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van de Wouw M, Wang Y, Workentine ML, Vaghef-Mehrabani E, Barth D, Mercer EM, Dewey D, Arrieta MC, Reimer RA, Tomfohr-Madsen L, Giesbrecht GF. Cluster-specific associations between the gut microbiota and behavioral outcomes in preschool-aged children. Microbiome 2024; 12:60. [PMID: 38515179 PMCID: PMC10956200 DOI: 10.1186/s40168-024-01773-5] [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: 04/28/2023] [Accepted: 01/31/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND The gut microbiota is recognized as a regulator of brain development and behavioral outcomes during childhood. Nonetheless, associations between the gut microbiota and behavior are often inconsistent among studies in humans, perhaps because many host-microbe relationships vary widely between individuals. This study aims to stratify children based on their gut microbiota composition (i.e., clusters) and to identify novel gut microbiome cluster-specific associations between the stool metabolomic pathways and child behavioral outcomes. METHODS Stool samples were collected from a community sample of 248 typically developing children (3-5 years). The gut microbiota was analyzed using 16S sequencing while LC-MS/MS was used for untargeted metabolomics. Parent-reported behavioral outcomes (i.e., Adaptive Skills, Internalizing, Externalizing, Behavioral Symptoms, Developmental Social Disorders) were assessed using the Behavior Assessment System for Children (BASC-2). Children were grouped based on their gut microbiota composition using the Dirichlet multinomial method, after which differences in the metabolome and behavioral outcomes were investigated. RESULTS Four different gut microbiota clusters were identified, where the cluster enriched in both Bacteroides and Bifidobacterium (Ba2) had the most distinct stool metabolome. The cluster characterized by high Bifidobacterium abundance (Bif), as well as cluster Ba2, were associated with lower Adaptive Skill scores and its subcomponent Social Skills. Cluster Ba2 also had significantly lower stool histidine to urocanate turnover, which in turn was associated with lower Social Skill scores in a cluster-dependent manner. Finally, cluster Ba2 had increased levels of compounds involved in Galactose metabolism (i.e., stachyose, raffinose, alpha-D-glucose), where alpha-D-glucose was associated with the Adaptive Skill subcomponent Daily Living scores (i.e., ability to perform basic everyday tasks) in a cluster-dependent manner. CONCLUSIONS These data show novel associations between the gut microbiota, its metabolites, and behavioral outcomes in typically developing preschool-aged children. Our results support the concept that cluster-based groupings could be used to develop more personalized interventions to support child behavioral outcomes. Video Abstract.
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Affiliation(s)
- Marcel van de Wouw
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Yanan Wang
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
- Microbiomes for One Systems Health, Health & Biosecurity, CSIRO, Adelaide, SA, Australia
| | - Matthew L Workentine
- Faculty of Veterinary Medicine, UCVM Bioinformatics, University of Calgary, Calgary, Alberta, Canada
| | - Elnaz Vaghef-Mehrabani
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
- Alberta Children's Hospital Research Institute (ACHRI), University of Calgary, Calgary, Alberta, Canada
| | - Delaney Barth
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Emily M Mercer
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
- Department of Physiology and Pharmacology, University of Calgary, Calgary, AB, Canada
- International Microbiome Centre, University of Calgary, Calgary, Alberta, Canada
| | - Deborah Dewey
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
- Alberta Children's Hospital Research Institute (ACHRI), University of Calgary, Calgary, Alberta, Canada
- Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute (HBI), University of Calgary, Calgary, Alberta, Canada
| | - Marie-Claire Arrieta
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
- Department of Physiology and Pharmacology, University of Calgary, Calgary, AB, Canada
- International Microbiome Centre, University of Calgary, Calgary, Alberta, Canada
| | - Raylene A Reimer
- Alberta Children's Hospital Research Institute (ACHRI), University of Calgary, Calgary, Alberta, Canada
- Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Alberta, Canada
| | - Lianne Tomfohr-Madsen
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
- Alberta Children's Hospital Research Institute (ACHRI), University of Calgary, Calgary, Alberta, Canada
- Faculty of Education, University of British Columbia, Vancouver, British Columbia, Canada
| | - Gerald F Giesbrecht
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada.
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada.
- Alberta Children's Hospital Research Institute (ACHRI), University of Calgary, Calgary, Alberta, Canada.
- Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.
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2
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Buchan MC, Richmond SA, Skinner K, Leatherdale ST. Identifying latent classes of physical activity profiles over time among adolescents in Ontario, Canada. BMC Public Health 2024; 24:856. [PMID: 38504203 PMCID: PMC10953222 DOI: 10.1186/s12889-024-18280-9] [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] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 03/05/2024] [Indexed: 03/21/2024] Open
Abstract
BACKGROUND Physical activity behaviours are known to be highly correlated. Adolescents who participate in one type of physical activity (e.g., physical education) have a greater likelihood of participating in other physical activities (e.g., organized sports); however, little research has examined participation rates in various physical activity behaviours concurrently. This study identified longitudinal physical activity profiles among secondary school aged youth in Ontario, Canada. METHODS We used data from the COMPASS Study, a school-based prospective cohort study of adolescents in Canada. Using a repeated measures latent class analysis, Ontario students who participated in grade 9 PE in 2015-16 were analysed through to 2018-19 (n = 1,917). Latent classes were defined by: PE participation, guideline adherence (≥ 60 min/day of moderate to vigorous activity over the last 7 days), and sport participation (varsity, community, and/or intramural). Multinomial logistic regression models were used to examine associations between latent class membership and student characteristics. RESULTS Three distinct latent classes were identified for females and four were identified for males. These classes were: (1) Guidelines (high probability of guideline adherence; females: 44%; males: 16%), (2) PE & Sports (high probability of PE and sport participation; females: 33%; males: 43%), (3) Guidelines & Sports (high probability of guideline adherence and sport participation; females: 23%; males: 23%;), and (4) Inactive (low probability of all physical activity indicators; males: 18%). Strength training, sleep, and English grade were associated with class membership among females. Ethno-racial identity, weekly spending money, strength training, and English and math grades were associated with class membership among males. CONCLUSIONS Findings suggest that latent physical activity profiles differ by sex. Guideline adherence was the most common class among females, indicating high levels of independent physical activity, whereas PE & Sport participation was the most common class among males, indicating greater tendency towards organized activities. Additionally, a substantial number of male students were not engaging in any physical activity. Participation in both PE and sports did not necessarily lead to meeting physical activity guidelines, highlighting that these activities alone may not be providing sufficient levels of physical activity that align with current recommendations for Canadian youth.
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Affiliation(s)
- M Claire Buchan
- School of Public Health Sciences, University of Waterloo, Waterloo, ON, N2L 3G5, Canada.
| | - Sarah A Richmond
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, M5T 3M7, Canada
- Public Health Ontario, Toronto, ON, M5G 1V2, Canada
| | - Kelly Skinner
- School of Public Health Sciences, University of Waterloo, Waterloo, ON, N2L 3G5, Canada
| | - Scott T Leatherdale
- School of Public Health Sciences, University of Waterloo, Waterloo, ON, N2L 3G5, Canada
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3
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Becker M, Fehr K, Goguen S, Miliku K, Field C, Robertson B, Yonemitsu C, Bode L, Simons E, Marshall J, Dawod B, Mandhane P, Turvey SE, Moraes TJ, Subbarao P, Rodriguez N, Aghaeepour N, Azad MB. Multimodal machine learning for modeling infant head circumference, mothers' milk composition, and their shared environment. Sci Rep 2024; 14:2977. [PMID: 38316895 PMCID: PMC10844250 DOI: 10.1038/s41598-024-52323-w] [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] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 01/17/2024] [Indexed: 02/07/2024] Open
Abstract
Links between human milk (HM) and infant development are poorly understood and often focus on individual HM components. Here we apply multi-modal predictive machine learning to study HM and head circumference (a proxy for brain development) among 1022 mother-infant dyads of the CHILD Cohort. We integrated HM data (19 oligosaccharides, 28 fatty acids, 3 hormones, 28 chemokines) with maternal and infant demographic, health, dietary and home environment data. Head circumference was significantly predictable at 3 and 12 months. Two of the most associated features were HM n3-polyunsaturated fatty acid C22:6n3 (docosahexaenoic acid, DHA; p = 9.6e-05) and maternal intake of fish (p = 4.1e-03), a key dietary source of DHA with established relationships to brain function. Thus, using a systems biology approach, we identified meaningful relationships between HM and brain development, which validates our statistical approach, gives credence to the novel associations we observed, and sets the foundation for further research with additional cohorts and HM analytes.
