493. [DOI: 10.1007/s00429-020-02136-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Accepted: 08/24/2020] [Indexed: 11/30/2022]
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47
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Nørgaard M, Ganz M, Svarer C, Frokjaer VG, Greve DN, Strother SC, Knudsen GM. Different preprocessing strategies lead to different conclusions: A [ 11C]DASB-PET reproducibility study. J Cereb Blood Flow Metab 2020; 40:1902-1911. [PMID: 31575336 PMCID: PMC7446563 DOI: 10.1177/0271678x19880450] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Positron emission tomography (PET) neuroimaging provides unique possibilities to study biological processes in vivo under basal and interventional conditions. For quantification of PET data, researchers commonly apply different arrays of sequential data analytic methods ("preprocessing pipeline"), but it is often unknown how the choice of preprocessing affects the final outcome. Here, we use an available data set from a double-blind, randomized, placebo-controlled [11C]DASB-PET study as a case to evaluate how the choice of preprocessing affects the outcome of the study. We tested the impact of 384 commonly used preprocessing strategies on a previously reported positive association between the change from baseline in neocortical serotonin transporter binding determined with [11C]DASB-PET, and change in depressive symptoms, following a pharmacological sex hormone manipulation intervention in 30 women. The two preprocessing steps that were most critical for the outcome were motion correction and kinetic modeling of the dynamic PET data. We found that 36% of the applied preprocessing strategies replicated the originally reported finding (p < 0.05). For preprocessing strategies with motion correction, the replication percentage was 72%, whereas it was 0% for strategies without motion correction. In conclusion, the choice of preprocessing strategy can have a major impact on a study outcome.
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Affiliation(s)
- Martin Nørgaard
- Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.,Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Melanie Ganz
- Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.,Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Claus Svarer
- Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Vibe G Frokjaer
- Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Douglas N Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Stephen C Strother
- Rotman Research Institute, Baycrest, Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Gitte M Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.,Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
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48
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Ramirez J, Holmes MF, Scott CJM, Ozzoude M, Adamo S, Szilagyi GM, Goubran M, Gao F, Arnott SR, Lawrence-Dewar JM, Beaton D, Strother SC, Munoz DP, Masellis M, Swartz RH, Bartha R, Symons S, Black SE. Ontario Neurodegenerative Disease Research Initiative (ONDRI): Structural MRI Methods and Outcome Measures. Front Neurol 2020; 11:847. [PMID: 32849254 PMCID: PMC7431907 DOI: 10.3389/fneur.2020.00847] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 07/07/2020] [Indexed: 01/18/2023] Open
Abstract
The Ontario Neurodegenerative Research Initiative (ONDRI) is a 3 years multi-site prospective cohort study that has acquired comprehensive multiple assessment platform data, including 3T structural MRI, from neurodegenerative patients with Alzheimer's disease, mild cognitive impairment, Parkinson's disease, amyotrophic lateral sclerosis, frontotemporal dementia, and cerebrovascular disease. This heterogeneous cross-section of patients with complex neurodegenerative and neurovascular pathologies pose significant challenges for standard neuroimaging tools. To effectively quantify regional measures of normal and pathological brain tissue volumes, the ONDRI neuroimaging platform implemented a semi-automated MRI processing pipeline that was able to address many of the challenges resulting from this heterogeneity. The purpose of this paper is to serve as a reference and conceptual overview of the comprehensive neuroimaging pipeline used to generate regional brain tissue volumes and neurovascular marker data that will be made publicly available online.
