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Bottenhorn KL, Sukumaran K, Cardenas-Iniguez C, Habre R, Schwartz J, Chen JC, Herting MM. Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development. ENVIRONMENT INTERNATIONAL 2024; 189:108769. [PMID: 38823157 DOI: 10.1016/j.envint.2024.108769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 05/08/2024] [Accepted: 05/21/2024] [Indexed: 06/03/2024]
Abstract
Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.
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Affiliation(s)
- Katherine L Bottenhorn
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Department of Psychology, Florida International University, Miami, FL, USA.
| | - Kirthana Sukumaran
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Carlos Cardenas-Iniguez
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Rima Habre
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Spatial Sciences Institute, University of Southern California, Los Angeles, CA, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jiu-Chiuan Chen
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Department of Neurology, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA
| | - Megan M Herting
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
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Bottenhorn KL, Sukumaran K, Cardenas-Iniguez C, Habre R, Schwartz J, Chen JC, Herting MM. Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.21.563430. [PMID: 38798573 PMCID: PMC11118378 DOI: 10.1101/2023.10.21.563430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.
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Park Y, Lee MJ, Yoo S, Kim CY, Namgung JY, Park Y, Park H, Lee EC, Yoon YD, Paquola C, Bernhardt BC, Park BY. GAN-MAT: Generative adversarial network-based microstructural profile covariance analysis toolbox. Neuroimage 2024; 291:120595. [PMID: 38554782 DOI: 10.1016/j.neuroimage.2024.120595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 03/25/2024] [Accepted: 03/28/2024] [Indexed: 04/02/2024] Open
Abstract
Multimodal magnetic resonance imaging (MRI) provides complementary information for investigating brain structure and function; for example, an in vivo microstructure-sensitive proxy can be estimated using the ratio between T1- and T2-weighted structural MRI. However, acquiring multiple imaging modalities is challenging in patients with inattentive disorders. In this study, we proposed a comprehensive framework to provide multiple imaging features related to the brain microstructure using only T1-weighted MRI. Our toolbox consists of (i) synthesizing T2-weighted MRI from T1-weighted MRI using a conditional generative adversarial network; (ii) estimating microstructural features, including intracortical covariance and moment features of cortical layer-wise microstructural profiles; and (iii) generating a microstructural gradient, which is a low-dimensional representation of the intracortical microstructure profile. We trained and tested our toolbox using T1- and T2-weighted MRI scans of 1,104 healthy young adults obtained from the Human Connectome Project database. We found that the synthesized T2-weighted MRI was very similar to the actual image and that the synthesized data successfully reproduced the microstructural features. The toolbox was validated using an independent dataset containing healthy controls and patients with episodic migraine as well as the atypical developmental condition of autism spectrum disorder. Our toolbox may provide a new paradigm for analyzing multimodal structural MRI in the neuroscience community and is openly accessible at https://github.com/CAMIN-neuro/GAN-MAT.
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Affiliation(s)
- Yeongjun Park
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Mi Ji Lee
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | | | - Chae Yeon Kim
- Department of Data Science, Inha University, Incheon, South Korea
| | | | - Yunseo Park
- Department of Data Science, Inha University, Incheon, South Korea
| | - Hyunjin Park
- School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, South Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
| | | | | | - Casey Paquola
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich, Jülich, Germany
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Bo-Yong Park
- Department of Data Science, Inha University, Incheon, South Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea; Department of Statistics and Data Science, Inha University, Incheon, South Korea.