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Affiliation(s)
- Martin Becker
- International Milk Composition (IMiC) Consortium, Winnipeg, Canada
- Stanford University, Stanford, 94305, USA
| | - Kelsey Fehr
- International Milk Composition (IMiC) Consortium, Winnipeg, Canada
- Manitoba Interdisciplinary Lactation Centre (MILC), Winnipeg, Canada
- Children's Hospital Research Institute of Manitoba, Winnipeg, Canada
- University of Manitoba, Winnipeg, R3E3P4, Canada
| | - Stephanie Goguen
- International Milk Composition (IMiC) Consortium, Winnipeg, Canada
- Manitoba Interdisciplinary Lactation Centre (MILC), Winnipeg, Canada
- Children's Hospital Research Institute of Manitoba, Winnipeg, Canada
- University of Manitoba, Winnipeg, R3E3P4, Canada
| | - Kozeta Miliku
- University of Toronto, Toronto, M5S 1A8, Canada
- McMaster University, Hamilton, M5S 1A8, Canada
| | | | | | - Chloe Yonemitsu
- University of California, San Diego, La Jolla, CA, 92093, USA
| | - Lars Bode
- International Milk Composition (IMiC) Consortium, Winnipeg, Canada
- University of California, San Diego, La Jolla, CA, 92093, USA
| | | | | | | | | | - Stuart E Turvey
- University of British Columbia and British Columbia Children's Hospital, Vancouver, V5Z4H4, Canada
| | | | - Padmaja Subbarao
- University of Toronto, Toronto, M5S 1A8, Canada
- McMaster University, Hamilton, M5S 1A8, Canada
- SickKids, Toronto, M5G 0A4, Canada
| | - Natalie Rodriguez
- International Milk Composition (IMiC) Consortium, Winnipeg, Canada
- Manitoba Interdisciplinary Lactation Centre (MILC), Winnipeg, Canada
- Children's Hospital Research Institute of Manitoba, Winnipeg, Canada
- University of Manitoba, Winnipeg, R3E3P4, Canada
| | - Nima Aghaeepour
- International Milk Composition (IMiC) Consortium, Winnipeg, Canada.
- Stanford University, Stanford, 94305, USA.
| | - Meghan B Azad
- International Milk Composition (IMiC) Consortium, Winnipeg, Canada.
- Manitoba Interdisciplinary Lactation Centre (MILC), Winnipeg, Canada.
- Children's Hospital Research Institute of Manitoba, Winnipeg, Canada.
- University of Manitoba, Winnipeg, R3E3P4, Canada.
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4
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Fast D, Charlesworth R, Thulien M, Krüsi A, Buxton J, West S, Chase C, Manson D. Staying Together No Matter What: Becoming Young Parents on the Streets of Vancouver. Cult Med Psychiatry 2023; 47:1043-1066. [PMID: 36692806 PMCID: PMC10654161 DOI: 10.1007/s11013-022-09813-1] [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] [Accepted: 12/27/2022] [Indexed: 01/25/2023]
Abstract
Among young people who use drugs in the context of entrenched poverty and homelessness, pregnancy is often viewed as an event that can meaningfully change the trajectory of their lives. However, youth's desires and decision-making do not always align with the perspectives of various professionals and systems regarding how best to intervene during pregnancies and early parenting. Drawing on longitudinal interviews and fieldwork with young people in Vancouver, Canada, we explore how their romantic relationships powerfully shaped understandings of what was right and wrong and which actions to take during pregnancy and early parenting, and how these moral worlds frequently clashed with the imperatives of healthcare, criminal justice, and child protection systems. We demonstrate how a disjuncture between youth's desires, decision-making and moralities, and the systems that are intended to help them, can further entrench young people in cycles of loss, defeat, and harm. These cycles are powerfully racialized for young Indigenous people in our context.
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Affiliation(s)
- Danya Fast
- Department of Medicine, Division of Social Medicine, University of British Columbia, Vancouver, Canada.
- British Columbia Centre on Substance Use, Vancouver, Canada.
| | | | | | - Andrea Krüsi
- Department of Medicine, Division of Social Medicine, University of British Columbia, Vancouver, Canada
- Centre for Gender & Sexual Health Equity, Vancouver, Canada
| | - Jane Buxton
- School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - Sarah West
- Indigenous Youth Researcher, Treatment Trajectories Study, British Columbia Centre on Substance Use, Vancouver, Canada
| | - Corrina Chase
- British Columbia Centre on Substance Use, Vancouver, Canada
- First Nations Health Authority, Vancouver, Canada
- Métis, Vancouver, Canada
| | - Daniel Manson
- Department of Medicine, Division of Social Medicine, University of British Columbia, Vancouver, Canada
- British Columbia Centre on Substance Use, Vancouver, Canada
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5
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Reece-Mills M, Baxter JAB. The SickKids Caribbean Initiative to improve care for children with cancer and blood disorders. Rev Panam Salud Publica 2023; 47:e130. [PMID: 37750055 PMCID: PMC10516326 DOI: 10.26633/rpsp.2023.130] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 06/23/2023] [Indexed: 09/27/2023] Open
Abstract
To improve pediatric hematology and oncology outcomes, there is a recognized potential for partnerships between low- and high-resource institutions within health care systems. The SickKids Caribbean Initiative is a partnership between health care professionals at the Hospital for Sick Children in Toronto, Canada, and seven Caribbean institutions across six countries (Bahamas, Barbados, Jamaica, Saint Lucia, Saint Vincent and the Grenadines, and Trinidad and Tobago). The primary aim of the SickKids Caribbean Initiative has been to improve the outcomes and the quality of life of children in the Caribbean aged <18 years who have cancer and blood disorders. This article describes five key activities undertaken within the SickKids Caribbean Initiative, including providing education and training, assisting with case consultations and diagnostic services, developing local oncology databases, engaging in advocacy and ensuring stakeholder engagement, and coordinating administration and project management.
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Affiliation(s)
- Michelle Reece-Mills
- Department of Child and Adolescent HealthFaculty of Medical SciencesUniversity of the West IndiesKingstonJamaicaDepartment of Child and Adolescent Health, Faculty of Medical Sciences, University of the West Indies, Kingston, Jamaica
| | - Jo-Anna B. Baxter
- Centre for Global Child HealthThe Hospital for Sick ChildrenTorontoCanadaCentre for Global Child Health, The Hospital for Sick Children, Toronto, Canada
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6
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Hänisch B, Hansen JY, Bernhardt BC, Eickhoff SB, Dukart J, Misic B, Valk SL. Cerebral chemoarchitecture shares organizational traits with brain structure and function. eLife 2023; 12:e83843. [PMID: 37440423 PMCID: PMC10371225 DOI: 10.7554/elife.83843] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 07/12/2023] [Indexed: 07/15/2023] Open
Abstract
Chemoarchitecture, the heterogeneous distribution of neurotransmitter transporter and receptor molecules, is a relevant component of structure-function relationships in the human brain. Here, we studied the organization of the receptome, a measure of interareal chemoarchitectural similarity, derived from Positron-Emission Tomography imaging studies of 19 different neurotransmitter transporters and receptors. Nonlinear dimensionality reduction revealed three main spatial gradients of cortical chemoarchitectural similarity - a centro-temporal gradient, an occipito-frontal gradient, and a temporo-occipital gradient. In subcortical nuclei, chemoarchitectural similarity distinguished functional communities and delineated a striato-thalamic axis. Overall, the cortical receptome shared key organizational traits with functional and structural brain anatomy, with node-level correspondence to functional, microstructural, and diffusion MRI-based measures decreasing along a primary-to-transmodal axis. Relative to primary and paralimbic regions, unimodal and heteromodal regions showed higher receptomic diversification, possibly supporting functional flexibility.
