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Zhang X, Grove J, Gu Y, Buus CK, Nielsen LK, Neufeld SA, Koko M, Malawsky DS, Wade E, Verhoef E, Gui A, Hegemann L, Geschwind DH, Wray NR, Havdahl A, Ronald A, St. Pourcain B, Robinson EB, Bourgeron T, Baron-Cohen S, Børglum AD, Martin HC, Warrier V. An axis of genetic heterogeneity in autism is indexed by age at diagnosis and is associated with varying developmental and mental health profiles. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.31.24311279. [PMID: 39132493 PMCID: PMC11312648 DOI: 10.1101/2024.07.31.24311279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
There is growing recognition that earliest signs of autism need not clearly manifest in the first three years of life. To what extent is this variation in developmental trajectories associated with age at autism diagnosis? Does the genetic profile of autism vary with age at autism diagnosis? Using longitudinal data from four birth cohorts, we demonstrate that two different trajectories of socio-emotional behaviours are associated with age at diagnosis. We further demonstrate that the age at autism diagnosis is partly heritable (h2 SNP = 0.12, s.e.m = 0.01), and is associated with two moderately correlated (rg = 0.38, s.e.m = 0.07) autism polygenic factors. One of these factors is associated with earlier diagnosis of autism, lower social and communication abilities in early childhood. The second factor is associated with later autism diagnosis, increased socio-emotional difficulties in adolescence, and has moderate to high positive genetic correlations with Attention-Deficit/Hyperactivity Disorder, mental health conditions, and trauma. Overall, our research identifies an axis of heterogeneity in autism, indexed by age at diagnosis, which partly explains heterogeneity in autism and the profiles of co-occurring neurodevelopmental and mental health profiles. Our findings have important implications for how we conceptualise autism and provide one model to explain some of the diversity within autism.
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Affiliation(s)
- Xinhe Zhang
- Department of Psychiatry, University of Cambridge
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Jakob Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, Aarhus, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Yuanjun Gu
- Department of Psychiatry, University of Cambridge
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Cornelia K. Buus
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, Denmark
| | - Lea K. Nielsen
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, Denmark
| | | | - Mahmoud Koko
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
| | - Daniel S Malawsky
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, Denmark
| | - Emma Wade
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, Denmark
| | - Ellen Verhoef
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Anna Gui
- Department of Psychology, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck University of London, London, WC1E 7HX, United Kingdom
| | - Laura Hegemann
- Department of Psychology, University of Oslo, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | | | | | | | - Daniel H. Geschwind
- Program in Neurobehavioral Genetics and Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Alexandra Havdahl
- Department of Psychology, University of Oslo, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- PsychGen Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Angelica Ronald
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck University of London, London, WC1E 7HX, United Kingdom
- School of Psychology, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom
| | - Beate St. Pourcain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, The Netherlands
| | - Elise B. Robinson
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
| | - Simon Baron-Cohen
- Department of Psychiatry, University of Cambridge
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Anders D. Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, Aarhus, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, Denmark
| | - Hilary C. Martin
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
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2
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Bazelmans T, Arthur R, Pasco G, Shephard E, Milosavljevic B, Ali JB, Pickles A, Johnson MH, Jones EJH, Charman T. Mid-childhood autism sibling recurrence in infants with a family history of autism. Autism Res 2024; 17:1501-1514. [PMID: 38973707 DOI: 10.1002/aur.3182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 06/10/2024] [Indexed: 07/09/2024]
Abstract
Autism sibling recurrence in prospective infant family history studies is ~20% at 3 years but systematic follow-up to mid-childhood is rare. In population and clinical cohorts autism is not recognized in some children until school-age or later. One hundred and fifty-nine infants with an older sibling with autism underwent research diagnostic assessments at 3 years and mid-childhood (6 to 12 years (mean 9)). We report the autism sibling recurrence rate in mid-childhood and compare developmental and behavioral profiles at mid-childhood and 3 years in those with earlier versus later recognized autism, and those who had, or had not, received a community autism diagnosis. The autism recurrence rate in this sample in mid-childhood was 37.1%, 95% CI [29.9%, 44.9%] and higher in boys than girls. Around half of those diagnosed with autism in mid-childhood had not received a diagnosis at 3 years. Later, diagnosis was more common in girls than boys. While some had sub-threshold symptoms at 3, in others late diagnosis followed a largely typical early presentation. Sibling recurrence based on community clinical diagnosis was 24.5%, 95% CI [18.4%, 31.9%]. Those who also had a community diagnosis tended to be older, have lower adaptive function and higher autism and inattention symptoms. Notwithstanding limitations of a single site study, modest sample size and limits to generalisability, autism sibling recurrence in family history infants may be higher in mid-childhood than in studies reporting diagnostic outcome at 3 years. Findings have implications for families and clinical services, and for prospective family history studies.