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Gu Y, Maria-Stauffer E, Bedford SA, Romero-Garcia R, Grove J, Børglum AD, Martin H, Baron-Cohen S, Bethlehem RA, Warrier V. Polygenic scores for autism are associated with neurite density in adults and children from the general population. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.10.24305539. [PMID: 38645251 PMCID: PMC11030520 DOI: 10.1101/2024.04.10.24305539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Genetic variants linked to autism are thought to change cognition and behaviour by altering the structure and function of the brain. Although a substantial body of literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic variants are linked to changes in cortical macro- and micro-structure. We investigated this using neuroimaging and genetic data from adults (UK Biobank, N = 31,748) and children (ABCD, N = 4,928). Using polygenic scores and genetic correlations we observe a robust negative association between common variants for autism and a magnetic resonance imaging derived phenotype for neurite density (intracellular volume fraction) in the general population. This result is consistent across both children and adults, in both the cortex and in white matter tracts, and confirmed using polygenic scores and genetic correlations. There were no sex differences in this association. Mendelian randomisation analyses provide no evidence for a causal relationship between autism and intracellular volume fraction, although this should be revisited using better powered instruments. Overall, this study provides evidence for shared common variant genetics between autism and cortical neurite density.
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Affiliation(s)
- Yuanjun Gu
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
| | | | - Saashi A. Bedford
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
| | | | | | - Rafael Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH
- Department of Medical Physiology and Biophysics, Instituto de Biomedicina de Sevilla (IBiS), HUVR/CSIC/Universidad de Sevilla/CIBERSAM, ISCIII, 41013, Sevilla, Spain, 41013
| | - Jakob Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, 8210, Denmark
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, Aarhus, 8000, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, 8000, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark, 8000
| | - Anders D. Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, 8210, Denmark
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, Aarhus, 8000, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, 8000, Denmark
| | - Hilary Martin
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK
| | | | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK
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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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6
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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: 3] [Impact Index Per Article: 3.0] [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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Sato J, Vandewouw MM, Bando N, Branson HM, O'Connor DL, Unger SL, Taylor MJ. White matter alterations and cognitive outcomes in children born very low birth weight. Neuroimage Clin 2021; 32:102843. [PMID: 34601309 PMCID: PMC8496319 DOI: 10.1016/j.nicl.2021.102843] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 09/23/2021] [Accepted: 09/24/2021] [Indexed: 10/25/2022]
Abstract
BACKGROUND Very low birth weight (VLBW) infants are at risk for disrupted white matter maturation, yet little is known about the contributing factors, particularly at preschool-age when cognitive difficulties begin to emerge. We examined white matter microstructure in five-year-old VLBW and full-term (FT) children, and its association with cognitive outcomes and birth weight. METHODS Multi-shell diffusion and MR images were obtained for 41 VLBW (mean birth weight: 1028.6 ± 256.8 g) and 26 FT (3295.4 ± 493.9 g) children. Fractional anisotropy (FA), radial diffusivity (RD), neurite orientation dispersion index (ODI) and density index (NDI) were estimated using diffusion tensor and neurite orientation dispersion and density imaging models. Between-group analyses used a general linear model with group and sex as explanatory variables. Within-group associations between white matter microstructure, cognitive outcomes and birth weight were also investigated. RESULTS VLBW compared to FT children showed lower FA and NDI across widespread white matter regions. Smaller clusters of atypical ODI were also found in VLBW children. Within-group analyses in FT children revealed that lower RD and higher NDI were associated with vocabulary acquisition and working memory. In VLBW children, higher FA and NDI, and lower RD and ODI, were associated with improved processing speed. In both groups, FA was positively associated with birth weight. CONCLUSIONS Our findings demonstrate white matter alterations in young VLBW children, including widespread reductions in axon density that may reflect sustained myelination disruptions. The associations with cognitive outcomes may also highlight which of the VLBW children are at higher risk for later cognitive difficulties.
