160 results on '"Shen, Mark D."'
Search Results
2. Brain volumes, cognitive, and adaptive skills in school-age children with Down syndrome
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Grzadzinski, Rebecca, Mata, Kattia, Bhatt, Ambika S., Jatkar, Alapika, Garic, Dea, Shen, Mark D., Girault, Jessica B., St. John, Tanya, Pandey, Juhi, Zwaigenbaum, Lonnie, Estes, Annette, Shen, Audrey M., Dager, Stephen, Schultz, Robert, Botteron, Kelly, Marrus, Natasha, Styner, Martin, Evans, Alan, Kim, Sun Hyung, McKinstry, Robert, Gerig, Guido, Piven, Joseph, and Hazlett, Heather
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- 2024
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3. Parent attitudes towards predictive testing for autism in the first year of life
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Washington, Aurora M., Mercer, Amanda H., Burrows, Catherine A., Dager, Stephen R., Elison, Jed T., Estes, Annette M., Grzadzinski, Rebecca, Lee, Chimei, Piven, Joseph, Pruett, Jr, John R., Shen, Mark D., Wilfond, Benjamin, Wolff, Jason, Zwaigenbaum, Lonnie, and MacDuffie, Katherine E.
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- 2024
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4. Differential cognitive and behavioral development from 6 to 24 months in autism and fragile X syndrome
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Mullin, Lindsay J., Rutsohn, Joshua, Gross, Julia L., Caravella, Kelly E., Grzadzinski, Rebecca L., Weisenfeld, Leigh Anne, Flake, Lisa, Botteron, Kelly N., Dager, Stephen R., Estes, Annette M., Pandey, Juhi, Schultz, Robert T., St. John, Tanya, Wolff, Jason J., Shen, Mark D., Piven, Joseph, Hazlett, Heather C., and Girault, Jessica B.
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- 2024
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5. White matter development and language abilities during infancy in autism spectrum disorder
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McFayden, Tyler C., Rutsohn, Joshua, Cetin, Gizem, Forsen, Elizabeth, Swanson, Meghan R., Meera, Shoba S., Wolff, Jason J., Elison, Jed T., Shen, Mark D., Botteron, Kelly, Dager, Stephen R., Estes, Annette, Gerig, Guido, McKinstry, Robert C., Pandey, Juhi, Schultz, Robert, St. John, Tanya, Styner, Martin, Truong, Young, Zwaigenbaum, Lonnie, Hazlett, Heather C., Piven, Joseph, and Girault, Jessica B.
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- 2024
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6. Enabling endpoint development for interventional clinical trials in individuals with Angelman syndrome: a prospective, longitudinal, observational clinical study (FREESIAS)
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Tjeertes, Jorrit, Bacino, Carlos A., Bichell, Terry Jo, Bird, Lynne M., Bustamante, Mariana, Crean, Rebecca, Jeste, Shafali, Komorowski, Robert W., Krishnan, Michelle L., Miller, Meghan T., Nobbs, David, Ochoa-Lubinoff, Cesar, Parkerson, Kimberly A., Rotenberg, Alexander, Sadhwani, Anjali, Shen, Mark D., Squassante, Lisa, Tan, Wen-Hann, Vincenzi, Brenda, Wheeler, Anne C., Hipp, Joerg F., and Berry-Kravis, Elizabeth
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- 2023
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7. Identification of subgroups of children in the Australian Autism Biobank using latent class analysis
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Montgomery, Alicia, Masi, Anne, Whitehouse, Andrew, Veenstra-VanderWeele, Jeremy, Shuffrey, Lauren, Shen, Mark D., Karlov, Lisa, Uljarevic, Mirko, Alvares, Gail, Woolfenden, Sue, Silove, Natalie, and Eapen, Valsamma
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- 2023
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8. Associations between early trajectories of amygdala development and later school-age anxiety in two longitudinal samples
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Burrows, Catherine A., Lasch, Carolyn, Gross, Julia, Girault, Jessica B., Rutsohn, Joshua, Wolff, Jason J., Swanson, Meghan R., Lee, Chimei M., Dager, Stephen R., Cornea, Emil, Stephens, Rebecca, Styner, Martin, John, Tanya St., Pandey, Juhi, Deva, Meera, Botteron, Kelly N., Estes, Annette M., Hazlett, Heather C., Pruett, John R., Jr., Schultz, Robert T., Zwaigenbaum, Lonnie, Gilmore, John H., Shen, Mark D., Piven, Joseph, and Elison, Jed T.
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- 2024
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9. A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder–Associated Impairment in Early Childhood
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Burrows, Catherine A., Grzadzinski, Rebecca L., Donovan, Kevin, Stallworthy, Isabella C., Rutsohn, Joshua, St. John, Tanya, Marrus, Natasha, Parish-Morris, Julia, MacIntyre, Leigh, Hampton, Jacqueline, Pandey, Juhi, Shen, Mark D., Botteron, Kelly N., Estes, Annette M., Dager, Stephen R., Hazlett, Heather C., Pruett, John R., Jr., Schultz, Robert T., Zwaigenbaum, Lonnie, Truong, Kinh N., Piven, Joseph, and Elison, Jed T.
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- 2022
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10. Extra-axial cerebrospinal fluid in high-risk and normal-risk children with autism aged 2–4 years: a case-control study
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Shen, Mark D, Nordahl, Christine W, Li, Deana D, Lee, Aaron, Angkustsiri, Kathleen, Emerson, Robert W, Rogers, Sally J, Ozonoff, Sally, and Amaral, David G
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Paediatrics ,Biomedical and Clinical Sciences ,Pediatric ,Clinical Research ,Brain Disorders ,Intellectual and Developmental Disabilities (IDD) ,Mental Health ,Neurosciences ,Autism ,2.1 Biological and endogenous factors ,4.1 Discovery and preclinical testing of markers and technologies ,4.2 Evaluation of markers and technologies ,Neurological ,Mental health ,Autism Spectrum Disorder ,Brain ,Case-Control Studies ,Cerebrospinal Fluid ,Child ,Preschool ,Female ,Humans ,Magnetic Resonance Imaging ,Male ,Clinical Sciences ,Public Health and Health Services ,Psychology ,Clinical sciences ,Applied and developmental psychology ,Clinical and health psychology - Abstract
BackgroundWe previously showed, in two separate cohorts, that high-risk infants who were later diagnosed with autism spectrum disorder had abnormally high extra-axial cerebrospinal fluid (CSF) volume from age 6-24 months. The presence of increased extra-axial CSF volume preceded the onset of behavioural symptoms of autism and was predictive of a later diagnosis of autism spectrum disorder. In this study, we aimed to establish whether increased extra-axial CSF volume is found in a large, independent sample of children diagnosed with autism spectrum disorder, whether extra-axial CSF remains abnormally increased beyond infancy, and whether it is present in both normal-risk and high-risk children with autism.MethodsIn this case-control MRI study, children with autism spectrum disorder or with typical development aged 2-4 years were recruited from the community to the UC Davis MIND Institute Autism Phenome Project, based in Sacramento, CA, USA. The autism spectrum disorder group comprised children with autism spectrum disorder who were either normal risk (ie, from simplex families) or high risk (ie, from multiplex families). Measurements of extra-axial CSF volume, brain volume, head circumference, sleep problems, and familial risk status were derived from MRI and behavioural assessments. We applied a previously validated machine learning algorithm based on extra-axial CSF volume, brain volume, age, and sex to the current dataset.FindingsBetween July 20, 2007, and Dec 13, 2012, 159 children with autism spectrum disorder (132 male, 27 female) and 77 with typical development (49 male, 28 female) underwent MRI scans. The autism spectrum disorder group had an average of 15·1% more extra-axial CSF than controls after accounting for differences in brain volume, weight, age, and sex (least-squares mean 116·74 cm3 [SE 3·33] in autism group vs 101·40 cm3 [3·93] in typical development group; p=0·007; Cohen's d = 0·39). Subgroups of normal-risk (n=132) and high-risk (n=27) children with autism spectrum disorder had nearly identical extra-axial CSF volumes (p=0·78), and both subgroups had significantly greater volumes than controls. Both extra-axial CSF volume (p=0·004) and brain volume (p
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- 2018
11. Towards a Data-Driven Approach to Screen for Autism Risk at 12 Months of Age
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Meera, Shoba S., Donovan, Kevin, Wolff, Jason J., Zwaigenbaum, Lonnie, Elison, Jed T., Kinh, Truong, Shen, Mark D., Estes, Annette M., Hazlett, Heather C., Watson, Linda R., Baranek, Grace T., Swanson, Meghan R., St. John, Tanya, Burrows, Catherine A., Schultz, Robert T., Dager, Stephen R., Botteron, Kelly N., Pandey, Juhi, and Piven, Joseph
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- 2021
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12. Commonly used genomic arrays may lose information due to imperfect coverage of discovered variants for autism spectrum disorder.
