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Mendoza C, Román C, Mangin JF, Hernández C, Guevara P. Short fiber bundle filtering and test-retest reproducibility of the Superficial White Matter. Front Neurosci 2024; 18:1394681. [PMID: 38737100 PMCID: PMC11088237 DOI: 10.3389/fnins.2024.1394681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 04/08/2024] [Indexed: 05/14/2024] Open
Abstract
In recent years, there has been a growing interest in studying the Superficial White Matter (SWM). The SWM consists of short association fibers connecting near giry of the cortex, with a complex organization due to their close relationship with the cortical folding patterns. Therefore, their segmentation from dMRI tractography datasets requires dedicated methodologies to identify the main fiber bundle shape and deal with spurious fibers. This paper presents an enhanced short fiber bundle segmentation based on a SWM bundle atlas and the filtering of noisy fibers. The method was tuned and evaluated over HCP test-retest probabilistic tractography datasets (44 subjects). We propose four fiber bundle filters to remove spurious fibers. Furthermore, we include the identification of the main fiber fascicle to obtain well-defined fiber bundles. First, we identified four main bundle shapes in the SWM atlas, and performed a filter tuning in a subset of 28 subjects. The filter based on the Convex Hull provided the highest similarity between corresponding test-retest fiber bundles. Subsequently, we applied the best filter in the 16 remaining subjects for all atlas bundles, showing that filtered fiber bundles significantly improve test-retest reproducibility indices when removing between ten and twenty percent of the fibers. Additionally, we applied the bundle segmentation with and without filtering to the ABIDE-II database. The fiber bundle filtering allowed us to obtain a higher number of bundles with significant differences in fractional anisotropy, mean diffusivity, and radial diffusivity of Autism Spectrum Disorder patients relative to controls.
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Affiliation(s)
- Cristóbal Mendoza
- Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
| | - Claudio Román
- Centro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso, Chile
| | | | - Cecilia Hernández
- Department of Computer Science, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
- Center for Biotechnology and Bioengineering (CeBiB), Santiago, Chile
| | - Pamela Guevara
- Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
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DiPiero M, Cordash H, Prigge MB, King CK, Morgan J, Guerrero-Gonzalez J, Adluru N, King JB, Lange N, Bigler ED, Zielinski BA, Alexander AL, Lainhart JE, Dean DC. Tract- and gray matter- based spatial statistics show white matter and gray matter microstructural differences in autistic males. Front Neurosci 2023; 17:1231719. [PMID: 37829720 PMCID: PMC10565827 DOI: 10.3389/fnins.2023.1231719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/07/2023] [Indexed: 10/14/2023] Open
Abstract
Background Autism spectrum disorder (ASD) is a neurodevelopmental condition commonly studied in the context of early childhood. As ASD is a life-long condition, understanding the characteristics of brain microstructure from adolescence into adulthood and associations to clinical features is critical for improving outcomes across the lifespan. In the current work, we utilized Tract Based Spatial Statistics (TBSS) and Gray Matter Based Spatial Statistics (GBSS) to examine the white matter (WM) and gray matter (GM) microstructure in neurotypical (NT) and autistic males. Methods Multi-shell diffusion MRI was acquired from 78 autistic and 81 NT males (12-to-46-years) and fit to the DTI and NODDI diffusion models. TBSS and GBSS were performed to analyze WM and GM microstructure, respectively. General linear models were used to investigate group and age-related group differences. Within the ASD group, relationships between WM and GM microstructure and measures of autistic symptoms were investigated. Results All dMRI measures were significantly associated with age across WM and GM. Significant group differences were observed across WM and GM. No significant age-by-group interactions were detected. Within the ASD group, positive relationships with WM microstructure were observed with ADOS-2 Calibrated Severity Scores. Conclusion Using TBSS and GBSS our findings provide new insights into group differences of WM and GM microstructure in autistic males from adolescence into adulthood. Detection of microstructural differences across the lifespan as well as their relationship to the level of autistic symptoms will deepen to our understanding of brain-behavior relationships of ASD and may aid in the improvement of intervention options for autistic adults.