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Affiliation(s)
- Julie Sato
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada; Psychology, University of Toronto, Toronto, Ontario, Canada; Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada.
| | - Marlee M Vandewouw
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada; Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada; Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Nicole Bando
- Translational Medicine, SickKids Research Institute, Toronto, Ontario, Canada
| | - Helen M Branson
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada; Medical Imaging, University of Toronto, Ontario, Canada
| | - Deborah L O'Connor
- Translational Medicine, SickKids Research Institute, Toronto, Ontario, Canada; Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada; Paediatrics, Mount Sinai Health, Toronto, Ontario, Canada
| | - Sharon L Unger
- Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada; Paediatrics, University of Toronto, Toronto, Ontario, Canada; Paediatrics, Mount Sinai Health, Toronto, Ontario, Canada; Division of Neonatology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Margot J Taylor
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada; Psychology, University of Toronto, Toronto, Ontario, Canada; Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada; Medical Imaging, University of Toronto, Ontario, Canada; Paediatrics, University of Toronto, Toronto, Ontario, Canada
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Andica C, Kamagata K, Kirino E, Uchida W, Irie R, Murata S, Aoki S. Neurite orientation dispersion and density imaging reveals white matter microstructural alterations in adults with autism. Mol Autism 2021; 12:48. [PMID: 34193257 PMCID: PMC8247240 DOI: 10.1186/s13229-021-00456-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Accepted: 06/24/2021] [Indexed: 11/10/2022] Open
Abstract
Background Evidences suggesting the association between behavioral anomalies in autism and white matter (WM) microstructural alterations are increasing. Diffusion tensor imaging (DTI) is widely used to infer tissue microstructure. However, due to its lack of specificity, the underlying pathology of reported differences in DTI measures in autism remains poorly understood. Herein, we applied neurite orientation dispersion and density imaging (NODDI) to quantify and define more specific causes of WM microstructural changes associated with autism in adults. Methods NODDI (neurite density index [NDI], orientation dispersion index, and isotropic volume fraction [ISOVF]) and DTI (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity, and radial diffusivity [RD]) measures were compared between autism (N = 26; 19 males and 7 females; 32.93 ± 9.24 years old) and age- and sex-matched typically developing (TD; N = 25; 17 males and 8 females; 34.43 ± 9.02 years old) groups using tract-based spatial statistics and region-of-interest analyses. Linear discriminant analysis using leave-one-out cross-validation (LDA-LOOCV) was also performed to assess the discriminative power of diffusion measures in autism and TD. Results Significantly lower NDI and higher ISOVF, suggestive of decreased neurite density and increased extracellular free-water, respectively, were demonstrated in the autism group compared with the TD group, mainly in commissural and long-range association tracts, but with distinct predominant sides. Consistent with previous reports, the autism group showed lower FA and higher MD and RD when compared with TD group. Notably, LDA-LOOCV suggests that NDI and ISOVF have relatively higher accuracy (82%) and specificity (NDI, 84%; ISOVF, 88%) compared with that of FA, MD, and RD (accuracy, 67–73%; specificity, 68–80%). Limitations The absence of histopathological confirmation limit the interpretation of our findings. Conclusions Our results suggest that NODDI measures might be useful as imaging biomarkers to diagnose autism in adults and assess its behavioral characteristics. Furthermore, NODDI allows interpretation of previous findings on changes in WM diffusion tensor metrics in individuals with autism.
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Affiliation(s)
- Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
| | - Koji Kamagata
- 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
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Ryusuke Irie
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Syo Murata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Radiological Sciences, Faculty of Healthy Sciences, Komazawa University, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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9
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McKenna F, Miles L, Donaldson J, Castellanos FX, Lazar M. Diffusion kurtosis imaging of gray matter in young adults with autism spectrum disorder. Sci Rep 2020; 10:21465. [PMID: 33293640 PMCID: PMC7722927 DOI: 10.1038/s41598-020-78486-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 10/29/2020] [Indexed: 01/20/2023] Open
Abstract
Prior ex vivo histological postmortem studies of autism spectrum disorder (ASD) have shown gray matter microstructural abnormalities, however, in vivo examination of gray matter microstructure in ASD has remained scarce due to the relative lack of non-invasive methods to assess it. The aim of this work was to evaluate the feasibility of employing diffusional kurtosis imaging (DKI) to describe gray matter abnormalities in ASD in vivo. DKI data were examined for 16 male participants with a diagnosis of ASD and IQ>80 and 17 age- and IQ-matched male typically developing (TD) young adults 18-25 years old. Mean (MK), axial (AK), radial (RK) kurtosis and mean diffusivity (MD) metrics were calculated for lobar and sub-lobar regions of interest. Significantly decreased MK, RK, and MD were found in ASD compared to TD participants in the frontal and temporal lobes and several sub-lobar regions previously associated with ASD pathology. In ASD participants, decreased kurtosis in gray matter ROIs correlated with increased repetitive and restricted behaviors and poor social interaction symptoms. Decreased kurtosis in ASD may reflect a pathology associated with a less restrictive microstructural environment such as decreased neuronal density and size, atypically sized cortical columns, or limited dendritic arborizations.
