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Mandelli V, Severino I, Eyler L, Pierce K, Courchesne E, Lombardo MV. A 3D approach to understanding heterogeneity in early developing autisms. medRxiv 2024:2024.05.08.24307039. [PMID: 38766085 PMCID: PMC11100949 DOI: 10.1101/2024.05.08.24307039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Phenotypic heterogeneity in early language, intellectual, motor, and adaptive functioning (LIMA) features are amongst the most striking features that distinguish different types of autistic individuals. Yet the current diagnostic criteria uses a single label of autism and implicitly emphasizes what individuals have in common as core social-communicative and restricted repetitive behavior difficulties. Subtype labels based on the non-core LIMA features may help to more meaningfully distinguish types of autisms with differing developmental paths and differential underlying biology. Using relatively large (n=615) publicly available data from early developing (24-68 months) standardized clinical tests tapping LIMA features, we show that stability-based relative cluster validation analysis can identify two robust and replicable clusters in the autism population with high levels of generalization accuracy (98%). These clusters can be described as Type I versus Type II autisms differentiated by relatively high versus low scores on LIMA features. These two types of autisms are also distinguished by different developmental trajectories over the first decade of life. Finally, these two types of autisms reveal striking differences in functional and structural neuroimaging phenotypes and their relationships with gene expression. This work emphasizes the potential importance of stratifying autism by a Type I versus Type II distinction focused on LIMA features and which may be of high prognostic and biological significance.
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Bedford SA, Lai MC, Lombardo MV, Chakrabarti B, Ruigrok A, Suckling J, Anagnostou E, Lerch JP, Taylor M, Nicolson R, Stelios G, Crosbie J, Schachar R, Kelley E, Jones J, Arnold PD, Courchesne E, Pierce K, Eyler LT, Campbell K, Barnes CC, Seidlitz J, Alexander-Bloch AF, Bullmore ET, Baron-Cohen S, Bethlehem RA. Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology. medRxiv 2023:2023.12.06.23299587. [PMID: 38106166 PMCID: PMC10723556 DOI: 10.1101/2023.12.06.23299587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Background Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Normative modelling provides a unified framework for studying age-specific and sex-specific divergences in neurodivergent brain development. Methods Here we use normative modelling and a large, multi-site neuroimaging dataset to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of typical brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD). Results We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume localised to the superior temporal cortex, whereas individuals with ADHD showed more global effects of cortical thickness increases but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only. Conclusions These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.
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Affiliation(s)
- Saashi A. Bedford
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ, UK
| | - Meng-Chuan Lai
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
- The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Department of Psychiatry, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei 100229, Taiwan
| | - Michael V. Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Bhismadev Chakrabarti
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
- Centre for Autism, School of Psychology and Clinical Language Sciences, University of Reading, Reading RG6 6ES, UK
| | - Amber Ruigrok
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
- Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester
| | - John Suckling
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ, UK
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Department of Pediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Jason P. Lerch
- Program in Neurosciences and Mental Health, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Margot Taylor
- Program in Neurosciences and Mental Health, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Rob Nicolson
- Department of Psychiatry, University of Western Ontario, London, Ontario, Canada
| | | | - Jennifer Crosbie
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5T 1R8, Canada
- Program in Neurosciences and Mental Health, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Russell Schachar
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5T 1R8, Canada
- Program in Neurosciences and Mental Health, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Elizabeth Kelley
- Department of Psychology, Queen’s University, Kingston, ON K7L 3N6 Canada
- Centre for Neuroscience Studies, Queen’s University, Kingston, ON K7L 3N6 Canada
- Department of Psychiatry, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - Jessica Jones
- Department of Psychology, Queen’s University, Kingston, ON K7L 3N6 Canada
- Centre for Neuroscience Studies, Queen’s University, Kingston, ON K7L 3N6 Canada
- Department of Psychiatry, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - Paul D. Arnold
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Eric Courchesne
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Karen Pierce
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Lisa T. Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | - Kathleen Campbell
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Cynthia Carter Barnes
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Aaron F. Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Edward T. Bullmore
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ, UK
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
- Cambridge Lifetime Autism Spectrum Service (CLASS), Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Richard A.I. Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
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Seidlitz J, Mallard TT, Vogel JW, Lee YH, Warrier V, Ball G, Hansson O, Hernandez LM, Mandal AS, Wagstyl K, Lombardo MV, Courchesne E, Glessner JT, Satterthwaite TD, Bethlehem RAI, Bernstock JD, Tasaki S, Ng B, Gaiteri C, Smoller JW, Ge T, Gur RE, Gandal MJ, Alexander-Bloch AF. The molecular genetic landscape of human brain size variation. Cell Rep 2023; 42:113439. [PMID: 37963017 DOI: 10.1016/j.celrep.2023.113439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 06/13/2023] [Accepted: 10/27/2023] [Indexed: 11/16/2023] Open
Abstract
Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.
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Affiliation(s)
- Jakob Seidlitz
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA
| | - Jacob W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Younga H Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge CB2 1TN, UK; Department of Psychology, University of Cambridge, Cambridge CB2 1TN, UK
| | - Gareth Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, VIC 3052, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Melbourne, VIC 3052, Australia
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö P663+Q9, Sweden; Memory Clinic, Skåne University Hospital, Malmö P663+Q9, Sweden
| | - Leanna M Hernandez
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Ayan S Mandal
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, 38068 Rovereto, Italy
| | - Eric Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA 92093, USA; Autism Center of Excellence, University of California, San Diego, San Diego, CA 92093, USA
| | - Joseph T Glessner
- The Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | | | - Joshua D Bernstock
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard University, Boston, MA 02115, USA; Department of Neurosurgery, Boston Children's Hospital, Harvard University, Boston, MA 02115, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Bernard Ng
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA; Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA; Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Raquel E Gur
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael J Gandal
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron F Alexander-Bloch
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
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Lesinger K, Rosenthal G, Pierce K, Courchesne E, Dinstein I, Avidan G. Functional connectivity of the human face network exhibits right hemispheric lateralization from infancy to adulthood. Sci Rep 2023; 13:20831. [PMID: 38012206 PMCID: PMC10682179 DOI: 10.1038/s41598-023-47581-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 11/14/2023] [Indexed: 11/29/2023] Open
Abstract
Adults typically exhibit right hemispheric dominance in the processing of faces. In this cross-sectional study, we investigated age-dependent changes in face processing lateralization from infancy to adulthood (1-48 years old; N = 194). We co-registered anatomical and resting state functional Magnetic Resonance Imaging (fMRI) scans of toddlers, children, adolescents, and adults into a common space and examined functional connectivity across the face, as well as place, and object-selective regions identified in adults. As expected, functional connectivity between core face-selective regions was stronger in the right compared to the left hemisphere in adults. Most importantly, the same lateralization was evident in all other age groups (infants, children, adolescents) and appeared only in face-selective regions, and not in place or object-selective regions. These findings suggest that the physiological development of face-selective brain areas may differ from that of object and place-selective areas. Specifically, the functional connectivity of the core-face selective regions exhibits rightward lateralization from infancy, years before these areas develop mature face-selective responses.
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Affiliation(s)
- Keren Lesinger
- Department of Psychology, Ben-Gurion University of the Negev, POB 653, 8410501, Beer Sheva, Israel
| | - Gideon Rosenthal
- Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, POB 653, 8410501, Beer Sheva, Israel
| | - Karen Pierce
- Department of Neurosciences, University of California, San Diego, USA
| | - Eric Courchesne
- Department of Neurosciences, University of California, San Diego, USA
| | - Ilan Dinstein
- Department of Psychology, Ben-Gurion University of the Negev, POB 653, 8410501, Beer Sheva, Israel
| | - Galia Avidan
- Department of Psychology, Ben-Gurion University of the Negev, POB 653, 8410501, Beer Sheva, Israel.
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Xiao Y, Wen TH, Kupis L, Eyler LT, Taluja V, Troxel J, Goel D, Lombardo MV, Pierce K, Courchesne E. Atypical functional connectivity of temporal cortex with precuneus and visual regions may be an early-age signature of ASD. Mol Autism 2023; 14:11. [PMID: 36899425 PMCID: PMC10007788 DOI: 10.1186/s13229-023-00543-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 02/24/2023] [Indexed: 03/12/2023] Open
Abstract
BACKGROUND Social and language abilities are closely intertwined during early typical development. In autism spectrum disorder (ASD), however, deficits in social and language development are early-age core symptoms. We previously reported that superior temporal cortex, a well-established social and language region, shows reduced activation to social affective speech in ASD toddlers; however, the atypical cortical connectivity that accompanies this deviance remains unknown. METHODS We collected clinical, eye tracking, and resting-state fMRI data from 86 ASD and non-ASD subjects (mean age 2.3 ± 0.7 years). Functional connectivity of left and right superior temporal regions with other cortical regions and correlations between this connectivity and each child's social and language abilities were examined. RESULTS While there was no group difference in functional connectivity, the connectivity between superior temporal cortex and frontal and parietal regions was significantly correlated with language, communication, and social abilities in non-ASD subjects, but these effects were absent in ASD subjects. Instead, ASD subjects, regardless of different social or nonsocial visual preferences, showed atypical correlations between temporal-visual region connectivity and communication ability (r(49) = 0.55, p < 0.001) and between temporal-precuneus connectivity and expressive language ability (r(49) = 0.58, p < 0.001). LIMITATIONS The distinct connectivity-behavior correlation patterns may be related to different developmental stages in ASD and non-ASD subjects. The use of a prior 2-year-old template for spatial normalization may not be optimal for a few subjects beyond this age range. CONCLUSIONS Superior temporal cortex is known to have reduced activation to social affective speech in ASD at early ages, and here we find in ASD toddlers that it also has atypical connectivity with visual and precuneus cortices that is correlated with communication and language ability, a pattern not seen in non-ASD toddlers. This atypicality may be an early-age signature of ASD that also explains why the disorder has deviant early language and social development. Given that these atypical connectivity patterns are also present in older individuals with ASD, we conclude these atypical connectivity patterns persist across age and may explain why successful interventions targeting language and social skills at all ages in ASD are so difficult to achieve.
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Affiliation(s)
- Yaqiong Xiao
- Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen, 518107, China.
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA.
| | - Teresa H Wen
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Lauren Kupis
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California, 9500 Gilman Drive, La Jolla, San Diego, CA, 92161, USA
- VISN 22 Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Vani Taluja
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Jaden Troxel
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Disha Goel
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Karen Pierce
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA.
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Pierce K, Wen TH, Zahiri J, Andreason C, Courchesne E, Barnes CC, Lopez L, Arias SJ, Esquivel A, Cheng A. Level of Attention to Motherese Speech as an Early Marker of Autism Spectrum Disorder. JAMA Netw Open 2023; 6:e2255125. [PMID: 36753277 PMCID: PMC9909502 DOI: 10.1001/jamanetworkopen.2022.55125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 12/19/2022] [Indexed: 02/09/2023] Open
Abstract
Importance Caregivers have long captured the attention of their infants by speaking in motherese, a playful speech style characterized by heightened affect. Reduced attention to motherese in toddlers with autism spectrum disorder (ASD) may be a contributor to downstream language and social challenges and could be diagnostically revealing. Objective To investigate whether attention toward motherese speech can be used as a diagnostic classifier of ASD and is associated with language and social ability. Design, Setting, and Participants This diagnostic study included toddlers aged 12 to 48 months, spanning ASD and non-ASD diagnostic groups, at a research center. Data were collected from February 2018 to April 2021 and analyzed from April 2021 to March 2022. Exposures Gaze-contingent eye-tracking test. Main Outcomes and Measures Using gaze-contingent eye tracking wherein the location of a toddler's fixation triggered a specific movie file, toddlers participated in 1 or more 1-minute eye-tracking tests designed to quantify attention to motherese speech, including motherese vs traffic (ie, noisy vehicles on a highway) and motherese vs techno (ie, abstract shapes with music). Toddlers were also diagnostically and psychometrically evaluated by psychologists. Levels of fixation within motherese and nonmotherese movies and mean number of saccades per second were calculated. Receiver operating characteristic (ROC) curves were used to evaluate optimal fixation cutoff values and associated sensitivity, specificity, positive predictive value (PPV), and negative predictive value. Within the ASD group, toddlers were stratified based on low, middle, or high levels of interest in motherese speech, and associations with social and language abilities were examined. Results A total of 653 toddlers were included (mean [SD] age, 26.45 [8.37] months; 480 males [73.51%]). Unlike toddlers without ASD, who almost uniformly attended to motherese speech with a median level of 82.25% and 80.75% across the 2 tests, among toddlers with ASD, there was a wide range, spanning 0% to 100%. Both the traffic and techno paradigms were effective diagnostic classifiers, with large between-group effect sizes (eg, ASD vs typical development: Cohen d, 1.0 in the techno paradigm). Across both paradigms, a cutoff value of 30% or less fixation on motherese resulted in an area under the ROC curve (AUC) of 0.733 (95% CI, 0.693-0.773) and 0.761 (95% CI, 0.717-0.804), respectively; specificity of 98% (95% CI, 95%-99%) and 96% (95% CI, 92%-98%), respectively; and PPV of 94% (95% CI, 86%-98%). Reflective of heterogeneity and expected subtypes in ASD, sensitivity was lower at 18% (95% CI, 14%-22%) and 29% (95% CI, 24%-34%), respectively. Combining metrics increased the AUC to 0.841 (95% CI, 0.805-0.877). Toddlers with ASD who showed the lowest levels of attention to motherese speech had weaker social and language abilities. Conclusions and Relevance In this diagnostic study, a subset of toddlers showed low levels of attention toward motherese speech. When a cutoff level of 30% or less fixation on motherese speech was used, toddlers in this range were diagnostically classified as having ASD with high accuracy. Insight into which toddlers show unusually low levels of attention to motherese may be beneficial not only for early ASD diagnosis and prognosis but also as a possible therapeutic target.
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Affiliation(s)
- Karen Pierce
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
| | - Teresa H. Wen
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
| | - Javad Zahiri
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
| | - Charlene Andreason
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
| | - Cynthia C. Barnes
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
| | - Linda Lopez
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
| | - Steven J. Arias
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
| | - Ahtziry Esquivel
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
| | - Amanda Cheng
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla
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Bao B, Zahiri J, Gazestani VH, Lopez L, Xiao Y, Kim R, Wen TH, Chiang AWT, Nalabolu S, Pierce K, Robasky K, Wang T, Hoekzema K, Eichler EE, Lewis NE, Courchesne E. A predictive ensemble classifier for the gene expression diagnosis of ASD at ages 1 to 4 years. Mol Psychiatry 2023; 28:822-833. [PMID: 36266569 PMCID: PMC9908553 DOI: 10.1038/s41380-022-01826-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 09/13/2022] [Accepted: 09/27/2022] [Indexed: 11/09/2022]
Abstract
Autism Spectrum Disorder (ASD) diagnosis remains behavior-based and the median age of diagnosis is ~52 months, nearly 5 years after its first-trimester origin. Accurate and clinically-translatable early-age diagnostics do not exist due to ASD genetic and clinical heterogeneity. Here we collected clinical, diagnostic, and leukocyte RNA data from 240 ASD and typically developing (TD) toddlers (175 toddlers for training and 65 for test). To identify gene expression ASD diagnostic classifiers, we developed 42,840 models composed of 3570 gene expression feature selection sets and 12 classification methods. We found that 742 models had AUC-ROC ≥ 0.8 on both Training and Test sets. Weighted Bayesian model averaging of these 742 models yielded an ensemble classifier model with accurate performance in Training and Test gene expression datasets with ASD diagnostic classification AUC-ROC scores of 85-89% and AUC-PR scores of 84-92%. ASD toddlers with ensemble scores above and below the overall ASD ensemble mean of 0.723 (on a scale of 0 to 1) had similar diagnostic and psychometric scores, but those below this ASD ensemble mean had more prenatal risk events than TD toddlers. Ensemble model feature genes were involved in cell cycle, inflammation/immune response, transcriptional gene regulation, cytokine response, and PI3K-AKT, RAS and Wnt signaling pathways. We additionally collected targeted DNA sequencing smMIPs data on a subset of ASD risk genes from 217 of the 240 ASD and TD toddlers. This DNA sequencing found about the same percentage of SFARI Level 1 and 2 ASD risk gene mutations in TD (12 of 105) as in ASD (13 of 112) toddlers, and classification based only on the presence of mutation in these risk genes performed at a chance level of 49%. By contrast, the leukocyte ensemble gene expression classifier correctly diagnostically classified 88% of TD and ASD toddlers with ASD risk gene mutations. Our ensemble ASD gene expression classifier is diagnostically predictive and replicable across different toddler ages, races, and ethnicities; out-performs a risk gene mutation classifier; and has potential for clinical translation.
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Affiliation(s)
- Bokan Bao
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Javad Zahiri
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Vahid H Gazestani
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Linda Lopez
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Yaqiong Xiao
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
- Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Raphael Kim
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Teresa H Wen
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Austin W T Chiang
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Srinivasa Nalabolu
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Kimberly Robasky
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, US
- School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Carolina Health and Informatics Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Tianyun Wang
- Department of Medical Genetics, Center for Medical Genetics, Peking University Health Science Center, 100191, Beijing, China
- Neuroscience Research Institute, Peking University; Key Laboratory for Neuroscience, Ministry of Education of China & National Health Commission of China, 100191, Beijing, China
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, 98195, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA.
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA.
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8
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Duan K, Eyler L, Pierce K, Lombardo M, Datko M, Hagler D, Taluja V, Zahiri J, Campbell K, Barnes C, Arias S, Nalabolu S, Troxel J, Courchesne E. Language, Social, and Face Regions Are Affected in Toddlers with Autism and Predictive of Language Outcome. Res Sq 2023:rs.3.rs-2451837. [PMID: 36778379 PMCID: PMC9915795 DOI: 10.21203/rs.3.rs-2451837/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Identifying prognostic early brain alterations is crucial for autism spectrum disorder (ASD). Leveraging structural MRI data from 166 ASD and 109 typical developing (TD) toddlers and controlling for brain size, we found that, compared to TD, ASD toddlers showed larger or thicker lateral temporal regions; smaller or thinner frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most of these differences were replicated in an independent cohort of 38 ASD and 37 TD toddlers. Moreover, the identified brain alterations were related to ASD symptom severity and cognitive impairments at intake, and, remarkably, they improved the accuracy for predicting later language outcome beyond intake clinical and demographic variables. In summary, brain regions involved in language, social, and face processing were altered in ASD toddlers. These early-age brain alterations may be the result of dysregulation in multiple neural processes and stages and are promising prognostic biomarkers for future language ability.
