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      Heritability of autism spectrum disorders: a meta‐analysis of twin studies

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          Abstract

          Background

          The etiology of Autism Spectrum Disorder ( ASD) has been recently debated due to emerging findings on the importance of shared environmental influences. However, two recent twin studies do not support this and instead re‐affirm strong genetic effects on the liability to ASD, a finding consistent with previous reports. This study conducts a systematic review and meta‐analysis of all twin studies of ASD published to date and explores the etiology along the continuum of a quantitative measure of ASD.

          Methods

          A PubMed Central, Science Direct, Google Scholar, Web of Knowledge structured search conducted online, to identify all twin studies on ASD published to date. Thirteen primary twin studies were identified, seven were included in the meta‐analysis by meeting Systematic Recruitment criterion; correction for selection and ascertainment strategies, and applied prevalences were assessed for these studies. In addition, a quantile DF extremes analysis was carried out on Childhood Autism Spectrum Test scores measured in a population sample of 6,413 twin pairs including affected twins.

          Results

          The meta‐analysis correlations for monozygotic twins ( MZ) were almost perfect at .98 (95% Confidence Interval, .96–.99). The dizygotic ( DZ) correlation, however, was .53 (95% CI .44–.60) when ASD prevalence rate was set at 5% (in line with the Broad Phenotype of ASD) and increased to .67 (95% CI .61–.72) when applying a prevalence rate of 1%. The meta‐analytic heritability estimates were substantial: 64–91%. Shared environmental effects became significant as the prevalence rate decreased from 5–1%: 07–35%. The DF analyses show that for the most part, there is no departure from linearity in heritability.

          Conclusions

          We demonstrate that: (a) ASD is due to strong genetic effects; (b) shared environmental effects become significant as a function of lower prevalence rate; (c) previously reported significant shared environmental influences are likely a statistical artefact of overinclusion of concordant DZ twins.

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          Most cited references15

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          Autism as a strongly genetic disorder: evidence from a British twin study.

          Two previous epidemiological studies of autistic twins suggested that autism was predominantly genetically determined, although the findings with regard to a broader phenotype of cognitive, and possibly social, abnormalities were contradictory. Obstetric and perinatal hazards were also invoked as environmentally determined aetiological factors. The first British twin sample has been re-examined and a second total population sample of autistic twins recruited. In the combined sample 60% of monozygotic (MZ) pairs were concordant for autism versus no dizygotic (DZ) pairs; 92% of MZ pairs were concordant for a broader spectrum of related cognitive or social abnormalities versus 10% of DZ pairs. The findings indicate that autism is under a high degree of genetic control and suggest the involvement of multiple genetic loci. Obstetric hazards usually appear to be consequences of genetically influenced abnormal development, rather than independent aetiological factors. Few new cases had possible medical aetiologies, refuting claims that recognized disorders are common aetiological influences.
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            Heritability of Autism Spectrum Disorder in a UK Population-Based Twin Sample.

            Most evidence to date highlights the importance of genetic influences on the liability to autism and related traits. However, most of these findings are derived from clinically ascertained samples, possibly missing individuals with subtler manifestations, and obtained estimates may not be representative of the population. To establish the relative contributions of genetic and environmental factors in liability to autism spectrum disorder (ASD) and a broader autism phenotype in a large population-based twin sample and to ascertain the genetic/environmental relationship between dimensional trait measures and categorical diagnostic constructs of ASD. We used data from the population-based cohort Twins Early Development Study, which included all twin pairs born in England and Wales from January 1, 1994, through December 31, 1996. We performed joint continuous-ordinal liability threshold model fitting using the full information maximum likelihood method to estimate genetic and environmental parameters of covariance. Twin pairs underwent the following assessments: the Childhood Autism Spectrum Test (CAST) (6423 pairs; mean age, 7.9 years), the Development and Well-being Assessment (DAWBA) (359 pairs; mean age, 10.3 years), the Autism Diagnostic Observation Schedule (ADOS) (203 pairs; mean age, 13.2 years), the Autism Diagnostic Interview-Revised (ADI-R) (205 pairs; mean age, 13.2 years), and a best-estimate diagnosis (207 pairs). Participants underwent screening using a population-based measure of autistic traits (CAST assessment), structured diagnostic assessments (DAWBA, ADI-R, and ADOS), and a best-estimate diagnosis. On all ASD measures, correlations among monozygotic twins (range, 0.77-0.99) were significantly higher than those for dizygotic twins (range, 0.22-0.65), giving heritability estimates of 56% to 95%. The covariance of CAST and ASD diagnostic status (DAWBA, ADOS and best-estimate diagnosis) was largely explained by additive genetic factors (76%-95%). For the ADI-R only, shared environmental influences were significant (30% [95% CI, 8%-47%]) but smaller than genetic influences (56% [95% CI, 37%-82%]). The liability to ASD and a more broadly defined high-level autism trait phenotype in this large population-based twin sample derives primarily from additive genetic and, to a lesser extent, nonshared environmental effects. The largely consistent results across different diagnostic tools suggest that the results are generalizable across multiple measures and assessment methods. Genetic factors underpinning individual differences in autismlike traits show considerable overlap with genetic influences on diagnosed ASD.
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              Autism diagnostic observation schedule: a standardized observation of communicative and social behavior.