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Affiliation(s)
- Tessel Bazelmans
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Rowan Arthur
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Greg Pasco
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | | | - Bosiljka Milosavljevic
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Jannath Begum Ali
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Andrew Pickles
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Mark H Johnson
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
- Department of Psychology, University of Cambridge, UK
| | - Emily J H Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Tony Charman
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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3
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Patti MA, Croen LA, Dickerson AS, Joseph RM, Ames JL, Ladd-Acosta C, Ozonoff S, Schmidt RJ, Volk HE, Hipwell AE, Magee KE, Karagas M, McEvoy C, Landa R, Elliott MR, Mitchell DK, D'Sa V, Deoni S, Pievsky M, Wu PC, Barry F, Stanford JB, Bilder DA, Trasande L, Bush NR, Lyall K. Reproducibility between preschool and school-age Social Responsiveness Scale forms in the Environmental influences on Child Health Outcomes program. Autism Res 2024; 17:1187-1204. [PMID: 38794898 PMCID: PMC11186723 DOI: 10.1002/aur.3147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 04/12/2024] [Indexed: 05/26/2024]
Abstract
Evidence suggests core autism trait consistency in older children, but development of these traits is variable in early childhood. The Social Responsiveness Scale (SRS) measures autism-related traits and broader autism phenotype, with two age-dependent forms in childhood (preschool, 2.5-4.5 years; school age, 4-18 years). Score consistency has been observed within forms, though reliability across forms has not been evaluated. Using data from the Environmental Influences on Child Health Outcomes (ECHO) program (n = 853), preschool, and school-age SRS scores were collected via maternal report when children were an average of 3.0 and 5.8 years, respectively. We compared reproducibility of SRS total scores (T-scores) and agreement above a clinically meaningful cutoff (T-scores ≥ 60) and examined predictors of discordance in cutoff scores across forms. Participant scores across forms were similar (mean difference: 3.3 points; standard deviation: 7), though preschool scores were on average lower than school-age scores. Most children (88%) were classified below the cutoff on both forms, and overall concordance was high (92%). However, discordance was higher in cohorts following younger siblings of autistic children (16%). Proportions of children with an autism diagnoses were also higher among those with discordant scores (27%) than among those with concordant scores (4%). Our findings indicate SRS scores are broadly reproducible across preschool and school-age forms, particularly for capturing broader, nonclinical traits, but also suggest that greater variability of autism-related traits in preschool-age children may reduce reliability with later school-age scores for those in the clinical range.