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Affiliation(s)
- Kuaikuai Duan
- Georgia Institute of Technology, Emory University, Georgia State University
| | | | | | | | | | - Donald Hagler
- Department of Radiology, School of Medicine, University of California San Diego, USA
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9
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Pham C, Bacon EC, Grzybowski A, Carter-Barnes C, Arias S, Xu R, Lopez L, Courchesne E, Pierce K. Examination of the impact of the Get SET Early program on equitable access to care within the screen-evaluate-treat chain in toddlers with autism spectrum disorder. Autism 2023:13623613221147416. [PMID: 36629055 PMCID: PMC10333446 DOI: 10.1177/13623613221147416] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
LAY ABSTRACT Delays in autism spectrum disorder identification and access to care could impact developmental outcomes. Although trends are encouraging, children from historically underrepresented minority backgrounds are often identified at later ages and have reduced engagement in services. It is unclear if disparities exist all along the screen-evaluation-treatment chain, or if early detection programs such as Get SET Early that standardize, these steps are effective at ameliorating disparities. As part of the Get SET Early model, primary care providers administered a parent-report screen at well-baby examinations, and parents designated race, ethnicity, and developmental concerns. Toddlers who scored in the range of concern, or whose primary care provider had concerns, were referred for an evaluation. Rates of screening and evaluation engagement within ethnic/racial groups were compared to US Census data. Age at screen, evaluation, and treatment engagement and quantity was compared across groups. Statistical models examined whether key factors such as parent concern were associated with ethnicity or race. No differences were found in the mean age at the first screen, evaluation, or initiation or quantity of behavioral therapy between participants. However, children from historically underrepresented minority backgrounds were more likely to fall into the range of concern on the parent-report screen, their parents expressed developmental concerns more often, and pediatricians were more likely to refer for an evaluation than their White/Not Hispanic counterparts. Overall results suggest that models that support transparent tracking of steps in the screen-evaluation-treatment chain and service referral pipelines may be an effective strategy for ensuring equitable access to care for all children.
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Affiliation(s)
| | | | | | | | | | - Ronghui Xu
- University of California, San Diego, USA
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10
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Antaki D, Guevara J, Maihofer AX, Klein M, Gujral M, Grove J, Carey CE, Hong O, Arranz MJ, Hervas A, Corsello C, Vaux KK, Muotri AR, Iakoucheva LM, Courchesne E, Pierce K, Gleeson JG, Robinson EB, Nievergelt CM, Sebat J. A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex. Nat Genet 2022; 54:1284-1292. [PMID: 35654974 PMCID: PMC9474668 DOI: 10.1038/s41588-022-01064-5] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 03/28/2022] [Indexed: 01/21/2023]
Abstract
The genetic etiology of autism spectrum disorder (ASD) is multifactorial, but how combinations of genetic factors determine risk is unclear. In a large family sample, we show that genetic loads of rare and polygenic risk are inversely correlated in cases and greater in females than in males, consistent with a liability threshold that differs by sex. De novo mutations (DNMs), rare inherited variants and polygenic scores were associated with various dimensions of symptom severity in children and parents. Parental age effects on risk for ASD in offspring were attributable to a combination of genetic mechanisms, including DNMs that accumulate in the paternal germline and inherited risk that influences behavior in parents. Genes implicated by rare variants were enriched in excitatory and inhibitory neurons compared with genes implicated by common variants. Our results suggest that a phenotypic spectrum of ASD is attributable to a spectrum of genetic factors that impact different neurodevelopmental processes.
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Affiliation(s)
- Danny Antaki
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - James Guevara
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Adam X Maihofer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Marieke Klein
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Madhusudan Gujral
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jakob Grove
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine and Center for Integrative Sequencing, iSEQ, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Caitlin E Carey
- Harvard T.H. Chan School of Public Health, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Oanh Hong
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Maria J Arranz
- Research Laboratory Unit, Fundacio Docencia i Recerca Mutua, Terrassa, Spain
| | - Amaia Hervas
- Child and Adolescent Mental Health Unit, Hospital Universitari Mútua de Terrassa, Barcelona, Spain
| | - Christina Corsello
- TEACCH Autism Program, University of North Carolina, Chapel Hill, NC, USA
| | | | - Alysson R Muotri
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics and Department of Cellular & Molecular Medicine, University of California San Diego, School of Medicine, Center for Academic Research and Training in Anthropogeny, Archealization Center, Kavli Institute for Brain and Mind, La Jolla, CA, USA
| | - Lilia M Iakoucheva
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Autism Center of Excellence, University of California San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Autism Center of Excellence, University of California San Diego, La Jolla, CA, USA
| | - Joseph G Gleeson
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Elise B Robinson
- Harvard T.H. Chan School of Public Health, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | | | - Jonathan Sebat
- Beyster Center for Psychiatric Genomics, University of California San Diego, La Jolla, CA, USA.
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
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11
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Bethlehem RAI, Seidlitz J, White SR, Vogel JW, Anderson KM, Adamson C, Adler S, Alexopoulos GS, Anagnostou E, Areces-Gonzalez A, Astle DE, Auyeung B, Ayub M, Bae J, Ball G, Baron-Cohen S, Beare R, Bedford SA, Benegal V, Beyer F, Blangero J, Blesa Cábez M, Boardman JP, Borzage M, Bosch-Bayard JF, Bourke N, Calhoun VD, Chakravarty MM, Chen C, Chertavian C, Chetelat G, Chong YS, Cole JH, Corvin A, Costantino M, Courchesne E, Crivello F, Cropley VL, Crosbie J, Crossley N, Delarue M, Delorme R, Desrivieres S, Devenyi GA, Di Biase MA, Dolan R, Donald KA, Donohoe G, Dunlop K, Edwards AD, Elison JT, Ellis CT, Elman JA, Eyler L, Fair DA, Feczko E, Fletcher PC, Fonagy P, Franz CE, Galan-Garcia L, Gholipour A, Giedd J, Gilmore JH, Glahn DC, Goodyer IM, Grant PE, Groenewold NA, Gunning FM, Gur RE, Gur RC, Hammill CF, Hansson O, Hedden T, Heinz A, Henson RN, Heuer K, Hoare J, Holla B, Holmes AJ, Holt R, Huang H, Im K, Ipser J, Jack CR, Jackowski AP, Jia T, Johnson KA, Jones PB, Jones DT, Kahn RS, Karlsson H, Karlsson L, Kawashima R, Kelley EA, Kern S, Kim KW, Kitzbichler MG, Kremen WS, Lalonde F, Landeau B, Lee S, Lerch J, Lewis JD, Li J, Liao W, Liston C, Lombardo MV, Lv J, Lynch C, Mallard TT, Marcelis M, Markello RD, Mathias SR, Mazoyer B, McGuire P, Meaney MJ, Mechelli A, Medic N, Misic B, Morgan SE, Mothersill D, Nigg J, Ong MQW, Ortinau C, Ossenkoppele R, Ouyang M, Palaniyappan L, Paly L, Pan PM, Pantelis C, Park MM, Paus T, Pausova Z, Paz-Linares D, Pichet Binette A, Pierce K, Qian X, Qiu J, Qiu A, Raznahan A, Rittman T, Rodrigue A, Rollins CK, Romero-Garcia R, Ronan L, Rosenberg MD, Rowitch DH, Salum GA, Satterthwaite TD, Schaare HL, Schachar RJ, Schultz AP, Schumann G, Schöll M, Sharp D, Shinohara RT, Skoog I, Smyser CD, Sperling RA, Stein DJ, Stolicyn A, Suckling J, Sullivan G, Taki Y, Thyreau B, Toro R, Traut N, Tsvetanov KA, Turk-Browne NB, Tuulari JJ, Tzourio C, Vachon-Presseau É, Valdes-Sosa MJ, Valdes-Sosa PA, Valk SL, van Amelsvoort T, Vandekar SN, Vasung L, Victoria LW, Villeneuve S, Villringer A, Vértes PE, Wagstyl K, Wang YS, Warfield SK, Warrier V, Westman E, Westwater ML, Whalley HC, Witte AV, Yang N, Yeo B, Yun H, Zalesky A, Zar HJ, Zettergren A, Zhou JH, Ziauddeen H, Zugman A, Zuo XN, Bullmore ET, Alexander-Bloch AF. Brain charts for the human lifespan. Nature 2022; 604:525-533. [PMID: 35388223 PMCID: PMC9021021 DOI: 10.1038/s41586-022-04554-y] [Citation(s) in RCA: 404] [Impact Index Per Article: 202.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 02/16/2022] [Indexed: 02/02/2023]
Abstract
Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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Affiliation(s)
- R A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - J Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
| | - S R White
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - J W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - K M Anderson
- Department of Psychology, Yale University, New Haven, CT, USA
| | - C Adamson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S Adler
- UCL Great Ormond Street Institute for Child Health, London, UK
| | - G S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, USA
| | - E Anagnostou
- Department of Pediatrics University of Toronto, Toronto, Canada
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - A Areces-Gonzalez
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- University of Pinar del Río "Hermanos Saiz Montes de Oca", Pinar del Río, Cuba
| | - D E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - B Auyeung
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - M Ayub
- Queen's University, Department of Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
- University College London, Mental Health Neuroscience Research Department, Division of Psychiatry, London, UK
| | - J Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
| | - G Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - S Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridge Lifetime Asperger Syndrome Service (CLASS), Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - R Beare
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S A Bedford
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - V Benegal
- Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - F Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - J Blangero
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Edinburg, TX, USA
| | - M Blesa Cábez
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - J P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - M Borzage
- Fetal and Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - J F Bosch-Bayard
- McGill Centre for Integrative Neuroscience, Ludmer Centre for Neuroinformatics and Mental Health, Montreal Neurological Institute, Montreal, Quebec, Canada
- McGill University, Montreal, Quebec, Canada
| | - N Bourke
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, Dementia Research Institute, London, UK
| | - V D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - M M Chakravarty
- McGill University, Montreal, Quebec, Canada
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - C Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - C Chertavian
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - G Chetelat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Y S Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J H Cole
- Centre for Medical Image Computing (CMIC), University College London, London, UK
- Dementia Research Centre (DRC), University College London, London, UK
| | - A Corvin
- Department of Psychiatry, Trinity College, Dublin, Ireland
| | - M Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Quebec, Canada
- Undergraduate program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - E Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
- Autism Center of Excellence, University of California, San Diego, San Diego, CA, USA
| | - F Crivello
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
| | - V L Cropley
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
| | - J Crosbie
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - N Crossley
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Instituto Milenio Intelligent Healthcare Engineering, Santiago, Chile
| | - M Delarue
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - R Delorme
- Child and Adolescent Psychiatry Department, Robert Debré University Hospital, AP-HP, Paris, France
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - S Desrivieres
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - G A Devenyi
- Cerebral Imaging Centre, McGill Department of Psychiatry, Douglas Mental Health University Institute, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M A Di Biase
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - R Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, London, UK
| | - K A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - G Donohoe
- Center for Neuroimaging, Cognition & Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - K Dunlop
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - A D Edwards
- Centre for the Developing Brain, King's College London, London, UK
- Evelina London Children's Hospital, London, UK
- MRC Centre for Neurodevelopmental Disorders, London, UK
| | - J T Elison
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - C T Ellis
- Department of Psychology, Yale University, New Haven, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - J A Elman
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - L Eyler
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, Los Angeles, CA, USA
| | - D A Fair
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - E Feczko
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - P C Fletcher
- Department of Psychiatry, University of Cambridge, and Wellcome Trust MRC Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - P Fonagy
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
- Anna Freud National Centre for Children and Families, London, UK
| | - C E Franz
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | | | - A Gholipour
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - J Giedd
- Department of Child and Adolescent Psychiatry, University of California, San Diego, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - J H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - D C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - I M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - P E Grant
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Groenewold
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - F M Gunning
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - R E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - R C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - C F Hammill
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Mouse Imaging Centre, Toronto, Ontario, Canada
| | - O Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - T Hedden
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - A Heinz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
| | - R N Henson
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - K Heuer
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Université de Paris, Paris, France
| | - J Hoare
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - B Holla
- Department of Integrative Medicine, NIMHANS, Bengaluru, India
- Accelerator Program for Discovery in Brain disorders using Stem cells (ADBS), Department of Psychiatry, NIMHANS, Bengaluru, India
| | - A J Holmes
- Departments of Psychology and Psychiatry, Yale University, New Haven, CT, USA
| | - R Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H Huang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - K Im
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Ipser
- Department of Psychiatry and Mental Health, Clinical Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - C R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - A P Jackowski
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
- National Institute of Developmental Psychiatry, Beijing, China
| | - T Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and BrainInspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - K A Johnson
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - P B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - D T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R S Kahn
- Department of Psychiatry, Icahn School of Medicine, Mount Sinai, NY, USA
| | - H Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - L Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - R Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - E A Kelley
- Queen's University, Departments of Psychology and Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
| | - S Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - K W Kim
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, South Korea
| | - M G Kitzbichler
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - W S Kremen
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - F Lalonde
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - B Landeau
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - S Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - J Lerch
- Mouse Imaging Centre, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - J D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - J Li
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - W Liao
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - C Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - M V Lombardo
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - J Lv
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- School of Biomedical Engineering and Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - C Lynch
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - T T Mallard
- Department of Psychology, University of Texas, Austin, TX, USA
| | - M Marcelis
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, Maastricht, The Netherlands
- Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, The Netherlands
| | - R D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S R Mathias
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - B Mazoyer
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - P McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - M J Meaney
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - A Mechelli
- Bordeaux University Hospital, Bordeaux, France
| | - N Medic
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - B Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - D Mothersill
- Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland
- School of Psychology and Center for Neuroimaging and Cognitive Genomics, National University of Ireland Galway, Galway, Ireland
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - J Nigg
- Department of Psychiatry, School of Medicine, Oregon Health and Science University, Portland, OR, USA
| | - M Q W Ong
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - C Ortinau
- Department of Pediatrics, Washington University in St Louis, St Louis, MO, USA
| | - R Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Lund University, Clinical Memory Research Unit, Lund, Sweden
| | - M Ouyang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - L Palaniyappan
- Robarts Research Institute and The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
| | - L Paly
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - P M Pan
- Department of Psychiatry, Federal University of Sao Poalo (UNIFESP), Sao Poalo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
| | - C Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
- Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - M M Park
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - T Paus
- Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Z Pausova
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - D Paz-Linares
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- Cuban Neuroscience Center, Havana, Cuba
| | - A Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - K Pierce
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
| | - X Qian
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J Qiu
- School of Psychology, Southwest University, Chongqing, China
| | - A Qiu
- Department of Biomedical Engineering, The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
| | - A Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - T Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - A Rodrigue
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - C K Rollins
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - R Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla, Dpto. de Fisiología Médica y Biofísica, Seville, Spain
| | - L Ronan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - M D Rosenberg
- Department of Psychology and Neuroscience Institute, University of Chicago, Chicago, IL, USA
| | - D H Rowitch
- Department of Paediatrics and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - G A Salum
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clinicas de Porto Alegre, Porto Alegre, Brazil
- National Institute of Developmental Psychiatry (INPD), São Paulo, Brazil
| | - T D Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - H L Schaare
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Juelich, Juelich, Germany
| | - R J Schachar
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - A P Schultz
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - G Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- PONS-Centre, Charite Mental Health, Dept of Psychiatry and Psychotherapy, Charite Campus Mitte, Berlin, Germany
| | - M Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Dementia Research Centre, Queen's Square Institute of Neurology, University College London, London, UK
| | - D Sharp
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, UK Dementia Research Institute, London, UK
| | - R T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - I Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - C D Smyser
- Departments of Neurology, Pediatrics, and Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - R A Sperling
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - D J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Dept of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - A Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - G Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - Y Taki
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - B Thyreau
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - R Toro
- Université de Paris, Paris, France
- Department of Neuroscience, Institut Pasteur, Paris, France
| | - N Traut
- Department of Neuroscience, Institut Pasteur, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - K A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - N B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - J J Tuulari
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Medicine, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
| | - C Tzourio
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France
| | - É Vachon-Presseau
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | | | - P A Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
- Alan Edwards Centre for Research on Pain (AECRP), McGill University, Montreal, Quebec, Canada
| | - S L Valk
- Institute for Neuroscience and Medicine 7, Forschungszentrum Jülich, Jülich, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - T van Amelsvoort
- Department of Psychiatry and Neurosychology, Maastricht University, Maastricht, The Netherlands
| | - S N Vandekar
- Department of Biostatistics, Vanderbilt University, Nashville, TN, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L Vasung
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - L W Victoria
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - S Villeneuve
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - P E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - K Wagstyl
- Wellcome Centre for Human Neuroimaging, London, UK
| | - Y S Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - S K Warfield
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - V Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - E Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - M L Westwater
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H C Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - A V Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
- Faculty of Medicine, CRC 1052 'Obesity Mechanisms', University of Leipzig, Leipzig, Germany
| | - N Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - B Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition and Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
| | - H Yun
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - A Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - H J Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - A Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - J H Zhou
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - H Ziauddeen
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - A Zugman
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Psychiatry, Escola Paulista de Medicina, São Paulo, Brazil
| | - X N Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Brain and Education, School of Education Science, Nanning Normal University, Nanning, China
| | - E T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - A F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
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Wen TH, Cheng A, Andreason C, Zahiri J, Xiao Y, Xu R, Bao B, Courchesne E, Barnes CC, Arias SJ, Pierce K. Large scale validation of an early-age eye-tracking biomarker of an autism spectrum disorder subtype. Sci Rep 2022; 12:4253. [PMID: 35277549 PMCID: PMC8917231 DOI: 10.1038/s41598-022-08102-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 02/28/2022] [Indexed: 01/07/2023] Open
Abstract
Few clinically validated biomarkers of ASD exist which can rapidly, accurately, and objectively identify autism during the first years of life and be used to support optimized treatment outcomes and advances in precision medicine. As such, the goal of the present study was to leverage both simple and computationally-advanced approaches to validate an eye-tracking measure of social attention preference, the GeoPref Test, among 1,863 ASD, delayed, or typical toddlers (12-48 months) referred from the community or general population via a primary care universal screening program. Toddlers participated in diagnostic and psychometric evaluations and the GeoPref Test: a 1-min movie containing side-by-side dynamic social and geometric images. Following testing, diagnosis was denoted as ASD, ASD features, LD, GDD, Other, typical sibling of ASD proband, or typical. Relative to other diagnostic groups, ASD toddlers exhibited the highest levels of visual attention towards geometric images and those with especially high fixation levels exhibited poor clinical profiles. Using the 69% fixation threshold, the GeoPref Test had 98% specificity, 17% sensitivity, 81% PPV, and 65% NPV. Sensitivity increased to 33% when saccades were included, with comparable validity across sex, ethnicity, or race. The GeoPref Test was also highly reliable up to 24 months following the initial test. Finally, fixation levels among twins concordant for ASD were significantly correlated, indicating that GeoPref Test performance may be genetically driven. As the GeoPref Test yields few false positives (~ 2%) and is equally valid across demographic categories, the current findings highlight the ability of the GeoPref Test to rapidly and accurately detect autism before the 2nd birthday in a subset of children and serve as a biomarker for a unique ASD subtype in clinical trials.