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Yao, Michael, Daniels, Jason, Grosvenor, Luke, Morrill, Valerie, Feinberg, Jason I., Bakulski, Kelly M., Piven, Joseph, Hazlett, Heather C., Shen, Mark D., Newschaffer, Craig, Lyall, Kristen, Schmidt, Rebecca J., Hertz-Picciotto, Irva, Croen, Lisa A., Fallin, M. Daniele, Ladd-Acosta, Christine, Volk, Heather, and Benke, Kelly
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AUTISM spectrum disorders ,GENETIC variation ,QUALITY control ,BRAIN imaging ,AUTISM - Abstract
Background: Common genetic variation has been shown to account for a large proportion of ASD heritability. Polygenic scores generated for autism spectrum disorder (ASD-PGS) using the most recent discovery data, however, explain less variance than expected, despite reporting significant associations with ASD and other ASD-related traits. Here, we investigate the extent to which information loss on the target study genome-wide microarray weakens the predictive power of the ASD-PGS. Methods: We studied genotype data from three cohorts of individuals with high familial liability for ASD: The Early Autism Risk Longitudinal Investigation (EARLI), Markers of Autism Risk in Babies-Learning Early Signs (MARBLES), and the Infant Brain Imaging Study (IBIS), and one population-based sample, Study to Explore Early Development Phase I (SEED I). Individuals were genotyped on different microarrays ranging from 1 to 5 million sites. Coverage of the top 88 genome-wide suggestive variants implicated in the discovery was evaluated in all four studies before quality control (QC), after QC, and after imputation. We then created a novel method to assess coverage on the resulting ASD-PGS by correlating a PGS informed by a comprehensive list of variants to a PGS informed with only the available variants. Results: Prior to imputations, None of the four cohorts directly or indirectly covered all 88 variants among the measured genotype data. After imputation, the two cohorts genotyped on 5-million arrays reached full coverage. Analysis of our novel metric showed generally high genome-wide coverage across all four studies, but a greater number of SNPs informing the ASD-PGS did not result in improved coverage according to our metric. Limitations. The studies we analyzed contained modest sample sizes. Our analyses included microarrays with more than 1-million sites, so smaller arrays such as Global Diversity and the PsychArray were not included. Our PGS metric for ASD is only generalizable to samples of European ancestries, though the coverage metric can be computed for traits that have sufficiently large-sized discovery findings in other ancestries. Conclusions: We show that commonly used genotyping microarrays have incomplete coverage for common ASD variants, and imputation cannot always recover lost information. Our novel metric provides an intuitive approach to reporting information loss in PGS and an alternative to reporting the total number of SNPs included in the PGS. While applied only to ASD here, this metric can easily be used with other traits. [ABSTRACT FROM AUTHOR]
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- 2024
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13. Extra-axial Cerebrospinal Fluid Relationships to Infant Brain Structure, Cognitive Development, and Risk for Schizophrenia
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Murphy, Veronica A., Shen, Mark D., Kim, Sun Hyung, Cornea, Emil, Styner, Martin, and Gilmore, John H.
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- 2020
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14. Methods for acquiring MRI data in children with autism spectrum disorder and intellectual impairment without the use of sedation
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Nordahl, Christine Wu, Mello, Melissa, Shen, Audrey M, Shen, Mark D, Vismara, Laurie A, Li, Deana, Harrington, Kayla, Tanase, Costin, Goodlin-Jones, Beth, Rogers, Sally, Abbeduto, Leonard, and Amaral, David G
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Biomedical and Clinical Sciences ,Neurosciences ,Biomedical Imaging ,Brain Disorders ,Intellectual and Developmental Disabilities (IDD) ,Mental Health ,Behavioral and Social Science ,Clinical Research ,Autism ,Pediatric ,Mental health ,Brain ,Neurodevelopment ,MRI ,Compliance ,Intellectual disability ,Low-functioning autism ,Applied behavior analysis ,Psychology - Abstract
BackgroundMagnetic resonance imaging (MRI) has been widely used in studies evaluating the neuropathology of autism spectrum disorder (ASD). Studies are often limited, however, to higher functioning individuals with ASD. MRI studies of individuals with ASD and comorbid intellectual disability (ID) are lacking, due in part to the challenges of acquiring images without the use of sedation.MethodsUtilizing principles of applied behavior analysis (ABA), we developed a protocol for acquiring structural MRI scans in school-aged children with ASD and intellectual impairment. Board certified behavior analysts worked closely with each child and their parent(s), utilizing behavior change techniques such as pairing, shaping, desensitization, and positive reinforcement, through a series of mock scanner visits to prepare the child for the MRI scan. An objective, quantitative assessment of motion artifact in T1- and diffusion-weighted scans was implemented to ensure that high-quality images were acquired.ResultsThe sample consisted of 17 children with ASD who are participants in the UC Davis Autism Phenome Project, a longitudinal MRI study aimed at evaluating brain developmental trajectories from early to middle childhood. At the time of their initial scan (2-3.5 years), all 17 children had a diagnosis of ASD and development quotient (DQ)
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- 2016
15. Functional Connectivity of the Amygdala Is Disrupted in Preschool-Aged Children With Autism Spectrum Disorder
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Shen, Mark D, Li, Deana D, Keown, Christopher L, Lee, Aaron, Johnson, Ryan T, Angkustsiri, Kathleen, Rogers, Sally J, Müller, Ralph-Axel, Amaral, David G, and Nordahl, Christine Wu
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Biological Psychology ,Biomedical and Clinical Sciences ,Psychology ,Behavioral and Social Science ,Neurosciences ,Mental Health ,Brain Disorders ,Clinical Research ,Autism ,Basic Behavioral and Social Science ,Eye Disease and Disorders of Vision ,Pediatric ,Intellectual and Developmental Disabilities (IDD) ,2.1 Biological and endogenous factors ,Mental health ,Amygdala ,Autism Spectrum Disorder ,Cerebral Cortex ,Child ,Preschool ,Connectome ,Humans ,Language ,Magnetic Resonance Imaging ,Male ,Social Perception ,autism ,functional magnetic resonance imaging ,neuroimaging ,amygdala ,development ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Developmental & Child Psychology ,Clinical sciences ,Paediatrics ,Applied and developmental psychology - Abstract
ObjectiveThe objective of this study was to determine whether functional connectivity of the amygdala is altered in preschool-age children with autism spectrum disorder (ASD) and to assess the clinical relevance of observed alterations in amygdala connectivity.MethodA resting-state functional connectivity magnetic resonance imaging study of the amygdala (and a parallel study of primary visual cortex) was conducted in 72 boys (mean age 3.5 years; n = 43 with ASD; n = 29 age-matched controls).ResultsThe ASD group showed significantly weaker connectivity between the amygdala and several brain regions involved in social communication and repetitive behaviors, including bilateral medial prefrontal cortex, temporal lobes, and striatum (p < .05, corrected). Weaker connectivity between the amygdala and frontal and temporal lobes was significantly correlated with increased autism severity in the ASD group (p < .05). In a parallel analysis examining the functional connectivity of primary visual cortex, the ASD group showed significantly weaker connectivity between visual cortex and sensorimotor regions (p < .05, corrected). Weaker connectivity between visual cortex and sensorimotor regions was not correlated with core autism symptoms, but instead was correlated with increased sensory hypersensitivity in the visual/auditory domain (p < .05).ConclusionThese findings indicate that preschool-age children with ASD have disrupted functional connectivity between the amygdala and regions of the brain important for social communication and language, which might be clinically relevant because weaker connectivity was associated with increased autism severity. Moreover, although amygdala connectivity was associated with behavioral domains that are diagnostic of ASD, altered connectivity of primary visual cortex was related to sensory hypersensitivity.