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Affiliation(s)
- Marissa DiPiero
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, United States
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Hassan Cordash
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Molly B. Prigge
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | - Carolyn K. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | - Jubel Morgan
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | | | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Jace B. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | - Nicholas Lange
- Department of Psychiatry, Harvard School of Medicine, Boston, MA, United States
| | - Erin D. Bigler
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
- Department of Neurology, University of Utah, Salt Lake City, UT, United States
- Department of Psychiatry, University of Utah, Salt Lake City, UT, United States
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo, UT, United States
- Department of Neurology, University of California, Davis, Davis, CA, United States
| | - Brandon A. Zielinski
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
- Department of Neurology, University of Utah, Salt Lake City, UT, United States
- Department of Pediatrics, University of Utah, Salt Lake City, UT, United States
- Departments of Pediatrics and Neurology, University of Florida, Gainesville, FL, United States
- McKnight Brain Institute, University of Florida, Gainesville, FL, United States
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Janet E. Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Douglas C. Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States
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Arai T, Kamagata K, Uchida W, Andica C, Takabayashi K, Saito Y, Tuerxun R, Mahemuti Z, Morita Y, Irie R, Kirino E, Aoki S. Reduced neurite density index in the prefrontal cortex of adults with autism assessed using neurite orientation dispersion and density imaging. Front Neurol 2023; 14:1110883. [PMID: 37638188 PMCID: PMC10450631 DOI: 10.3389/fneur.2023.1110883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 07/27/2023] [Indexed: 08/29/2023] Open
Abstract
Background Core symptoms of autism-spectrum disorder (ASD) have been associated with prefrontal cortex abnormalities. However, the mechanisms behind the observation remain incomplete, partially due to the challenges of modeling complex gray matter (GM) structures. This study aimed to identify GM microstructural alterations in adults with ASD using neurite orientation dispersion and density imaging (NODDI) and voxel-wise GM-based spatial statistics (GBSS) to reduce the partial volume effects from the white matter and cerebrospinal fluid. Materials and methods A total of 48 right-handed participants were included, of which 22 had ASD (17 men; mean age, 34.42 ± 8.27 years) and 26 were typically developing (TD) individuals (14 men; mean age, 32.57 ± 9.62 years). The metrics of NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) were compared between groups using GBSS. Diffusion tensor imaging (DTI) metrics and surface-based cortical thickness were also compared. The associations between magnetic resonance imaging-based measures and ASD-related scores, including ASD-spectrum quotient, empathizing quotient, and systemizing quotient were also assessed in the region of interest (ROI) analysis. Results After controlling for age, sex, and intracranial volume, GBSS demonstrated significantly lower NDI in the ASD group than in the TD group in the left prefrontal cortex (caudal middle frontal, lateral orbitofrontal, pars orbitalis, pars triangularis, rostral middle frontal, and superior frontal region). In the ROI analysis of individuals with ASD, a significantly positive correlation was observed between the NDI in the left rostral middle frontal, superior frontal, and left frontal pole and empathizing quotient score. No significant between-group differences were observed in all DTI metrics, other NODDI (i.e., ODI and ISOVF) metrics, and cortical thickness. Conclusion GBSS analysis was used to demonstrate the ability of NODDI metrics to detect GM microstructural alterations in adults with ASD, while no changes were detected using DTI and cortical thickness evaluation. Specifically, we observed a reduced neurite density index in the left prefrontal cortices associated with reduced empathic abilities.