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Affiliation(s)
- Teresa H Wen
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA.
| | - Amanda Cheng
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Charlene Andreason
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Javad Zahiri
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Yaqiong Xiao
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Ronghui Xu
- Herbert Wertheim School of Public Health and Department of Mathematics, University of California, San Diego, La Jolla, CA, USA
| | - Bokan Bao
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
- Department of Bioinformatics and Systems Biology, University of California, San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Cynthia Carter Barnes
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Steven J Arias
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA.
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13
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Xiao Y, Wen TH, Kupis L, Eyler LT, Goel D, Vaux K, Lombardo MV, Lewis NE, Pierce K, Courchesne E. Neural responses to affective speech, including motherese, map onto clinical and social eye tracking profiles in toddlers with ASD. Nat Hum Behav 2022; 6:443-454. [PMID: 34980898 DOI: 10.1038/s41562-021-01237-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 10/22/2021] [Indexed: 12/11/2022]
Abstract
Affective speech, including motherese, captures an infant's attention and enhances social, language and emotional development. Decreased behavioural response to affective speech and reduced caregiver-child interactions are early signs of autism in infants. To understand this, we measured neural responses to mild affect speech, moderate affect speech and motherese using natural sleep functional magnetic resonance imaging and behavioural preference for motherese using eye tracking in typically developing toddlers and those with autism. By combining diverse neural-clinical data using similarity network fusion, we discovered four distinct clusters of toddlers. The autism cluster with the weakest superior temporal responses to affective speech and very poor social and language abilities had reduced behavioural preference for motherese, while the typically developing cluster with the strongest superior temporal response to affective speech showed the opposite effect. We conclude that significantly reduced behavioural preference for motherese in autism is related to impaired development of temporal cortical systems that normally respond to parental affective speech.
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Affiliation(s)
- Yaqiong Xiao
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA.
| | - Teresa H Wen
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Lauren Kupis
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- VISN 22 Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Disha Goel
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Keith Vaux
- Point Loma Pediatrics, UC San Diego Health Physician Network, San Diego, CA, USA
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA.
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA.
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14
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Lombardo MV, Busuoli EM, Schreibman L, Stahmer AC, Pramparo T, Landi I, Mandelli V, Bertelsen N, Barnes CC, Gazestani V, Lopez L, Bacon EC, Courchesne E, Pierce K. Pre-treatment clinical and gene expression patterns predict developmental change in early intervention in autism. Mol Psychiatry 2021; 26:7641-7651. [PMID: 34341515 PMCID: PMC8872998 DOI: 10.1038/s41380-021-01239-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/29/2021] [Accepted: 07/13/2021] [Indexed: 12/12/2022]
Abstract
Early detection and intervention are believed to be key to facilitating better outcomes in children with autism, yet the impact of age at treatment start on the outcome is poorly understood. While clinical traits such as language ability have been shown to predict treatment outcome, whether or not and how information at the genomic level can predict treatment outcome is unknown. Leveraging a cohort of toddlers with autism who all received the same standardized intervention at a very young age and provided a blood sample, here we find that very early treatment engagement (i.e., <24 months) leads to greater gains while controlling for time in treatment. Pre-treatment clinical behavioral measures predict 21% of the variance in the rate of skill growth during early intervention. Pre-treatment blood leukocyte gene expression patterns also predict the rate of skill growth, accounting for 13% of the variance in treatment slopes. Results indicated that 295 genes can be prioritized as driving this effect. These treatment-relevant genes highly interact at the protein level, are enriched for differentially histone acetylated genes in autism postmortem cortical tissue, and are normatively highly expressed in a variety of subcortical and cortical areas important for social communication and language development. This work suggests that pre-treatment biological and clinical behavioral characteristics are important for predicting developmental change in the context of early intervention and that individualized pre-treatment biology related to histone acetylation may be key.
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Affiliation(s)
- Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.
- Department of Psychiatry, Autism Research Centre, University of Cambridge, Cambridge, UK.
| | - Elena Maria Busuoli
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
- Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy
| | - Laura Schreibman
- Department of Psychology, University of California, San Diego, La Jolla, CA, USA
| | - Aubyn C Stahmer
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Sacramento, CA, USA
| | - Tiziano Pramparo
- Department of Neurosciences, Autism Center of Excellence, University of California, San Diego, La Jolla, CA, USA
| | - Isotta Landi
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Veronica Mandelli
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
- Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy
| | - Natasha Bertelsen
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
- Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy
| | - Cynthia Carter Barnes
- Department of Neurosciences, Autism Center of Excellence, University of California, San Diego, La Jolla, CA, USA
| | - Vahid Gazestani
- Department of Neurosciences, Autism Center of Excellence, University of California, San Diego, La Jolla, CA, USA
| | - Linda Lopez
- Department of Neurosciences, Autism Center of Excellence, University of California, San Diego, La Jolla, CA, USA
| | - Elizabeth C Bacon
- Department of Neurosciences, Autism Center of Excellence, University of California, San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Department of Neurosciences, Autism Center of Excellence, University of California, San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Department of Neurosciences, Autism Center of Excellence, University of California, San Diego, La Jolla, CA, USA.
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15
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Streuli S, Ibrahim N, Mohamed A, Sharma M, Esmailian M, Sezan I, Farrell C, Sawyer M, Meyer D, El-Maleh K, Thamman R, Marchetti A, Lincoln A, Courchesne E, Sahid A, Bhavnani SP. Development of a culturally and linguistically sensitive virtual reality educational platform to improve vaccine acceptance within a refugee population: the SHIFA community engagement-public health innovation programme. BMJ Open 2021; 11:e051184. [PMID: 34521673 PMCID: PMC8442061 DOI: 10.1136/bmjopen-2021-051184] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVES To combat misinformation, engender trust and increase health literacy, we developed a culturally and linguistically appropriate virtual reality (VR) vaccination education platform using community-engaged approaches within a Somali refugee community. DESIGN Community-based participatory research (CBPR) methods including focus group discussions, interviews, and surveys were conducted with Somali community members and expert advisors to design the educational content. Co-design approaches with community input were employed in a phased approach to develop the VR storyline. PARTICIPANTS 60 adult Somali refugees and seven expert advisors who specialise in healthcare, autism research, technology development and community engagement. SETTING Somali refugees participated at the offices of a community-based organisation, Somali Family Service, in San Diego, California and online. Expert advisors responded to surveys virtually. RESULTS We find that a CBPR approach can be effectively used for the co-design of a VR educational programme. Additionally, cultural and linguistic sensitivities can be incorporated within a VR educational programme and are essential factors for effective community engagement. Finally, effective VR utilisation requires flexibility so that it can be used among community members with varying levels of health and technology literacy. CONCLUSION We describe using community co-design to create a culturally and linguistically sensitive VR experience promoting vaccination within a refugee community. Our approach to VR development incorporated community members at each step of the process. Our methodology is potentially applicable to other populations where cultural sensitivities and language are common health education barriers.
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Affiliation(s)
- Samantha Streuli
- Department of Anthropology, University of California San Diego, La Jolla, California, USA
| | - Najla Ibrahim
- Department of Health and Wellness, Somali Family Service of San Diego, San Diego, CA, USA
| | - Alia Mohamed
- Department of Biology, San Diego State University, San Diego, CA, USA
| | - Manupriya Sharma
- Department of Physics and Engineering, Palomar College, San Marcos, California, USA
| | | | | | - Carrie Farrell
- School of Public Affairs, San Diego State University, San Diego, California, USA
| | - Mark Sawyer
- Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Dan Meyer
- Department of Cardiovascular & Thoracic Surgery, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | | | - Ritu Thamman
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Alex Marchetti
- Farmer School of Business, Miami University, Oxford, Ohio, USA
| | - Alan Lincoln
- Deparment of Clinical Psychology, Alliant International University-San Diego, San Diego, California, USA
| | - Eric Courchesne
- Department of Neurosciences, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Ahmed Sahid
- Somali Family Service of San Diego, San Diego, California, USA
| | - Sanjeev P Bhavnani
- Healthcare Innovation and Practice Transformation Laboratory, Scripps Clinic La Jolla-Genesee Executive Plaza, San Diego, California, USA
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16
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Lombardo MV, Eyler L, Pramparo T, Gazestani VH, Hagler DJ, Chen CH, Dale AM, Seidlitz J, Bethlehem RAI, Bertelsen N, Barnes CC, Lopez L, Campbell K, Lewis NE, Pierce K, Courchesne E. Atypical genomic cortical patterning in autism with poor early language outcome. Sci Adv 2021; 7:eabh1663. [PMID: 34516910 PMCID: PMC8442861 DOI: 10.1126/sciadv.abh1663] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 07/15/2021] [Indexed: 05/21/2023]
Abstract
Cortical regionalization develops via genomic patterning along anterior-posterior (A-P) and dorsal-ventral (D-V) gradients. Here, we find that normative A-P and D-V genomic patterning of cortical surface area (SA) and thickness (CT), present in typically developing and autistic toddlers with good early language outcome, is absent in autistic toddlers with poor early language outcome. Autistic toddlers with poor early language outcome are instead specifically characterized by a secondary and independent genomic patterning effect on CT. Genes involved in these effects can be traced back to midgestational A-P and D-V gene expression gradients and different prenatal cell types (e.g., progenitor cells and excitatory neurons), are functionally important for vocal learning and human-specific evolution, and are prominent in prenatal coexpression networks enriched for high-penetrance autism risk genes. Autism with poor early language outcome may be explained by atypical genomic cortical patterning starting in prenatal development, which may detrimentally affect later regional functional specialization and circuit formation.
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Affiliation(s)
- Michael V. Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Lisa Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- VISN 22 Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Tiziano Pramparo
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Vahid H. Gazestani
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Donald J. Hagler
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Chi-Hua Chen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Anders M. Dale
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Richard A. I. Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Natasha Bertelsen
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
- Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy
| | - Cynthia Carter Barnes
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Linda Lopez
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Kathleen Campbell
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of Utah, Salt Lake City, UT, USA
| | - Nathan E. Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
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17
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Pierce K, Gazestani V, Bacon E, Courchesne E, Cheng A, Barnes CC, Nalabolu S, Cha D, Arias S, Lopez L, Pham C, Gaines K, Gyurjyan G, Cook-Clark T, Karins K. Get SET Early to Identify and Treatment Refer Autism Spectrum Disorder at 1 Year and Discover Factors That Influence Early Diagnosis. J Pediatr 2021; 236:179-188. [PMID: 33915154 DOI: 10.1016/j.jpeds.2021.04.041] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 04/20/2021] [Accepted: 04/21/2021] [Indexed: 12/31/2022]
Abstract
OBJECTIVES To examine the impact of a new approach, Get SET Early, on the rates of early autism spectrum disorder (ASD) detection and factors that influence the screen-evaluate-treat chain. STUDY DESIGN After attending Get SET Early training, 203 pediatricians administered 57 603 total screens using the Communication and Symbolic Behavior Scales Infant-Toddler Checklist at 12-, 18-, and 24-month well-baby examinations, and parents designated presence or absence of concern. For screen-positive toddlers, pediatricians specified if the child was being referred for evaluation, and if not, why not. RESULTS Collapsed across ages, toddlers were evaluated and referred for treatment at a median age of 19 months, and those screened at 12 months (59.4% of sample) by 15 months. Pediatricians referred one-third of screen-positive toddlers for evaluation, citing lack of confidence in the accuracy of screen-positive results as the primary reason for nonreferral. If a parent expressed concerns, referral probability doubled, and the rate of an ASD diagnosis increased by 37%. Of 897 toddlers evaluated, almost one-half were diagnosed as ASD, translating into an ASD prevalence of 1%. CONCLUSIONS The Get SET Early model was effective at detecting ASD and initiating very early treatment. Results also underscored the need for change in early identification approaches to formally operationalize and incorporate pediatrician judgment and level of parent concern into the process.
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Affiliation(s)
- Karen Pierce
- Department of Neurosciences, University of California, San Diego, La Jolla, CA.
| | - Vahid Gazestani
- Department of Neurosciences, University of California, San Diego, La Jolla, CA; Department of Pediatrics, University of California, San Diego, La Jolla, CA
| | - Elizabeth Bacon
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Eric Courchesne
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Amanda Cheng
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | | | - Srinivasa Nalabolu
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Debra Cha
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Steven Arias
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Linda Lopez
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Christie Pham
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Kim Gaines
- San Diego Regional Center, San Diego, CA
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18
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Kellman BP, Baghdassarian HM, Pramparo T, Shamie I, Gazestani V, Begzati A, Li S, Nalabolu S, Murray S, Lopez L, Pierce K, Courchesne E, Lewis NE. Multiple freeze-thaw cycles lead to a loss of consistency in poly(A)-enriched RNA sequencing. BMC Genomics 2021; 22:69. [PMID: 33478392 PMCID: PMC7818915 DOI: 10.1186/s12864-021-07381-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 01/08/2021] [Indexed: 11/10/2022] Open
Abstract
Background Both RNA-Seq and sample freeze-thaw are ubiquitous. However, knowledge about the impact of freeze-thaw on downstream analyses is limited. The lack of common quality metrics that are sufficiently sensitive to freeze-thaw and RNA degradation, e.g. the RNA Integrity Score, makes such assessments challenging. Results Here we quantify the impact of repeated freeze-thaw cycles on the reliability of RNA-Seq by examining poly(A)-enriched and ribosomal RNA depleted RNA-seq from frozen leukocytes drawn from a toddler Autism cohort. To do so, we estimate the relative noise, or percentage of random counts, separating technical replicates. Using this approach we measured noise associated with RIN and freeze-thaw cycles. As expected, RIN does not fully capture sample degradation due to freeze-thaw. We further examined differential expression results and found that three freeze-thaws should extinguish the differential expression reproducibility of similar experiments. Freeze-thaw also resulted in a 3′ shift in the read coverage distribution along the gene body of poly(A)-enriched samples compared to ribosomal RNA depleted samples, suggesting that library preparation may exacerbate freeze-thaw-induced sample degradation. Conclusion The use of poly(A)-enrichment for RNA sequencing is pervasive in library preparation of frozen tissue, and thus, it is important during experimental design and data analysis to consider the impact of repeated freeze-thaw cycles on reproducibility. Graphical abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07381-z.
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Affiliation(s)
- Benjamin P Kellman
- Department of Pediatrics, University of California, San Diego, USA.,Bioinformatics and Systems Biology Program, University of California San Diego, San Diego, USA
| | - Hratch M Baghdassarian
- Department of Pediatrics, University of California, San Diego, USA.,Bioinformatics and Systems Biology Program, University of California San Diego, San Diego, USA
| | - Tiziano Pramparo
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, San Diego, USA
| | - Isaac Shamie
- Department of Pediatrics, University of California, San Diego, USA.,Bioinformatics and Systems Biology Program, University of California San Diego, San Diego, USA
| | - Vahid Gazestani
- Department of Pediatrics, University of California, San Diego, USA.,Autism Center of Excellence, Department of Neuroscience, University of California San Diego, San Diego, USA
| | - Arjana Begzati
- Department of Medicine, University of California San Diego, San Diego, USA
| | - Shangzhong Li
- Department of Pediatrics, University of California, San Diego, USA.,Department of Bioengineering, University of California San Diego, San Diego, USA
| | - Srinivasa Nalabolu
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, San Diego, USA
| | - Sarah Murray
- Department of Pathology, University of California San Diego, San Diego, USA
| | - Linda Lopez
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, San Diego, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, San Diego, USA
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, San Diego, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, USA. .,Department of Bioengineering, University of California San Diego, San Diego, USA. .,Novo Nordisk Foundation Center for Biosustainability, University of California, San Diego, La Jolla, USA.
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19
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Wang T, Hoekzema K, Vecchio D, Wu H, Sulovari A, Coe BP, Gillentine MA, Wilfert AB, Perez-Jurado LA, Kvarnung M, Sleyp Y, Earl RK, Rosenfeld JA, Geisheker MR, Han L, Du B, Barnett C, Thompson E, Shaw M, Carroll R, Friend K, Catford R, Palmer EE, Zou X, Ou J, Li H, Guo H, Gerdts J, Avola E, Calabrese G, Elia M, Greco D, Lindstrand A, Nordgren A, Anderlid BM, Vandeweyer G, Van Dijck A, Van der Aa N, McKenna B, Hancarova M, Bendova S, Havlovicova M, Malerba G, Bernardina BD, Muglia P, van Haeringen A, Hoffer MJV, Franke B, Cappuccio G, Delatycki M, Lockhart PJ, Manning MA, Liu P, Scheffer IE, Brunetti-Pierri N, Rommelse N, Amaral DG, Santen GWE, Trabetti E, Sedláček Z, Michaelson JJ, Pierce K, Courchesne E, Kooy RF, Nordenskjöld M, Romano C, Peeters H, Bernier RA, Gecz J, Xia K, Eichler EE. Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders. Nat Commun 2020; 11:4932. [PMID: 33004838 PMCID: PMC7530681 DOI: 10.1038/s41467-020-18723-y] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 09/04/2020] [Indexed: 02/08/2023] Open
Abstract
Most genes associated with neurodevelopmental disorders (NDDs) were identified with an excess of de novo mutations (DNMs) but the significance in case-control mutation burden analysis is unestablished. Here, we sequence 63 genes in 16,294 NDD cases and an additional 62 genes in 6,211 NDD cases. By combining these with published data, we assess a total of 125 genes in over 16,000 NDD cases and compare the mutation burden to nonpsychiatric controls from ExAC. We identify 48 genes (25 newly reported) showing significant burden of ultra-rare (MAF < 0.01%) gene-disruptive mutations (FDR 5%), six of which reach family-wise error rate (FWER) significance (p < 1.25E-06). Among these 125 targeted genes, we also reevaluate DNM excess in 17,426 NDD trios with 6,499 new autism trios. We identify 90 genes enriched for DNMs (FDR 5%; e.g., GABRG2 and UIMC1); of which, 61 reach FWER significance (p < 3.64E-07; e.g., CASZ1). In addition to doubling the number of patients for many NDD risk genes, we present phenotype-genotype correlations for seven risk genes (CTCF, HNRNPU, KCNQ3, ZBTB18, TCF12, SPEN, and LEO1) based on this large-scale targeted sequencing effort.