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- 2016
16. Associations between early trajectories of amygdala development and later school-age anxiety in two longitudinal samples
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Burrows, Catherine A., primary, Lasch, Carolyn, additional, Gross, Julia, additional, Girault, Jessica B., additional, Rutsohn, Joshua, additional, Wolff, Jason J., additional, Swanson, Meghan R., additional, Lee, Chimei M., additional, Dager, Stephen R., additional, Cornea, Emil, additional, Stephens, Rebecca, additional, Styner, Martin, additional, John, Tanya St., additional, Pandey, Juhi, additional, Deva, Meera, additional, Botteron, Kelly N., additional, Estes, Annette M., additional, Hazlett, Heather C., additional, Pruett, John R., additional, Schultz, Robert T., additional, Zwaigenbaum, Lonnie, additional, Gilmore, John H., additional, Shen, Mark D., additional, Piven, Joseph, additional, and Elison, Jed T., additional
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- 2023
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17. Naturalistic Language Recordings Reveal 'Hypervocal' Infants at High Familial Risk for Autism
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Swanson, Meghan R., Shen, Mark D., Wolff, Jason J., Boyd, Brian, Clements, Mark, Rehg, James, Elison, Jed T., Paterson, Sarah, Parish-Morris, Julia, Chappell, J. Chad, Hazlett, Heather C., Emerson, Robert W., Botteron, Kelly, Pandey, Juhi, Schultz, Robert T., Dager, Stephen R., Zwaigenbaum, Lonnie, Estes, Annette M., and Piven, Joseph
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Children's early language environments are related to later development. Little is known about this association in siblings of children with autism spectrum disorder (ASD), who often experience language delays or have ASD. Fifty-nine 9-month-old infants at high or low familial risk for ASD contributed full-day in-home language recordings. High-risk infants produced more vocalizations than low-risk peers; conversational turns and adult words did not differ by group. Vocalization differences were driven by a subgroup of "hypervocal" infants. Despite more vocalizations overall, these infants engaged in less social babbling during a standardized clinic assessment, and they experienced fewer conversational turns relative to their rate of vocalizations. Two ways in which these individual and environmental differences may relate to subsequent development are discussed.
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- 2018
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18. Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders
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Stamova, Boryana S, Tian, Yingfang, Nordahl, Christine W, Shen, Mark D, Rogers, Sally, Amaral, David G, and Sharp, Frank R
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Abstract Background Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods RNA from blood was processed on whole genome exon arrays for 2-4–year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P
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- 2013
19. Early brain enlargement and elevated extra-axial fluid in infants who develop autism spectrum disorder
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Shen, Mark D, Nordahl, Christine W, Young, Gregory S, Wootton-Gorges, Sandra L, Lee, Aaron, Liston, Sarah E, Harrington, Kayla R, Ozonoff, Sally, and Amaral, David G
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Paediatrics ,Biomedical and Clinical Sciences ,Psychology ,Behavioral and Social Science ,Mental Health ,Pediatric ,Intellectual and Developmental Disabilities (IDD) ,Neurosciences ,Clinical Research ,Biomedical Imaging ,Autism ,Brain Disorders ,4.2 Evaluation of markers and technologies ,4.1 Discovery and preclinical testing of markers and technologies ,Mental health ,Age Factors ,Brain ,Child Development Disorders ,Pervasive ,Child ,Preschool ,Developmental Disabilities ,Female ,Functional Laterality ,Head ,Humans ,Image Processing ,Computer-Assisted ,Infant ,Longitudinal Studies ,Magnetic Resonance Imaging ,Male ,Time Factors ,autism ,magnetic resonance imaging ,infant brain development ,cerebrospinal fluid ,external hydrocephalus ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Neurology & Neurosurgery ,Biomedical and clinical sciences ,Health sciences - Abstract
Prospective studies of infants at risk for autism spectrum disorder have provided important clues about the early behavioural symptoms of autism spectrum disorder. Diagnosis of autism spectrum disorder, however, is not currently made until at least 18 months of age. There is substantially less research on potential brain-based differences in the period between 6 and 12 months of age. Our objective in the current study was to use magnetic resonance imaging to identify any consistently observable brain anomalies in 6-9 month old infants who would later develop autism spectrum disorder. We conducted a prospective infant sibling study with longitudinal magnetic resonance imaging scans at three time points (6-9, 12-15, and 18-24 months of age), in conjunction with intensive behavioural assessments. Fifty-five infants (33 'high-risk' infants having an older sibling with autism spectrum disorder and 22 'low-risk' infants having no relatives with autism spectrum disorder) were imaged at 6-9 months; 43 of these (27 high-risk and 16 low-risk) were imaged at 12-15 months; and 42 (26 high-risk and 16 low-risk) were imaged again at 18-24 months. Infants were classified as meeting criteria for autism spectrum disorder, other developmental delays, or typical development at 24 months or later (mean age at outcome: 32.5 months). Compared with the other two groups, infants who developed autism spectrum disorder (n = 10) had significantly greater extra-axial fluid at 6-9 months, which persisted and remained elevated at 12-15 and 18-24 months. Extra-axial fluid is characterized by excessive cerebrospinal fluid in the subarachnoid space, particularly over the frontal lobes. The amount of extra-axial fluid detected as early as 6 months was predictive of more severe autism spectrum disorder symptoms at the time of outcome. Infants who developed autism spectrum disorder also had significantly larger total cerebral volumes at both 12-15 and 18-24 months of age. This is the first magnetic resonance imaging study to prospectively evaluate brain growth trajectories from infancy in children who develop autism spectrum disorder. The presence of excessive extra-axial fluid detected as early as 6 months and the lack of resolution by 24 months is a hitherto unreported brain anomaly in infants who later develop autism spectrum disorder. This is also the first magnetic resonance imaging evidence of brain enlargement in autism before age 2. These findings raise the potential for the use of structural magnetic resonance imaging to aid in the early detection of children at risk for autism spectrum disorder or other neurodevelopmental disorders.