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Affiliation(s)
- Takashi Arai
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Koji Kamagata
- Faculty of Health Data Science, Juntendo University, Chiba, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Faculty of Health Data Science, Juntendo University, Chiba, Japan
| | - Kaito Takabayashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuya Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Rukeye Tuerxun
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Zaimire Mahemuti
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuichi Morita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Ryusuke Irie
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Eiji Kirino
- Department of Psychiatry, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Psychiatry, Juntendo University Shizuoka Hospital, Shizuoka, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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Villaseñor PJ, Cortés-Servín D, Pérez-Moriel A, Aquiles A, Luna-Munguía H, Ramirez-Manzanares A, Coronado-Leija R, Larriva-Sahd J, Concha L. Multi-tensor diffusion abnormalities of gray matter in an animal model of cortical dysplasia. Front Neurol 2023; 14:1124282. [PMID: 37342776 PMCID: PMC10278582 DOI: 10.3389/fneur.2023.1124282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 04/18/2023] [Indexed: 06/23/2023] Open
Abstract
Focal cortical dysplasias are a type of malformations of cortical development that are a common cause of drug-resistant focal epilepsy. Surgical treatment is a viable option for some of these patients, with their outcome being highly related to complete surgical resection of lesions visible in magnetic resonance imaging (MRI). However, subtle lesions often go undetected on conventional imaging. Several methods to analyze MRI have been proposed, with the common goal of rendering subtle cortical lesions visible. However, most image-processing methods are targeted to detect the macroscopic characteristics of cortical dysplasias, which do not always correspond to the microstructural disarrangement of these cortical malformations. Quantitative analysis of diffusion-weighted MRI (dMRI) enables the inference of tissue characteristics, and novel methods provide valuable microstructural features of complex tissue, including gray matter. We investigated the ability of advanced dMRI descriptors to detect diffusion abnormalities in an animal model of cortical dysplasia. For this purpose, we induced cortical dysplasia in 18 animals that were scanned at 30 postnatal days (along with 19 control animals). We obtained multi-shell dMRI, to which we fitted single and multi-tensor representations. Quantitative dMRI parameters derived from these methods were queried using a curvilinear coordinate system to sample the cortical mantle, providing inter-subject anatomical correspondence. We found region- and layer-specific diffusion abnormalities in experimental animals. Moreover, we were able to distinguish diffusion abnormalities related to altered intra-cortical tangential fibers from those associated with radial cortical fibers. Histological examinations revealed myelo-architectural abnormalities that explain the alterations observed through dMRI. The methods for dMRI acquisition and analysis used here are available in clinical settings and our work shows their clinical relevance to detect subtle cortical dysplasias through analysis of their microstructural properties.
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Affiliation(s)
- Paulina J. Villaseñor
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | - David Cortés-Servín
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | | | - Ana Aquiles
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | - Hiram Luna-Munguía
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | | | - Ricardo Coronado-Leija
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States
| | - Jorge Larriva-Sahd
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | - Luis Concha
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
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DiPiero MA, Surgent OJ, Travers BG, Alexander AL, Lainhart JE, Dean Iii DC. Gray matter microstructure differences in autistic males: A gray matter based spatial statistics study. Neuroimage Clin 2022; 37:103306. [PMID: 36587584 PMCID: PMC9817031 DOI: 10.1016/j.nicl.2022.103306] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 11/29/2022] [Accepted: 12/24/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a complex neurodevelopmental condition. Understanding the brain's microstructure and its relationship to clinical characteristics is important to advance our understanding of the neural supports underlying ASD. In the current work, we implemented Gray-Matter Based Spatial Statistics (GBSS) to examine and characterize cortical microstructure and assess differences between typically developing (TD) and autistic males. METHODS A multi-shell diffusion MRI (dMRI) protocol was acquired from 83 TD and 70 autistic males (5-to-21-years) and fit to the DTI and NODDI models. GBSS was performed for voxelwise analysis of cortical gray matter (GM). General linear models were used to investigate group differences, while age-by-group interactions assessed age-related differences between groups. Within the ASD group, relationships between cortical microstructure and measures of autistic symptoms were investigated. RESULTS All dMRI measures were significantly associated with age across the GM skeleton. Group differences and age-by-group interactions are reported. Group-wise increases in neurite density in autistic individuals were observed across frontal, temporal, and occipital regions of the right hemisphere. Significant age-by-group interactions of neurite density were observed within the middle frontal gyrus, precentral gyrus, and frontal pole. Negative relationships between neurite dispersion and the ADOS-2 Calibrated Severity Scores (CSS) were observed within the ASD group. DISCUSSION Findings demonstrate group and age-related differences between groups in neurite density in ASD across right-hemisphere brain regions supporting cognitive processes. Results provide evidence of altered neurodevelopmental processes affecting GM microstructure in autistic males with implications for the role of cortical microstructure in the level of autistic symptoms. CONCLUSION Using dMRI and GBSS, our findings provide new insights into group and age-related differences of the GM microstructure in autistic males. Defining where and when these cortical GM differences arise will contribute to our understanding of brain-behavior relationships of ASD and may aid in the development and monitoring of targeted and individualized interventions.
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Affiliation(s)
- Marissa A DiPiero
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Olivia J Surgent
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Brittany G Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Occupational Therapy Program, University of Wisconsin-Madison, Madison, WI, USA; Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Andrew L Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Janet E Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Douglas C Dean Iii
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA; Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA.