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Affiliation(s)
- Tianyun Wang
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Davide Vecchio
- Rare Disease and Medical Genetics, Academic Department of Pediatrics, Bambino Gesù Children's Hospital, Rome, Italy
- Genetics and Rare Diseases Research Division, Bambino Gesù Children's Hospital, Rome, Italy
| | - Huidan Wu
- Center for Medical Genetics & Hunan Provincial Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Bradley P Coe
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Amy B Wilfert
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Luis A Perez-Jurado
- Paediatric and Reproductive Genetics unit, Women's and Children's Hospital, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
- Genetics Unit, Universitat Pompeu Fabra, Hospital del Mar Research Institute (IMIM) and CIBERER, Barcelona, Spain
| | - Malin Kvarnung
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Yoeri Sleyp
- Centre for Human Genetics, KU Leuven and Leuven Autism Research (LAuRes), Leuven, Belgium
| | - Rachel K Earl
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Jill A Rosenfeld
- Department of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Baylor Genetics, Houston, TX, USA
| | | | - Lin Han
- Center for Medical Genetics & Hunan Provincial Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Bing Du
- Center for Medical Genetics & Hunan Provincial Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Chris Barnett
- Paediatric and Reproductive Genetics unit, Women's and Children's Hospital, Adelaide, SA, Australia
- Adelaide Medical School and the Robinson Research Institute, the University of Adelaide, Adelaide, SA, Australia
| | - Elizabeth Thompson
- Paediatric and Reproductive Genetics unit, Women's and Children's Hospital, Adelaide, SA, Australia
| | - Marie Shaw
- Adelaide Medical School and the Robinson Research Institute, the University of Adelaide, Adelaide, SA, Australia
| | - Renee Carroll
- Adelaide Medical School and the Robinson Research Institute, the University of Adelaide, Adelaide, SA, Australia
| | - Kathryn Friend
- Genetics and Molecular Pathology, SA Pathology, Adelaide, SA, Australia
| | - Rachael Catford
- Genetics and Molecular Pathology, SA Pathology, Adelaide, SA, Australia
| | - Elizabeth E Palmer
- Genetics of Learning Disability Service, Hunter New England Health Service, Waratah, NSW, Australia
- School of Women's and Children's Health, University of New South Wales, Randwick, NSW, Australia
| | - Xiaobing Zou
- Children Development Behavior Center, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Jianjun Ou
- Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China
| | - Honghui Li
- Key Laboratory of Developmental Disorders in Children, Liuzhou Maternity and Child Healthcare Hospital, Liuzhou, China
| | - Hui Guo
- Center for Medical Genetics & Hunan Provincial Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Jennifer Gerdts
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | | | | | | | | | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Britt-Marie Anderlid
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Geert Vandeweyer
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | - Anke Van Dijck
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | | | - Brooke McKenna
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Miroslava Hancarova
- Department of Biology and Medical Genetics, Charles University 2nd Faculty of Medicine and University Hospital Motol, Prague, Czech Republic
| | - Sarka Bendova
- Department of Biology and Medical Genetics, Charles University 2nd Faculty of Medicine and University Hospital Motol, Prague, Czech Republic
| | - Marketa Havlovicova
- Department of Biology and Medical Genetics, Charles University 2nd Faculty of Medicine and University Hospital Motol, Prague, Czech Republic
| | - Giovanni Malerba
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | | | | | - Arie van Haeringen
- Department of Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Mariette J V Hoffer
- Department of Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Gerarda Cappuccio
- Department of Translational Medicine, Federico II University, Naples, Italy
- Telethon Institute of Genetics and Medicine, Pozzuoli, Naples, Italy
| | | | - Paul J Lockhart
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Melanie A Manning
- Division of Medical Genetics, Department of Pediatrics, Stanford University, Stanford, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Pengfei Liu
- Department of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Baylor Genetics, Houston, TX, USA
| | - Ingrid E Scheffer
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Royal Children's Hospital, Melbourne, VIC, Australia
- Department of Medicine, University of Melbourne, Austin Health, Melbourne, Australia
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Nicola Brunetti-Pierri
- Department of Translational Medicine, Federico II University, Naples, Italy
- Telethon Institute of Genetics and Medicine, Pozzuoli, Naples, Italy
| | - Nanda Rommelse
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
- Karakter Child and Adolescent Psychiatry Center, Nijmegen, Netherlands
| | - David G Amaral
- Department of Psychiatry and Behavioral Sciences and the MIND Institute, University of California, Davis, Sacramento, CA, USA
| | - Gijs W E Santen
- Department of Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Elisabetta Trabetti
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Zdeněk Sedláček
- Department of Biology and Medical Genetics, Charles University 2nd Faculty of Medicine and University Hospital Motol, Prague, Czech Republic
| | - Jacob J Michaelson
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Karen Pierce
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine, University of California San Diego, La Jolla, CA, USA
| | - R Frank Kooy
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | - Magnus Nordenskjöld
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Hilde Peeters
- Centre for Human Genetics, KU Leuven and Leuven Autism Research (LAuRes), Leuven, Belgium
| | - Raphael A Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Jozef Gecz
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
- Adelaide Medical School and the Robinson Research Institute, the University of Adelaide, Adelaide, SA, Australia
- Genetics and Molecular Pathology, SA Pathology, Adelaide, SA, Australia
| | - Kun Xia
- Center for Medical Genetics & Hunan Provincial Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
- CAS Center for Excellence in Brain Science and Intelligences Technology (CEBSIT), Chinese Academy of Sciences, Shanghai, China
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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20
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Courchesne E, Gazestani VH, Lewis NE. Prenatal Origins of ASD: The When, What, and How of ASD Development. Trends Neurosci 2020; 43:326-342. [PMID: 32353336 PMCID: PMC7373219 DOI: 10.1016/j.tins.2020.03.005] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 01/28/2020] [Accepted: 03/04/2020] [Indexed: 02/08/2023]
Abstract
Autism spectrum disorder (ASD) is a largely heritable, multistage prenatal disorder that impacts a child's ability to perceive and react to social information. Most ASD risk genes are expressed prenatally in many ASD-relevant brain regions and fall into two categories: broadly expressed regulatory genes that are expressed in the brain and other organs, and brain-specific genes. In trimesters one to three (Epoch-1), one set of broadly expressed (the majority) and brain-specific risk genes disrupts cell proliferation, neurogenesis, migration, and cell fate, while in trimester three and early postnatally (Epoch-2) another set (the majority being brain specific) disrupts neurite outgrowth, synaptogenesis, and the 'wiring' of the cortex. A proposed model is that upstream, highly interconnected regulatory ASD gene mutations disrupt transcriptional programs or signaling pathways resulting in dysregulation of downstream processes such as proliferation, neurogenesis, synaptogenesis, and neural activity. Dysregulation of signaling pathways is correlated with ASD social symptom severity. Since the majority of ASD risk genes are broadly expressed, many ASD individuals may benefit by being treated as having a broader medical disorder. An important future direction is the noninvasive study of ASD cell biology.
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Affiliation(s)
- Eric Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA 92093, USA; Autism Center of Excellence, University of California, San Diego, San Diego, CA 92037, USA.
| | - Vahid H Gazestani
- Department of Neuroscience, University of California, San Diego, San Diego, CA 92093, USA; Autism Center of Excellence, University of California, San Diego, San Diego, CA 92037, USA; Department of Pediatrics, University of California, San Diego, San Diego, CA 92093, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, San Diego, CA 92093, USA; Department of Bioengineering, University of California, San Diego, San Diego, CA 92093, USA
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21
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Abstract
While many children with autism spectrum disorder are now detected at young ages given the rise in screening and general awareness, little is known regarding the prognosis of early detected children. The brain is shaped by experience-dependent mechanisms; thus, what a child pays attention to plays a pivotal role in shaping brain development. Eye tracking can provide an index of a child's visual attention and, as such, holds promise as a technology for revealing prognostic markers. In this, 49 children aged 1-3 years with autism spectrum disorder participated in an eye-tracking test, the GeoPref Test, that revealed preference for social versus nonsocial images. Next, children participated in a comprehensive test battery 5-9 years following the initial GeoPref Test. Statistical tests examined whether early age eye tracking predicted later school-age outcomes in symptom severity, social functioning, adaptive behavior, joint attention, and IQ. Results indicated that toddlers with higher preference for geometric images demonstrated greater symptom severity and fewer gaze shifts at school age. This relationship was not found in relation to IQ or adaptive behavior. Overall, the GeoPref Test holds promise as a symptom severity prognostic tool; further development of eye-tracking paradigms may enhance prognostic power and prove valuable in validating treatment progress.
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22
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Lombardo MV, Eyler L, Moore A, Datko M, Carter Barnes C, Cha D, Courchesne E, Pierce K. Default mode-visual network hypoconnectivity in an autism subtype with pronounced social visual engagement difficulties. eLife 2019; 8:47427. [PMID: 31843053 PMCID: PMC6917498 DOI: 10.7554/elife.47427] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Accepted: 11/08/2019] [Indexed: 12/17/2022] Open
Abstract
Social visual engagement difficulties are hallmark early signs of autism (ASD) and are easily quantified using eye tracking methods. However, it is unclear how these difficulties are linked to atypical early functional brain organization in ASD. With resting state fMRI data in a large sample of ASD toddlers and other non-ASD comparison groups, we find ASD-related functional hypoconnnectivity between ‘social brain’ circuitry such as the default mode network (DMN) and visual and attention networks. An eye tracking-identified ASD subtype with pronounced early social visual engagement difficulties (GeoPref ASD) is characterized by marked DMN-occipito-temporal cortex (OTC) hypoconnectivity. Increased DMN-OTC hypoconnectivity is also related to increased severity of social-communication difficulties, but only in GeoPref ASD. Early and pronounced social-visual circuit hypoconnectivity is a key underlying neurobiological feature describing GeoPref ASD and may be critical for future social-communicative development and represent new treatment targets for early intervention in these individuals. Many parents of children with autism spectrum disorder (ASD) spot the first signs when their child is still a toddler, by noticing that their child is less interested than other toddlers in people and in social play. These early differences in behavior can have long-term implications for brain development. The brains of toddlers with little interest in social stimuli will receive less social input than those of other toddlers. This will make it even harder for the brain to develop the circuits required to support social skills. But even among children with ASD, there are large differences in children's interest in the social world. One way of measuring these differences is to track eye movements. Lombardo et al. presented toddlers with and without ASD with images of moving colorful geometric shapes next to videos of dancing children. The majority of toddlers, including most of those with ASD, spent more time looking at the children than the shapes. But about 20% of the toddlers with ASD spent most of their time looking at the shapes. These toddlers also had the most severe social symptoms. To find out why, Lombardo et al. measured the toddlers' brain activity while they slept. During sleep, or when at rest, the brain shows stereotyped patterns of activity. Groups of brain regions that work together – such as those involved in vision – fire in synchrony. Lombardo et al. found that toddlers who preferred looking at shapes over people showed different patterns of brain activity while asleep compared to other children. In the toddlers who preferred shapes, brain networks involved in social skills were less likely to coordinate their activity with networks that support vision and attention. These findings suggest there may be multiple subtypes of ASD, with different symptoms resulting from different patterns of brain activity. At present, all children who receive a diagnosis of ASD receive much the same behavioral therapy. But in the future, studies of brain networks could allow children to receive more specific diagnoses. This could in turn lead to more effective and personalized treatments.
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Affiliation(s)
- Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.,Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Lisa Eyler
- Department of Psychiatry, University of California, San Diego, San Diego, United States.,VISN 22 Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego, United States
| | - Adrienne Moore
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, San Diego, United States
| | - Michael Datko
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, San Diego, United States
| | - Cynthia Carter Barnes
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, San Diego, United States
| | - Debra Cha
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, San Diego, United States
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, San Diego, United States
| | - Karen Pierce
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, San Diego, United States
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23
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Gazestani VH, Pramparo T, Nalabolu S, Kellman BP, Murray S, Lopez L, Pierce K, Courchesne E, Lewis NE. A perturbed gene network containing PI3K-AKT, RAS-ERK and WNT-β-catenin pathways in leukocytes is linked to ASD genetics and symptom severity. Nat Neurosci 2019; 22:1624-1634. [PMID: 31551593 PMCID: PMC6764590 DOI: 10.1038/s41593-019-0489-x] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Accepted: 08/07/2019] [Indexed: 12/14/2022]
Abstract
Hundreds of genes are implicated in autism spectrum disorder (ASD) but the mechanisms through which they contribute to ASD pathophysiology remain elusive. Here, we analyzed leukocyte transcriptomics from 1–4 year-old male toddlers with ASD or typical development from the general population. We discovered a perturbed gene network that includes genes that are highly expressed during fetal brain development and which is dysregulated in hiPSC-derived neuron models of ASD. High-confidence ASD risk genes emerge as upstream regulators of the network, and many risk genes may impact the network by modulating RAS/ERK, PI3K/AKT, and WNT/β-catenin signaling pathways. We found that the degree of dysregulation in this network correlated with the severity of ASD symptoms in the toddlers. These results demonstrate how the heterogeneous genetics of ASD may dysregulate a core network to influence brain development at prenatal and very early postnatal ages and, thereby, the severity of later ASD symptoms.
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Affiliation(s)
- Vahid H Gazestani
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA.,Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Novo Nordisk Foundation Center for Biosustainability, University of California San Diego, La Jolla, CA, USA
| | - Tiziano Pramparo
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Srinivasa Nalabolu
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Benjamin P Kellman
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | - Sarah Murray
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Linda Lopez
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA.
| | - Nathan E Lewis
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA. .,Novo Nordisk Foundation Center for Biosustainability, University of California San Diego, La Jolla, CA, USA. .,Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA. .,Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
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24
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Pierce K, Gazestani VH, Bacon E, Barnes CC, Cha D, Nalabolu S, Lopez L, Moore A, Pence-Stophaeros S, Courchesne E. Evaluation of the Diagnostic Stability of the Early Autism Spectrum Disorder Phenotype in the General Population Starting at 12 Months. JAMA Pediatr 2019; 173:578-587. [PMID: 31034004 PMCID: PMC6547081 DOI: 10.1001/jamapediatrics.2019.0624] [Citation(s) in RCA: 160] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Universal early screening for autism spectrum disorder (ASD) in primary care is becoming increasingly common and is believed to be a pivotal step toward early treatment. However, the diagnostic stability of ASD in large cohorts from the general population, particularly in those younger than 18 months, is unknown. Changes in the phenotypic expression of ASD across early development compared with toddlers with other delays are also unknown. OBJECTIVES To examine the diagnostic stability of ASD in a large cohort of toddlers starting at 12 months of age and to compare this stability with that of toddlers with other disorders, such as developmental delay. DESIGN, SETTING, AND PARTICIPANTS In this prospective cohort study performed from January 1, 2006, to December 31, 2018, a total of 2241 toddlers were referred from the general population through a universal screening program in primary care or community referral. Eligible toddlers received their first diagnostic evaluation between 12 and 36 months of age and had at least 1 subsequent evaluation. EXPOSURES Diagnosis was denoted after each evaluation visit as ASD, ASD features, language delay, developmental delay, other developmental issue, typical sibling of an ASD proband, or typical development. MAIN OUTCOMES AND MEASURES Diagnostic stability coefficients were calculated within 2-month age bands, and logistic regression models were used to explore the associations of sex, age, diagnosis at first visit, and interval between first and last diagnosis with stability. Toddlers with a non-ASD diagnosis at their first visit diagnosed with ASD at their last were designated as having late-identified ASD. RESULTS Among the 1269 toddlers included in the study (918 [72.3%] male; median age at first evaluation, 17.6 months [interquartile range, 14.0-24.4 months]; median age at final evaluation, 36.2 months [interquartile range, 33.4-40.9 months]), the overall diagnostic stability for ASD was 0.84 (95% CI, 0.80-0.87), which was higher than any other diagnostic group. Only 7 toddlers (1.8%) initially considered to have ASD transitioned into a final diagnosis of typical development. Diagnostic stability of ASD within the youngest age band (12-13 months) was lowest at 0.50 (95% CI, 0.32-0.69) but increased to 0.79 by 14 months and 0.83 by 16 months (age bands of 12 vs 14 and 16 months; odds ratio, 4.25; 95% CI, 1.59-11.74). A total of 105 toddlers (23.8%) were not designated as having ASD at their first visit but were identified at a later visit. CONCLUSIONS AND RELEVANCE The findings suggest that an ASD diagnosis becomes stable starting at 14 months of age and overall is more stable than other diagnostic categories, including language or developmental delay. After a toddler is identified as having ASD, there may be a low chance that he or she will test within typical levels at 3 years of age. This finding opens the opportunity to test the impact of very early-age treatment of ASD.
