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de Vrij FM, Bouwkamp CG, Gunhanlar N, Shpak G, Lendemeijer B, Baghdadi M, Gopalakrishna S, Ghazvini M, Li TM, Quadri M, Olgiati S, Breedveld GJ, Coesmans M, Mientjes E, de Wit T, Verheijen FW, Beverloo HB, Cohen D, Kok RM, Bakker PR, Nijburg A, Spijker AT, Haffmans PMJ, Hoencamp E, Bergink V, Vorstman JA, Wu T, Olde Loohuis LM, Amin N, Langen CD, Hofman A, Hoogendijk WJ, van Duijn CM, Ikram MA, Vernooij MW, Tiemeier H, Uitterlinden AG, Elgersma Y, Distel B, Gribnau J, White T, Bonifati V, Kushner SA. Candidate CSPG4 mutations and induced pluripotent stem cell modeling implicate oligodendrocyte progenitor cell dysfunction in familial schizophrenia. Mol Psychiatry 2019; 24:757-771. [PMID: 29302076 PMCID: PMC6755981 DOI: 10.1038/s41380-017-0004-2] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Revised: 09/24/2017] [Accepted: 11/01/2017] [Indexed: 01/09/2023]
Abstract
Schizophrenia is highly heritable, yet its underlying pathophysiology remains largely unknown. Among the most well-replicated findings in neurobiological studies of schizophrenia are deficits in myelination and white matter integrity; however, direct etiological genetic and cellular evidence has thus far been lacking. Here, we implement a family-based approach for genetic discovery in schizophrenia combined with functional analysis using induced pluripotent stem cells (iPSCs). We observed familial segregation of two rare missense mutations in Chondroitin Sulfate Proteoglycan 4 (CSPG4) (c.391G > A [p.A131T], MAF 7.79 × 10-5 and c.2702T > G [p.V901G], MAF 2.51 × 10-3). The CSPG4A131T mutation was absent from the Swedish Schizophrenia Exome Sequencing Study (2536 cases, 2543 controls), while the CSPG4V901G mutation was nominally enriched in cases (11 cases vs. 3 controls, P = 0.026, OR 3.77, 95% CI 1.05-13.52). CSPG4/NG2 is a hallmark protein of oligodendrocyte progenitor cells (OPCs). iPSC-derived OPCs from CSPG4A131T mutation carriers exhibited abnormal post-translational processing (P = 0.029), subcellular localization of mutant NG2 (P = 0.007), as well as aberrant cellular morphology (P = 3.0 × 10-8), viability (P = 8.9 × 10-7), and myelination potential (P = 0.038). Moreover, transfection of healthy non-carrier sibling OPCs confirmed a pathogenic effect on cell survival of both the CSPG4A131T (P = 0.006) and CSPG4V901G (P = 3.4 × 10-4) mutations. Finally, in vivo diffusion tensor imaging of CSPG4A131T mutation carriers demonstrated a reduction of brain white matter integrity compared to unaffected sibling and matched general population controls (P = 2.2 × 10-5). Together, our findings provide a convergence of genetic and functional evidence to implicate OPC dysfunction as a candidate pathophysiological mechanism of familial schizophrenia.
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Affiliation(s)
- Femke M de Vrij
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Christian G Bouwkamp
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Nilhan Gunhanlar
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Guy Shpak
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Bas Lendemeijer
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Maarouf Baghdadi
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Mehrnaz Ghazvini
- Department of Developmental Biology, and Erasmus MC iPS Facility, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Tracy M Li
- Department of Developmental Biology, and Erasmus MC iPS Facility, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Marialuisa Quadri
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Simone Olgiati
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Guido J Breedveld
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Michiel Coesmans
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
- Delta Psychiatric Center, Poortugaal, The Netherlands
| | - Edwin Mientjes
- Department of Neuroscience, Erasmus Medical Center, Rotterdam, The Netherlands
- ENCORE Expertise Center for Neurodevelopmental Disorders, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ton de Wit
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Frans W Verheijen
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - H Berna Beverloo
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Dan Cohen
- Mental Health Care Organization North-Holland North, Heerhugowaard, The Netherlands
| | - Rob M Kok
- Parnassia Psychiatric Institute, The Hague, The Netherlands
| | - P Roberto Bakker
- Department of Psychiatry and Psychology, School of Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
- Psychiatric Center GGZ Centraal, Amersfoort, The Netherlands
| | - Aviva Nijburg
- Parnassia Psychiatric Institute, The Hague, The Netherlands
| | | | - P M Judith Haffmans
- Faculty of Social and Behavioral Sciences Clinical, Health and Neuro Psychology, Department of Affective Disorders, PsyQ, Leiden University, Leiden, The Netherlands
| | - Erik Hoencamp
- Parnassia Psychiatric Institute, The Hague, The Netherlands
- Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - Veerle Bergink
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jacob A Vorstman
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Psychiatry, The Hospital for Sick Children and University of Toronto, Toronto, Ontario, Canada
- Program in Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Timothy Wu
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Loes M Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Carolyn D Langen
- Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands
- Biomedical Imaging Group Rotterdam, Departments of Radiology & Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Witte J Hoogendijk
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - M Arfan Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ype Elgersma
- Department of Neuroscience, Erasmus Medical Center, Rotterdam, The Netherlands
- ENCORE Expertise Center for Neurodevelopmental Disorders, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ben Distel
- Department of Medical Biochemistry, Academic Medical Centre, Amsterdam, The Netherlands
| | - Joost Gribnau
- Department of Developmental Biology, and Erasmus MC iPS Facility, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Tonya White
- Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Vincenzo Bonifati
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Steven A Kushner
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands.
