Julia Bassell1, Siddharth Srivastava2, Anna K Prohl3, Benoit Scherrer3, Kush Kapur2, Rajna Filip-Dhima4, Elizabeth Berry-Kravis5, Latha Soorya6, Audrey Thurm7, Craig M Powell8, Jonathan A Bernstein9, Joseph D Buxbaum10, Alexander Kolevzon11, Simon K Warfield3, Mustafa Sahin12. 1. Warren Alpert Medical School of Brown University, Providence, Rhode Island. 2. Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts. 3. Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts. 4. F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts. 5. Department of Pediatrics, Rush University Medical Center, Chicago, Illinois; Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois; Department of Biochemistry, Rush University Medical Center, Chicago, Illinois. 6. Department of Psychiatry, Rush University Medical Center, Chicago, Illinois. 7. Pediatrics and Developmental Neuroscience Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland. 8. Department of Neurobiology, University of Alabama at Birmingham School of Medicine, Birmingham, Alabama; Civitan International Research Center, University of Alabama at Birmingham School of Medicine, Birmingham, Alabama. 9. Department of Pediatrics, Stanford University School of Medicine, Stanford, California. 10. Seaver Autism Center for Research and Treatment, Mount Sinai School of Medicine, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, New York; Department of Neuroscience, Mount Sinai School of Medicine, New York, New York. 11. Seaver Autism Center for Research and Treatment, Mount Sinai School of Medicine, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York. 12. Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts; F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts. Electronic address: mustafa.sahin@childrens.harvard.edu.
Abstract
BACKGROUND: This cohort study utilized diffusion tensor imaging tractography to compare the uncinate fasciculus and inferior longitudinal fasciculus in children with Phelan-McDermid syndrome with age-matched controls and investigated trends between autism spectrum diagnosis and the integrity of the uncinate fasciculus and inferior longitudinal fasciculus white matter tracts. METHODS: This research was conducted under a longitudinal study that aims to map the genotype, phenotype, and natural history of Phelan-McDermid syndrome and identify biomarkers using neuroimaging (ClinicalTrial NCT02461420). Patients were aged three to 21 years and underwent longitudinal neuropsychologic assessment over 24 months. MRI processing and analyses were completed using previously validated image analysis software distributed as the Computational Radiology Kit (http://crl.med.harvard.edu/). Whole-brain connectivity was generated for each subject using a stochastic streamline tractography algorithm, and automatically defined regions of interest were used to map the uncinate fasciculus and inferior longitudinal fasciculus. RESULTS: There were 10 participants (50% male; mean age 11.17 years) with Phelan-McDermid syndrome (n = 8 with autism). Age-matched controls, enrolled in a separate longitudinal study (NIH R01 NS079788), underwent the same neuroimaging protocol. There was a statistically significant decrease in the uncinate fasciculus fractional anisotropy measure and a statistically significant increase in uncinate fasciculus mean diffusivity measure, in the patient group versus controls in both right and left tracts (P ≤ 0.024). CONCLUSION: Because the uncinate fasciculus plays a critical role in social and emotional interaction, this tract may underlie some deficits seen in the Phelan-McDermid syndrome population. These findings need to be replicated in a larger cohort.
BACKGROUND: This cohort study utilized diffusion tensor imaging tractography to compare the uncinate fasciculus and inferior longitudinal fasciculus in children with Phelan-McDermid syndrome with age-matched controls and investigated trends between autism spectrum diagnosis and the integrity of the uncinate fasciculus and inferior longitudinal fasciculus white matter tracts. METHODS: This research was conducted under a longitudinal study that aims to map the genotype, phenotype, and natural history of Phelan-McDermid syndrome and identify biomarkers using neuroimaging (ClinicalTrial NCT02461420). Patients were aged three to 21 years and underwent longitudinal neuropsychologic assessment over 24 months. MRI processing and analyses were completed using previously validated image analysis software distributed as the Computational Radiology Kit (http://crl.med.harvard.edu/). Whole-brain connectivity was generated for each subject using a stochastic streamline tractography algorithm, and automatically defined regions of interest were used to map the uncinate fasciculus and inferior longitudinal fasciculus. RESULTS: There were 10 participants (50% male; mean age 11.17 years) with Phelan-McDermid syndrome (n = 8 with autism). Age-matched controls, enrolled in a separate longitudinal study (NIH R01 NS079788), underwent the same neuroimaging protocol. There was a statistically significant decrease in the uncinate fasciculus fractional anisotropy measure and a statistically significant increase in uncinate fasciculus mean diffusivity measure, in the patient group versus controls in both right and left tracts (P ≤ 0.024). CONCLUSION: Because the uncinate fasciculus plays a critical role in social and emotional interaction, this tract may underlie some deficits seen in the Phelan-McDermid syndrome population. These findings need to be replicated in a larger cohort.
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