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Affiliation(s)
- Karen Pierce
- Department of Neurosciences, University of California, San Diego, La Jolla
| | - Vahid H. Gazestani
- Department of Neurosciences, University of California, San Diego, La Jolla,Department of Pediatrics, University of California, San Diego, La Jolla
| | - Elizabeth Bacon
- Department of Neurosciences, University of California, San Diego, La Jolla
| | | | - Debra Cha
- Department of Neurosciences, University of California, San Diego, La Jolla
| | - Srinivasa Nalabolu
- Department of Neurosciences, University of California, San Diego, La Jolla
| | - Linda Lopez
- Department of Neurosciences, University of California, San Diego, La Jolla
| | - Adrienne Moore
- Department of Neurosciences, University of California, San Diego, La Jolla
| | | | - Eric Courchesne
- Department of Neurosciences, University of California, San Diego, La Jolla
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25
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Courchesne E, Pramparo T, Gazestani VH, Lombardo MV, Pierce K, Lewis NE. The ASD Living Biology: from cell proliferation to clinical phenotype. Mol Psychiatry 2019; 24:88-107. [PMID: 29934544 PMCID: PMC6309606 DOI: 10.1038/s41380-018-0056-y] [Citation(s) in RCA: 128] [Impact Index Per Article: 25.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2017] [Revised: 02/08/2018] [Accepted: 02/19/2018] [Indexed: 12/17/2022]
Abstract
Autism spectrum disorder (ASD) has captured the attention of scientists, clinicians and the lay public because of its uncertain origins and striking and unexplained clinical heterogeneity. Here we review genetic, genomic, cellular, postmortem, animal model, and cell model evidence that shows ASD begins in the womb. This evidence leads to a new theory that ASD is a multistage, progressive disorder of brain development, spanning nearly all of prenatal life. ASD can begin as early as the 1st and 2nd trimester with disruption of cell proliferation and differentiation. It continues with disruption of neural migration, laminar disorganization, altered neuron maturation and neurite outgrowth, disruption of synaptogenesis and reduced neural network functioning. Among the most commonly reported high-confidence ASD (hcASD) genes, 94% express during prenatal life and affect these fetal processes in neocortex, amygdala, hippocampus, striatum and cerebellum. A majority of hcASD genes are pleiotropic, and affect proliferation/differentiation and/or synapse development. Proliferation and subsequent fetal stages can also be disrupted by maternal immune activation in the 1st trimester. Commonly implicated pathways, PI3K/AKT and RAS/ERK, are also pleiotropic and affect multiple fetal processes from proliferation through synapse and neural functional development. In different ASD individuals, variation in how and when these pleiotropic pathways are dysregulated, will lead to different, even opposing effects, producing prenatal as well as later neural and clinical heterogeneity. Thus, the pathogenesis of ASD is not set at one point in time and does not reside in one process, but rather is a cascade of prenatal pathogenic processes in the vast majority of ASD toddlers. Despite this new knowledge and theory that ASD biology begins in the womb, current research methods have not provided individualized information: What are the fetal processes and early-age molecular and cellular differences that underlie ASD in each individual child? Without such individualized knowledge, rapid advances in biological-based diagnostic, prognostic, and precision medicine treatments cannot occur. Missing, therefore, is what we call ASD Living Biology. This is a conceptual and paradigm shift towards a focus on the abnormal prenatal processes underlying ASD within each living individual. The concept emphasizes the specific need for foundational knowledge of a living child's development from abnormal prenatal beginnings to early clinical stages. The ASD Living Biology paradigm seeks this knowledge by linking genetic and in vitro prenatal molecular, cellular and neural measurements with in vivo post-natal molecular, neural and clinical presentation and progression in each ASD child. We review the first such study, which confirms the multistage fetal nature of ASD and provides the first in vitro fetal-stage explanation for in vivo early brain overgrowth. Within-child ASD Living Biology is a novel research concept we coin here that advocates the integration of in vitro prenatal and in vivo early post-natal information to generate individualized and group-level explanations, clinically useful prognoses, and precision medicine approaches that are truly beneficial for the individual infant and toddler with ASD.
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Affiliation(s)
- Eric Courchesne
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA, 92037, USA.
| | - Tiziano Pramparo
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA, 92037, USA
| | - Vahid H Gazestani
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA, 92037, USA
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA
| | - Michael V Lombardo
- Department of Psychology, Center for Applied Neuroscience, University of Cyprus, Nicosia, Cyprus
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Karen Pierce
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA, 92037, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA
- Novo Nordisk Foundation Center for Biosustainability at University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA
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26
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Lombardo MV, Pramparo T, Gazestani V, Warrier V, Bethlehem RAI, Carter Barnes C, Lopez L, Lewis NE, Eyler L, Pierce K, Courchesne E. Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes. Nat Neurosci 2018; 21:1680-1688. [PMID: 30482947 PMCID: PMC6445349 DOI: 10.1038/s41593-018-0281-3] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 10/24/2018] [Indexed: 12/21/2022]
Abstract
Heterogeneity in early language development in autism spectrum disorders (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here we identify a large-scale association between multiple coordinated blood leukocyte gene co-expression modules and multivariate functional neuroimaging (fMRI) response to speech. Gene co-expression modules associated with multivariate fMRI response to speech are different for all pairwise comparisons between typically developing toddlers and toddlers with ASD and either poor versus good early language outcome. Associated co-expression modules are enriched in genes that are broadly expressed in the brain and many other tissues. These co-expression modules are also enriched for ASD, prenatal, human-specific and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known. Associations between neuroimaging measures and gene expression levels in blood leukocytes may offer a unique in-vivo window into identifying brain-relevant molecular mechanisms in ASD.
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Affiliation(s)
- Michael V Lombardo
- Department of Psychology, University of Cyprus, Nicosia, Cyprus. .,Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - Tiziano Pramparo
- Department of Neuroscience, University of California, San Diego, La Jolla, CA, USA
| | - Vahid Gazestani
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Varun Warrier
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Richard A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Linda Lopez
- Department of Neuroscience, University of California, San Diego, La Jolla, CA, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.,Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.,Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, La Jolla, CA, USA
| | - Lisa Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.,Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Karen Pierce
- Department of Neuroscience, University of California, San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Department of Neuroscience, University of California, San Diego, La Jolla, CA, USA.
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Brandler WM, Antaki D, Gujral M, Kleiber ML, Whitney J, Maile MS, Hong O, Chapman TR, Tan S, Tandon P, Pang T, Tang SC, Vaux KK, Yang Y, Harrington E, Juul S, Turner DJ, Thiruvahindrapuram B, Kaur G, Wang Z, Kingsmore SF, Gleeson JG, Bisson D, Kakaradov B, Telenti A, Venter JC, Corominas R, Toma C, Cormand B, Rueda I, Guijarro S, Messer KS, Nievergelt CM, Arranz MJ, Courchesne E, Pierce K, Muotri AR, Iakoucheva LM, Hervas A, Scherer SW, Corsello C, Sebat J. Paternally inherited cis-regulatory structural variants are associated with autism. Science 2018; 360:327-331. [PMID: 29674594 DOI: 10.1126/science.aan2261] [Citation(s) in RCA: 137] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 08/07/2017] [Accepted: 02/27/2018] [Indexed: 12/15/2022]
Abstract
The genetic basis of autism spectrum disorder (ASD) is known to consist of contributions from de novo mutations in variant-intolerant genes. We hypothesize that rare inherited structural variants in cis-regulatory elements (CRE-SVs) of these genes also contribute to ASD. We investigated this by assessing the evidence for natural selection and transmission distortion of CRE-SVs in whole genomes of 9274 subjects from 2600 families affected by ASD. In a discovery cohort of 829 families, structural variants were depleted within promoters and untranslated regions, and paternally inherited CRE-SVs were preferentially transmitted to affected offspring and not to their unaffected siblings. The association of paternal CRE-SVs was replicated in an independent sample of 1771 families. Our results suggest that rare inherited noncoding variants predispose children to ASD, with differing contributions from each parent.
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Affiliation(s)
- William M Brandler
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA.,Human Longevity, Inc., San Diego, CA 92121, USA
| | - Danny Antaki
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA.,Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA 92093, USA
| | - Madhusudan Gujral
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | - Morgan L Kleiber
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | - Joe Whitney
- The Centre for Applied Genomics, Genetics, and Genome Biology, The Hospital for Sick Children, Toronto, Canada
| | - Michelle S Maile
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | - Oanh Hong
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | - Timothy R Chapman
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | - Shirley Tan
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | - Prateek Tandon
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | - Timothy Pang
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Rady Children's Hospital, San Diego, CA 92123, USA
| | - Shih C Tang
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA.,Rady Children's Hospital, San Diego, CA 92123, USA
| | - Keith K Vaux
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Yan Yang
- Oxford Nanopore Technologies, Inc., NY 10013, USA
| | | | - Sissel Juul
- Oxford Nanopore Technologies, Inc., NY 10013, USA
| | | | - Bhooma Thiruvahindrapuram
- The Centre for Applied Genomics, Genetics, and Genome Biology, The Hospital for Sick Children, Toronto, Canada
| | - Gaganjot Kaur
- The Centre for Applied Genomics, Genetics, and Genome Biology, The Hospital for Sick Children, Toronto, Canada
| | - Zhuozhi Wang
- The Centre for Applied Genomics, Genetics, and Genome Biology, The Hospital for Sick Children, Toronto, Canada
| | - Stephen F Kingsmore
- Rady Children's Institute for Genomic Medicine, Rady Children's Hospital, San Diego, CA 92123, USA
| | - Joseph G Gleeson
- Howard Hughes Medical Institute, Rady Children's Institute of Genomic Medicine, Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | | | | | | | - J Craig Venter
- Human Longevity, Inc., San Diego, CA 92121, USA.,J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Roser Corominas
- Genetics Unit, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Spain
| | - Claudio Toma
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Catalonia, Spain.,Neuroscience Research Australia, Sydney, Australia.,School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Bru Cormand
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Spain.,Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Catalonia, Spain.,Institut de Biomedicina de la Universitat de Barcelona (IBUB), Catalonia, Spain.,Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues, Catalonia, Spain
| | - Isabel Rueda
- Department of Psychiatry, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Silvina Guijarro
- Child and Adolescent Mental Health Unit, Hospital Universitari Mútua de Terrassa, Barcelona, Spain
| | - Karen S Messer
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA 92093, USA
| | - Caroline M Nievergelt
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Maria J Arranz
- Research Laboratory Unit, Fundacio Docencia I Recerca Mutua Terrassa, Barcelona, Spain
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA 92093, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA 92093, USA
| | - Alysson R Muotri
- Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
| | - Lilia M Iakoucheva
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Amaia Hervas
- Child and Adolescent Mental Health Unit, Hospital Universitari Mútua de Terrassa, Barcelona, Spain
| | - Stephen W Scherer
- The Centre for Applied Genomics, Genetics, and Genome Biology, The Hospital for Sick Children, Toronto, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Canada.,McLaughlin Centre, University of Toronto, Toronto, Canada
| | - Christina Corsello
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Rady Children's Hospital, San Diego, CA 92123, USA
| | - Jonathan Sebat
- Beyster Center for Genomics of Psychiatric Diseases, University of California San Diego, La Jolla, CA 92093, USA. .,Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.,Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
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Bacon EC, Osuna S, Courchesne E, Pierce K. Naturalistic language sampling to characterize the language abilities of 3-year-olds with autism spectrum disorder. Autism 2018; 23:699-712. [PMID: 29754501 DOI: 10.1177/1362361318766241] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Characterization of language in naturalistic settings in autism spectrum disorder has been lacking, particularly at young ages, but such information is important for parents, teachers, and clinicians to better support language development in real-world settings. Factors contributing to this lack of clarity include conflicting definitions of language abilities, use of non-naturalistic standardized assessments, and restricted samples. The current study examined one of the largest datasets of naturalistic language samples in toddlers with autism spectrum disorder, and language delay and typically developing contrast groups at age 3. A range of indices including length of phrase, grammatical markings, and social use of language was assayed during a naturalistic observation of a parent-child play session. In contrast to historical estimates, results indicated only 3.7% of children with autism spectrum disorder used no words, and 34% were minimally verbal. Children with autism spectrum disorder and language delay exhibited similar usage of grammatical markings, although both were reduced compared to typically developing children. The greatest difference between autism spectrum disorder and language delay groups was the quantity of social language. Overall, findings highlight a range of language deficits in autism spectrum disorder, but also illustrate that the most severe level of impairments is not as common in naturalistic settings as previously estimated by standardized assessments.
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Abstract
A common theory of autism spectrum disorder (ASD) symptom onset includes toddlers who do not display symptoms until well after age 2, which are termed late-onset ASD cases. Objectives were to analyze differences in clinical phenotype between toddlers identified as ASD at initial evaluations (early diagnosed) versus those initially considered nonspectrum, then later identified as ASD (late diagnosed). Two hundred seventy-three toddlers recruited from the general population based on a failed developmental screening form or parent or physician concerns were followed longitudinally from 12 months and identified as early- and late-diagnosed cases of ASD, language delayed, or typically developing. Toddlers completed common standardized assessments and experimental eye-tracking and observational measures every 9-12 months until age 3. Longitudinal performance on standardized assessments and experimental tests from initial evaluations were compared. Delay in social communication skills was seen in both ASD groups at early-age initial assessment, including increased preference for nonsocial stimuli, increased stereotypic play, reduced exploration, and use of gestures. On standardized psychometric assessments, early-diagnosed toddlers showed more impairment initially while late-diagnosed toddlers showed a slowing in language acquisition. Similar social communication impairments were present at very early ages in both early-detected ASD and so-called late-onset ASD. Data indicate ASD is present whether detected or not by current methods, and development of more sensitive tools is needed.
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Lombardo MV, Moon HM, Su J, Palmer TD, Courchesne E, Pramparo T. Maternal immune activation dysregulation of the fetal brain transcriptome and relevance to the pathophysiology of autism spectrum disorder. Mol Psychiatry 2018; 23:1001-1013. [PMID: 28322282 PMCID: PMC5608645 DOI: 10.1038/mp.2017.15] [Citation(s) in RCA: 110] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2016] [Revised: 12/31/2016] [Accepted: 01/09/2017] [Indexed: 12/12/2022]
Abstract
Maternal immune activation (MIA) via infection during pregnancy is known to increase risk for autism spectrum disorder (ASD). However, it is unclear how MIA disrupts fetal brain gene expression in ways that may explain this increased risk. Here we examine how MIA dysregulates rat fetal brain gene expression (at a time point analogous to the end of the first trimester of human gestation) in ways relevant to ASD-associated pathophysiology. MIA downregulates expression of ASD-associated genes, with the largest enrichments in genes known to harbor rare highly penetrant mutations. MIA also downregulates expression of many genes also known to be persistently downregulated in the ASD cortex later in life and which are canonically known for roles in affecting prenatally late developmental processes at the synapse. Transcriptional and translational programs that are downstream targets of highly ASD-penetrant FMR1 and CHD8 genes are also heavily affected by MIA. MIA strongly upregulates expression of a large number of genes involved in translation initiation, cell cycle, DNA damage and proteolysis processes that affect multiple key neural developmental functions. Upregulation of translation initiation is common to and preserved in gene network structure with the ASD cortical transcriptome throughout life and has downstream impact on cell cycle processes. The cap-dependent translation initiation gene, EIF4E, is one of the most MIA-dysregulated of all ASD-associated genes and targeted network analyses demonstrate prominent MIA-induced transcriptional dysregulation of mTOR and EIF4E-dependent signaling. This dysregulation of translation initiation via alteration of the Tsc2-mTor-Eif4e axis was further validated across MIA rodent models. MIA may confer increased risk for ASD by dysregulating key aspects of fetal brain gene expression that are highly relevant to pathophysiology affecting ASD.
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Affiliation(s)
- M V Lombardo
- Center for Applied Neuroscience, Department of Psychology, University of Cyprus, Nicosia, Cyprus,Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK,Neuroscience University of California, San Diego, 8110 La Jolla Shores Drive Suite 201, La Jolla, CA 92093, USA. E-mail: or
| | - H M Moon
- Department of Neurosurgery, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - J Su
- Department of Neurosurgery, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - T D Palmer
- Department of Neurosurgery, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - E Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
| | - T Pramparo
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA,Neuroscience University of California, San Diego, 8110 La Jolla Shores Drive Suite 201, La Jolla, CA 92093, USA. E-mail: or
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31
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Moore A, Wozniak M, Yousef A, Barnes CC, Cha D, Courchesne E, Pierce K. The geometric preference subtype in ASD: identifying a consistent, early-emerging phenomenon through eye tracking. Mol Autism 2018; 9:19. [PMID: 29581878 PMCID: PMC5861622 DOI: 10.1186/s13229-018-0202-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Accepted: 03/02/2018] [Indexed: 01/11/2023] Open
Abstract
Background The wide range of ability and disability in ASD creates a need for tools that parse the phenotypic heterogeneity into meaningful subtypes. Using eye tracking, our past studies revealed that when presented with social and geometric images, a subset of ASD toddlers preferred viewing geometric images, and these toddlers also had greater symptom severity than ASD toddlers with greater social attention. This study tests whether this "GeoPref test" effect would generalize across different social stimuli. Methods Two hundred and twenty-seven toddlers (76 ASD) watched a 90-s video, the Complex Social GeoPref test, of dynamic geometric images paired with social images of children interacting and moving. Proportion of visual fixation time and number of saccades per second to both images were calculated. To allow for cross-paradigm comparisons, a subset of 126 toddlers also participated in the original GeoPref test. Measures of cognitive and social functioning (MSEL, ADOS, VABS) were collected and related to eye tracking data. To examine utility as a diagnostic indicator to detect ASD toddlers, validation statistics (e.g., sensitivity, specificity, ROC, AUC) were calculated for the Complex Social GeoPref test alone and when combined with the original GeoPref test. Results ASD toddlers spent a significantly greater amount of time viewing geometric images than any other diagnostic group. Fixation patterns from ASD toddlers who participated in both tests revealed a significant correlation, supporting the idea that these tests identify a phenotypically meaningful ASD subgroup. Combined use of both original and Complex Social GeoPref tests identified a subgroup of about 1 in 3 ASD toddlers from the "GeoPref" subtype (sensitivity 35%, specificity 94%, AUC 0.75.) Replicating our previous studies, more time looking at geometric images was associated with significantly greater ADOS symptom severity. Conclusions Regardless of the complexity of the social images used (low in the original GeoPref test vs high in the new Complex Social GeoPref test), eye tracking of toddlers can accurately identify a specific ASD "GeoPref" subtype with elevated symptom severity. The GeoPref tests are predictive of ASD at the individual subject level and thus potentially useful for various clinical applications (e.g., early identification, prognosis, or development of subtype-specific treatments).