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Langen CD, Cremers LGM, de Groot M, White T, Ikram MA, Niessen WJ, Vernooij MW. Disconnection due to white matter hyperintensities is associated with lower cognitive scores. Neuroimage 2018; 183:745-756. [PMID: 30144572 DOI: 10.1016/j.neuroimage.2018.08.037] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 07/27/2018] [Accepted: 08/16/2018] [Indexed: 11/17/2022] Open
Abstract
Previous studies have linked global burden of age-related white matter hyperintensities (WMHs) to cognitive impairment. We aimed to determine how WMHs in individual white matter connections relate to measures of cognitive function relative to measures of connectivity which do not take WMHs into account. Brain connectivity and WMH-related disconnectivity were derived from 3714 participants of the population-based Rotterdam Study. Connectivity was represented by the structural connectome, which was defined using diffusion tensor data, whereas the disconnectome represented disconnectivity due to WMH. The relationship between (dis)connectivity and cognitive measures was estimated using linear regression. We found that lower disconnectivity and higher connectivity corresponded to better cognitive function. There were many more significant associations with cognitive function in the disconnectome than in the connectome. Most connectome associations attenuated when disconnection was included in the model. WMH-related disconnectivity was especially related to worse executive functioning. Better cognitive speed corresponded to higher connectivity in specific connections independent of WMH presence. We conclude that WMH-related disconnectivity explains more variation in cognitive function than does connectivity. Efficient wiring in specific connections is important to information processing speed independent of WMH presence.
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Affiliation(s)
- Carolyn D Langen
- Department of Radiology and Nuclear Medicine, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands; Department of Medical Informatics, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands.
| | - Lotte G M Cremers
- Department of Radiology and Nuclear Medicine, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands.
| | - Marius de Groot
- Department of Radiology and Nuclear Medicine, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands; Department of Medical Informatics, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands.
| | - Tonya White
- Department of Radiology and Nuclear Medicine, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands; Department of Child and Adolescent Psychiatry, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands.
| | - M Arfan Ikram
- Department of Radiology and Nuclear Medicine, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands.
| | - Wiro J Niessen
- Department of Radiology and Nuclear Medicine, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands; Department of Medical Informatics, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands; Imaging Physics, Faculty of Applied Sciences, PO Box 5046, 2600GA, Delft University of Technology, Delft, the Netherlands.
| | - Meike W Vernooij
- Department of Radiology and Nuclear Medicine, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC, PO Box 2040, 3000CA, Rotterdam, the Netherlands.
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Langen CD, Muetzel R, Blanken L, van der Lugt A, Tiemeier H, Verhulst F, Niessen WJ, White T. Differential patterns of age-related cortical and subcortical functional connectivity in 6-to-10 year old children: A connectome-wide association study. Brain Behav 2018; 8:e01031. [PMID: 29961267 PMCID: PMC6085897 DOI: 10.1002/brb3.1031] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 05/15/2018] [Accepted: 05/16/2018] [Indexed: 12/21/2022] Open
Abstract
INTRODUCTION Typical brain development is characterized by specific patterns of maturation of functional networks. Cortico-cortical connectivity generally increases, whereas subcortico-cortical connections often decrease. Little is known about connectivity changes amongst different subcortical regions in typical development. METHODS This study examined age- and gender-related differences in functional connectivity between and within cortical and subcortical regions using two different approaches. The participants included 411 six- to ten-year-old typically developing children sampled from the population-based Generation R study. Functional connectomes were defined in native space using regions of interest from subject-specific FreeSurfer segmentations. Connections were defined as: (a) the correlation between regional mean time-series; and (b) the focal maximum of voxel-wise correlations within FreeSurfer regions. The association of age and gender with each functional connection was determined using linear regression. The preprocessing included the exclusion of children with excessive head motion and scrubbing to reduce the influence of minor head motion during scanning. RESULTS Cortico-cortical associations echoed previous findings that connectivity shifts from short to long-range with age. Subcortico-cortical associations with age were primarily negative in the focal network approach but were both positive and negative in the mean time-series network approach. Between subcortical regions, age-related associations were negative in both network approaches. Few connections had significant associations with gender. CONCLUSIONS The present study replicates previously reported age-related patterns of connectivity in a relatively narrow age-range of children. In addition, we extended these findings by demonstrating decreased connectivity within the subcortex with increasing age. Lastly, we show the utility of a more focal approach that challenges the spatial assumptions made by the traditional mean time series approach.