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Affiliation(s)
- Faye McKenna
- Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, 660 First Ave, Fourth Floor, New York, NY, USA.
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA.
| | - Laura Miles
- Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, 660 First Ave, Fourth Floor, New York, NY, USA
| | - Jeffrey Donaldson
- Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, 660 First Ave, Fourth Floor, New York, NY, USA
| | - F Xavier Castellanos
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Mariana Lazar
- Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, 660 First Ave, Fourth Floor, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA
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10
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Abstract
The prevalence of obesity in children and adolescents worldwide has quadrupled since 1975 and is a key predictor of obesity later in life. Previous work has consistently observed relationships between macroscale measures of reward-related brain regions (e.g., the nucleus accumbens [NAcc]) and unhealthy eating behaviors and outcomes; however, the mechanisms underlying these associations remain unclear. Recent work has highlighted a potential role of neuroinflammation in the NAcc in animal models of diet-induced obesity. Here, we leverage a diffusion MRI technique, restriction spectrum imaging, to probe the microstructure (cellular density) of subcortical brain regions. More specifically, we test the hypothesis that the cell density of reward-related regions is associated with obesity-related metrics and early weight gain. In a large cohort of nine- and ten-year-olds enrolled in the Adolescent Brain Cognitive Development (ABCD) study, we demonstrate that cellular density in the NAcc is related to individual differences in waist circumference at baseline and is predictive of increases in waist circumference after 1 y. These findings suggest a neurobiological mechanism for pediatric obesity consistent with rodent work showing that high saturated fat diets increase gliosis and neuroinflammation in reward-related brain regions, which in turn lead to further unhealthy eating and obesity.
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11
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Hope TR, Selnes P, Rektorová I, Anderkova L, Nemcova-Elfmarkova N, Balážová Z, Dale A, Bjørnerud A, Fladby T. Diffusion tensor and restriction spectrum imaging reflect different aspects of neurodegeneration in Parkinson's disease. PLoS One 2019; 14:e0217922. [PMID: 31150514 PMCID: PMC6544302 DOI: 10.1371/journal.pone.0217922] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Accepted: 05/21/2019] [Indexed: 11/19/2022] Open
Abstract
To meet the need for Parkinson's disease biomarkers and evidence for amount and distribution of pathological changes, MRI diffusion tensor imaging (DTI) has been explored in a number of previous studies. However, conflicting results warrant further investigations. As tissue microstructure, particularly of the grey matter, is heterogeneous, a more precise diffusion model may benefit tissue characterization. The purpose of this study was to analyze the diffusion-based imaging technique restriction spectrum imaging (RSI) and DTI, and their ability to detect microstructural changes within brain regions associated with motor function in Parkinson's disease. Diffusion weighted (DW) MR images of a total of 100 individuals, (46 Parkinson's disease patients and 54 healthy controls) were collected using b-values of 0-4000s/mm2. Output diffusion-based maps were estimated based on the RSI-model combining the full set of DW-images (Cellular Index (CI), Neurite Density (ND)) and DTI-model combining b = 0 and b = 1000 s/mm2 (fractional anisotropy (FA), Axial-, Mean- and Radial diffusivity (AD, MD, RD)). All parametric maps were analyzed in a voxel-wise group analysis, with focus on typical brain regions associated with Parkinson's disease pathology. CI, ND and DTI diffusivity metrics (AD, MD, RD) demonstrated the ability to differentiate between groups, with strongest performance within the thalamus, prone to pathology in Parkinson's disease. Our results indicate that RSI may improve the predictive power of diffusion-based MRI, and provide additional information when combined with the standard diffusivity measurements. In the absence of major atrophy, diffusion techniques may reveal microstructural pathology. Our results suggest that protocols for MRI diffusion imaging may be adapted to more sensitive detection of pathology at different sites of the central nervous system.