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Affiliation(s)
- Adrienne Moore
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla, CA USA
| | - Madeline Wozniak
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla, CA USA
| | - Andrew Yousef
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla, CA USA
| | - Cindy Carter Barnes
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla, CA USA
| | - Debra Cha
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla, CA USA
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla, CA USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neurosciences, University of California San Diego, La Jolla, CA USA
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32
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Geisheker MR, Heymann G, Wang T, Coe BP, Turner TN, Stessman HA, Hoekzema K, Kvarnung M, Shaw M, Friend K, Liebelt J, Barnett C, Thompson EM, Haan E, Guo H, Anderlid BM, Nordgren A, Lindstrand A, Vandeweyer G, Alberti A, Avola E, Vinci M, Giusto S, Pramparo T, Pierce K, Nalabolu S, Michaelson JJ, Sedlacek Z, Santen GW, Peeters H, Hakonarson H, Courchesne E, Romano C, Kooy RF, Bernier RA, Nordenskjöld M, Gecz J, Xia K, Zweifel LS, Eichler EE. Hotspots of missense mutation identify neurodevelopmental disorder genes and functional domains. Nat Neurosci 2017; 20:1043-1051. [PMID: 28628100 PMCID: PMC5539915 DOI: 10.1038/nn.4589] [Citation(s) in RCA: 116] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 05/19/2017] [Indexed: 12/17/2022]
Abstract
Although de novo missense mutations have been predicted to account for more cases of autism than gene-truncating mutations, most research has focused on the latter. We identified the properties of de novo missense mutations in patients with neurodevelopmental disorders (NDDs) and highlight 35 genes with excess missense mutations. Additionally, 40 amino acid sites were recurrently mutated in 36 genes, and targeted sequencing of 20 sites in 17,688 patients with NDD identified 21 new patients with identical missense mutations. One recurrent site substitution (p.A636T) occurs in a glutamate receptor subunit, GRIA1. This same amino acid substitution in the homologous but distinct mouse glutamate receptor subunit Grid2 is associated with Lurcher ataxia. Phenotypic follow-up in five individuals with GRIA1 mutations shows evidence of specific learning disabilities and autism. Overall, we find significant clustering of de novo mutations in 200 genes, highlighting specific functional domains and synaptic candidate genes important in NDD pathology.
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Affiliation(s)
| | - Gabriel Heymann
- Department of Pharmacology, University of Washington, Seattle, Washington, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, USA
| | - Tianyun Wang
- The State Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Bradley P. Coe
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Tychele N. Turner
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Holly A.F. Stessman
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Malin Kvarnung
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Marie Shaw
- Robinson Research Institute and the University of Adelaide at the Women’s and Children’s Hospital, North Adelaide, South Australia, Australia
| | - Kathryn Friend
- Robinson Research Institute and the University of Adelaide at the Women’s and Children’s Hospital, North Adelaide, South Australia, Australia
- SA Pathology, Adelaide, South Australia, Australia
| | - Jan Liebelt
- South Australian Clinical Genetics Service, SA Pathology (at Women’s and Children’s Hospital), Adelaide, South Australia, Australia
| | - Christopher Barnett
- South Australian Clinical Genetics Service, SA Pathology (at Women’s and Children’s Hospital), Adelaide, South Australia, Australia
- School of Paediatrics and Reproductive Health, University of Adelaide, Adelaide, South Australia, Australia
| | - Elizabeth M. Thompson
- South Australian Clinical Genetics Service, SA Pathology (at Women’s and Children’s Hospital), Adelaide, South Australia, Australia
- School of Medicine, University of Adelaide, Adelaide, South Australia, Australia
| | - Eric Haan
- South Australian Clinical Genetics Service, SA Pathology (at Women’s and Children’s Hospital), Adelaide, South Australia, Australia
- School of Medicine, University of Adelaide, Adelaide, South Australia, Australia
| | - Hui Guo
- The State Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Britt-Marie Anderlid
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Geert Vandeweyer
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | - Antonino Alberti
- Unit of Pediatrics & Medical Genetics, IRCCS Associazione Oasi Maria Santissima, Troina, Italy
| | - Emanuela Avola
- Unit of Pediatrics & Medical Genetics, IRCCS Associazione Oasi Maria Santissima, Troina, Italy
| | - Mirella Vinci
- Laboratory of Medical Genetics, IRCCS Associazione Oasi Maria Santissima, Troina, Italy
| | - Stefania Giusto
- Unit of Neurology, IRCCS Associazione Oasi Maria Santissima, Troina, Italy
| | - Tiziano Pramparo
- University of California, San Diego, Autism Center of Excellence, La Jolla, California, USA
| | - Karen Pierce
- University of California, San Diego, Autism Center of Excellence, La Jolla, California, USA
| | - Srinivasa Nalabolu
- University of California, San Diego, Autism Center of Excellence, La Jolla, California, USA
| | | | - Zdenek Sedlacek
- Department of Biology and Medical Genetics, Charles University 2nd Faculty of Medicine and University Hospital Motol, Prague, Czech Republic
| | - Gijs W.E. Santen
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Hilde Peeters
- Centre for Human Genetics, KU Leuven and Leuven Autism Research, Leuven, Belgium
| | - Hakon Hakonarson
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Division of Genetics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Eric Courchesne
- University of California, San Diego, Autism Center of Excellence, La Jolla, California, USA
| | - Corrado Romano
- Unit of Pediatrics & Medical Genetics, IRCCS Associazione Oasi Maria Santissima, Troina, Italy
| | - R. Frank Kooy
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | - Raphael A. Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, USA
| | - Magnus Nordenskjöld
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Jozef Gecz
- Robinson Research Institute and the University of Adelaide at the Women’s and Children’s Hospital, North Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Kun Xia
- The State Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Larry S. Zweifel
- Department of Pharmacology, University of Washington, Seattle, Washington, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
- Howard Hughes Medical Institute, Seattle, Washington, USA
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33
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Abstract
Background Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology. Methods Two ASD cortical transcriptome datasets were re-analyzed using consensus weighted gene co-expression network analysis (WGCNA) to identify common co-expression modules across datasets. Linear mixed-effect models and Bayesian replication statistics were used to identify replicable differentially expressed modules. Eigengene network analysis was then utilized to identify between-group differences in how co-expression modules interact and cluster into hierarchical meta-modular organization. Protein-protein interaction analyses were also used to determine whether dysregulated co-expression modules show enhanced interactions. Results We find replicable evidence for 10 gene co-expression modules that are differentially expressed in ASD cortex. Rather than being independent non-interacting sources of pathology, these dysregulated co-expression modules work in synergy and physically interact at the protein level. These systems-level transcriptional signals are characterized by downregulation of synaptic processes coordinated with upregulation of immune/inflammation, response to other organism, catabolism, viral processes, translation, protein targeting and localization, cell proliferation, and vasculature development. Hierarchical organization of meta-modules (clusters of highly correlated modules) is also highly affected in ASD. Conclusions These findings highlight that dysregulation of the ASD cortical transcriptome is characterized by the dysregulation of multiple coordinated transcriptional programs producing synergistic systems-level effects that cannot be fully appreciated by studying the individual component biological processes in isolation. Electronic supplementary material The online version of this article (doi:10.1186/s13229-017-0147-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Michael V Lombardo
- Department of Psychology and Center for Applied Neuroscience, University of Cyprus, Nicosia, Cyprus.,Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Eric Courchesne
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California, San Diego, La Jolla, CA USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA USA.,Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, La Jolla, CA USA
| | - Tiziano Pramparo
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California, San Diego, La Jolla, CA USA
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Marchetto MC, Belinson H, Tian Y, Freitas BC, Fu C, Vadodaria K, Beltrao-Braga P, Trujillo CA, Mendes AP, Padmanabhan K, Nunez Y, Ou J, Ghosh H, Wright R, Brennand K, Pierce K, Eichenfield L, Pramparo T, Eyler L, Barnes CC, Courchesne E, Geschwind DH, Gage FH, Wynshaw-Boris A, Muotri AR. Altered proliferation and networks in neural cells derived from idiopathic autistic individuals. Mol Psychiatry 2017; 22:820-835. [PMID: 27378147 PMCID: PMC5215991 DOI: 10.1038/mp.2016.95] [Citation(s) in RCA: 260] [Impact Index Per Article: 37.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Revised: 04/29/2016] [Accepted: 05/05/2016] [Indexed: 02/07/2023]
Abstract
Autism spectrum disorders (ASD) are common, complex and heterogeneous neurodevelopmental disorders. Cellular and molecular mechanisms responsible for ASD pathogenesis have been proposed based on genetic studies, brain pathology and imaging, but a major impediment to testing ASD hypotheses is the lack of human cell models. Here, we reprogrammed fibroblasts to generate induced pluripotent stem cells, neural progenitor cells (NPCs) and neurons from ASD individuals with early brain overgrowth and non-ASD controls with normal brain size. ASD-derived NPCs display increased cell proliferation because of dysregulation of a β-catenin/BRN2 transcriptional cascade. ASD-derived neurons display abnormal neurogenesis and reduced synaptogenesis leading to functional defects in neuronal networks. Interestingly, defects in neuronal networks could be rescued by insulin growth factor 1 (IGF-1), a drug that is currently in clinical trials for ASD. This work demonstrates that selection of ASD subjects based on endophenotypes unraveled biologically relevant pathway disruption and revealed a potential cellular mechanism for the therapeutic effect of IGF-1.
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Affiliation(s)
| | - Haim Belinson
- University of California San Francisco, Department of Pediatrics, Institute for Human Genetics, CA 94143, USA
| | - Yuan Tian
- University of California Los Angeles, Program in Neurogenetics, Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, Los Angeles, CA 90402, USA
| | - Beatriz C. Freitas
- University of California San Diego, Department of Pediatrics/Rady Children’s Hospital San Diego, Department of Cellular & Molecular Medicine, Stem Cell Program, La Jolla, CA 92093-0695, USA
| | - Chen Fu
- Case Western Reserve University, Department of Genetics and Genome Sciences, Cleveland, OH 44106, USA
| | | | - Patricia Beltrao-Braga
- University of California San Diego, Department of Pediatrics/Rady Children’s Hospital San Diego, Department of Cellular & Molecular Medicine, Stem Cell Program, La Jolla, CA 92093-0695, USA
- University of São Paulo, Department of Obstetrics, Department of Surgery, Center for Cellular and Molecular Therapy, São Paulo, Brazil
| | - Cleber A. Trujillo
- University of California San Diego, Department of Pediatrics/Rady Children’s Hospital San Diego, Department of Cellular & Molecular Medicine, Stem Cell Program, La Jolla, CA 92093-0695, USA
| | - Ana P.D. Mendes
- The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA
| | - Krishnan Padmanabhan
- University of Rochester School of Medicine and Dentistry, Department of Neuroscience, 601 Elmwood Avenue, Box 603 Rochester, NY 14642
| | - Yanelli Nunez
- The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA
- University of California San Diego, Department of Pediatrics/Rady Children’s Hospital San Diego, Department of Cellular & Molecular Medicine, Stem Cell Program, La Jolla, CA 92093-0695, USA
| | - Jing Ou
- University of California Los Angeles, Program in Neurogenetics, Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, Los Angeles, CA 90402, USA
| | - Himanish Ghosh
- The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA
| | - Rebecca Wright
- The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA
| | - Kristen Brennand
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA
| | - Karen Pierce
- University of California San Diego, Department of Neurosciences, La Jolla, CA 92093, USA
| | - Lawrence Eichenfield
- University of California San Diego, Department of Neurosciences, La Jolla, CA 92093, USA
| | - Tiziano Pramparo
- University of California San Diego, Department of Neurosciences, La Jolla, CA 92093, USA
| | - Lisa Eyler
- University of California San Diego, Department of Neurosciences, La Jolla, CA 92093, USA
| | - Cynthia C. Barnes
- University of California San Diego, Department of Neurosciences, La Jolla, CA 92093, USA
| | - Eric Courchesne
- University of California San Diego, Department of Neurosciences, La Jolla, CA 92093, USA
| | - Daniel H. Geschwind
- University of California Los Angeles, Program in Neurogenetics, Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, Los Angeles, CA 90402, USA
| | - Fred H. Gage
- The Salk Institute, Laboratory of Genetics, La Jolla, CA 92037, USA
| | - Anthony Wynshaw-Boris
- University of California San Francisco, Department of Pediatrics, Institute for Human Genetics, CA 94143, USA
- Case Western Reserve University, Department of Genetics and Genome Sciences, Cleveland, OH 44106, USA
| | - Alysson R. Muotri
- University of California San Diego, Department of Pediatrics/Rady Children’s Hospital San Diego, Department of Cellular & Molecular Medicine, Stem Cell Program, La Jolla, CA 92093-0695, USA
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McConnell MJ, Moran JV, Abyzov A, Akbarian S, Bae T, Cortes-Ciriano I, Erwin JA, Fasching L, Flasch DA, Freed D, Ganz J, Jaffe AE, Kwan KY, Kwon M, Lodato MA, Mills RE, Paquola ACM, Rodin RE, Rosenbluh C, Sestan N, Sherman MA, Shin JH, Song S, Straub RE, Thorpe J, Weinberger DR, Urban AE, Zhou B, Gage FH, Lehner T, Senthil G, Walsh CA, Chess A, Courchesne E, Gleeson JG, Kidd JM, Park PJ, Pevsner J, Vaccarino FM. Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network. Science 2017; 356:356/6336/eaal1641. [PMID: 28450582 DOI: 10.1126/science.aal1641] [Citation(s) in RCA: 167] [Impact Index Per Article: 23.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Neuropsychiatric disorders have a complex genetic architecture. Human genetic population-based studies have identified numerous heritable sequence and structural genomic variants associated with susceptibility to neuropsychiatric disease. However, these germline variants do not fully account for disease risk. During brain development, progenitor cells undergo billions of cell divisions to generate the ~80 billion neurons in the brain. The failure to accurately repair DNA damage arising during replication, transcription, and cellular metabolism amid this dramatic cellular expansion can lead to somatic mutations. Somatic mutations that alter subsets of neuronal transcriptomes and proteomes can, in turn, affect cell proliferation and survival and lead to neurodevelopmental disorders. The long life span of individual neurons and the direct relationship between neural circuits and behavior suggest that somatic mutations in small populations of neurons can significantly affect individual neurodevelopment. The Brain Somatic Mosaicism Network has been founded to study somatic mosaicism both in neurotypical human brains and in the context of complex neuropsychiatric disorders.
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36
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Stessman HAF, Xiong B, Coe BP, Wang T, Hoekzema K, Fenckova M, Kvarnung M, Gerdts J, Trinh S, Cosemans N, Vives L, Lin J, Turner TN, Santen G, Ruivenkamp C, Kriek M, van Haeringen A, Aten E, Friend K, Liebelt J, Barnett C, Haan E, Shaw M, Gecz J, Anderlid BM, Nordgren A, Lindstrand A, Schwartz C, Kooy RF, Vandeweyer G, Helsmoortel C, Romano C, Alberti A, Vinci M, Avola E, Giusto S, Courchesne E, Pramparo T, Pierce K, Nalabolu S, Amaral D, Scheffer IE, Delatycki MB, Lockhart PJ, Hormozdiari F, Harich B, Castells-Nobau A, Xia K, Peeters H, Nordenskjöld M, Schenck A, Bernier RA, Eichler EE. Targeted sequencing identifies 91 neurodevelopmental-disorder risk genes with autism and developmental-disability biases. Nat Genet 2017; 49:515-526. [PMID: 28191889 PMCID: PMC5374041 DOI: 10.1038/ng.3792] [Citation(s) in RCA: 353] [Impact Index Per Article: 50.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Accepted: 01/22/2017] [Indexed: 12/12/2022]
Abstract
Gene-disruptive mutations contribute to the biology of neurodevelopmental disorders (NDDs), but most of the related pathogenic genes are not known. We sequenced 208 candidate genes from >11,730 cases and >2,867 controls. We identified 91 genes, including 38 new NDD genes, with an excess of de novo mutations or private disruptive mutations in 5.7% of cases. Drosophila functional assays revealed a subset with increased involvement in NDDs. We identified 25 genes showing a bias for autism versus intellectual disability and highlighted a network associated with high-functioning autism (full-scale IQ >100). Clinical follow-up for NAA15, KMT5B, and ASH1L highlighted new syndromic and nonsyndromic forms of disease.