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- 2013
20. Subcortical Brain and Behavior Phenotypes Differentiate Infants With Autism Versus Language Delay
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Piven, J., Hazlett, H.C., Chappell, C., Dager, S., Estes, A.M., Shaw, D., Botteron, K., McKinstry, R., Constantino, J., Pruett, J., Schultz, R.T., Pandey, J., Paterson, S., Zwaigenbaum, L., Elison, J.T., Wolff, J.J., Evans, A.C., Collins, D.L., Pike, G.B., Fonov, V., Kostopoulos, P., Das, S., Gerig, G., Styner, M., Gu, H., Swanson, Meghan R., Shen, Mark D., Wolff, Jason J., Elison, Jed T., Emerson, Robert W., Styner, Martin A., Hazlett, Heather C., Truong, Kinh, Watson, Linda R., Paterson, Sarah, Marrus, Natasha, Botteron, Kelly N., Pandey, Juhi, Schultz, Robert T., Dager, Stephen R., Zwaigenbaum, Lonnie, Estes, Annette M., and Piven, Joseph
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- 2017
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21. Increased Extra-axial Cerebrospinal Fluid in High-Risk Infants Who Later Develop Autism
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Shen, Mark D., Kim, Sun Hyung, McKinstry, Robert C., Gu, Hongbin, Hazlett, Heather C., Nordahl, Christine W., Emerson, Robert W., Shaw, Dennis, Elison, Jed T., Swanson, Meghan R., Fonov, Vladimir S., Gerig, Guido, Dager, Stephen R., Botteron, Kelly N., Paterson, Sarah, Schultz, Robert T., Evans, Alan C., Estes, Annette M., Zwaigenbaum, Lonnie, Styner, Martin A., Amaral, David G., Piven, Joseph, Piven, J., Hazlett, H.C., Chappell, C., Dager, S., Estes, A., Shaw, D., Botteron, K., McKinstry, R., Constantino, J., Pruett, J., Schultz, R., Zwaigenbaum, L., Elison, J., Evans, A.C., Collins, D.L., Pike, G.B., Fonov, V., Kostopoulos, P., Das, S., Gerig, G., Styner, M., and Gu, H.
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- 2017
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22. Differential Cognitive and Behavioral Development from 6 to 24 Months in Autism and Fragile X Syndrome
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Mullin, Lindsay J., primary, Rutsohn, Joshua, additional, Gross, Julia L., additional, Caravella, Kelly E., additional, Weisenfeld, Leigh Anne, additional, Flake, Lisa, additional, Botteron, Kelly N., additional, Dager, Stephen R., additional, Estes, Annette M., additional, Pandey, Juhi, additional, Schultz, Robert T., additional, John, Tanya St., additional, Wolff, Jason J., additional, Shen, Mark D., additional, Piven, Joseph, additional, Hazlett, Heather C., additional, and Girault, Jessica B., additional
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- 2023
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23. Additional file 1 of Identification of subgroups of children in the Australian Autism Biobank using latent class analysis
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Montgomery, Alicia, Masi, Anne, Whitehouse, Andrew, Veenstra-VanderWeele, Jeremy, Shuffrey, Lauren, Shen, Mark D., Karlov, Lisa, Uljarevic, Mirko, Alvares, Gail, Woolfenden, Sue, Silove, Natalie, and Eapen, Valsamma
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Additional file 1: Table S1: Indicator Variables Describing Core Autism Traits based on 3di Data. Table S2: Indicator Variables Describing Comorbid Conditions.
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- 2023
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24. Enabling endpoint development for interventional clinical trials in individuals with Angelman syndrome: a prospective, longitudinal, observational clinical study (FREESIAS)
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Tjeertes, Jorrit, primary, Bacino, Carlos A., additional, Bichell, Terry Jo, additional, Bird, Lynne M., additional, Bustamante, Mariana, additional, Crean, Rebecca, additional, Jeste, Shafali, additional, Komorowski, Robert W., additional, Krishnan, Michelle L., additional, Miller, Meghan T., additional, Nobbs, David, additional, Ochoa-Lubinoff, Cesar, additional, Parkerson, Kimberly A., additional, Rotenberg, Alexander, additional, Sadhwani, Anjali, additional, Shen, Mark D., additional, Squassante, Lisa, additional, Tan, Wen-Hann, additional, Vincenzi, Brenda, additional, Wheeler, Anne C., additional, Hipp, Joerg F., additional, and Berry-Kravis, Elizabeth, additional
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- 2023
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25. Cerebrospinal fluid and the early brain development of autism
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Shen, Mark D.
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- 2018
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26. Walking, Gross Motor Development, and Brain Functional Connectivity in Infants and Toddlers
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Marrus, Natasha, Eggebrecht, Adam T, Todorov, Alexandre, Elison, Jed T, Wolff, Jason J, Cole, Lyndsey, Gao, Wei, Pandey, Juhi, Shen, Mark D, Swanson, Meghan R, Emerson, Robert W, Klohr, Cheryl L, Adams, Chloe M, Estes, Annette M, Zwaigenbaum, Lonnie, Botteron, Kelly N, McKinstry, Robert C, Constantino, John N, Evans, Alan C, Hazlett, Heather C, Dager, Stephen R, Paterson, Sarah J, Schultz, Robert T, Styner, Martin A, Gerig, Guido, Schlaggar, Bradley L, Piven, Joseph, and Pruett, John R, Jr.
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- 2018
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27. Atypical lexicosemantic function of extrastriate cortex in autism spectrum disorder: Evidence from functional and effective connectivity
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Shen, Mark D., Shih, Patricia, Öttl, Birgit, Keehn, Brandon, Leyden, Kelly M., Gaffrey, Michael S., and Müller, Ralph-Axel
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- 2012
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28. Sleep, cerebrospinal fluid, and the glymphatic system: A systematic review
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Chong, Pearlynne L.H., primary, Garic, Dea, additional, Shen, Mark D., additional, Lundgaard, Iben, additional, and Schwichtenberg, Amy J., additional
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- 2022
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29. Longitudinal Prediction of Infant MR Images With Multi-Contrast Perceptual Adversarial Learning
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Peng, Liying, primary, Lin, Lanfen, additional, Lin, Yusen, additional, Chen, Yen-wei, additional, Mo, Zhanhao, additional, Vlasova, Roza M., additional, Kim, Sun Hyung, additional, Evans, Alan C., additional, Dager, Stephen R., additional, Estes, Annette M., additional, McKinstry, Robert C., additional, Botteron, Kelly N., additional, Gerig, Guido, additional, Schultz, Robert T., additional, Hazlett, Heather C., additional, Piven, Joseph, additional, Burrows, Catherine A., additional, Grzadzinski, Rebecca L., additional, Girault, Jessica B., additional, Shen, Mark D., additional, and Styner, Martin A., additional
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- 2021
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30. Subcortical Brain Development in Autism and Fragile X Syndrome: Evidence for Dynamic, Age- and Disorder-Specific Trajectories in Infancy.
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Shen, Mark D., Swanson, Meghan R., Wolff, Jason J., Elison, Jed T., Girault, Jessica B., Kim, Sun Hyung, Smith, Rachel G., Graves, Michael M., Weisenfeld, Leigh Anne H., Flake, Lisa, MacIntyre, Leigh, Gross, Julia L., Burrows, Catherine A., Fonov, Vladimir S., Collins, D. Louis, Evans, Alan C., Gerig, Guido, McKinstry, Robert C., Pandey, Juhi, and St. John, Tanya
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BRAIN , *MAGNETIC resonance imaging , *FRAGILE X syndrome , *AUTISM , *RESEARCH funding , *DISEASE complications - Abstract
Objective: Previous research has demonstrated that the amygdala is enlarged in children with autism spectrum disorder (ASD). However, the precise onset of this enlargement during infancy, how it relates to later diagnostic behaviors, whether the timing of enlargement in infancy is specific to the amygdala, and whether it is specific to ASD (or present in other neurodevelopmental disorders, such as fragile X syndrome) are all unknown.Methods: Longitudinal MRIs were acquired at 6-24 months of age in 29 infants with fragile X syndrome, 58 infants at high likelihood for ASD who were later diagnosed with ASD, 212 high-likelihood infants not diagnosed with ASD, and 109 control infants (1,099 total scans).Results: Infants who developed ASD had typically sized amygdala volumes at 6 months, but exhibited significantly faster amygdala growth between 6 and 24 months, such that by 12 months the ASD group had significantly larger amygdala volume (Cohen's d=0.56) compared with all other groups. Amygdala growth rate between 6 and 12 months was significantly associated with greater social deficits at 24 months when the infants were diagnosed with ASD. Infants with fragile X syndrome had a persistent and significantly enlarged caudate volume at all ages between 6 and 24 months (d=2.12), compared with all other groups, which was significantly associated with greater repetitive behaviors.Conclusions: This is the first MRI study comparing fragile X syndrome and ASD in infancy, demonstrating strikingly different patterns of brain and behavior development. Fragile X syndrome-related changes were present from 6 months of age, whereas ASD-related changes unfolded over the first 2 years of life, starting with no detectable group differences at 6 months. Increased amygdala growth rate between 6 and 12 months occurs prior to social deficits and well before diagnosis. This gradual onset of brain and behavior changes in ASD, but not fragile X syndrome, suggests an age- and disorder-specific pattern of cascading brain changes preceding autism diagnosis. [ABSTRACT FROM AUTHOR]- Published