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Affiliation(s)
- Tuva R. Hope
- Diagnostic Physics, Division of Radiology & Nuclear Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- * E-mail:
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, Loerenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Irena Rektorová
- Central European Institute of Technology, CEITEC Masaryk University, Brno, Czech Republic
- First Department of Neurology, Medical Faculty, Masaryk University and St. Anne’s University Hospital, Brno, Czech Republic
| | - Lubomira Anderkova
- Central European Institute of Technology, CEITEC Masaryk University, Brno, Czech Republic
| | | | - Zuzana Balážová
- Central European Institute of Technology, CEITEC Masaryk University, Brno, Czech Republic
| | - Anders Dale
- Department of Neurosciences, University of California, San Diego, La Jolla, California, United States of America
- Deparment of Radiology, University of California San Diego, San Diego, La Jolla, California, United States of America
- Deparment of Cognitive Sciences, University of California San Diego, San Diego, La Jolla, California, United States of America
| | - Atle Bjørnerud
- Diagnostic Physics, Division of Radiology & Nuclear Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Department of Physics, University of Oslo, Oslo, Norway
| | - Tormod Fladby
- Department of Neurology, Akershus University Hospital, Loerenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
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12
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Young JM, Vandewouw MM, Mossad SI, Morgan BR, Lee W, Smith ML, Sled JG, Taylor MJ. White matter microstructural differences identified using multi-shell diffusion imaging in six-year-old children born very preterm. NEUROIMAGE-CLINICAL 2019; 23:101855. [PMID: 31103872 PMCID: PMC6737393 DOI: 10.1016/j.nicl.2019.101855] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 04/08/2019] [Accepted: 05/02/2019] [Indexed: 10/29/2022]
Abstract
INTRODUCTION The underlying microstructural properties of white matter differences in children born very preterm (<32 weeks gestational age) can be investigated in depth using multi-shell diffusion imaging. The present study compared white matter across the whole brain using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics in children born very preterm and full-term children at six years of age. We also investigated associations between white matter microstructure with early brain injury and developmental outcomes. METHOD Multi-shell diffusion imaging, T1-weighted anatomical MR images and developmental assessments were acquired in 23 children born very preterm (16 males; mean scan age: 6.57 ± 0.34 years) and 24 full-term controls (10 males, mean scan age: 6.62 ± 0.37 years). DTI metrics were obtained and neurite orientation dispersion index (ODI) and density index (NDI) were estimated using the NODDI diffusion model. FSL's tract-based spatial statistics were performed on traditional DTI metrics and NODDI metrics. Voxel-wise comparisons were performed to test between-group differences and within-group associations with developmental outcomes (intelligence and visual motor abilities) as well as early white matter injury and germinal matrix/intraventricular haemorrhage (GMH/IVH). RESULTS In comparison to term-born children, the children born very preterm exhibited lower fractional anisotropy (FA) across many white matter regions as well as higher mean diffusivity (MD), radial diffusivity (RD), and ODI. Within-group analyses of the children born very preterm revealed associations between higher FA and NDI with higher IQ and VMI. Lower ODI was found within the corona radiata in those with a history of white matter injury. Within the full-term group, associations were found between higher NDI and ODI with lower IQ. CONCLUSION Children born very preterm exhibit lower FA and higher ODI than full-term children. NODDI metrics provide more biologically specific information beyond DTI metrics as well as additional information of the impact of prematurity and white matter microstructure on cognitive outcomes at six years of age.