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Grants
- UH3OD023285 NIH ECHO Program, funded by the office of the Director, NIH
- UG3 OD023342 NIH HHS
- UH3OD023288 NIH ECHO Program, funded by the office of the Director, NIH
- U24OD023319 NIH ECHO Program, funded by the office of the Director, NIH
- UH3OD023244 NIH ECHO Program, funded by the office of the Director, NIH
- UH3OD023313 NIH ECHO Program, funded by the office of the Director, NIH
- UH3OD023305 NIH ECHO Program, funded by the office of the Director, NIH
- UH3OD023275 NIH ECHO Program, funded by the office of the Director, NIH
- UH3OD023328 NIH ECHO Program, funded by the office of the Director, NIH
- UH3OD023342 NIH ECHO Program, funded by the office of the Director, NIH
- U2C OD023375 NIH HHS
- UH3OD023271 NIH ECHO Program, funded by the office of the Director, NIH
- U24OD023382 NIH ECHO Program, funded by the office of the Director, NIH
- UH3OD023249 NIH ECHO Program, funded by the office of the Director, NIH
- U2COD023375 NIH ECHO Program, funded by the office of the Director, NIH
- UH3 OD023342 NIH HHS
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Affiliation(s)
- Marisa A Patti
- AJ Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania, USA
| | - Lisa A Croen
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Aisha S Dickerson
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Robert M Joseph
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Jennifer L Ames
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Christine Ladd-Acosta
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Sally Ozonoff
- Department of Psychiatry and Behavioral Sciences, MIND Institute, University of California Davis, Sacramento, California, USA
| | - Rebecca J Schmidt
- Department of Public Health Sciences, MIND Institute, University of California Davis, Sacramento, California, USA
| | - Heather E Volk
- Wendy Klag Center for Autism and Developmental Disabilities Research, Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Alison E Hipwell
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Kelsey E Magee
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Margaret Karagas
- Department of Epidemiology, Dartmouth Geisel School of Medicine, Hanover, New Hampshire, USA
| | - Cindy McEvoy
- Department of Pediatrics, Papé Pediatric Research Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Rebecca Landa
- Center for Autism Services, Science and Innovation, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Michael R Elliott
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan, USA
| | - Daphne Koinis Mitchell
- Bradley-Hasbro Research Center and the Department of Pediatrics, Rhode Island Hospital and the Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Viren D'Sa
- Bradley-Hasbro Research Center and the Department of Pediatrics, Rhode Island Hospital and the Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Sean Deoni
- Bradley-Hasbro Research Center and the Department of Pediatrics, Rhode Island Hospital and the Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Michelle Pievsky
- Department of Psychiatry and Human Behavior, Hasbro Children's Hospital, Providence, Rhode Island, USA
| | - Pei-Chi Wu
- Bradley-Hasbro Research Center and the Department of Pediatrics, Rhode Island Hospital and the Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Fatoumata Barry
- Bradley-Hasbro Research Center and the Department of Pediatrics, Rhode Island Hospital and the Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Joseph B Stanford
- Department of Family and Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Deborah A Bilder
- Department of Psychiatry, University of Utah Huntsman Mental Health Institute, Salt Lake City, Utah, USA
| | - Leonardo Trasande
- Department of Pediatrics, New York University Grossman School of Medicine, New York, New York, USA
| | - Nicole R Bush
- Department of Psychiatry and Behavioral Sciences, Department of Pediatrics, University of California, San Francisco, California, USA
| | - Kristen Lyall
- AJ Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania, USA
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Arman S. What is the overall prognosis of preschool autism spectrum disorder diagnoses? A Cochrane Review summary with commentary. Dev Med Child Neurol 2024; 66:13-15. [PMID: 37837302 DOI: 10.1111/dmcn.15775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023]
Affiliation(s)
- Sina Arman
- Department of Physical Medicine and Rehabilitation, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
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Cirnigliaro L, Valle MS, Casabona A, Randazzo M, La Bruna F, Pettinato F, Narzisi A, Rizzo R, Barone R. The Developmental Autism Early Screening (DAES): A Novel Test for Screening Autism Spectrum Disorder. J Autism Dev Disord 2023:10.1007/s10803-023-06184-3. [PMID: 38109035 DOI: 10.1007/s10803-023-06184-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/05/2023] [Indexed: 12/19/2023]
Abstract
This study was undertaken to set a novel developmental screening test for autism spectrum disorder (ASD) using the Griffiths Scales of Child Development (Griffith III) (Green et al., 2016; Stroud et al., 2016), in order to intercept the early atypical developmental patterns indicating ASD risk in the first 3 years of age. An observational and interactive ASD screener, the Developmental Autism Early Screening (DAES), was developed by detecting Griffiths III items differentiating toddlers with ASD risk from those with global developmental delay (DD) or neurotypical development. The DAES was validated with ASD-specific diagnostic instruments (ADOS-2) and the cut-off score based on sensitivity, specificity and positive predictive value that best differentiates between ASD and non-ASD children was identified. We enrolled a total sample of 297 subjects, including children at risk for ASD or DD and neurotypical children. At a cut-off score of 12.5, the DAES had a sensitivity of 93%, specificity of 98.4%, positive predictive value of 96.3% and negative predictive value of 96.9% for identifying children at risk for ASD from non-ASD participants (DD/neurotypical children). The DAES total score correlated significantly with the ADOS-2 calibrated severity scores (CSS) (R = 0.53, p < 0.001). Three ASD risk ranges were identified according to DAES total and ADOS-2 CSS: Little-to-no risk (CSS: 1-3, DAES: 1-7); Mild-to-moderate risk (CSS: 4-5, DAES: 8-14); Moderate-to-severe risk (CSS: 6-10, DAES ≥ 15). The DAES provides a direct approach based on developmental profiles to stratify risk for ASD in early childhood ensuring at risk children the most appropriate diagnostic procedures and targeted intervention.