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Affiliation(s)
- Joel Ramirez
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Melissa F Holmes
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher J M Scott
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Miracle Ozzoude
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Sabrina Adamo
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Gregory M Szilagyi
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Fuqiang Gao
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | | | | | - Derek Beaton
- Rotman Research Institute, Baycrest, Toronto, ON, Canada
| | - Stephen C Strother
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,Rotman Research Institute, Baycrest, Toronto, ON, Canada
| | - Douglas P Munoz
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON, Canada
| | - Robert Bartha
- Department of Medical Biophysics, Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Sean Symons
- Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON, Canada
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49
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Ramirez J, Dilliott AA, Binns MA, Breen DP, Evans EC, Beaton D, McLaughlin PM, Kwan D, Holmes MF, Ozzoude M, Scott CJM, Strother SC, Symons S, Swartz RH, Grimes D, Jog M, Masellis M, Black SE, Joutel A, Marras C, Rogaeva E, Hegele RA, Lang AE. Parkinson's Disease, NOTCH3 Genetic Variants, and White Matter Hyperintensities. Mov Disord 2020; 35:2090-2095. [PMID: 32573853 DOI: 10.1002/mds.28171] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 05/01/2020] [Accepted: 05/26/2020] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND White matter hyperintensities (WMH) on magnetic resonance imaging may influence clinical presentation in patients with Parkinson's disease (PD), although their significance and pathophysiological origins remain unresolved. Studies examining WMH have identified pathogenic variants in NOTCH3 as an underlying cause of inherited forms of cerebral small vessel disease. METHODS We examined NOTCH3 variants, WMH volumes, and clinical correlates in 139 PD patients in the Ontario Neurodegenerative Disease Research Initiative cohort. RESULTS We identified 13 PD patients (~9%) with rare (<1% of general population), nonsynonymous NOTCH3 variants. Bayesian linear modeling demonstrated a doubling of WMH between variant negative and positive patients (3.1 vs. 6.9 mL), with large effect sizes for periventricular WMH (d = 0.8) and lacunes (d = 1.2). Negative correlations were observed between WMH and global cognition (r = -0.2). CONCLUSION The NOTCH3 rare variants in PD may significantly contribute to increased WMH burden, which in turn may negatively influence cognition. © 2020 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Joel Ramirez
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Allison A Dilliott
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Malcolm A Binns
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - David P Breen
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, United Kingdom.,Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Emily C Evans
- Mississauga Academy of Medicine, University of Toronto Mississauga, Mississauga, Ontario, Canada
| | - Derek Beaton
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Paula M McLaughlin
- Queen's University, Centre for Neuroscience Studies, Kingston, Ontario.,Nova Scotia Health Authority, Dalhousie University, Department of Medicine-Geriatrics, Halifax, Nova Scotia, Canada
| | - Donna Kwan
- Queen's University, Centre for Neuroscience Studies, Kingston, Ontario
| | - Melissa F Holmes
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Miracle Ozzoude
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Christopher J M Scott
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | | | - Sean Symons
- Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Ontario, Canada
| | - David Grimes
- University of Ottawa Brain and Mind Research Institute, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Mandar Jog
- Department of Clinical Neurological Sciences, Western University, London, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Ontario, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Ontario, Canada
| | - Anne Joutel
- Institute of Psychiatry and Neuroscience of Paris- Institut national de la santé et de la recherche médicale (INSERM), Paris Descartes University, Paris, France
| | - Connie Marras
- Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Ekaterina Rogaeva
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Ontario, Canada
| | - Robert A Hegele
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Anthony E Lang
- Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, Ontario, Canada
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50
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McLaughlin PM, Sunderland KM, Beaton D, Binns MA, Kwan D, Levine B, Orange JB, Peltsch AJ, Roberts AC, Strother SC, Troyer AK. The Quality Assurance and Quality Control Protocol for Neuropsychological Data Collection and Curation in the Ontario Neurodegenerative Disease Research Initiative (ONDRI) Study. Assessment 2020; 28:1267-1286. [PMID: 32321297 DOI: 10.1177/1073191120913933] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
As large research initiatives designed to generate big data on clinical cohorts become more common, there is an increasing need to establish standard quality assurance (QA; preventing errors) and quality control (QC; identifying and correcting errors) procedures for critical outcome measures. The present article describes the QA and QC approach developed and implemented for the neuropsychology data collected as part of the Ontario Neurodegenerative Disease Research Initiative study. We report on the efficacy of our approach and provide data quality metrics. Our findings demonstrate that even with a comprehensive QA protocol, the proportion of data errors still can be high. Additionally, we show that several widely used neuropsychological measures are particularly susceptible to error. These findings highlight the need for large research programs to put into place active, comprehensive, and separate QA and QC procedures before, during, and after protocol deployment. Detailed recommendations and considerations for future studies are provided.
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Affiliation(s)
- Paula M McLaughlin
- Queen's University, Kingston, Ontario, Canada.,Dalhousie University, Halifax, Nova Scotia, Canada
| | | | - Derek Beaton
- Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Malcolm A Binns
- Baycrest Health Sciences, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada
| | - Donna Kwan
- Queen's University, Kingston, Ontario, Canada
| | - Brian Levine
- Baycrest Health Sciences, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada
| | | | | | - Angela C Roberts
- Western University, London, Ontario, Canada.,Northwestern University, Evanston, IL, USA
| | - Stephen C Strother
- Baycrest Health Sciences, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada
| | - Angela K Troyer
- Baycrest Health Sciences, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada
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