- 2022
- Full Text
- View/download PDF
31. Infant Visual Brain Development and Inherited Genetic Liability in Autism.
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Girault, Jessica B., Donovan, Kevin, Hawks, Zoë, Talovic, Muhamed, Forsen, Elizabeth, Elison, Jed T., Shen, Mark D., Swanson, Meghan R., Wolff, Jason J., Kim, Sun Hyung, Nishino, Tomoyuki, Davis, Savannah, Snyder, Abraham Z., Botteron, Kelly N., Estes, Annette M., Dager, Stephen R., Hazlett, Heather C., Gerig, Guido, McKinstry, Robert, and Pandey, Juhi
- Subjects
BRAIN ,MAGNETIC resonance imaging ,CONTINUING education units ,AUTISM ,RESEARCH funding ,LONGITUDINAL method - Abstract
Objective: Autism spectrum disorder (ASD) is heritable, and younger siblings of ASD probands are at higher likelihood of developing ASD themselves. Prospective MRI studies of siblings report that atypical brain development precedes ASD diagnosis, although the link between brain maturation and genetic factors is unclear. Given that familial recurrence of ASD is predicted by higher levels of ASD traits in the proband, the authors investigated associations between proband ASD traits and brain development among younger siblings.Methods: In a sample of 384 proband-sibling pairs (89 pairs concordant for ASD), the authors examined associations between proband ASD traits and sibling brain development at 6, 12, and 24 months in key MRI phenotypes: total cerebral volume, cortical surface area, extra-axial cerebrospinal fluid, occipital cortical surface area, and splenium white matter microstructure. Results from primary analyses led the authors to implement a data-driven approach using functional connectivity MRI at 6 months.Results: Greater levels of proband ASD traits were associated with larger total cerebral volume and surface area and larger surface area and reduced white matter integrity in components of the visual system in siblings who developed ASD. This aligned with weaker functional connectivity between several networks and the visual system among all siblings during infancy.Conclusions: The findings provide evidence that specific early brain MRI phenotypes of ASD reflect quantitative variation in familial ASD traits. Multimodal anatomical and functional convergence on cortical regions, fiber pathways, and functional networks involved in visual processing suggest that inherited liability has a role in shaping the prodromal development of visual circuitry in ASD. [ABSTRACT FROM AUTHOR]- Published
- 2022
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- View/download PDF
32. A Novel Method for High-Dimensional Anatomical Mapping of Extra-Axial Cerebrospinal Fluid: Application to the Infant Brain
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Mostapha, Mahmoud, primary, Kim, Sun Hyung, additional, Evans, Alan C., additional, Dager, Stephen R., additional, Estes, Annette M., additional, McKinstry, Robert C., additional, Botteron, Kelly N., additional, Gerig, Guido, additional, Pizer, Stephen M., additional, Schultz, Robert T., additional, Hazlett, Heather C., additional, Piven, Joseph, additional, Girault, Jessica B., additional, Shen, Mark D., additional, and Styner, Martin A., additional
- Published
- 2020
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33. Sex differences associated with corpus callosum development in human infants: A longitudinal multimodal imaging study
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Schmied, Astrid, primary, Soda, Takahiro, additional, Gerig, Guido, additional, Styner, Martin, additional, Swanson, Meghan R., additional, Elison, Jed T., additional, Shen, Mark D., additional, McKinstry, Robert C., additional, Pruett, John R., additional, Botteron, Kelly N., additional, Estes, Annette M., additional, Dager, Stephen R., additional, Hazlett, Heather C., additional, Schultz, Robert T., additional, Piven, Joseph, additional, and Wolff, Jason J., additional
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- 2020
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34. Sleep Onset Problems and Subcortical Development in Infants Later Diagnosed With Autism Spectrum Disorder
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MacDuffie, Katherine E., primary, Shen, Mark D., additional, Dager, Stephen R., additional, Styner, Martin A., additional, Kim, Sun Hyung, additional, Paterson, Sarah, additional, Pandey, Juhi, additional, St. John, Tanya, additional, Elison, Jed T., additional, Wolff, Jason J., additional, Swanson, Meghan R., additional, Botteron, Kelly N., additional, Zwaigenbaum, Lonnie, additional, Piven, Joseph, additional, and Estes, Annette M., additional
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- 2020
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35. Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness
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Mitra, Anish, Snyder, Abraham Z., Tagliazucchi, Enzo Rodolfo, Laufs, Helmut, Elison, Jed, Emerson, Robert W., Shen, Mark D., Wolff, Jason J., Botteron, Kelly N., Dager, Stephen, Estes, Annette M., Evans, A.C., Gerig, Guido, Hazlett, Heather C., Paterson, Sarah J., Schultz, Robert T., Styner, Martin A., Zwaigenbaum, Lonnie, Chappell, C., Estes, A., Shaw, D., Botteron, K., McKinstry, R., Constantino, J., Pruett, J., Schultz, R., Paterson, S., Collins, D.L., Pike, G.B., Fonov, V., Kostopoulos, P., Dasso, Sergio Alberto, Styner, M., Gu, H., Schlaggar, Bradley L., Piven, Joseph, Pruett, John R., and Raichle, Marcus
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Physiology ,Ciencias Físicas ,lcsh:Medicine ,Audiology ,Electroencephalography ,Pediatrics ,Diagnostic Radiology ,purl.org/becyt/ford/1 [https] ,Families ,0302 clinical medicine ,Mathematical and Statistical Techniques ,Thalamus ,Functional Magnetic Resonance Imaging ,Medicine and Health Sciences ,lcsh:Science ,Children ,Default mode network ,Brain Mapping ,Principal Component Analysis ,Multidisciplinary ,medicine.diagnostic_test ,Radiology and Imaging ,05 social sciences ,Brain ,Software Engineering ,Sleep in non-human animals ,Magnetic Resonance Imaging ,3. Good health ,Child, Preschool ,Physical Sciences ,Engineering and Technology ,Wakefulness ,Anatomy ,Psychology ,Infants ,psychological phenomena and processes ,Statistics (Mathematics) ,CIENCIAS NATURALES Y EXACTAS ,Research Article ,Adult ,medicine.medical_specialty ,Computer and Information Sciences ,Imaging Techniques ,NEUROIMAGING ,Otras Ciencias Biológicas ,Neuroimaging ,Research and Analysis Methods ,Non-rapid eye movement sleep ,050105 experimental psychology ,Ciencias Biológicas ,03 medical and health sciences ,DEVELOPMENT ,Diagnostic Medicine ,medicine ,Connectome ,Humans ,0501 psychology and cognitive sciences ,Statistical Methods ,purl.org/becyt/ford/1.6 [https] ,Preprocessing ,Resting state fMRI ,lcsh:R ,Biology and Life Sciences ,Infant ,purl.org/becyt/ford/1.3 [https] ,SLEEP ,Astronomía ,Age Groups ,People and Places ,Multivariate Analysis ,lcsh:Q ,Population Groupings ,Functional magnetic resonance imaging ,Physiological Processes ,Sleep ,030217 neurology & neurosurgery ,Mathematics ,Neuroscience - Abstract
Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI. Fil: Mitra, Anish. Washington University School Of Medicine In St. Louis; Estados Unidos Fil: Snyder, Abraham Z.. Washington University School Of Medicine In St. Louis; Estados Unidos Fil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina Fil: Laufs, Helmut. Christian-albrechts-universitat Zu Kiel; Alemania Fil: Elison, Jed. University of Minnesota; Estados Unidos Fil: Emerson, Robert W.. University of North Carolina; Estados Unidos Fil: Shen, Mark D.. University of North Carolina; Estados Unidos Fil: Wolff, Jason J.. University of Minnesota; Estados Unidos Fil: Botteron, Kelly N.. Washington University School Of Medicine In St. Louis; Estados Unidos Fil: Dager, Stephen. University Of Washington, Seattle; Estados Unidos Fil: Estes, Annette M.. University Of Washington, Seattle; Estados Unidos Fil: Evans, A.C.. McGill University. Montreal Neurological Institute and Hospital; Canadá Fil: Gerig, Guido. University of New York; Estados Unidos Fil: Hazlett, Heather C.. University of North Carolina; Estados Unidos Fil: Paterson, Sarah J.. University of Pennsylvania; Estados Unidos Fil: Schultz, Robert T.. University of Pennsylvania; Estados Unidos Fil: Styner, Martin A.. University of North Carolina; Estados Unidos Fil: Zwaigenbaum, Lonnie. University of Alberta; Canadá Fil: Chappell, C.. Ibis Network Pi; Estados Unidos Fil: Estes, A.. University Of Washington, Seattle; Estados Unidos Fil: Shaw, D.. University Of Washington, Seattle; Estados Unidos Fil: Botteron, K.. University Of Washington, Seattle; Estados Unidos Fil: McKinstry, R.. University Of Washington, Seattle; Estados Unidos Fil: Constantino, J.. University Of Washington, Seattle; Estados Unidos Fil: Pruett, J.. University Of Washington, Seattle; Estados Unidos Fil: Schultz, R.. The Children?s Hospital Of Philadelphia; Estados Unidos Fil: Paterson, S.. The Children?s Hospital Of Philadelphia; Estados Unidos Fil: Collins, D.L.. McGill University. Montreal Neurological Institute and Hospital; Canadá Fil: Pike, G.B.. McGill University. Montreal Neurological Institute and Hospital; Canadá Fil: Fonov, V.. McGill University. Montreal Neurological Institute and Hospital; Canadá Fil: Kostopoulos, P.. McGill University. Montreal Neurological Institute and Hospital; Canadá Fil: Dasso, Sergio Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina Fil: Styner, M.. The University Of North Carolina System; Estados Unidos Fil: Gu, H.. Statistical Analysis Core; Estados Unidos Fil: Schlaggar, Bradley L.. Washington University School Of Medicine In St. Louis; Estados Unidos Fil: Piven, Joseph. University of North Carolina; Estados Unidos Fil: Pruett, John R.. Washington University School Of Medicine In St. Louis; Estados Unidos Fil: Raichle, Marcus. Washington University School Of Medicine In St. Louis; Estados Unidos
- Published
- 2017
36. A novel framework for the local extraction of extra-axial cerebrospinal fluid from MR brain images
- Author
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Shen, Mark D., primary, Kim, SunHyung, primary, Swanson, Meghan, primary, Collins, Louis, primary, Fonov, Vladimir, primary, Gerig, Guido, primary, Piven, Joseph, primary, Styner, Martin A., primary, and Mostapha, Mahmoud, primary
- Published
- 2018
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- View/download PDF
37. Neural circuitry at age 6 months associated with later repetitive behavior and sensory responsiveness in autism
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Shen, Mark D, Swanson, Meghan R, Hazlett, Heather, Piven, Joseph, and Styner, Martin
- Abstract
Background Restricted and repetitive behaviors are defining features of autism spectrum disorder (ASD). Under revised diagnostic criteria for ASD, this behavioral domain now includes atypical responses to sensory stimuli. To date, little is known about the neural circuitry underlying these features of ASD early in life. Methods Longitudinal diffusion tensor imaging data were collected from 217 infants at high familial risk for ASD. Forty-four of these infants were diagnosed with ASD at age 2. Targeted cortical, cerebellar, and striatal white matter pathways were defined and measured at ages 6, 12, and 24 months. Dependent variables included the Repetitive Behavior Scale-Revised and the Sensory Experiences Questionnaire. Results Among children diagnosed with ASD, repetitive behaviors and sensory response patterns were strongly correlated, even when accounting for developmental level or social impairment. Longitudinal analyses indicated that the genu and cerebellar pathways were significantly associated with both repetitive behaviors and sensory responsiveness but not social deficits. At age 6 months, fractional anisotropy in the genu significantly predicted repetitive behaviors and sensory responsiveness at age 2. Cerebellar pathways significantly predicted later sensory responsiveness. Exploratory analyses suggested a possible disordinal interaction based on diagnostic status for the association between fractional anisotropy and repetitive behavior. Conclusions Our findings suggest that restricted and repetitive behaviors contributing to a diagnosis of ASD at age 2 years are associated with structural properties of callosal and cerebellar white matter pathways measured during infancy and toddlerhood. We further identified that repetitive behaviors and unusual sensory response patterns co-occur and share common brain-behavior relationships. These results were strikingly specific given the absence of association between targeted pathways and social deficits.
- Published
- 2017
- Full Text
- View/download PDF
38. Brain and behavior development in autism from birth through infancy
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Shen, Mark D., primary and Piven, Joseph, additional
- Published
- 2017
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39. Subcortical Brain and Behavior Phenotypes Differentiate Infants With Autism Versus Language Delay
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Swanson, Meghan R., primary, Shen, Mark D., additional, Wolff, Jason J., additional, Elison, Jed T., additional, Emerson, Robert W., additional, Styner, Martin A., additional, Hazlett, Heather C., additional, Truong, Kinh, additional, Watson, Linda R., additional, Paterson, Sarah, additional, Marrus, Natasha, additional, Botteron, Kelly N., additional, Pandey, Juhi, additional, Schultz, Robert T., additional, Dager, Stephen R., additional, Zwaigenbaum, Lonnie, additional, Estes, Annette M., additional, Piven, Joseph, additional, Piven, J., additional, Hazlett, H.C., additional, Chappell, C., additional, Dager, S., additional, Estes, A.M., additional, Shaw, D., additional, Botteron, K., additional, McKinstry, R., additional, Constantino, J., additional, Pruett, J., additional, Schultz, R.T., additional, Pandey, J., additional, Paterson, S., additional, Zwaigenbaum, L., additional, Elison, J.T., additional, Wolff, J.J., additional, Evans, A.C., additional, Collins, D.L., additional, Pike, G.B., additional, Fonov, V., additional, Kostopoulos, P., additional, Das, S., additional, Gerig, G., additional, Styner, M., additional, and Gu, H., additional
- Published
- 2017
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40. Decreased Axon Caliber Underlies Loss of Fiber Tract Integrity, Disproportional Reductions in White Matter Volume, and Microcephaly in Angelman Syndrome Model Mice
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Judson, Matthew C., primary, Burette, Alain C., additional, Thaxton, Courtney L., additional, Pribisko, Alaine L., additional, Shen, Mark D., additional, Rumple, Ashley M., additional, Del Cid, Wilmer A., additional, Paniagua, Beatriz, additional, Styner, Martin, additional, Weinberg, Richard J., additional, and Philpot, Benjamin D., additional
- Published
- 2017
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41. Quantitative trait variation in ASD probands and toddler sibling outcomes at 24 months.