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Affiliation(s)
| | - Bo Xiong
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Department of forensic medicine and Institute of Brain Research, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Bradley P. Coe
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Tianyun Wang
- The State Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Michaela Fenckova
- Department of Human Genetics, Radboud university medical center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Malin Kvarnung
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Jennifer Gerdts
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Sandy Trinh
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Nele Cosemans
- Centre for Human Genetics, KU Leuven and Leuven Autism Research (LAuRes), Leuven, Belgium
| | - Laura Vives
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Janice Lin
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Tychele N. Turner
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Gijs Santen
- Department of Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Claudia Ruivenkamp
- Department of Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Marjolein Kriek
- Department of Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Arie van Haeringen
- Department of Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Emmelien Aten
- Department of Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Kathryn Friend
- Robinson Research Institute and the University of Adelaide at the Women’s and Children’s Hospital, North Adelaide, Australia
- SA Pathology, Adelaide, Australia
| | - Jan Liebelt
- South Australian Clinical Genetics Service, SA Pathology (at Women’s and Children’s Hospital), Adelaide, Australia, Australia
| | - Christopher Barnett
- South Australian Clinical Genetics Service, SA Pathology (at Women’s and Children’s Hospital), Adelaide, Australia, Australia
| | - Eric Haan
- Robinson Research Institute and the University of Adelaide at the Women’s and Children’s Hospital, North Adelaide, Australia
- South Australian Clinical Genetics Service, SA Pathology (at Women’s and Children’s Hospital), Adelaide, Australia, Australia
| | - Marie Shaw
- Robinson Research Institute and the University of Adelaide at the Women’s and Children’s Hospital, North Adelaide, Australia
| | - Jozef Gecz
- Robinson Research Institute and the University of Adelaide at the Women’s and Children’s Hospital, North Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Britt-Marie Anderlid
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Charles Schwartz
- Center for Molecular Studies, J.C. Self Research Institute of Human Genetics, Greenwood Genetic Center, Greenwood, South Carolina, USA
| | - R. Frank Kooy
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | - Geert Vandeweyer
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | | | | | | | | | | | - Stefania Giusto
- Unit of Neurology, IRCCS Associazione Oasi Maria Santissima, Troina, Italy
| | | | | | - Karen Pierce
- UCSD, Autism Center of Excellence, La Jolla, CA, USA
| | | | - David Amaral
- MIND Institute and the University of California Davis School of Medicine, Sacramento, CA, USA
| | - Ingrid E. Scheffer
- Department of Paediatrics, University of Melbourne, Royal Children’s Hospital, Melbourne, Victoria, Australia
- Department of Medicine, University of Melbourne, Austin Health, Melbourne, Australia
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Martin B. Delatycki
- Department of Paediatrics, University of Melbourne, Royal Children’s Hospital, Melbourne, Victoria, Australia
- Victorian Clinical Genetics Services, Parkville, Victoria, Australia
- Bruce Lefroy Centre for Genetic Health Research, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Paul J. Lockhart
- Department of Paediatrics, University of Melbourne, Royal Children’s Hospital, Melbourne, Victoria, Australia
- Bruce Lefroy Centre for Genetic Health Research, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Fereydoun Hormozdiari
- Department of Biochemistry and Molecular Medicine, University of California at Davis, Davis, CA, USA
| | - Benjamin Harich
- Department of Human Genetics, Radboud university medical center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Anna Castells-Nobau
- Department of Human Genetics, Radboud university medical center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Kun Xia
- The State Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Hilde Peeters
- Centre for Human Genetics, KU Leuven and Leuven Autism Research (LAuRes), Leuven, Belgium
| | - Magnus Nordenskjöld
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Annette Schenck
- Department of Human Genetics, Radboud university medical center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Raphael A. Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
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Fingher N, Dinstein I, Ben-Shachar M, Haar S, Dale AM, Eyler L, Pierce K, Courchesne E. Toddlers later diagnosed with autism exhibit multiple structural abnormalities in temporal corpus callosum fibers. Cortex 2017; 97:291-305. [PMID: 28202133 DOI: 10.1016/j.cortex.2016.12.024] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 12/06/2016] [Accepted: 12/31/2016] [Indexed: 01/09/2023]
Abstract
Interhemispheric functional connectivity abnormalities are often reported in autism and it is thus not surprising that structural defects of the corpus callosum (CC) are consistently found using both traditional MRI and DTI techniques. Past DTI studies however, have subdivided the CC into 2 or 3 segments without regard for where fibers may project to within the cortex, thus placing limitations on our ability to understand the nature, timing and neurobehavioral impact of early CC abnormalities in autism. Leveraging a unique cohort of 97 toddlers (68 autism; 29 typical) we utilized a novel technique that identified seven CC tracts according to their cortical projections. Results revealed that younger (<2.5 years old), but not older toddlers with autism exhibited abnormally low mean, radial, and axial diffusivity values in the CC tracts connecting the occipital lobes and the temporal lobes. Fractional anisotropy and the cross sectional area of the temporal CC tract were significantly larger in young toddlers with autism. These findings indicate that water diffusion is more restricted and unidirectional in the temporal CC tract of young toddlers who develop autism. Such results may be explained by a potential overabundance of small caliber axons generated by excessive prenatal neural proliferation as proposed by previous genetic, animal model, and postmortem studies of autism. Furthermore, early diffusion measures in the temporal CC tract of the young toddlers were correlated with outcome measures of autism severity at later ages. These findings regarding the potential nature, timing, and location of early CC abnormalities in autism add to accumulating evidence, which suggests that altered inter-hemispheric connectivity, particularly across the temporal lobes, is a hallmark of the disorder.
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Affiliation(s)
- Noa Fingher
- Department of Brain and Cognitive Sciences, Ben-Gurion University, Israel.
| | - Ilan Dinstein
- Department of Brain and Cognitive Sciences, Ben-Gurion University, Israel; Department of Psychology, Ben-Gurion University, Israel
| | - Michal Ben-Shachar
- Department of English Literature and Linguistics, Bar Ilan University, Israel; The Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel
| | - Shlomi Haar
- Department of Brain and Cognitive Sciences, Ben-Gurion University, Israel
| | - Anders M Dale
- Department of Neurosciences, University of California San Diego, USA; Department of Radiology, University of California San Diego, USA
| | - Lisa Eyler
- Department of Radiology, University of California San Diego, USA; Desert-Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, USA
| | - Karen Pierce
- Department of Neurosciences, University of California San Diego, USA
| | - Eric Courchesne
- Department of Neurosciences, University of California San Diego, USA
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Pierce K, Courchesne E, Bacon E. To Screen or Not to Screen Universally for Autism is not the Question: Why the Task Force Got It Wrong. J Pediatr 2016; 176:182-94. [PMID: 27421956 PMCID: PMC5679123 DOI: 10.1016/j.jpeds.2016.06.004] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2015] [Revised: 04/27/2016] [Accepted: 06/02/2016] [Indexed: 12/12/2022]
Affiliation(s)
- Karen Pierce
- Department of Neurosciences and Autism Center of Excellence, School of Medicine, University of California San Diego, La Jolla, CA.
| | - Eric Courchesne
- Department of Neurosciences and Autism Center of Excellence, School of Medicine, University of California San Diego, La Jolla, CA
| | - Elizabeth Bacon
- Department of Neurosciences and Autism Center of Excellence, School of Medicine, University of California San Diego, La Jolla, CA
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Solso S, Xu R, Proudfoot J, Hagler DJ, Campbell K, Venkatraman V, Barnes CC, Ahrens-Barbeau C, Pierce K, Dale A, Eyler L, Courchesne E. Diffusion Tensor Imaging Provides Evidence of Possible Axonal Overconnectivity in Frontal Lobes in Autism Spectrum Disorder Toddlers. Biol Psychiatry 2016; 79:676-84. [PMID: 26300272 PMCID: PMC4699869 DOI: 10.1016/j.biopsych.2015.06.029] [Citation(s) in RCA: 110] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2014] [Revised: 06/22/2015] [Accepted: 06/23/2015] [Indexed: 12/31/2022]
Abstract
BACKGROUND Theories of brain abnormality in autism spectrum disorder (ASD) have focused on underconnectivity as an explanation for social, language, and behavioral deficits but are based mainly on studies of older autistic children and adults. METHODS In 94 ASD and typical toddlers ages 1 to 4 years, we examined the microstructure (indexed by fractional anisotropy) and volume of axon pathways using in vivo diffusion tensor imaging of fronto-frontal, fronto-temporal, fronto-striatal, and fronto-amygdala axon pathways, as well as posterior contrast tracts. Differences between ASD and typical toddlers in the nature of the relationship of age to these measures were tested. RESULTS Frontal tracts in ASD toddlers displayed abnormal age-related changes with greater fractional anisotropy and volume than normal at younger ages but an overall slower than typical apparent rate of continued development across the span of years. Posterior cortical contrast tracts had few significant abnormalities. CONCLUSIONS Frontal fiber tracts displayed deviant early development and age-related changes that could underlie impaired brain functioning and impact social and communication behaviors in ASD.
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Affiliation(s)
- Stephanie Solso
- Department of Neuroscience, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - Ronghui Xu
- CTRI, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - James Proudfoot
- CTRI, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - Donald J. Hagler
- Department of Radiology, Multimodal Imaging Laboratory, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - Kathleen Campbell
- Department of Neuroscience, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - Vijay Venkatraman
- Department of Radiology, Multimodal Imaging Laboratory, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - Cynthia Carter Barnes
- Department of Neuroscience, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - Clelia Ahrens-Barbeau
- Department of Neuroscience, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - Karen Pierce
- Department of Neuroscience, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - Anders Dale
- Department of Neuroscience, School of Medicine, University of California San Diego, La Jolla, CA 92093,Department of Radiology, Multimodal Imaging Laboratory, School of Medicine, University of California San Diego, La Jolla, CA 92093
| | - Lisa Eyler
- Department of Neuroscience, School of Medicine, University of California San Diego, La Jolla, CA 92093,Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA 92093,Desert-Pacific Mental Illness Research, Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA 92161
| | - Eric Courchesne
- Department of Neuroscience, School of Medicine, University of California San Diego, La Jolla.
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40
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Brandler WM, Antaki D, Gujral M, Noor A, Rosanio G, Chapman TR, Barrera DJ, Lin GN, Malhotra D, Watts AC, Wong LC, Estabillo JA, Gadomski TE, Hong O, Fajardo KVF, Bhandari A, Owen R, Baughn M, Yuan J, Solomon T, Moyzis AG, Maile MS, Sanders SJ, Reiner GE, Vaux KK, Strom CM, Zhang K, Muotri AR, Akshoomoff N, Leal SM, Pierce K, Courchesne E, Iakoucheva LM, Corsello C, Sebat J. Frequency and Complexity of De Novo Structural Mutation in Autism. Am J Hum Genet 2016; 98:667-79. [PMID: 27018473 PMCID: PMC4833290 DOI: 10.1016/j.ajhg.2016.02.018] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2015] [Accepted: 02/18/2016] [Indexed: 12/22/2022] Open
Abstract
Genetic studies of autism spectrum disorder (ASD) have established that de novo duplications and deletions contribute to risk. However, ascertainment of structural variants (SVs) has been restricted by the coarse resolution of current approaches. By applying a custom pipeline for SV discovery, genotyping, and de novo assembly to genome sequencing of 235 subjects (71 affected individuals, 26 healthy siblings, and their parents), we compiled an atlas of 29,719 SV loci (5,213/genome), comprising 11 different classes. We found a high diversity of de novo mutations, the majority of which were undetectable by previous methods. In addition, we observed complex mutation clusters where combinations of de novo SVs, nucleotide substitutions, and indels occurred as a single event. We estimate a high rate of structural mutation in humans (20%) and propose that genetic risk for ASD is attributable to an elevated frequency of gene-disrupting de novo SVs, but not an elevated rate of genome rearrangement.
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Affiliation(s)
- William M Brandler
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Danny Antaki
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA; Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Madhusudan Gujral
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Amina Noor
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Gabriel Rosanio
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Timothy R Chapman
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Daniel J Barrera
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Guan Ning Lin
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Dheeraj Malhotra
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Amanda C Watts
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | | | | | - Therese E Gadomski
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Oanh Hong
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Karin V Fuentes Fajardo
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Abhishek Bhandari
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Renius Owen
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA 92675, USA
| | - Michael Baughn
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Jeffrey Yuan
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Terry Solomon
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Alexandra G Moyzis
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Michelle S Maile
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Stephan J Sanders
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Gail E Reiner
- Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Keith K Vaux
- Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Charles M Strom
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA 92675, USA
| | - Kang Zhang
- Department of Ophthalmology, University of California, San Diego, La Jolla, CA 92093, USA
| | - Alysson R Muotri
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | | | - Suzanne M Leal
- Center for Statistical Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Karen Pierce
- Department of Neuroscience, University of California, San Diego, La Jolla, CA 92093, USA
| | - Eric Courchesne
- Department of Neuroscience, University of California, San Diego, La Jolla, CA 92093, USA
| | - Lilia M Iakoucheva
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | | | - Jonathan Sebat
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
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Pramparo T, Lombardo MV, Campbell K, Barnes CC, Marinero S, Solso S, Young J, Mayo M, Dale A, Ahrens-Barbeau C, Murray SS, Lopez L, Lewis N, Pierce K, Courchesne E. Cell cycle networks link gene expression dysregulation, mutation, and brain maldevelopment in autistic toddlers. Mol Syst Biol 2015; 11:841. [PMID: 26668231 PMCID: PMC4704485 DOI: 10.15252/msb.20156108] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Genetic mechanisms underlying abnormal early neural development in toddlers with Autism Spectrum Disorder (ASD) remain uncertain due to the impossibility of direct brain gene expression measurement during critical periods of early development. Recent findings from a multi‐tissue study demonstrated high expression of many of the same gene networks between blood and brain tissues, in particular with cell cycle functions. We explored relationships between blood gene expression and total brain volume (TBV) in 142 ASD and control male toddlers. In control toddlers, TBV variation significantly correlated with cell cycle and protein folding gene networks, potentially impacting neuron number and synapse development. In ASD toddlers, their correlations with brain size were lost as a result of considerable changes in network organization, while cell adhesion gene networks significantly correlated with TBV variation. Cell cycle networks detected in blood are highly preserved in the human brain and are upregulated during prenatal states of development. Overall, alterations were more pronounced in bigger brains. We identified 23 candidate genes for brain maldevelopment linked to 32 genes frequently mutated in ASD. The integrated network includes genes that are dysregulated in leukocyte and/or postmortem brain tissue of ASD subjects and belong to signaling pathways regulating cell cycle G1/S and G2/M phase transition. Finally, analyses of the CHD8 subnetwork and altered transcript levels from an independent study of CHD8 suppression further confirmed the central role of genes regulating neurogenesis and cell adhesion processes in ASD brain maldevelopment.
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Affiliation(s)
- Tiziano Pramparo
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Michael V Lombardo
- Department of Psychology, University of Cyprus, Nicosia, Cyprus Center for Applied Neuroscience, University of Cyprus, Nicosia, Cyprus Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Kathleen Campbell
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Cynthia Carter Barnes
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Steven Marinero
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Stephanie Solso
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Julia Young
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Maisi Mayo
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Anders Dale
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Clelia Ahrens-Barbeau
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Sarah S Murray
- Scripps Genomic Medicine & The Scripps Translational Sciences Institute (STSI), La Jolla, CA, USA Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Linda Lopez
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Nathan Lewis
- Novo Nordisk Foundation Center for Biosustainability at the UCSD School of Medicine, and Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
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Lombardo MV, Pierce K, Eyler LT, Carter Barnes C, Ahrens-Barbeau C, Solso S, Campbell K, Courchesne E. Different functional neural substrates for good and poor language outcome in autism. Neuron 2015; 86:567-77. [PMID: 25864635 DOI: 10.1016/j.neuron.2015.03.023] [Citation(s) in RCA: 114] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Revised: 01/18/2015] [Accepted: 03/05/2015] [Indexed: 12/17/2022]
Abstract
Autism (ASD) is vastly heterogeneous, particularly in early language development. While ASD language trajectories in the first years of life are highly unstable, by early childhood these trajectories stabilize and are predictive of longer-term outcome. Early neural substrates that predict/precede such outcomes are largely unknown, but could have considerable translational and clinical impact. Pre-diagnosis fMRI response to speech in ASD toddlers with relatively good language outcome was highly similar to non-ASD comparison groups and robustly recruited language-sensitive superior temporal cortices. In contrast, language-sensitive superior temporal cortices were hypoactive in ASD toddlers with poor language outcome. Brain-behavioral relationships were atypically reversed in ASD, and a multimodal combination of pre-diagnostic clinical behavioral measures and speech-related fMRI response showed the most promise as an ASD prognosis classifier. Thus, before ASD diagnoses and outcome become clinically clear, distinct functional neuroimaging phenotypes are already present that can shed insight on an ASD toddler's later outcome. VIDEO ABSTRACT.
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Affiliation(s)
- Michael V Lombardo
- Department of Psychology, University of Cyprus, 1 Panepistimiou Avenue, Aglantzia, Nicosia 1678, Cyprus; Center for Applied Neuroscience, University of Cyprus, 1 Panepistimiou Avenue, Aglantzia, Nicosia 1678, Cyprus; Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge CB2 8AH, UK.
| | - Karen Pierce
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA 92093, USA
| | - Lisa T Eyler
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92161, USA; VISN 22 Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, 3350 La Jolla Village Drive, San Diego, CA 92161, USA
| | - Cindy Carter Barnes
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA 92093, USA
| | - Clelia Ahrens-Barbeau
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA 92093, USA
| | - Stephanie Solso
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA 92093, USA
| | - Kathleen Campbell
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA 92093, USA
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neuroscience, University of California, San Diego, 8110 La Jolla Shores Drive, Suite 201, La Jolla, CA 92093, USA.
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Pramparo T, Pierce K, Lombardo MV, Carter Barnes C, Marinero S, Ahrens-Barbeau C, Murray SS, Lopez L, Xu R, Courchesne E. Prediction of autism by translation and immune/inflammation coexpressed genes in toddlers from pediatric community practices. JAMA Psychiatry 2015; 72:386-94. [PMID: 25739104 DOI: 10.1001/jamapsychiatry.2014.3008] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE The identification of genomic signatures that aid early identification of individuals at risk for autism spectrum disorder (ASD) in the toddler period remains a major challenge because of the genetic and phenotypic heterogeneity of the disorder. Generally, ASD is not diagnosed before the fourth to fifth birthday. OBJECTIVE To apply a functional genomic approach to identify a biologically relevant signature with promising performance in the diagnostic classification of infants and toddlers with ASD. DESIGN, SETTING, AND PARTICIPANTS Proof-of-principle study of leukocyte RNA expression levels from 2 independent cohorts of children aged 1 to 4 years (142 discovery participants and 73 replication participants) using Illumina microarrays. Coexpression analysis of differentially expressed genes between Discovery ASD and control toddlers were used to define gene modules and eigengenes used in a diagnostic classification analysis. Independent validation of the classifier performance was tested on the replication cohort. Pathway enrichment and protein-protein interaction analyses were used to confirm biological relevance of the functional networks in the classifier. Participant recruitment occurred in general pediatric clinics and community settings. Male infants and toddlers (age range, 1-4 years) were enrolled in the study. Recruitment criteria followed the 1-Year Well-Baby Check-Up Approach. Diagnostic judgment followed DSM-IV-TR and Autism Diagnostic Observation Schedule criteria for autism. Participants with ASD were compared with control groups composed of typically developing toddlers as well as toddlers with global developmental or language delay. MAIN OUTCOMES AND MEASURES Logistic regression and receiver operating characteristic curve analysis were used in a classification test to establish the accuracy, specificity, and sensitivity of the module-based classifier. RESULTS Our signature of differentially coexpressed genes was enriched in translation and immune/inflammation functions and produced 83% accuracy. In an independent test with approximately half of the sample and a different microarray, the diagnostic classification of ASD vs control samples was 75% accurate. Consistent with its ASD specificity, our signature did not distinguish toddlers with global developmental or language delay from typically developing toddlers (62% accuracy). CONCLUSIONS AND RELEVANCE This proof-of-principle study demonstrated that genomic biomarkers with very good sensitivity and specificity for boys with ASD in general pediatric settings can be identified. It also showed that a blood-based clinical test for at-risk male infants and toddlers could be refined and routinely implemented in pediatric diagnostic settings.