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Affiliation(s)
- Benjamin Hänisch
- Institute of Neuroscience and Medicine, Brain and Behaviour, Forschungszentrum Jülich, Jülich, Germany
| | - Justine Y Hansen
- Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Boris C Bernhardt
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour, Forschungszentrum Jülich, Jülich, Germany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain and Behaviour, Forschungszentrum Jülich, Jülich, Germany
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Sofie Louise Valk
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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7
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Wang X, Gong Z, Wang T, Law J, Chen X, Wanggou S, Wang J, Ying B, Francisco M, Dong W, Xiong Y, Fan JJ, MacLeod G, Angers S, Li X, Dirks PB, Liu X, Huang X, Sun Y. Mechanical nanosurgery of chemoresistant glioblastoma using magnetically controlled carbon nanotubes. Sci Adv 2023; 9:eade5321. [PMID: 36989359 PMCID: PMC10058241 DOI: 10.1126/sciadv.ade5321] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Glioblastoma (GBM) is the most common and aggressive primary brain cancer. Despite multimodal treatment including surgery, radiotherapy, and chemotherapy, median patient survival has remained at ~15 months for decades. This situation demands an outside-the-box treatment approach. Using magnetic carbon nanotubes (mCNTs) and precision magnetic field control, we report a mechanical approach to treat chemoresistant GBM. We show that GBM cells internalize mCNTs, the mobilization of which by rotating magnetic field results in cell death. Spatiotemporally controlled mobilization of intratumorally delivered mCNTs suppresses GBM growth in vivo. Functionalization of mCNTs with anti-CD44 antibody, which recognizes GBM cell surface-enriched antigen CD44, increases mCNT recognition of cancer cells, prolongs mCNT enrichment within the tumor, and enhances therapeutic efficacy. Using mouse models of GBM with upfront or therapy-induced resistance to temozolomide, we show that mCNT treatment is effective in treating chemoresistant GBM. Together, we establish mCNT-based mechanical nanosurgery as a treatment option for GBM.
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Affiliation(s)
- Xian Wang
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
| | - Zheyuan Gong
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Tiancong Wang
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Junhui Law
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Xin Chen
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
- Songjiang Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Siyi Wanggou
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jintian Wang
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Binbin Ying
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Michelle Francisco
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
| | - Weifan Dong
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Yi Xiong
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jerry J. Fan
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Graham MacLeod
- Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Stephane Angers
- Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, ON, Canada
- Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada
- Department of Biochemistry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Xuejun Li
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Peter B. Dirks
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Xinyu Liu
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Xi Huang
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Corresponding author. (X.H.); (Y.S.)
| | - Yu Sun
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Corresponding author. (X.H.); (Y.S.)
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8
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Benkarim O, Paquola C, Park BY, Kebets V, Hong SJ, Vos de Wael R, Zhang S, Yeo BTT, Eickenberg M, Ge T, Poline JB, Bernhardt BC, Bzdok D. Population heterogeneity in clinical cohorts affects the predictive accuracy of brain imaging. PLoS Biol 2022; 20:e3001627. [PMID: 35486643 PMCID: PMC9094526 DOI: 10.1371/journal.pbio.3001627] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 05/11/2022] [Accepted: 04/11/2022] [Indexed: 12/18/2022] Open
Abstract
Brain imaging research enjoys increasing adoption of supervised machine learning for single-participant disease classification. Yet, the success of these algorithms likely depends on population diversity, including demographic differences and other factors that may be outside of primary scientific interest. Here, we capitalize on propensity scores as a composite confound index to quantify diversity due to major sources of population variation. We delineate the impact of population heterogeneity on the predictive accuracy and pattern stability in 2 separate clinical cohorts: the Autism Brain Imaging Data Exchange (ABIDE, n = 297) and the Healthy Brain Network (HBN, n = 551). Across various analysis scenarios, our results uncover the extent to which cross-validated prediction performances are interlocked with diversity. The instability of extracted brain patterns attributable to diversity is located preferentially in regions part of the default mode network. Collectively, our findings highlight the limitations of prevailing deconfounding practices in mitigating the full consequences of population diversity.
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Affiliation(s)
- Oualid Benkarim
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
| | - Casey Paquola
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich, Jülich, Germany
| | - Bo-yong Park
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
- Department of Data Science, Inha University, Incheon, South Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, South Korea
| | - Valeria Kebets
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, South Korea
- Center for the Developing Brain, Child Mind Institute, New York, New York, United States of America
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Reinder Vos de Wael
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
| | - Shaoshi Zhang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), National University of Singapore, Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore
| | - B. T. Thomas Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), National University of Singapore, Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore
| | | | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Jean-Baptiste Poline
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
| | - Boris C. Bernhardt
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
| | - Danilo Bzdok
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Canada
- School of Computer Science, McGill University, Montreal, Canada
- Mila—Quebec Artificial Intelligence Institute, Montreal, Canada
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Fuller A, Siddiqi A, Shahidi FV, Anderson LN, Hildebrand V, Keown-Stoneman CDG, Maguire JL, Birken C. Understanding income-related differences in distribution of child growth, behaviour and development using a cross-sectional sample of a clinical cohort study. BMJ Open 2022; 12:e056991. [PMID: 35168982 PMCID: PMC8852748 DOI: 10.1136/bmjopen-2021-056991] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
OBJECTIVES Children from low-income households are at an increased risk of social, behavioural and physical health problems. Prior studies have generally relied on dichotomous outcome measures. However, inequities may exist along the range of outcome distribution. Our objective was to examine differences in distribution of three child health outcomes by income categories (high vs low): body mass index (BMI), behaviour difficulties and development. DESIGN AND SETTING This was a cross-sectional study using data from a primary care-based research network with sites in three Canadian cities, and 15 practices enrolling participants. PARTICIPANTS, INDEPENDENT VARIABLE AND OUTCOMES The independent variable was annual household income, dichotomised at the median income for Toronto (<$C80 000 or ≥$C80 000). Outcomes were: (1) growth (BMI z-score (zBMI) at 5 years, 1628 participants); (2) behaviour (Strengths and Difficulties Questionnaire (SDQ) at 3-5 years, 649 participants); (3) development (Infant Toddler Checklist (ITC) at 18 months, 1405 participants). We used distributional decomposition to compare distributions of these outcomes for each income group, and then to construct a counterfactual distribution that describes the hypothetical distribution of the low-income group with the predictor profile of the higher-income group. RESULTS We included data from 1628 (zBMI), 649 (SDQ) and 1405 (ITC) children. Children with lower family income had a higher risk distribution for all outcomes. For all outcomes, thecounterfactual distribution, which represented the distribution of children with lower-income who were assigned the predictor profile of the higher-income group, was more favourable than their observed distributions. CONCLUSION Comparing the distributions of child health outcomes and understanding different risk profiles for children from higher-income and lower-income groups can offer a deeper understanding of inequities in child health outcomes. These methods may offer an approach that can be implemented in larger datasets to inform future interventions.
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Affiliation(s)
- Anne Fuller
- Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
- Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
- Child Health Evaluative Sciences, SickKids Research Institute, Toronto, Ontario, Canada
| | - Arjumand Siddiqi
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Faraz V Shahidi
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Institute for Work and Health, Toronto, Ontario, Canada
| | - Laura N Anderson
- Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Vincent Hildebrand
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Economics, York University - Glendon Campus, Toronto, Ontario, Canada
| | - Charles D G Keown-Stoneman
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada
| | - Jonathon L Maguire
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada
- Paediatrics, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Catherine Birken
- Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
- Child Health Evaluative Sciences, SickKids Research Institute, Toronto, Ontario, Canada
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10
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Yin S, Hong SJ, Di Martino A, Milham MP, Park BY, Benkarim O, Bethlehem RAI, Bernhardt BC, Paquola C. OUP accepted manuscript. Cereb Cortex 2022; 32:4565-4575. [PMID: 35059701 PMCID: PMC9574241 DOI: 10.1093/cercor/bhab502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/04/2022] Open
Abstract
Autism spectrum disorder (ASD) and anxiety disorders (ANX) are common neurodevelopmental conditions with several overlapping symptoms. Notably, many children and adolescents with ASD also have an ANX diagnosis, suggesting shared pathological mechanisms. Here, we leveraged structural imaging and phenotypic data from 112 youth (33 ASD, 37 ANX, 42 typically developing controls) to assess shared and distinct cortical thickness patterns of the disorders. ANX was associated with widespread increases in cortical thickness, while ASD related to a mixed pattern of subtle increases and decreases across the cortical mantle. Despite the qualitative difference in the case–control contrasts, the statistical maps from the ANX-vs-controls and ASD-vs-controls analyses were significantly correlated when correcting for spatial autocorrelation. Dimensional analysis, regressing trait anxiety and social responsiveness against cortical thickness measures, partially recapitulated diagnosis-based findings. Collectively, our findings provide evidence for a common axis of neurodevelopmental disturbances as well as distinct effects of ASD and ANX on cortical thickness.