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Girault, Jessica B., Swanson, Meghan R., Meera, Shoba S., Grzadzinski, Rebecca L., Shen, Mark D., Burrows, Catherine A., Wolff, Jason J., Pandey, Juhi, John, Tanya St, Estes, Annette, Zwaigenbaum, Lonnie, Botteron, Kelly N., Hazlett, Heather C., Dager, Stephen R., Schultz, Robert T., Constantino, John N., Piven, Joseph, for the IBIS Network, Chappell, C., and Shaw, D.
- Abstract
Background: Younger siblings of children with autism spectrum disorder (ASD) are at increased likelihood of receiving an ASD diagnosis and exhibiting other developmental concerns. It is unknown how quantitative variation in ASD traits and broader developmental domains in older siblings with ASD (probands) may inform outcomes in their younger siblings. Methods: Participants included 385 pairs of toddler siblings and probands from the Infant Brain Imaging Study. ASD probands (mean age 5.5 years, range 1.7 to 15.5 years) were phenotyped using the Autism Diagnostic Interview-Revised (ADI-R), the Social Communication Questionnaire (SCQ), and the Vineland Adaptive Behavior Scales, Second Edition (VABS-II). Siblings were assessed using the ADI-R, VABS-II, Mullen Scales of Early Learning (MSEL), and Autism Diagnostic Observation Schedule (ADOS) and received a clinical best estimate diagnosis at 24 months using DSM-IV-TR criteria (n = 89 concordant for ASD; n = 296 discordant). We addressed two aims: (1) to determine whether proband characteristics are predictive of recurrence in siblings and (2) to assess associations between proband traits and sibling dimensional outcomes at 24 months. Results: Regarding recurrence risk, proband SCQ scores were found to significantly predict sibling 24-month diagnostic outcome (OR for a 1-point increase in SCQ = 1.06; 95% CI = 1.01, 1.12). Regarding quantitative trait associations, we found no significant correlations in ASD traits among proband-sibling pairs. However, quantitative variation in proband adaptive behavior, communication, and expressive and receptive language was significantly associated with sibling outcomes in the same domains; proband scores explained 9–18% of the variation in cognition and behavior in siblings with ASD. Receptive language was particularly strongly associated in concordant pairs (ICC = 0.50, p < 0.001). Conclusions: Proband ASD symptomology, indexed by the SCQ, is a predictor of familial ASD recurrence risk. While quantitative variation in social communication and restricted and repetitive behavior were not associated among sibling pairs, standardized ratings of proband language and communication explained significant variation in the same domains in the sibling at 24 months, especially among toddlers with an ASD diagnosis. These data suggest that proband characteristics can alert clinicians to areas of developmental concern for young children with familial risk for ASD. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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- View/download PDF
42. Early language exposure supports later language skills in infants with and without autism.
- Author
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Swanson, Meghan R., Donovan, Kevin, Paterson, Sarah, Wolff, Jason J., Parish‐Morris, Julia, Meera, Shoba S., Watson, Linda R., Estes, Annette M., Marrus, Natasha, Elison, Jed T., Shen, Mark D., McNeilly, Heidi B., MacIntyre, Leigh, Zwaigenbaum, Lonnie, St. John, Tanya, Botteron, Kelly, Dager, Stephen, and Piven, Joseph
- Abstract
The way that parents communicate with their typically developing infants is associated with later infant language development. Here we aim to show that these associations are observed in infants subsequently diagnosed with autism spectrum disorder (ASD). This study had three groups: high‐familial‐risk infants who did not have ASD (n = 46); high‐familial‐risk infants who had ASD (n = 14); and low‐familial‐risk infants who exhibited typical development (n = 36). All‐day home language recordings were collected at 9 and 15 months, and language skills were assessed at 24 months. Across all infants in the study, including those with ASD, a richer home language environment (e.g., hearing more adult words and experiencing more conversational turns) at 9 and 15 months was associated with better language skills. Higher parental educational attainment was associated with a richer home language environment. Mediation analyses showed that the effect of education on child language skills was explained by the richness of the home language environment. Exploratory analyses revealed that typically developing infants experience an increase in caregiver–child conversational turns across 9–15 months, a pattern not seen in children with ASD. The current study shows that parent behavior during the earliest stages of life can have a significant impact on later development, highlighting the home language environment as means to support development in infants with ASD. Autism Res 2019, 12: 1784–1795. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. Lay Summary: It has long been understood that caregiver speech supports language skills in typically developing infants. In this study, parents of infants who were later diagnosed with ASD and parents of infants in the control groups completed all‐day home language recordings. We found that for all infants in our study, those who heard more caregiver speech had better language skills later in life. Parental education level was also related to how much caregiver speech an infant experienced. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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43. Enlarged Perivascular Spaces in Infancy and Autism Diagnosis, Cerebrospinal Fluid Volume, and Later Sleep Problems.
- Author
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Garic, Dea, McKinstry, Robert C., Rutsohn, Joshua, Slomowitz, Rebecca, Wolff, Jason, MacIntyre, Leigh C., Weisenfeld, Leigh Anne H., Kim, Sun Hyung, Pandey, Juhi, St. John, Tanya, Estes, Annette M., Schultz, Robert T., Hazlett, Heather C., Dager, Stephen R., Botteron, Kelly N., Styner, Martin, Piven, Joseph, and Shen, Mark D.
- Published
- 2023
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44. A Novel Framework for the Local Extraction of Extra-Axial Cerebrospinal Fluid from MR Brain Images.
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Mostapha, Mahmoud, Shen, Mark D., SunHyung Kim, Swanson, Meghan, Collins, D. Louis, Fonov, Vladimir, Gerig, Guido, Piven, Joseph, and Styner, Martin A.
- Published
- 2018
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45. Development of White Matter Circuitry in Infants With Fragile X Syndrome.
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Swanson, Meghan R., Wolff, Jason J., Shen, Mark D., Styner, Martin, Estes, Annette, Gerig, Guido, McKinstry, Robert C., Botteron, Kelly N., Piven, Joseph, Hazlett, Heather C., and Infant Brain Imaging Study (IBIS) Network
- Subjects
FRAGILE X syndrome ,HUMAN chromosome abnormalities ,HEALTH outcome assessment ,WHITE matter (Nerve tissue) ,NEURAL circuitry - Abstract
Importance: Fragile X syndrome (FXS) is a genetic neurodevelopmental disorder and the most common inherited cause of intellectual disability in males. However, there are no published data on brain development in children with FXS during infancy.Objective: To characterize the development of white matter at ages 6, 12, and 24 months in infants with FXS compared with that of typically developing controls.Design, Setting, and Participants: Longitudinal behavioral and brain imaging data were collected at 1 or more time points from 27 infants with FXS and 73 typically developing controls between August 1, 2008, and June 14, 2016, at 2 academic medical centers. Infants in the control group had no first- or second-degree relatives with intellectual or psychiatric disorders, including FXS and autism spectrum disorder.Main Outcomes and Measures: Nineteen major white matter pathways were defined in common atlas space based on anatomically informed methods. Diffusion parameters, including fractional anisotropy, were compared between groups using linear mixed effects modeling. Fiber pathways showing group differences were subsequently examined in association with direct measures of verbal and nonverbal development.Results: There were significant differences in the development of 12 of 19 fiber tracts between the 27 infants with FXS (22 boys and 5 girls) and the 73 infants in the control group (46 boys and 27 girls), with lower fractional anisotropy in bilateral subcortical-frontal, occipital-temporal, temporal-frontal, and cerebellar-thalamic pathways, as well as 4 of 6 subdivisions of the corpus callosum. For all 12 of these pathways, there were significant main effects between groups but not for the interaction of age × group, indicating that lower fractional anisotropy was present and stable from age 6 months in infants with FXS. Lower fractional anisotropy values in the uncinate fasciculi were correlated with lower nonverbal developmental quotient in the FXS group (left uncinate, F = 10.06; false discovery rate-corrected P = .03; right uncinate, F = 21.8; P = .004).Conclusions and Relevance: The results substantiate in human infants the essential role of fragile X gene expression in the early development of white matter. The findings also suggest that the neurodevelopmental effects of FXS are well established at 6 months of age. [ABSTRACT FROM AUTHOR]- Published
- 2018
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46. Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age.