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Affiliation(s)
- Tiziano Pramparo
- UC San Diego Autism Center of Excellence, Department of Neuroscience, University of California, San Diego School of Medicine, La Jolla
| | - Karen Pierce
- UC San Diego Autism Center of Excellence, Department of Neuroscience, University of California, San Diego School of Medicine, La Jolla
| | - Michael V Lombardo
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom3Department of Psychology, University of Cyprus, Nicosia, Cyprus4Center for Applied Neuroscience, University of Cyprus, Nicosia, Cyprus
| | - Cynthia Carter Barnes
- UC San Diego Autism Center of Excellence, Department of Neuroscience, University of California, San Diego School of Medicine, La Jolla
| | - Steven Marinero
- UC San Diego Autism Center of Excellence, Department of Neuroscience, University of California, San Diego School of Medicine, La Jolla
| | - Clelia Ahrens-Barbeau
- UC San Diego Autism Center of Excellence, Department of Neuroscience, University of California, San Diego School of Medicine, La Jolla
| | - Sarah S Murray
- Scripps Genomic Medicine and Scripps Translational Sciences Institute, La Jolla, California6Department of Pathology, University of California, San Diego, La Jolla
| | - Linda Lopez
- UC San Diego Autism Center of Excellence, Department of Neuroscience, University of California, San Diego School of Medicine, La Jolla
| | - Ronghui Xu
- Department of Family and Preventive Medicine, University of California, San Diego, La Jolla8Department of Mathematics, University of California, San Diego, La Jolla
| | - Eric Courchesne
- UC San Diego Autism Center of Excellence, Department of Neuroscience, University of California, San Diego School of Medicine, La Jolla
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Stoner R, Chow ML, Boyle MP, Sunkin SM, Mouton PR, Roy S, Wynshaw-Boris A, Colamarino SA, Lein ES, Courchesne E. Patches of disorganization in the neocortex of children with autism. N Engl J Med 2014; 370:1209-1219. [PMID: 24670167 PMCID: PMC4499461 DOI: 10.1056/nejmoa1307491] [Citation(s) in RCA: 470] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
BACKGROUND Autism involves early brain overgrowth and dysfunction, which is most strongly evident in the prefrontal cortex. As assessed on pathological analysis, an excess of neurons in the prefrontal cortex among children with autism signals a disturbance in prenatal development and may be concomitant with abnormal cell type and laminar development. METHODS To systematically examine neocortical architecture during the early years after the onset of autism, we used RNA in situ hybridization with a panel of layer- and cell-type-specific molecular markers to phenotype cortical microstructure. We assayed markers for neurons and glia, along with genes that have been implicated in the risk of autism, in prefrontal, temporal, and occipital neocortical tissue from postmortem samples obtained from children with autism and unaffected children between the ages of 2 and 15 years. RESULTS We observed focal patches of abnormal laminar cytoarchitecture and cortical disorganization of neurons, but not glia, in prefrontal and temporal cortical tissue from 10 of 11 children with autism and from 1 of 11 unaffected children. We observed heterogeneity between cases with respect to cell types that were most abnormal in the patches and the layers that were most affected by the pathological features. No cortical layer was uniformly spared, with the clearest signs of abnormal expression in layers 4 and 5. Three-dimensional reconstruction of layer markers confirmed the focal geometry and size of patches. CONCLUSIONS In this small, explorative study, we found focal disruption of cortical laminar architecture in the cortexes of a majority of young children with autism. Our data support a probable dysregulation of layer formation and layer-specific neuronal differentiation at prenatal developmental stages. (Funded by the Simons Foundation and others.).
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Affiliation(s)
- Rich Stoner
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
| | - Maggie L Chow
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
| | - Maureen P Boyle
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
| | - Susan M Sunkin
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
| | - Peter R Mouton
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
| | - Subhojit Roy
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
| | - Anthony Wynshaw-Boris
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
| | - Sophia A Colamarino
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
| | - Ed S Lein
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
| | - Eric Courchesne
- University of California, San Diego, Autism Center of Excellence (R.S., M.L.C., M.P.B., E.C.), and the Departments of Neuroscience (R.S., M.L.C., M.P.B., S.R., E.C.) and Pathology (S.R.), University of California, San Diego, School of Medicine, La Jolla; Allen Institute for Brain Science, Seattle (M.P.B., S.M.S., E.S.L.); the Department of Pathology and Cell Biology, University of South Florida School of Medicine and Alzheimer's Institute and Research Center, Tampa (P.R.M.); the Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland (A.W.-B.); and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA (S.A.C.)
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Abstract
Abstract Patients with parietal volume loss showed electrophysiological and behavioral signs of abnormally narrow regions of enhancement of sensory stimulation at an attended location. On a test of focused spatial attention, when compared to normal control subjects and patients without parietal abnormality, patients with abnormalities of parietal cortex demonstrated (1) faster button press RTs to targets, (2) earlier P3b event-related potential (ERP) latencies to targets, and (3) larger than normal P1 ERP attention effects (i.e., greater than normal enhancement of sensory responses at an attended location). These data are evidence for visual attention distributed as a spotlight at the attentional focus with little surrounding processing enhancement. This dysfunctional attentional map facilitates simple responses within the attentional beam quite well, but could hinder responses outside the beam. Severely gated sensory responses outside the immediate attentional focus are likely to result in severely delayed responses to information in those locations. This would be consistent with the response delays seen in patients with parietal damage following an incorrect spatial cue (extinction-like pattern), and also with clinical observations of inattention in such patients. The patterns of sensory enhancement seen in these data suggest a mechanism that may underlie the impairments in spatial attention that follow damage to parietal cortex, and help to specify the role of parietal cortex in spatial attention.
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Manning JH, Courchesne E, Fox PT. Intrinsic connectivity network mapping in young children during natural sleep. Neuroimage 2013; 83:288-93. [PMID: 23727317 DOI: 10.1016/j.neuroimage.2013.05.020] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2012] [Revised: 05/01/2013] [Accepted: 05/03/2013] [Indexed: 01/26/2023] Open
Abstract
Structural and functional neuroimaging have substantively informed the pathophysiology of numerous adult neurological and psychiatric disorders. While structural neuroimaging is readily acquired in sedated young children, pediatric application of functional neuroimaging has been limited by the behavioral demands of in-scanner task performance. Here, we investigated whether functional magnetic resonance imaging (fMRI) acquired during natural sleep and without experimental stimulation offers a viable strategy for studying young children. We targeted the lengthy epoch of non-rapid eye movement, stage 3 (NREM3) sleep typically observed at sleep onset in sleep-deprived children. Seven healthy, preschool-aged children (24-58 months) were studied, acquiring fMRI measurements of cerebral blood flow (CBF) and of intrinsic connectivity networks (ICNs), with concurrent sleep-stage monitoring. ICN data (T2* fMRI) were reliably obtained during NREM3 sleep; CBF data (arterial spin labeled fMRI) were not reliably obtained, as scanner noises disrupted sleep. Applying independent component analysis (ICA) to T2* data, distinct ICNs were observed which corresponded closely with those reported in the adult literature. Notably, a network associated with orthography in adults was not observed, suggesting that ICNs exhibit a developmental trajectory. We conclude that resting-state fMRI obtained in sleep is a promising paradigm for neurophysiological investigations of young children.
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Affiliation(s)
- Janessa H Manning
- Research Imaging Institute, University of Texas Health Science Center, 7703 Floyd Curl Dr., San Antonio, TX 78229, USA.
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Glatt SJ, Tsuang MT, Winn M, Chandler SD, Collins M, Lopez L, Weinfeld M, Carter C, Schork N, Pierce K, Courchesne E. Blood-based gene expression signatures of infants and toddlers with autism. J Am Acad Child Adolesc Psychiatry 2012; 51:934-44.e2. [PMID: 22917206 PMCID: PMC3756503 DOI: 10.1016/j.jaac.2012.07.007] [Citation(s) in RCA: 69] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2012] [Revised: 05/31/2012] [Accepted: 07/11/2012] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental disorders that onset clinically during the first years of life. ASD risk biomarkers expressed early in life could significantly impact diagnosis and treatment, but no transcriptome-wide biomarker classifiers derived from fresh blood samples from children with autism have yet emerged. METHOD Using a community-based, prospective, longitudinal method, we identified 60 infants and toddlers at risk for ASDs (autistic disorder and pervasive developmental disorder), 34 at-risk for language delay, 17 at-risk for global developmental delay, and 68 typically developing comparison children. Diagnoses were confirmed via longitudinal follow-up. Each child's mRNA expression profile in peripheral blood mononuclear cells was determined by microarray. RESULTS Potential ASD biomarkers were discovered in one-half of the sample and used to build a classifier, with high diagnostic accuracy in the remaining half of the sample. CONCLUSIONS The mRNA expression abnormalities reliably observed in peripheral blood mononuclear cells, which are safely and easily assayed in infants, offer the first potential peripheral blood-based, early biomarker panel of risk for autism in infants and toddlers. Future work should verify these biomarkers and evaluate whether they may also serve as indirect indices of deviant molecular neural mechanisms in autism.
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Morgan JT, Chana G, Abramson I, Semendeferi K, Courchesne E, Everall IP. Abnormal microglial-neuronal spatial organization in the dorsolateral prefrontal cortex in autism. Brain Res 2012; 1456:72-81. [PMID: 22516109 DOI: 10.1016/j.brainres.2012.03.036] [Citation(s) in RCA: 150] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2011] [Revised: 03/08/2012] [Accepted: 03/15/2012] [Indexed: 12/27/2022]
Abstract
Microglial activation and alterations in neuron number have been reported in autism. However, it is unknown whether microglial activation in the disorder includes a neuron-directed microglial response that might reflect neuronal dysfunction, or instead indicates a non-directed, pro-activation brain environment. To address this question, we examined microglial and neuronal organization in the dorsolateral prefrontal cortex, a region of pronounced early brain overgrowth in autism, via spatial pattern analysis of 13 male postmortem autism subjects and 9 controls. We report that microglia are more frequently present near neurons in the autism cases at a distance interval of 25 μm, as well as 75 and 100 μm. Many interactions are observed between near-distance microglia and neurons that appear to involve encirclement of the neurons by microglial processes. Analysis of a young subject subgroup preliminarily suggests that this alteration may be present from an early age in autism. We additionally observed that neuron-neuron clustering, although normal in cases with autism as a whole, increases with advancing age in autism, suggesting a gradual loss of normal neuronal organization in the disorder. Microglia-microglia organization is normal in autism at all ages, indicating that aberrantly close microglia-neuron association in the disorder is not a result of altered microglial distribution. Our findings confirm that at least some microglial activation in the dorsolateral prefrontal cortex in autism is associated with a neuron-specific reaction, and suggest that neuronal organization may degrade later in life in the disorder.
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Affiliation(s)
- John T Morgan
- Department of Neuroscience, School of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0602, USA.
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Chow ML, Pramparo T, Winn ME, Barnes CC, Li HR, Weiss L, Fan JB, Murray S, April C, Belinson H, Fu XD, Wynshaw-Boris A, Schork NJ, Courchesne E. Age-dependent brain gene expression and copy number anomalies in autism suggest distinct pathological processes at young versus mature ages. PLoS Genet 2012; 8:e1002592. [PMID: 22457638 PMCID: PMC3310790 DOI: 10.1371/journal.pgen.1002592] [Citation(s) in RCA: 144] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2011] [Accepted: 01/22/2012] [Indexed: 01/09/2023] Open
Abstract
Autism is a highly heritable neurodevelopmental disorder, yet the genetic underpinnings of the disorder are largely unknown. Aberrant brain overgrowth is a well-replicated observation in the autism literature; but association, linkage, and expression studies have not identified genetic factors that explain this trajectory. Few studies have had sufficient statistical power to investigate whole-genome gene expression and genotypic variation in the autistic brain, especially in regions that display the greatest growth abnormality. Previous functional genomic studies have identified possible alterations in transcript levels of genes related to neurodevelopment and immune function. Thus, there is a need for genetic studies involving key brain regions to replicate these findings and solidify the role of particular functional pathways in autism pathogenesis. We therefore sought to identify abnormal brain gene expression patterns via whole-genome analysis of mRNA levels and copy number variations (CNVs) in autistic and control postmortem brain samples. We focused on prefrontal cortex tissue where excess neuron numbers and cortical overgrowth are pronounced in the majority of autism cases. We found evidence for dysregulation in pathways governing cell number, cortical patterning, and differentiation in young autistic prefrontal cortex. In contrast, adult autistic prefrontal cortex showed dysregulation of signaling and repair pathways. Genes regulating cell cycle also exhibited autism-specific CNVs in DNA derived from prefrontal cortex, and these genes were significantly associated with autism in genome-wide association study datasets. Our results suggest that CNVs and age-dependent gene expression changes in autism may reflect distinct pathological processes in the developing versus the mature autistic prefrontal cortex. Our results raise the hypothesis that genetic dysregulation in the developing brain leads to abnormal regional patterning, excess prefrontal neurons, cortical overgrowth, and neural dysfunction in autism. Autism is a disorder characterized by aberrant social, communication, and restricted and repetitive behaviors. It develops clinically in the first years of life. Toddlers and children with autism often exhibit early brain enlargement and excess neuron numbers in the prefrontal cortex. Adults with autism generally do not display enlargement but instead may have a smaller brain size. Thus, we investigated DNA and mRNA patterns in prefrontal cortex from young versus adult postmortem individuals with autism to identify age-related gene expression differences as well as possible genetic correlates of abnormal brain enlargement, excess neuron numbers, and abnormal functioning in this disorder. We found abnormalities in genetic pathways governing cell number, neurodevelopment, and cortical lateralization in autism. We also found that the key pathways associated with autism are different between younger and older autistic individuals. These findings suggest that dysregulated gene pathways in the early stages of neurodevelopment could lead to later behavioral and cognitive deficits associated with autism.
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Affiliation(s)
- Maggie L. Chow
- Department of Neuroscience, NIH–UCSD Autism Center of Excellence, School of Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Tiziano Pramparo
- Department of Neuroscience, NIH–UCSD Autism Center of Excellence, School of Medicine, University of California San Diego, La Jolla, California, United States of America
- Division of Medical Genetics, Department of Pediatrics and Institute of Human Genetics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Mary E. Winn
- Scripps Genomic Medicine and The Scripps Translational Sciences Institute (STSI), La Jolla, California, United States of America
- Graduate Program in Biomedical Sciences, Department of Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Cynthia Carter Barnes
- Department of Neuroscience, NIH–UCSD Autism Center of Excellence, School of Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Hai-Ri Li
- Department of Cellular and Molecular Medicine, School of Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Lauren Weiss
- Department of Psychiatry, School of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Jian-Bing Fan
- Illumina, San Diego, California, United States of America
| | - Sarah Murray
- Scripps Genomic Medicine and The Scripps Translational Sciences Institute (STSI), La Jolla, California, United States of America
| | - Craig April
- Illumina, San Diego, California, United States of America
| | - Haim Belinson
- Division of Medical Genetics, Department of Pediatrics and Institute of Human Genetics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Xiang-Dong Fu
- Department of Cellular and Molecular Medicine, School of Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Anthony Wynshaw-Boris
- Division of Medical Genetics, Department of Pediatrics and Institute of Human Genetics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Nicholas J. Schork
- Scripps Genomic Medicine and The Scripps Translational Sciences Institute (STSI), La Jolla, California, United States of America
- * E-mail: (NJS); (EC)
| | - Eric Courchesne
- Department of Neuroscience, NIH–UCSD Autism Center of Excellence, School of Medicine, University of California San Diego, La Jolla, California, United States of America
- * E-mail: (NJS); (EC)
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Chow ML, Winn ME, Li HR, April C, Wynshaw-Boris A, Fan JB, Fu XD, Courchesne E, Schork NJ. Preprocessing and Quality Control Strategies for Illumina DASL Assay-Based Brain Gene Expression Studies with Semi-Degraded Samples. Front Genet 2012; 3:11. [PMID: 22375143 PMCID: PMC3286152 DOI: 10.3389/fgene.2012.00011] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2011] [Accepted: 01/19/2012] [Indexed: 11/25/2022] Open
Abstract
Available statistical preprocessing or quality control analysis tools for gene expression microarray datasets are known to greatly affect downstream data analysis, especially when degraded samples, unique tissue samples, or novel expression assays are used. It is therefore important to assess the validity and impact of the assumptions built in to preprocessing schemes for a dataset. We developed and assessed a data preprocessing strategy for use with the Illumina DASL-based gene expression assay with partially degraded postmortem prefrontal cortex samples. The samples were obtained from individuals with autism as part of an investigation of the pathogenic factors contributing to autism. Using statistical analysis methods and metrics such as those associated with multivariate distance matrix regression and mean inter-array correlation, we developed a DASL-based assay gene expression preprocessing pipeline to accommodate and detect problems with microarray-based gene expression values obtained with degraded brain samples. Key steps in the pipeline included outlier exclusion, data transformation and normalization, and batch effect and covariate corrections. Our goal was to produce a clean dataset for subsequent downstream differential expression analysis. We ultimately settled on available transformation and normalization algorithms in the R/Bioconductor package lumi based on an assessment of their use in various combinations. A log2-transformed, quantile-normalized, and batch and seizure-corrected procedure was likely the most appropriate for our data. We empirically tested different components of our proposed preprocessing strategy and believe that our results suggest that a preprocessing strategy that effectively identifies outliers, normalizes the data, and corrects for batch effects can be applied to all studies, even those pursued with degraded samples.
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Affiliation(s)
- Maggie L Chow
- Department of Neuroscience, UC San Diego Autism Center of Excellence, School of Medicine, National Institutes of Health, University of California San Diego La Jolla, CA, USA
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