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Affiliation(s)
- Shelly Yin
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal H3A 2B4, Canada
| | - Seok-Jun Hong
- Center for the Developing Brain and Autism Research Centre, Child Mind Institute, New York City, NY 10022, USA
| | - Adriana Di Martino
- Center for the Developing Brain and Autism Research Centre, Child Mind Institute, New York City, NY 10022, USA
| | - Michael P Milham
- Center for the Developing Brain and Autism Research Centre, Child Mind Institute, New York City, NY 10022, USA
| | - Bo-Yong Park
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal H3A 2B4, Canada
| | - Oualid Benkarim
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal H3A 2B4, Canada
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11
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Saunders NR, Moore Hepburn C, Huang A, de Oliveira C, Strauss R, Fiksenbaum L, Pageau P, Liu N, Gomez D, Macpherson A. Firearm injury epidemiology in children and youth in Ontario, Canada: a population-based study. BMJ Open 2021; 11:e053859. [PMID: 34794997 PMCID: PMC8603258 DOI: 10.1136/bmjopen-2021-053859] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND AND OBJECTIVE Despite firearms contributing to significant morbidity and mortality globally, firearm injury epidemiology is seldom described outside of the USA. We examined firearm injuries among youth in Canada, including weapon type, and intent. DESIGN Population-based, pooled cross-sectional study using linked health administrative and demographic databases. SETTING Ontario, Canada. PARTICIPANTS All children and youth from birth to 24 years, residing in Ontario from 1 April 2003 to 31 March 2018. EXPOSURE Firearm injury intent and weapon type using the International Classification of Disease-10 CM codes with Canadian enhancements. Secondary exposures were sociodemographics including age, sex, rurality and income. MAIN OUTCOMES Any hospital or death record of a firearm injury with counts and rates of firearm injuries described overall and stratified by weapon type and injury intent. Multivariable Poisson regression stratified by injury intent was used to calculate rate ratios of firearm injuries by weapon type. RESULTS Of 5486 children and youth with a firearm injury (annual rate: 8.8/100 000 population), 90.7% survived. Most injuries occurred in males (90.1%, 15.5/100 000 population). 62.3% (3416) of injuries were unintentional (5.5/100 000 population) of which 1.9% were deaths, whereas 26.5% (1452) were assault related (2.3/100 00 population) of which 18.7% were deaths. Self-injury accounted for 3.7% (204) of cases of which 72.0% were deaths. Across all intents, adjusted regression models showed males were at an increased risk of injury. Non-powdered firearms accounted for half (48.6%, 3.9/100 000 population) of all injuries. Compared with handguns, non-powdered firearms had a higher risk of causing unintentional injuries (adjusted rate ratio (aRR) 14.75, 95% CI 12.01 to 18.12) but not assault (aRR 0.84, 95% CI 0.70 to 1.00). CONCLUSIONS Firearm injuries are a preventable public health problem among youth in Ontario, Canada. Unintentional injuries and those caused by non-powdered firearms were most common and assault and self-injury contributed to substantial firearm-related deaths and should be a focus of prevention efforts.
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Affiliation(s)
- Natasha Ruth Saunders
- Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada
- ICES, Toronto, Ontario, Canada
- Child Health Evaluative Sciences, SickKids Research Institute, Toronto, Ontario, Canada
| | | | | | | | | | - Lisa Fiksenbaum
- Child Health Evaluative Sciences, SickKids Research Institute, Toronto, Ontario, Canada
| | - Paul Pageau
- Department of Emergency Medicine, University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada
| | | | - David Gomez
- ICES, Toronto, Ontario, Canada
- Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Alison Macpherson
- ICES, Toronto, Ontario, Canada
- School of Kinesiology and Health Science, York University Faculty of Health, Toronto, Ontario, Canada
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12
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Schurz M, Uddin LQ, Kanske P, Lamm C, Sallet J, Bernhardt BC, Mars RB, Bzdok D. Variability in Brain Structure and Function Reflects Lack of Peer Support. Cereb Cortex 2021; 31:4612-4627. [PMID: 33982758 PMCID: PMC8408465 DOI: 10.1093/cercor/bhab109] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [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] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 03/02/2021] [Accepted: 03/24/2021] [Indexed: 01/10/2023] Open
Abstract
Humans are a highly social species. Complex interactions for mutual support range from helping neighbors to building social welfare institutions. During times of distress or crisis, sharing life experiences within one's social circle is critical for well-being. By translating pattern-learning algorithms to the UK Biobank imaging-genetics cohort (n = ~40 000 participants), we have delineated manifestations of regular social support in multimodal whole-brain measurements. In structural brain variation, we identified characteristic volumetric signatures in the salience and limbic networks for high- versus low-social support individuals. In patterns derived from functional coupling, we also located interindividual differences in social support in action-perception circuits related to binding sensory cues and initiating behavioral responses. In line with our demographic profiling analysis, the uncovered neural substrates have potential implications for loneliness, substance misuse, and resilience to stress.
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Affiliation(s)
- Matthias Schurz
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, The Netherlands
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, UK
- Institute of Psychology, University of Innsbruck, 6020 Innsbruck, Austria
- Address correspondence to Matthias Schurz, PhD, Donders Institute for Brain, Cognition, & Behaviour, Radboud University, Montessorilaan 3, B.0305, 6525 HR Nijmegen, Netherlands. and Danilo Bzdok, MD, PhD, Montreal Neurological Institute, 3801 rue University, Bureau #872D, Montréal (Québec) H3A 2B4, Canada.
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, Florida 33124, USA
- Neuroscience Program, University of Miami Miller School of Medicine, Miami, Florida 33136, USA
| | - Philipp Kanske
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, 01187 Dresden, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Claus Lamm
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, 1010 Vienna, Austria
| | - Jérôme Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, UK
- University of Lyon, Univ Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Rogier B Mars
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, The Netherlands
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK
| | - Danilo Bzdok
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), McGill University, Montreal, Quebec H3A 2B4, Canada
- Department of Biomedical Engineering, Faculty of Medicine, School of Computer Science, McGill University, Montreal, Quebec H3A 2B4, Canada
- Mila-Quebec Artificial Intelligence Institute, Montreal, Quebec H2S 3H1, Canada
- Address correspondence to Matthias Schurz, PhD, Donders Institute for Brain, Cognition, & Behaviour, Radboud University, Montessorilaan 3, B.0305, 6525 HR Nijmegen, Netherlands. and Danilo Bzdok, MD, PhD, Montreal Neurological Institute, 3801 rue University, Bureau #872D, Montréal (Québec) H3A 2B4, Canada.
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13
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Park BY, Bethlehem RAI, Paquola C, Larivière S, Rodríguez-Cruces R, Vos de Wael R, Bullmore ET, Bernhardt BC. An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization. eLife 2021; 10:e64694. [PMID: 33787489 PMCID: PMC8087442 DOI: 10.7554/elife.64694] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [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] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Accepted: 03/30/2021] [Indexed: 12/13/2022] Open
Abstract
Adolescence is a critical time for the continued maturation of brain networks. Here, we assessed structural connectome development in a large longitudinal sample ranging from childhood to young adulthood. By projecting high-dimensional connectomes into compact manifold spaces, we identified a marked expansion of structural connectomes, with strongest effects in transmodal regions during adolescence. Findings reflected increased within-module connectivity together with increased segregation, indicating increasing differentiation of higher-order association networks from the rest of the brain. Projection of subcortico-cortical connectivity patterns into these manifolds showed parallel alterations in pathways centered on the caudate and thalamus. Connectome findings were contextualized via spatial transcriptome association analysis, highlighting genes enriched in cortex, thalamus, and striatum. Statistical learning of cortical and subcortical manifold features at baseline and their maturational change predicted measures of intelligence at follow-up. Our findings demonstrate that connectome manifold learning can bridge the conceptual and empirical gaps between macroscale network reconfigurations, microscale processes, and cognitive outcomes in adolescent development.