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Peterson BS, Liu J, Dantec L, Newman C, Sawardekar S, Goh S, Bansal R. Using tissue microstructure and multimodal MRI to parse the phenotypic heterogeneity and cellular basis of autism spectrum disorder. J Child Psychol Psychiatry 2022; 63:855-870. [PMID: 34762311 PMCID: PMC9091058 DOI: 10.1111/jcpp.13531] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/08/2021] [Indexed: 01/11/2023]
Abstract
BACKGROUND Identifying the brain bases for phenotypic heterogeneity in Autism Spectrum Disorder (ASD) will advance understanding of its pathogenesis and improve its clinical management. METHODS We compared Diffusion Tensor Imaging (DTI) indices and connectome measures between 77 ASD and 88 Typically Developing (TD) control participants. We also assessed voxel-wise associations of DTI indices with measures of regional cerebral blood flow (rCBF) and N-acetylaspartate (NAA) to understand how tissue microstructure associates with cellular metabolism and neuronal density, respectively. RESULTS Autism Spectrum Disorder participants had significantly lower fractional anisotropy (FA) and higher diffusivity values in deep white matter tracts, likely representing ether reduced myelination by oligodendrocytes or a reduced density of myelinated axons. Greater abnormalities in these measures and regions were associated with higher ASD symptom scores. Participant age, sex and IQ significantly moderated these group differences. Path analyses showed that reduced NAA levels accounted significantly for higher diffusivity and higher rCBF values in ASD compared with TD participants. CONCLUSIONS Reduced neuronal density (reduced NAA) likely underlies abnormalities in DTI indices of white matter microstructure in ASD, which in turn are major determinants of elevated blood flow. Together, these findings suggest the presence of reduced axonal density and axonal pathology in ASD white matter. Greater pathology in turn accounts for more severe symptoms, lower intellectual ability, and reduced global efficiency for measures of white matter connectivity in ASD.
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Affiliation(s)
- Bradley S. Peterson
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
| | - Jiaqi Liu
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | - Louis Dantec
- École Polytechnique Universitaire de Marseille, France
| | | | - Siddhant Sawardekar
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | | | - Ravi Bansal
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
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Mo K, Sadoway T, Bonato S, Ameis SH, Anagnostou E, Lerch JP, Taylor MJ, Lai MC. Sex/gender differences in the human autistic brains: A systematic review of 20 years of neuroimaging research. Neuroimage Clin 2021; 32:102811. [PMID: 34509922 PMCID: PMC8436080 DOI: 10.1016/j.nicl.2021.102811] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 06/25/2021] [Accepted: 08/29/2021] [Indexed: 12/01/2022]
Abstract
Our current understanding of autism is largely based on clinical experiences and research involving male individuals given the male-predominance in prevalence and the under-inclusion of female individuals due to small samples, co-occurring conditions, or simply being missed for diagnosis. There is a significantly biased 'male lens' in this field with autistic females insufficiently understood. We therefore conducted a systematic review to examine how sex and gender modulate brain structure and function in autistic individuals. Findings from the past 20 years are yet to converge on specific brain regions/networks with consistent sex/gender-modulating effects. Despite at least three well-powered studies identifying specific patterns of significant sex/gender-modulation of autism-control differences, many other studies are likely underpowered, suggesting a critical need for future investigation into sex/gender-based heterogeneity with better-powered designs. Future research should also formally investigate the effects of gender, beyond biological sex, which is mostly absent in the current literature. Understanding the roles of sex and gender in the development of autism is an imperative step to extend beyond the 'male lens' in this field.
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Affiliation(s)
- Kelly Mo
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
| | - Tara Sadoway
- Department of Paediatric Laboratory Medicine, Hospital for Sick Children, Toronto, Canada
| | - Sarah Bonato
- Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
| | - Stephanie H Ameis
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, Hospital for Sick Children, Toronto, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Evdokia Anagnostou
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada; Department of Paediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Jason P Lerch
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom; Neurosciences & Mental Health Program, SickKids Research Institute, Toronto, Canada
| | - Margot J Taylor
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Neurosciences & Mental Health Program, SickKids Research Institute, Toronto, Canada; Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
| | - Meng-Chuan Lai
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, Hospital for Sick Children, Toronto, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Neurosciences & Mental Health Program, SickKids Research Institute, Toronto, Canada; Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.
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