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Affiliation(s)
- Julia M Young
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada.
| | - Marlee M Vandewouw
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada
| | - Sarah I Mossad
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - Benjamin R Morgan
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada
| | - Wayne Lee
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada
| | - Mary Lou Smith
- Department of Psychology, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - John G Sled
- Translational Medicine, SickKids Research Institute, Toronto, ON, Canada; Department of Biomedical Physics, University of Toronto, Toronto, ON, Canada
| | - Margot J Taylor
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada; Neurosciences and Mental Health, SickKids Research Institute, Toronto, ON, Canada; Department of Medical Imaging, University of Toronto, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada
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13
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Dadalko OI, Travers BG. Evidence for Brainstem Contributions to Autism Spectrum Disorders. Front Integr Neurosci 2018; 12:47. [PMID: 30337860 PMCID: PMC6180283 DOI: 10.3389/fnint.2018.00047] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 09/18/2018] [Indexed: 12/27/2022] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects one in 59 children in the United States. Although there is a mounting body of knowledge of cortical and cerebellar contributions to ASD, our knowledge about the early developing brainstem in ASD is only beginning to accumulate. Understanding how brainstem neurotransmission is implicated in ASD is important because many of this condition’s sensory and motor symptoms are consistent with brainstem pathology. Therefore, the purpose of this review was to integrate epidemiological, behavioral, histological, neuroimaging, and animal evidence of brainstem contributions to ASD. Because ASD is a neurodevelopmental condition, we examined the available data through a lens of hierarchical brain development. The review of the literature suggests that developmental alterations of the brainstem could have potential cascading effects on cortical and cerebellar formation, ultimately leading to ASD symptoms. This view is supported by human epidemiology findings and data from animal models of ASD, showing that perturbed development of the brainstem substructures, particularly during the peak formation of the brainstem’s monoaminergic centers, may relate to ASD or ASD-like behaviors. Furthermore, we review evidence from human histology, psychophysiology, and neuroimaging suggesting that brainstem development and maturation may be atypical in ASD and may be related to key ASD symptoms, such as atypical sensorimotor features and social responsiveness. From this review there emerges the need of future research to validate early detection of the brainstem-based somatosensory and psychophysiological behaviors that emerge in infancy, and to examine the brainstem across the life span, while accounting for age. In all, there is preliminary evidence for brainstem involvement in ASD, but a better understanding of the brainstem’s role would likely pave the way for earlier diagnosis and treatment of ASD.
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Affiliation(s)
- Olga I Dadalko
- Motor and Brain Development Lab, Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Brittany G Travers
- Motor and Brain Development Lab, Occupational Therapy Program in the Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, United States
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14
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Decreased neurite density within frontostriatal networks is associated with executive dysfunction in temporal lobe epilepsy. Epilepsy Behav 2018; 78:187-193. [PMID: 29126704 PMCID: PMC5756677 DOI: 10.1016/j.yebeh.2017.09.012] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 09/11/2017] [Accepted: 09/16/2017] [Indexed: 11/21/2022]
Abstract
OBJECTIVE Executive dysfunction is observed in a sizable number of patients with refractory temporal lobe epilepsy (TLE). The frontostriatal network has been proposed to play a significant role in executive functioning, however, because of the complex architecture of these tracts, it is difficult to generate measures of fiber tract microstructure using standard diffusion tensor imaging. To examine the association between frontostriatal network compromise and executive dysfunction in TLE, we applied an advanced, multishell diffusion model, restriction spectrum imaging (RSI), that isolates measures of intraaxonal diffusion and may provide better estimates of fiber tract compromise in TLE. METHODS Restriction spectrum imaging scans were obtained from 32 patients with TLE [16 right TLE (RTLE); 16 left TLE (LTLE)] and 24 healthy controls (HC). An RSI-derived measure of intraaxonal anisotropic diffusion (neurite density; ND) was calculated for the inferior frontostriatal tract (IFS) and superior frontostriatal tract (SFS) and compared between patients with TLE and HC. Spearman correlations were performed to evaluate the relationships between ND of each tract and verbal (i.e., D-KEFS Category Switching Accuracy and Color-Word Interference Inhibition/Switching) and visuomotor (Trail Making Test) set-shifting performances in patients with TLE. RESULTS Patients with TLE demonstrated reductions in ND of the left and right IFS, but not SFS, compared with HC. Reduction in ND of left and right IFS was associated with poorer performance on verbal set-shifting in TLE. Increases in extracellular diffusion (isotropic hindered; IH) were not associated with executive dysfunction in the patient group. SIGNIFICANCE Restriction spectrum imaging-derived ND revealed microstructural changes within the IFS in patients with TLE, which was associated with poorer executive functioning. This suggests that axonal/myelin loss to fiber networks connecting the striatum to the inferior frontal cortex is likely contributing to executive dysfunction in TLE.