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Affiliation(s)
- Bo-yong Park
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
- Department of Data Science, Inha UniversityIncheonRepublic of Korea
| | - Richard AI Bethlehem
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
- Brain Mapping Unit, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Casey Paquola
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum JülichJülichGermany
| | - Sara Larivière
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Raul Rodríguez-Cruces
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Edward T Bullmore
- Brain Mapping Unit, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
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14
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Hatton SN, Huynh KH, Bonilha L, Abela E, Alhusaini S, Altmann A, Alvim MKM, Balachandra AR, Bartolini E, Bender B, Bernasconi N, Bernasconi A, Bernhardt B, Bargallo N, Caldairou B, Caligiuri ME, Carr SJA, Cavalleri GL, Cendes F, Concha L, Davoodi-bojd E, Desmond PM, Devinsky O, Doherty CP, Domin M, Duncan JS, Focke NK, Foley SF, Gambardella A, Gleichgerrcht E, Guerrini R, Hamandi K, Ishikawa A, Keller SS, Kochunov PV, Kotikalapudi R, Kreilkamp BAK, Kwan P, Labate A, Langner S, Lenge M, Liu M, Lui E, Martin P, Mascalchi M, Moreira JCV, Morita-Sherman ME, O’Brien TJ, Pardoe HR, Pariente JC, Ribeiro LF, Richardson MP, Rocha CS, Rodríguez-Cruces R, Rosenow F, Severino M, Sinclair B, Soltanian-Zadeh H, Striano P, Taylor PN, Thomas RH, Tortora D, Velakoulis D, Vezzani A, Vivash L, von Podewils F, Vos SB, Weber B, Winston GP, Yasuda CL, Zhu AH, Thompson PM, Whelan CD, Jahanshad N, Sisodiya SM, McDonald CR. White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study. Brain 2020; 143:2454-2473. [PMID: 32814957 PMCID: PMC7567169 DOI: 10.1093/brain/awaa200] [Citation(s) in RCA: 101] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 04/07/2020] [Accepted: 04/30/2020] [Indexed: 12/22/2022] Open
Abstract
The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research.
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Affiliation(s)
- Sean N Hatton
- Department of Neurosciences, Center for Multimodal Imaging and Genetics,
University of California San Diego, La Jolla 92093 CA, USA
| | - Khoa H Huynh
- Center for Multimodal Imaging and Genetics, University of California San
Diego, La Jolla 92093 CA, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina,
Charleston 29425 SC, USA
| | - Eugenio Abela
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry,
Psychology and Neuroscience, Kings College London, London SE5 9NU UK
| | - Saud Alhusaini
- Neurology Department, Yale School of Medicine, New Haven 6510 CT,
USA
- Molecular and Cellular Therapeutics, The Royal College of Surgeons in
Ireland, Dublin, Ireland
| | - Andre Altmann
- Centre of Medical Image Computing, Department of Medical Physics and Biomedical
Engineering, University College London, London WC1V 6LJ, UK
| | - Marina K M Alvim
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Akshara R Balachandra
- Center for Multimodal Imaging and Genetics, UCSD School of
Medicine, La Jolla 92037 CA, USA
- Boston University School of Medicine, Boston 2118 MA, USA
| | - Emanuele Bartolini
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories,
Children’s Hospital A. Meyer-University of Florence, Florence, Italy
- USL Centro Toscana, Neurology Unit, Nuovo Ospedale Santo Stefano,
Prato, Italy
| | - Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University Hospital
Tübingen, Tübingen 72076, Germany
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill
University, Montreal H3A 2B4 QC, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill
University, Montreal H3A 2B4 QC, Canada
| | - Boris Bernhardt
- Montreal Neurological Institute, McGill University, Montreal
H3A2B4 QC, Canada
| | - Núria Bargallo
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques
August Pi i Sunyer (IDIBAPS), Barcelona 8036 Barcelona, Spain
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill
University, Montreal H3A 2B4 QC, Canada
| | - Maria E Caligiuri
- Neuroscience Research Center, University Magna Graecia, viale Europa,
Germaneto, 88100, Catanzaro, Italy
| | - Sarah J A Carr
- Neuroscience, Institute of Psychiatry, Psychology and
Neuroscience, De Crespigny Park, London SE5 8AF, UK
| | - Gianpiero L Cavalleri
- Royal College of Surgeons in Ireland, School of Pharmacy and Biomolecular
Sciences, Dublin D02 YN77 Ireland
- FutureNeuro Research Centre, Science Foundation Ireland, Dublin
D02 YN77, Ireland
| | - Fernando Cendes
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autonoma de
Mexico, Queretaro 76230, Mexico
| | - Esmaeil Davoodi-bojd
- Radiology and Research Administration, Henry Ford Hospital, 1
Detroit 48202 MI, USA
| | - Patricia M Desmond
- Department of Radiology, Royal Melbourne Hospital, University of
Melbourne, Melbourne 3050 Victoria, Australia
| | | | - Colin P Doherty
- Division of Neurology, Trinity College Dublin, TBSI, Pearce
Street, Dublin D02 R590, Ireland
- FutureNeuro SFI Centre for Neurological Disease, RCSI, St Stephen’s
Green, Dublin D02 H903, Ireland
| | - Martin Domin
- Functional Imaging Unit, University Medicine Greifswald,
Greifswald 17475 M/V, Germany
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of
Neurology, Queen Square, London WC1N 3BG, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont-St-Peter,
Buckinghamshire SL9 0RJ, UK
| | - Niels K Focke
- Clinical Neurophysiology, University Medicine Göttingen, 37099
Göttingen, Germany
- Department of Epileptology, University of Tübingen, 72076
Tübingen, Germany
| | | | - Antonio Gambardella
- Royal College of Surgeons in Ireland, School of Pharmacy and Biomolecular
Sciences, Dublin D02 YN77 Ireland
- Institute of Neurology, University Magna Graecia, 88100,
Catanzaro, Italy
| | | | - Renzo Guerrini
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories,
Children’s Hospital A. Meyer-University of Florence, Florence, Italy
| | - Khalid Hamandi
- The Wales Epilepsy Unit, Cardiff and Vale University Health
Board, Cardiff CF144XW, UK
- Brain Research Imaging Centre, Cardiff University, Cardiff CF24
4HQ, UK
| | - Akari Ishikawa
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Simon S Keller
- Institute of Translational Medicine, University of Liverpool,
Liverpool L69 3BX, UK
- Walton Centre NHS Foundation Trust, Liverpool L9 7LJ, UK
| | - Peter V Kochunov
- Maryland Psychiatric Research Center, 55 Wade Ave, Baltimore
21228, MD, USA
| | - Raviteja Kotikalapudi
- Department of Neurology and Epileptology, University Hospital
Tübingen, Tübingen 72076 BW, Germany
- Department of Diagnostic and Interventional Neuroradiology, University Hospital
Tübingen, Tübingen 72076 BW, Germany
| | - Barbara A K Kreilkamp
- Institute of Translational Medicine, University of Liverpool,
Liverpool L69 3BX, UK
- Walton Centre NHS Foundation Trust, Liverpool L9 7LJ, UK
| | - Patrick Kwan
- Department of Neuroscience, Central Clinical School, Monash
University, Melbourne 3004 Victoria, Australia
- Department of Medicine, University of Melbourne, Royal Melbourne
Hospital, Parkville 3050 Victoria, Australia
| | - Angelo Labate
- Neuroscience Research Center, University Magna Graecia, viale Europa,
Germaneto, 88100, Catanzaro, Italy
- Institute of Neurology, University Magna Graecia, 88100,
Catanzaro, Italy
| | - Soenke Langner
- Institute for Diagnostic Radiology and Neuroradiology, Ernst Moritz Arndt
University Greifswald Faculty of Medicine, Greifswald 17475, Germany
- Institute for Diagnostic and Interventional Radiology, Pediatric and
Neuroradiology, Rostock University Medical Centre, Rostock 18057, Germany
| | - Matteo Lenge
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories,
Children’s Hospital A. Meyer-University of Florence, Florence, Italy
- Functional and Epilepsy Neurosurgery Unit, Children’s Hospital A.