- Author
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Emerson, Robert W., Adams, Chloe, Tomoyuki Nishino, Cody Hazlett, Heather, Wolff, Jason J., Zwaigenbaum, Lonnie, Constantino, John N., Shen, Mark D., Swanson, Meghan R., Elison, Jed T., Kandala, Sridhar, Estes, Annette M., Botteron, Kelly N., Collins, Louis, Dager, Stephen R., Evans, Alan C., Gerig, Guido, Hongbin Gu, McKinstry, Robert C., and Paterson, Sarah
- Subjects
BRAIN imaging ,DIAGNOSIS of autism in children ,PSYCHOLOGICAL testing of infants ,AUTISM spectrum disorders in children ,PERVASIVE child development disorders - Abstract
The article discusses the application of prospective neuroimaging to detect autism spectrum disorder (ASD) among 6-month-old infants. It mentions that the ASD is a neurodevelopment disorder characterized by deficits in social behavior and the presence of restrictive and repetitive behaviors. It notes that the functional connectivity magnetic resonance imaging identified which children would receive a research clinical best estimate diagnosis of ASD.
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- 2017
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47. Neural circuitry at age 6 months associated with later repetitive behavior and sensory responsiveness in autism.
- Author
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Wolff, Jason J., Swanson, Meghan R., Elison, Jed T., Gerig, Guido, Pruett Jr., John R., Styner, Martin A., Vachet, Clement, Botteron, Kelly N., Dager, Stephen R., Estes, Annette M., Hazlett, Heather C., Schultz, Robert T., Shen, Mark D., Zwaigenbaum, Lonnie, and Piven, Joseph
- Subjects
NEURAL circuitry ,AUTISM - Abstract
Background: Restricted and repetitive behaviors are defining features of autism spectrum disorder (ASD). Under revised diagnostic criteria for ASD, this behavioral domain now includes atypical responses to sensory stimuli. To date, little is known about the neural circuitry underlying these features of ASD early in life. Methods: Longitudinal diffusion tensor imaging data were collected from 217 infants at high familial risk for ASD. Forty-four of these infants were diagnosed with ASD at age 2. Targeted cortical, cerebellar, and striatal white matter pathways were defined and measured at ages 6, 12, and 24 months. Dependent variables included the Repetitive Behavior Scale-Revised and the Sensory Experiences Questionnaire. Results: Among children diagnosed with ASD, repetitive behaviors and sensory response patterns were strongly correlated, even when accounting for developmental level or social impairment. Longitudinal analyses indicated that the genu and cerebellar pathways were significantly associated with both repetitive behaviors and sensory responsiveness but not social deficits. At age 6 months, fractional anisotropy in the genu significantly predicted repetitive behaviors and sensory responsiveness at age 2. Cerebellar pathways significantly predicted later sensory responsiveness. Exploratory analyses suggested a possible disordinal interaction based on diagnostic status for the association between fractional anisotropy and repetitive behavior. Conclusions: Our findings suggest that restricted and repetitive behaviors contributing to a diagnosis of ASD at age 2 years are associated with structural properties of callosal and cerebellar white matter pathways measured during infancy and toddlerhood. We further identified that repetitive behaviors and unusual sensory response patterns co-occur and share common brain-behavior relationships. These results were strikingly specific given the absence of association between targeted pathways and social deficits. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
48. A novel framework for the local extraction of extra-axial cerebrospinal fluid from MR brain images
- Author
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Angelini, Elsa D., Landman, Bennett A., Mostapha, Mahmoud, Shen, Mark D., Kim, SunHyung, Swanson, Meghan, Collins, D. Louis, Fonov, Vladimir, Gerig, Guido, Piven, Joseph, and Styner, Martin A.
- Published
- 2018
- Full Text
- View/download PDF
49. Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness
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Tagliazucchi, Enzo, Constantino, Schultz, Robert T., Chappell, Paterson, Styner, Schultz, Collins, Zwaigenbaum, Lonnie, McKinstry, Snyder, Abraham Z., Gerig, Guido, Wolff, Jason J., Laufs, Helmut, Pruett, Shaw, Botteron, Kelly N., Botteron, Dager, Stephen, Paterson, Sarah J., Hazlett, Heather C., Raichle, Marcus, Schlaggar, Bradley L., Emerson, Robert W., Evans, Piven, Joseph, Das, Estes, Elison, Jed, Kostopoulos, Pruett, John R., Pike, Styner, Martin A., Shen, Mark D., Fonov, Estes, Annette M., and Mitra, Anish
- Subjects
psychological phenomena and processes ,3. Good health - Abstract
Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.
50. Comparative profiling of white matter development in the human and mouse brain reveals volumetric deficits and delayed myelination in Angelman syndrome.
- Author
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Ozarkar SS, Patel RK, Vulli T, Smith AL, Shen MD, Burette AC, Philpot BD, Styner MA, and Hazlett HC
- Abstract
Background: Angelman syndrome (AS), a severe neurodevelopmental disorder resulting from the loss of the maternal UBE3A gene, is marked by changes in the brain's white matter (WM). The extent of WM abnormalities seems to correlate with the severity of clinical symptoms, but these deficits are still not well characterized or understood. This study provides the first large-scale measurement of WM volume reduction in children with AS. Furthermore, we probed the underlying neuropathology by examining the progression of myelination in an AS mouse model., Methods: We conducted magnetic resonance imaging (MRI) on children with AS (n=32) and neurotypical controls (n=99) aged 0.5-12 years. In parallel, we examined myelination in postnatal Ube3a maternal-null mice ( Ube3a
m-/p+ ; AS model), Ube3a paternal-null mice ( Ube3am+/p- ), and wildtype controls ( Ube3am+/p+ ) using immunohistochemistry, Western blotting, and electron microscopy., Results: Our data revealed that AS individuals exhibit significant reductions in brain volume by ~1 year of age, with WM reduced by 26% and gray matter by 21% by 6-12 years of age-approximately twice the reductions observed in the adult AS mouse model. In our AS mouse model, we saw a global delay in the onset of myelination, which normalized within days (likely corresponding to months or years in human development). This myelination delay is caused by the loss of UBE3A in neurons rather than UBE3A haploinsufficiency in oligodendrocytes. Interestingly, ultrastructural analyses did not reveal any abnormalities in myelinated or unmyelinated axons., Limitations: It is difficult to extrapolate the timing and duration of the myelination delay observed in AS model mice to individuals with AS., Conclusions: This study reveals WM deficits as a hallmark in children with AS, demonstrating for the first time that these deficits are already apparent at 1 year of age. Parallel studies in a mouse model of AS show that these deficits may be associated with delayed onset of myelination due to the loss of neuronal (but not glial) UBE3A. These findings emphasize the potential of WM as both a therapeutic target for interventions and a valuable biomarker for tracking the progression of AS and the effectiveness of potential treatments., Competing Interests: Competing interests The authors declare no competing interests. Conflicts of Interest The authors declare no conflicts of interest Additional Declarations: No competing interests reported.- Published
- 2024
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