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Affiliation(s)
- Lara Cirnigliaro
- Child Neurology and Psychiatry Unit, Department of Clinical and Experimental Medicine, University of Catania, Policlinico Via Santa Sofia, 78, 95123, Catania, Italy
| | - Maria Stella Valle
- Laboratory of Neuro-Biomechanics, Department of Biomedical and Biotechnological Sciences, School of Medicine, University of Catania, Catania, Italy
| | - Antonino Casabona
- Laboratory of Neuro-Biomechanics, Department of Biomedical and Biotechnological Sciences, School of Medicine, University of Catania, Catania, Italy
| | - Martina Randazzo
- Child Neurology and Psychiatry Unit, Department of Clinical and Experimental Medicine, University of Catania, Policlinico Via Santa Sofia, 78, 95123, Catania, Italy
| | - Francesca La Bruna
- Child Neurology and Psychiatry Unit, Department of Clinical and Experimental Medicine, University of Catania, Policlinico Via Santa Sofia, 78, 95123, Catania, Italy
| | - Fabio Pettinato
- Child Neurology and Psychiatry Unit, Department of Clinical and Experimental Medicine, University of Catania, Policlinico Via Santa Sofia, 78, 95123, Catania, Italy
| | | | - Renata Rizzo
- Child Neurology and Psychiatry Unit, Department of Clinical and Experimental Medicine, University of Catania, Policlinico Via Santa Sofia, 78, 95123, Catania, Italy
| | - Rita Barone
- Child Neurology and Psychiatry Unit, Department of Clinical and Experimental Medicine, University of Catania, Policlinico Via Santa Sofia, 78, 95123, Catania, Italy.
- Reseach Unit of Rare Diseases and Neurodevelopmental Disorders, Oasi Research Institute-IRCCS, Troina, Italy.
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Finding the Proportion of Females with Autistic Spectrum Disorder Who Develop Anorexia Nervosa, the True Prevalence of Female ASD and Its Clinical Significance. CHILDREN (BASEL, SWITZERLAND) 2023; 10:children10020272. [PMID: 36832401 PMCID: PMC9955974 DOI: 10.3390/children10020272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 01/24/2023] [Accepted: 01/27/2023] [Indexed: 02/04/2023]
Abstract
It appears that up to 80% of females with autistic spectrum disorder (ASD) have not been diagnosed by the age of 18. This translates to a prevalence of about 5-6%, and if true, has serious implications for female mental health. One way of finding the true value is to use Bayes' Theorem with a comorbid condition as a more easily recognizable flag. An obvious choice is anorexia nervosa (AN), but it transpires that the proportion of women with ASD who develop AN is unknown. This study uses published data in novel ways to provide two methods of estimating a range for this variable, and gives a median value of 8.3% for AN in ASD and, with four other methods, a median prevalence of 6% for female ASD. The clinical implications of the diagnosis and management of ASD and its comorbidities are discussed and, as an example, a solution is provided for the rate of ASD in symptomatic generalized joint hypermobility. It is probable that one in six women with a mental health condition is autistic.
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