Meyer-University of Florence, Florence 50139, Italy
| | - Min Liu
- Department of Neurology, Montreal Neurological Institute,
Montreal H3A 2B4 QC, Canada
| | - Elaine Lui
- Department of Radiology, Royal Melbourne Hospital, University of
Melbourne, Melbourne 3050 Victoria, Australia
- Department of Medicine and Radiology, University of Melbourne,
3Parkville 3050 Victoria, Australia
| | - Pascal Martin
- Department of Epileptology, University of Tübingen, 72076
Tübingen, Germany
| | - Mario Mascalchi
- Meyer Children Hospital University of Florence, Florence 50130
Tuscany, Italy
| | - José C V Moreira
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Marcia E Morita-Sherman
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
- Cleveland Clinic, Cleveland 44195 OH, USA
| | - Terence J O’Brien
- Department of Neuroscience, Central Clinical School, Monash
University, Melbourne 3004 Victoria, Australia
- Department of Medicine, University of Melbourne, Royal Melbourne
Hospital, Parkville 3050 Victoria, Australia
- Department of Neurology, Alfred Health, Melbourne 3004 Victoria,
Australia
| | - Heath R Pardoe
- Department of Neurology, New York University School of Medicine,
New York City 10016 NY, USA
| | - José C Pariente
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques
August Pi i Sunyer (IDIBAPS), Barcelona 8036 Barcelona, Spain
| | - Letícia F Ribeiro
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Mark P Richardson
- Division of Neuroscience, King’s College London, Institute of
Psychiatry, London SE5 8AB, UK
| | - Cristiane S Rocha
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Raúl Rodríguez-Cruces
- Montreal Neurological Institute, McGill University, Montreal
H3A2B4 QC, Canada
- Institute of Neurobiology, Universidad Nacional Autonoma de
Mexico, Queretaro 76230, Mexico
| | - Felix Rosenow
- Epilepsy Center Frankfurt Rhine-Main, University Hospital Frankfurt,
Germany, Frankfurt 60528 Hesse, Germany
- Center for Personalized Translational Epilepsy Research (CePTER),
Goethe-University Frankfurt, Frankfurt a. M. 60528, Germany
| | - Mariasavina Severino
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa 16147
Liguria, Italy
| | - Benjamin Sinclair
- Department of Medicine, University of Melbourne, Royal Melbourne
Hospital, Parkville 3050 Victoria, Australia
- Department of Neurology, Alfred Health, Melbourne 3004 Victoria,
Australia
| | - Hamid Soltanian-Zadeh
- Radiology and Research Administration, Henry Ford Health System,
Detroit 48202-2692 MI, USA
- School of Electrical and Computer Engineering, University of
Tehran, Tehran 14399-57131, Iran
| | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genoa 16147 Liguria, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal
and Child Health, University of Genova, Genova, Italy
| | - Peter N Taylor
- School of Computing, Newcastle University, Urban Sciences Building, Science
Square, Newcastle upon Tyne NE4 5TG, UK
| | - Rhys H Thomas
- Translational and Clinical Research Institute, Newcastle
University, Newcastle upon Tyne NE2 4HH, UK
- Royal Victoria Infirmary, Newcastle upon Tyne NE1 4LP, UK
| | - Domenico Tortora
- Radiology and Research Administration, Henry Ford Health System,
Detroit 48202-2692 MI, USA
| | - Dennis Velakoulis
- Royal Melbourne Hospital, Melbourne 3050 Victoria, Australia
- University of Melbourne, Parkville, Melbourne 3050 Victoria,
Australia
| | - Annamaria Vezzani
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano
20156 Italy
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Monash
University, Melbourne 3004 Victoria, Australia
- Department of Medicine, University of Melbourne, Royal Melbourne
Hospital, Parkville 3050 Victoria, Australia
| | - Felix von Podewils
- Epilepsy Center, University Medicine Greifswald, Greifswald 17489
Mecklenburg-Vorpommern, Germany
| | - Sjoerd B Vos
- Centre for Medical Image Computing, University College London,
London, WC1V 6LJ, UK
- Epilepsy Society, MRI Unit, Chalfont St Peter, Buckinghamshire,
SL9 0RJ, UK
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University of
Bonn, Venusberg Campus 1, Bonn 53127 NRW, Germany
| | - Gavin P Winston
- Epilepsy Society, MRI Unit, Chalfont St Peter, Buckinghamshire,
SL9 0RJ, UK
- Department of Medicine, Division of Neurology, Queen's
University, Kingston K7L 3N6 ON, Canada
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont-St-Peter,
Buckinghamshire, SL9 0RJ UK
| | - Clarissa L Yasuda
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Alyssa H Zhu
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and
Informatics, USC Keck School of Medicine, Los Angeles 90232 CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and
Informatics, USC Keck School of Medicine, Los Angeles 90232 CA, USA
| | - Christopher D Whelan
- Molecular and Cellular Therapeutics, The Royal College of Surgeons in
Ireland, Dublin, Ireland
- Research and Early Development (RED), Biogen Inc., Cambridge, MA
02139, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and
Informatics, USC Keck School of Medicine, Los Angeles 90232 CA, USA
| | - Sanjay M Sisodiya
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont-St-Peter,
Buckinghamshire, SL9 0RJ UK
- Chalfont Centre for Epilepsy, Chalfont-St-Peter, SL9 0RJ Bucks,
UK
| | - Carrie R McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics,
University of California San Diego, La Jolla 92093 CA, USA
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15
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Paul B, Thulien M, Knight R, Milloy MJ, Howard B, Nelson S, Fast D. "Something that actually works": Cannabis use among young people in the context of street entrenchment. PLoS One 2020; 15:e0236243. [PMID: 32722721 PMCID: PMC7386570 DOI: 10.1371/journal.pone.0236243] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 06/19/2020] [Indexed: 12/14/2022] Open
Abstract
Background Cannabis is one of the most widely used substances among vulnerable young people (<26 years of age) experiencing street entrenchment. Although previous research has documented the role cannabis can play in harm reduction, substance use and mental health treatment and pain management, this research has predominantly been quantitative and focused on adult drug-using populations. Little qualitative work has examined how young people who use drugs understand, experience, and engage with cannabis in the context of street entrenchment and drug use trajectories that include the use of other substances such as alcohol, opioids and crystal methamphetamine (meth). Methods Semi-structured, in-depth qualitative interviews were conducted between 2017 and 2019 with 56 young people recruited from a cohort of street-involved youth in Vancouver, Canada. We also conducted 13 interviews with 12 youth-focused care providers across the same time period. Interview data were triangulated by drawing on the findings of a program of anthropological research conducted by the senior author since 2008. Interviews were transcribed verbatim and thematic analysis was conducted. Results The vast majority of study participants engaged in daily, intensive cannabis use at the same time as they cycled on and off other substances that were perceived as much more harmful (primarily alcohol, fentanyl, heroin and meth). While most participants derived significant pleasure from the use of cannabis, no participants in our study described using cannabis for purely recreational purposes. A number of participants explicitly framed cannabis as a form of mental health and substance use treatment that was more effective and “healthier” than the long-term use of psychopharmaceuticals and medication-assisted substance use treatment (e.g., opioid agonist therapies). Cannabis use was also understood to ameliorate some of the harms of, or even facilitate transitions out of, periods of street-based homelessness. While the majority of our participants highlighted the positive effects of regular cannabis consumption, some described how intensive cannabis use could generate significant harms. Conclusion In the context of the recent legalization of non-medical cannabis use in Canada and amid ongoing overdose and housing crises, it is imperative that future policy and programming interventions and provider education and training be responsive to the ways in which vulnerable youth in our setting are actively using cannabis to navigate their everyday lives and healthcare needs.