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15
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Reas ET, Hagler DJ, White NS, Kuperman JM, Bartsch H, Cross K, Loi RQ, Balachandra AR, Meloy MJ, Wierenga CE, Galasko D, Brewer JB, Dale AM, McEvoy LK. Sensitivity of restriction spectrum imaging to memory and neuropathology in Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2017; 9:55. [PMID: 28764771 PMCID: PMC5539622 DOI: 10.1186/s13195-017-0281-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 06/27/2017] [Indexed: 11/24/2022]
Abstract
Background Diffusion imaging has demonstrated sensitivity to structural brain changes in Alzheimer’s disease (AD). However, there remains a need for a more complete characterization of microstructural alterations occurring at the earliest disease stages, and how these changes relate to underlying neuropathology. This study evaluated the sensitivity of restriction spectrum imaging (RSI), an advanced diffusion magnetic resonance imaging (MRI) technique, to microstructural brain changes in mild cognitive impairment (MCI) and AD. Methods MRI and neuropsychological test data were acquired from 31 healthy controls, 12 individuals with MCI, and 13 individuals with mild AD, aged 63–93 years. Cerebrospinal fluid amyloid-β levels were measured in a subset (n = 38) of participants. RSI measures of neurite density (ND) and isotropic free water (IF) were computed in fiber tracts and in hippocampal and entorhinal cortex gray matter, respectively. Analyses evaluated whether these measures predicted memory performance, correlated with amyloid-β levels, and distinguished impaired individuals from controls. For comparison, analyses were repeated with standard diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA) and mean diffusivity. Results Both RSI and DTI measures correlated with episodic memory and disease severity. RSI, but not DTI, measures correlated with amyloid-β42 levels. ND and FA in the arcuate fasciculus and entorhinal cortex IF most strongly predicted recall performance. RSI measures of arcuate fasciculus ND and entorhinal cortex IF best discriminated memory impaired participants from healthy participants. Conclusions RSI is highly sensitive to microstructural changes in the early stages of AD, and is associated with biochemical markers of AD pathology. Reduced ND in cortical association fibers and increased medial temporal lobe free-water diffusion predicted episodic memory, distinguished cognitively impaired from healthy individuals, and correlated with amyloid-β. Although further research is needed to assess the sensitivity of RSI to preclinical AD and disease progression, these results suggest that RSI may be a promising tool to better understand neuroanatomical changes in AD and their association with neuropathology. Electronic supplementary material The online version of this article (doi:10.1186/s13195-017-0281-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Emilie T Reas
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA. .,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA.
| | - Donald J Hagler
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
| | - Nathan S White
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
| | - Joshua M Kuperman
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
| | - Hauke Bartsch
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
| | - Karalani Cross
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Richard Q Loi
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA.,Wayne State University School of Medicine, Detroit, MI, USA
| | - Akshara R Balachandra
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
| | - M J Meloy
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Christina E Wierenga
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.,Department of Veterans Affairs, San Diego Healthcare system, La Jolla, CA, USA
| | - Douglas Galasko
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - James B Brewer
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA.,Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA.,Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA.,Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA
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