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Affiliation(s)
- Carolyn D Langen
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.,Department of Medical Informatics, Erasmus MC, Rotterdam, The Netherlands
| | - Ryan Muetzel
- Department of Child and Adolescent Psychiatry, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.,The Generation R Study Group, Erasmus MC, Rotterdam, The Netherlands
| | - Laura Blanken
- Department of Child and Adolescent Psychiatry, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.,The Generation R Study Group, Erasmus MC, Rotterdam, The Netherlands
| | - Aad van der Lugt
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Frank Verhulst
- Department of Child and Adolescent Psychiatry, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Wiro J Niessen
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.,Department of Medical Informatics, Erasmus MC, Rotterdam, The Netherlands.,Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - Tonya White
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.,Department of Child and Adolescent Psychiatry, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
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Langen CD, Zonneveld HI, White T, Huizinga W, Cremers LGM, de Groot M, Ikram MA, Niessen WJ, Vernooij MW. White matter lesions relate to tract-specific reductions in functional connectivity. Neurobiol Aging 2016; 51:97-103. [PMID: 28063366 DOI: 10.1016/j.neurobiolaging.2016.12.004] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [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: 08/04/2016] [Revised: 10/19/2016] [Accepted: 12/05/2016] [Indexed: 11/30/2022]
Abstract
White matter lesions play a role in cognitive decline and dementia. One presumed pathway is through disconnection of functional networks. Little is known about location-specific effects of lesions on functional connectivity. This study examined location-specific effects within anatomically-defined white matter tracts in 1584 participants of the Rotterdam Study, aged 50-95. Tracts were delineated from diffusion magnetic resonance images using probabilistic tractography. Lesions were segmented on fluid-attenuated inversion recovery images. Functional connectivity was defined across each tract on resting-state functional magnetic resonance images by using gray matter parcellations corresponding to the tract ends and calculating the correlation of the mean functional activity between the gray matter regions. A significant relationship between both local and brain-wide lesion load and tract-specific functional connectivity was found in several tracts using linear regressions, also after Bonferroni correction. Indirect connectivity analyses revealed that tract-specific functional connectivity is affected by lesions in several tracts simultaneously. These results suggest that local white matter lesions can decrease tract-specific functional connectivity, both in direct and indirect connections.
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Affiliation(s)
- Carolyn D Langen
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Medical Informatics, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Hazel I Zonneveld
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Tonya White
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Child and Adolescent Psychiatry, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Wyke Huizinga
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Medical Informatics, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Lotte G M Cremers
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Marius de Groot
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Medical Informatics, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mohammad Arfan Ikram
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Wiro J Niessen
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Medical Informatics, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, the Netherlands
| | - Meike W Vernooij
- Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands.
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Langen CD, White T, Ikram MA, Vernooij MW, Niessen WJ. Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia. PLoS One 2015; 10:e0137484. [PMID: 26331844 PMCID: PMC4557994 DOI: 10.1371/journal.pone.0137484] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Accepted: 08/16/2015] [Indexed: 11/18/2022] Open
Abstract
Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, “bi-modal comparison plots” show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using “worm plots”. Group differences in connections are examined with an existing visualization, the “connectogram”. These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the “Statistical Analysis of Minimum cost path based Structural Connectivity” method and the average fractional anisotropy along the fiber. The functional measures were Pearson’s correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.
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Affiliation(s)
- Carolyn D. Langen
- Biomedical Imaging Group Rotterdam, Departments of Radiology & Medical Informatics, Erasmus MC, Rotterdam, The Netherlands
- * E-mail:
| | - Tonya White
- Department of Child and Adolescent Psychiatry, Erasmus Medical Centre, Rotterdam, Netherlands
- Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - Meike W. Vernooij
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - Wiro J. Niessen
- Biomedical Imaging Group Rotterdam, Departments of Radiology & Medical Informatics, Erasmus MC, Rotterdam, The Netherlands
- Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
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