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Affiliation(s)
- Braedon Paul
- Department of Medicine, University of British Columbia, Vancouver, Canada
| | | | - Rod Knight
- Department of Medicine, University of British Columbia, Vancouver, Canada
- British Columbia Centre on Substance Use, Vancouver, Canada
| | - M. J. Milloy
- Department of Medicine, University of British Columbia, Vancouver, Canada
- British Columbia Centre on Substance Use, Vancouver, Canada
| | - Ben Howard
- British Columbia Centre on Substance Use, Vancouver, Canada
- At-Risk Youth Study Peer Research Associate Team, Vancouver, Canada
| | - Scarlett Nelson
- British Columbia Centre on Substance Use, Vancouver, Canada
- At-Risk Youth Study Peer Research Associate Team, Vancouver, Canada
| | - Danya Fast
- Department of Medicine, University of British Columbia, Vancouver, Canada
- British Columbia Centre on Substance Use, Vancouver, Canada
- * E-mail:
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16
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Sisodiya SM, Whelan CD, Hatton SN, Huynh K, Altmann A, Ryten M, Vezzani A, Caligiuri ME, Labate A, Gambardella A, Ives‐Deliperi V, Meletti S, Munsell BC, Bonilha L, Tondelli M, Rebsamen M, Rummel C, Vaudano AE, Wiest R, Balachandra AR, Bargalló N, Bartolini E, Bernasconi A, Bernasconi N, Bernhardt B, Caldairou B, Carr SJ, Cavalleri GL, Cendes F, Concha L, Desmond PM, Domin M, Duncan JS, Focke NK, Guerrini R, Hamandi K, Jackson GD, Jahanshad N, Kälviäinen R, Keller SS, Kochunov P, Kowalczyk MA, Kreilkamp BA, Kwan P, Lariviere S, Lenge M, Lopez SM, Martin P, Mascalchi M, Moreira JC, Morita‐Sherman ME, Pardoe HR, Pariente JC, Raviteja K, Rocha CS, Rodríguez‐Cruces R, Seeck M, Semmelroch MK, Sinclair B, Soltanian‐Zadeh H, Stein DJ, Striano P, Taylor PN, Thomas RH, Thomopoulos SI, Velakoulis D, Vivash L, Weber B, Yasuda CL, Zhang J, Thompson PM, McDonald CR. The ENIGMA-Epilepsy working group: Mapping disease from large data sets. Hum Brain Mapp 2020; 43:113-128. [PMID: 32468614 PMCID: PMC8675408 DOI: 10.1002/hbm.25037] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 05/01/2020] [Accepted: 05/03/2020] [Indexed: 02/06/2023] Open
Abstract
Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy.
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Affiliation(s)
- Sanjay M. Sisodiya
- Department of Clinical and Experimental EpilepsyUCL Queen Square Institute of NeurologyLondonUK
- Chalfont Centre for EpilepsyBucksUK
| | - Christopher D. Whelan
- Department of Molecular and Cellular TherapeuticsThe Royal College of Surgeons in IrelandDublinIreland
| | - Sean N. Hatton
- Center for Multimodal Imaging and GeneticsUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Khoa Huynh
- Center for Multimodal Imaging and GeneticsUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Andre Altmann
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Mina Ryten
- UCL Queen Square Institute of NeurologyLondonUK
| | - Annamaria Vezzani
- Department of NeuroscienceIstituto di Ricerche Farmacologiche Mario Negri IRCCSMilanItaly
| | - Maria Eugenia Caligiuri
- Neuroscience Research Center, Department of Medical and Surgical SciencesUniversity “Magna Græcia" of CatanzaroCatanzaroItaly
| | - Angelo Labate
- Neuroscience Research Center, Department of Medical and Surgical SciencesUniversity “Magna Græcia" of CatanzaroCatanzaroItaly
- Institute of NeurologyUniversity “Magna Græcia" of CatanzaroCatanzaroItaly
| | - Antonio Gambardella
- Neuroscience Research Center, Department of Medical and Surgical SciencesUniversity “Magna Græcia" of CatanzaroCatanzaroItaly
- Institute of NeurologyUniversity “Magna Græcia" of CatanzaroCatanzaroItaly
| | | | - Stefano Meletti
- Department of Biomedical, Metabolic, and Neural SciencesUniversity of Modena and Reggio EmiliaModenaItaly
- Neurology UnitOCB Hospital, AOU ModenaModenaItaly
| | - Brent C. Munsell
- Department of PsychiatryUniversity of North CarolinaChapel HillNorth CarolinaUSA
- Department of Computer ScienceUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - Leonardo Bonilha
- Department of NeurologyMedical University of South CarolinaCharlestonSouth CarolinaUSA
| | | | - Michael Rebsamen
- Support Center for Advanced NeuroimagingUniversity Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of BernBernSwitzerland
| | - Christian Rummel
- Support Center for Advanced NeuroimagingUniversity Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of BernBernSwitzerland
| | - Anna Elisabetta Vaudano
- Department of Biomedical, Metabolic, and Neural SciencesUniversity of Modena and Reggio EmiliaModenaItaly
- Neurology UnitOCB Hospital, AOU ModenaModenaItaly
| | - Roland Wiest
- Support Center for Advanced NeuroimagingUniversity Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of BernBernSwitzerland
| | - Akshara R. Balachandra
- Center for Multimodal Imaging and GeneticsUniversity of California San DiegoLa JollaCaliforniaUSA
- Boston University School of MedicineBostonMassachusettsUSA
| | - Núria Bargalló
- Magnetic Resonance Image Core FacilityInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de BarcelonaBarcelonaSpain
- Radiology Department of Center of Image DiagnosisHospital Clinic de BarcelonaBarcelonaSpain
| | - Emanuele Bartolini
- Neurology UnitUSL Centro Toscana, Nuovo Ospedale Santo StefanoPratoItaly
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy LaboratoryMontreal Neurological Institute, McGill UniversityMontrealQuébecCanada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy LaboratoryMontreal Neurological Institute, McGill UniversityMontrealQuébecCanada
| | - Boris Bernhardt
- McConnell Brain Imaging CenterMontreal Neurological Institute, McGill UniversityMontrealQuébecCanada
| | - Benoit Caldairou
- Neuroimaging of Epilepsy LaboratoryMontreal Neurological Institute, McGill UniversityMontrealQuébecCanada
| | - Sarah J.A. Carr
- NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceLondonUK
| | - Gianpiero L. Cavalleri
- School of Pharmacy and Biomolecular SciencesThe Royal College of Surgeons in IrelandDublinIreland
- FutureNeuro SFI Research CentreDublinIreland
| | - Fernando Cendes
- Department of Neurology and Neuroimaging LaboratoryUniversity of Campinas – UNICAMPCampinasSão PauloBrazil
| | - Luis Concha
- Instituto de NeurobiologíaUniversidad Nacional Autónoma de MéxicoQuerétaroMexico
| | - Patricia M. Desmond
- Department of RadiologyRoyal Melbourne Hospital, University of MelbourneMelbourneVictoriaAustralia
| | - Martin Domin
- Functional Imaging Unit, Department of Diagnostic Radiology and NeuroradiologyUniversity Medicine GreifswaldGreifswaldGermany
| | - John S. Duncan
- Department of Clinical and Experimental EpilepsyUCL Queen Square Institute of NeurologyLondonUK
- Chalfont Centre for EpilepsyBucksUK
| | - Niels K. Focke
- University Medicine GöttingenClinical NeurophysiologyGöttingenGermany
| | - Renzo Guerrini
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and LaboratoriesChildren's Hospital A. Meyer‐University of FlorenceFlorenceItaly
| | - Khalid Hamandi
- The Wales Epilepsy Unit, Department of NeurologyUniversity Hospital of WalesCardiffUK
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUK
| | - Graeme D. Jackson
- Department of NeurologyAustin HealthHeidelbergVictoriaAustralia
- Florey Department of Neuroscience and Mental HealthUniversity of MelbourneVictoriaAustralia
| | - Neda Jahanshad
- Imaging Genetics CenterMark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Reetta Kälviäinen
- Kuopio University HospitalMember of EpiCARE ERNKuopioFinland
- Institute of Clinical MedicineNeurology, University of Eastern FinlandKuopioFinland
| | - Simon S. Keller
- Institute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
- The Walton CentreNHS Foundation TrustLiverpoolUK
| | - Peter Kochunov
- Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Magdalena A. Kowalczyk
- Florey Department of Neuroscience and Mental HealthUniversity of MelbourneVictoriaAustralia
| | - Barbara A.K. Kreilkamp
- Institute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
- The Walton CentreNHS Foundation TrustLiverpoolUK
| | - Patrick Kwan
- Department of Neuroscience, Central Clinical SchoolMonash UniversityMelbourneVictoriaAustralia