              The Autism Diagnostic Observation Schedule (ADOS), a standardized protocol for observation of social and communicative behavior associated with autism, is described. The instrument consists of a series of structured and semistructured presses for interaction, accompanied by coding of specific target behaviors associated with particular tasks and by general ratings of the quality of behaviors. Interrater reliability for five raters exceeded weighted kappas of .55 for each item and each pair of raters for matched samples of 15 to 40 autistic and nonautistic, mildly mentally handicapped children (M IQ = 59) between the ages of 6 and 18 years. Test-retest reliability was adequate. Further analyses compared these groups to two additional samples of autistic and nonautistic subjects with normal intelligence (M IQ = 95), matched for sex and chronological age. Analyses yielded clear diagnostic differences in general ratings of social behavior, specific aspects of communication, and restricted or stereotypic behaviors and interests. Clinical guidelines for the diagnosis of autism in the draft version of ICD-10 were operationalized in terms of abnormalities on specific ADOS items. An algorithm based on these items was shown to have high reliability and discriminant validity.
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                Author and article information

                Journal
                J Child Psychol Psychiatry
                J Child Psychol Psychiatry
                10.1111/(ISSN)1469-7610
                JCPP
                Journal of Child Psychology and Psychiatry, and Allied Disciplines
                John Wiley and Sons Inc. (Hoboken )
                0021-9630
                1469-7610
                27 December 2015
                May 2016
                : 57
                : 5 ( doiID: 10.1111/jcpp.2016.57.issue-5 )
                : 585-595
                Affiliations
                [ 1 ] MRC Social, Genetic and Developmental Psychiatry Centre IOPPNKing's College London LondonUK
                Author notes
                [*] [* ] Correspondence

                Frühling Rijsdijk, MRC Social, Genetic and Developmental Psychiatry Centre, IOPPN, King's College London, 16 DeCrespigny Park, Denmark Hill, London SE5 8AF, UK; Email: fruhling.rijsdijk@ 123456kcl.ac.uk

                [†]

                Joint first authors.

                Article
                JCPP12499
                10.1111/jcpp.12499
                4996332
                26709141
                7d4fec6f-2189-453b-b67b-fde251815888
                © 2015 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 October 2015
                Page count
                Pages: 11
                Funding
                Funded by: Medical Research Council 1 + 3 PhD studentship
                Award ID: MR/J500380/1
                Funded by: National Institute Health Research Senior Investigator Award & Biomedical Research Centre in Mental Health at the South London & Maudsley National Health Service UK Foundation Trust
                Funded by: UK Medical Research Council (MRC)
                Award ID: G0500870
                Award ID: G0901245
                Award ID: previously G0500079
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                jcpp12499
                May 2016
                Converter:WILEY_ML3GV2_TO_NLMPMC version:4.9.4 mode:remove_FC converted:24.08.2016

                Clinical Psychology & Psychiatry
                autism spectrum disorders,meta‐analysis,heritability,twin studies,df extremes analysis

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