| | - Sara Lariviere
- McConnell Brain Imaging CenterMontreal Neurological Institute, McGill UniversityMontrealQuébecCanada
| | - Matteo Lenge
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and LaboratoriesChildren's Hospital A. Meyer‐University of FlorenceFlorenceItaly
- Functional and Epilepsy Neurosurgery Unit, Neurosurgery DepartmentChildren's Hospital A. Meyer‐University of FlorenceFlorenceItaly
| | - Seymour M. Lopez
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Pascal Martin
- Department of Neurology and EpileptologyHertie Institute for Clinical Brain Research, University Hospital TübingenTübingenGermany
| | - Mario Mascalchi
- 'Mario Serio' Department of Clinical and Experimental Medical SciencesUniversity of FlorenceFlorenceItaly
| | - José C.V. Moreira
- Department of Neurology and Neuroimaging LaboratoryUniversity of Campinas – UNICAMPCampinasSão PauloBrazil
| | - Marcia E. Morita‐Sherman
- Department of Neurology and Neuroimaging LaboratoryUniversity of Campinas – UNICAMPCampinasSão PauloBrazil
- Cleveland Clinic Neurological InstituteClevelandOhioUSA
| | - Heath R. Pardoe
- Department of NeurologyNew York University School of MedicineNew YorkNew YorkUSA
| | - Jose C. Pariente
- Magnetic Resonance Image Core FacilityInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de BarcelonaBarcelonaSpain
| | - Kotikalapudi Raviteja
- Department of Neurology and EpileptologyHertie Institute for Clinical Brain Research, University Hospital TübingenTübingenGermany
- Department of Diagnostic and Interventional NeuroradiologyUniversity Hospitals TübingenTübingenGermany
- Department of Clinical NeurophysiologyUniversity Hospital GöttingenGoettingenGermany
| | - Cristiane S. Rocha
- Department of Neurology and Neuroimaging LaboratoryUniversity of Campinas – UNICAMPCampinasSão PauloBrazil
| | - Raúl Rodríguez‐Cruces
- Instituto de NeurobiologíaUniversidad Nacional Autónoma de MéxicoQuerétaroMexico
- Montreal Neurological Institute and HospitalMcGill UniversityMontrealQuébecCanada
| | | | - Mira K.H.G. Semmelroch
- Florey Department of Neuroscience and Mental HealthUniversity of MelbourneVictoriaAustralia
- The Florey Institute of Neuroscience and Mental HealthAustin CampusHeidelbergVictoriaAustralia
| | - Benjamin Sinclair
- Department of NeuroscienceMonash UniversityMelbourneVictoriaAustralia
- Alfred HealthMelbourneVictoriaAustralia
| | - Hamid Soltanian‐Zadeh
- Radiology and Research AdministrationHenry Ford Health SystemDetroitMichiganUSA
- School of Electrical and Computer EngineeringCollege of Engineering, University of TehranTehranIran
| | - Dan J. Stein
- South African Medical Research Council Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience InstituteUniversity of Cape Townon Risk & Resilience in Mental DisordersCape TownSouth Africa
| | - Pasquale Striano
- Pediatric Neurology and Muscular Diseases UnitIRCCS Istituto 'G. Gaslini'GenovaItaly
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child HealthUniversity of GenovaItaly
| | - Peter N. Taylor
- School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Rhys H. Thomas
- Institute of Translational and Clinical ResearchNewcastle UniversityNewcastle upon TyneUK
| | - Sophia I. Thomopoulos
- Imaging Genetics CenterMark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Dennis Velakoulis
- Department of Medicine, Royal Melbourne HospitalUniversity of MelbourneParkvilleVictoriaUK
- Department of NeuropsychiatryRoyal Melbourne HospitalParkvilleVictoriaAustralia
| | - Lucy Vivash
- Department of NeuroscienceMonash UniversityMelbourneVictoriaAustralia
- Department of NeurologyRoyal Melbourne HospitalMelbourneVictoriaAustralia
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition ResearchUniversity of BonnBonnGermany
| | - Clarissa Lin Yasuda
- Department of Neurology and Neuroimaging LaboratoryUniversity of Campinas – UNICAMPCampinasSão PauloBrazil
| | - Junsong Zhang
- Cognitive Science DepartmentSchool of Informatics, Xiamen UniversityXiamenChina
| | - Paul M. Thompson
- Imaging Genetics CenterMark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Carrie R. McDonald
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
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17
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Uusküla-Reimand L, Hou H, Samavarchi-Tehrani P, Rudan MV, Liang M, Medina-Rivera A, Mohammed H, Schmidt D, Schwalie P, Young EJ, Reimand J, Hadjur S, Gingras AC, Wilson MD. Topoisomerase II beta interacts with cohesin and CTCF at topological domain borders. Genome Biol 2016; 17:182. [PMID: 27582050 PMCID: PMC5006368 DOI: 10.1186/s13059-016-1043-8] [Citation(s) in RCA: 147] [Impact Index Per Article: 18.4] [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] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 08/10/2016] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Type II DNA topoisomerases (TOP2) regulate DNA topology by generating transient double stranded breaks during replication and transcription. Topoisomerase II beta (TOP2B) facilitates rapid gene expression and functions at the later stages of development and differentiation. To gain new insight into the genome biology of TOP2B, we used proteomics (BioID), chromatin immunoprecipitation, and high-throughput chromosome conformation capture (Hi-C) to identify novel proximal TOP2B protein interactions and characterize the genomic landscape of TOP2B binding at base pair resolution. RESULTS Our human TOP2B proximal protein interaction network included members of the cohesin complex and nucleolar proteins associated with rDNA biology. TOP2B associates with DNase I hypersensitivity sites, allele-specific transcription factor (TF) binding, and evolutionarily conserved TF binding sites on the mouse genome. Approximately half of all CTCF/cohesion-bound regions coincided with TOP2B binding. Base pair resolution ChIP-exo mapping of TOP2B, CTCF, and cohesin sites revealed a striking structural ordering of these proteins along the genome relative to the CTCF motif. These ordered TOP2B-CTCF-cohesin sites flank the boundaries of topologically associating domains (TADs) with TOP2B positioned externally and cohesin internally to the domain loop. CONCLUSIONS TOP2B is positioned to solve topological problems at diverse cis-regulatory elements and its occupancy is a highly ordered and prevalent feature of CTCF/cohesin binding sites that flank TADs.
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Affiliation(s)
- Liis Uusküla-Reimand
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON Canada
- Department of Gene Technology, Tallinn University of Technology, Tallinn, Estonia
| | - Huayun Hou
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON Canada
| | | | - Matteo Vietri Rudan
- Research Department of Cancer Biology, Cancer Institute, University College London, London, UK
| | - Minggao Liang
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON Canada
| | - Alejandra Medina-Rivera
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON Canada
- Present address: International Laboratory for Research in Human Genomics, Universidad Nacional Autónoma de México, Juriquilla, Querétaro Mexico
| | - Hisham Mohammed
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
- Present address: The Babraham Institute, Cambridge, UK
| | - Dominic Schmidt
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
- Present address: Syncona Partners LLP, London, UK
| | - Petra Schwalie
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
- Present address: Laboratory of Systems Biology and Genetics, Lausanne, Switzerland
| | - Edwin J. Young
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON Canada
| | - Jüri Reimand
- Ontario Institute for Cancer Research, Toronto, ON Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON Canada
| | - Suzana Hadjur
- Research Department of Cancer Biology, Cancer Institute, University College London, London, UK
| | - Anne-Claude Gingras
- Department of Molecular Genetics, University of Toronto, Toronto, ON Canada
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON Canada
| | - Michael D. Wilson
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON Canada
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