Fiona McEwen

Heritability of Autism Spectrum Disorder in a UK Population-Based Twin Sample

IMPORTANCE 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. OBJECTIVES 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. DESIGN, SETTING, AND PARTICIPANTS 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). MAIN OUTCOMES AND MEASURES 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. RESULTS 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%]). CONCLUSIONS AND RELEVANCE 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.

Predicting the diagnosis of autism in adults using the Autism-Spectrum Quotient (AQ) questionnaire

Background Many adults with autism spectrum disorder (ASD) remain undiagnosed. Specialist assessment clinics enable the detection of these cases, but such services are often overstretched. It has been proposed that unnecessary referrals to these services could be reduced by prioritizing individuals who score highly on the Autism-Spectrum Quotient (AQ), a self-report questionnaire measure of autistic traits. However, the ability of the AQ to predict who will go on to receive a diagnosis of ASD in adults is unclear. Method We studied 476 adults, seen consecutively at a national ASD diagnostic referral service for suspected ASD. We tested AQ scores as predictors of ASD diagnosis made by expert clinicians according to International Classification of Diseases (ICD)-10 criteria, informed by the Autism Diagnostic Observation Schedule-Generic (ADOS-G) and Autism Diagnostic Interview-Revised (ADI-R) assessments. Results Of the participants, 73% received a clinical diagnosis of ASD. Self-report AQ scores did not significantly predict receipt of a diagnosis. While AQ scores provided high sensitivity of 0.77 [95% confidence interval (CI) 0.72–0.82] and positive predictive value of 0.76 (95% CI 0.70–0.80), the specificity of 0.29 (95% CI 0.20–0.38) and negative predictive value of 0.36 (95% CI 0.22–0.40) were low. Thus, 64% of those who scored below the AQ cut-off were ‘false negatives’ who did in fact have ASD. Co-morbidity data revealed that generalized anxiety disorder may ‘mimic’ ASD and inflate AQ scores, leading to false positives. Conclusions The AQs utility for screening referrals was limited in this sample. Recommendations supporting the AQs role in the assessment of adult ASD, e.g. UK NICE guidelines, may need to be reconsidered.

Diagnosing Autism Spectrum Disorder in community settings using the development and well-being assessment: validation in a UK population-based twin sample

Background Increasing numbers of people are being referred for the assessment of autism spectrum disorder (ASD). The NICE (UK) and the American Academy of Pediatrics recommend gathering a developmental history using a tool that operationalises ICD/DSM criteria. However, the best‐established diagnostic interview instruments are time consuming, costly and rarely used outside national specialist centres. What is needed is a brief, cost‐effective measure validated in community settings. We tested the Development and Well‐Being Assessment (DAWBA) for diagnosing ASD in a sample of children/adolescents representative of those presenting in community mental health settings. Methods A general population sample of twins (TEDS) was screened and 276 adolescents were selected as at low (CAST score < 12; n = 164) or high risk for ASD (CAST score ≥ 15 and/or parent reported that ASD suspected/previously diagnosed; n = 112). Parents completed the ASD module of the DAWBA interview by telephone or online. Families were visited at home: the ADI‐R and autism diagnostic observation schedule (ADOS) were completed to allow a best‐estimate research diagnosis of ASD to be made. Results Development and Well‐Being Assessment ASD symptom scores correlated highly with ADI‐R algorithm scores (ρ = .82, p < .001). Good sensitivity (0.88) and specificity (0.85) were achieved using DAWBA computerised algorithms. Clinician review of responses to DAWBA questions minimally changed sensitivity (0.86) and specificity (0.87). Positive (0.82–0.95) and negative (0.90) predictive values were high. Eighty‐six per cent of children were correctly classified. Performance was improved by using it in conjunction with the ADOS. Conclusions The DAWBA is a brief structured interview that showed good sensitivity and specificity in this general population sample. It requires little training, is easy to administer (online or by interview) and diagnosis is aided by an algorithm. It holds promise as a tool for assisting with assessment in community settings and may help services implement the recommendations made by NICE and the American Academy of Pediatrics regarding diagnosis of young people on the autism spectrum.

Is childhood cruelty to animals a marker for physical maltreatment in a prospective cohort study of children

Childhood cruelty to animals is thought to indicate that a child may have been maltreated. This study examined: (a) prevalence of cruelty to animals among 5- to 12-year-old children; (b) the association between cruelty to animals, child physical maltreatment, and adult domestic violence; and (c) whether cruelty to animals is a marker of maltreatment taking into account age, persistence of cruelty, and socioeconomic disadvantage. Data were from the Environmental Risk (E-Risk) Longitudinal Twin Study, an epidemiological representative cohort of 2,232 children living in the United Kingdom. Mothers reported on cruelty to animals when children were 5, 7, 10, and 12 years, on child maltreatment up to age 12, and adult domestic violence. Nine percent of children were cruel to animals during the study and 2.6% persistently (≥2 time-points). Children cruel to animals were more likely to have been maltreated than other children (OR=3.32) although the majority (56.4%) had not been maltreated. Animal cruelty was not associated with domestic violence when maltreatment was controlled for. In disadvantaged families, 6 in 10 children cruel to animals had been maltreated. In other families, the likelihood of maltreatment increased with age (from 3 in 10 5-year-olds to 4.5 in 10 12-year-olds) and persistence (4.5 in 10 of those persistently cruel). Although childhood cruelty to animals is associated with maltreatment, not every child showing cruelty had been maltreated. The usefulness of cruelty to animals as a marker for maltreatment increases with the childs age, persistence of behavior, and poorer social background.

Autism Spectrum Disorders and Other Mental Health Problems: Exploring Etiological Overlaps and Phenotypic Causal Associations

OBJECTIVE Recent studies have highlighted the impact of coexisting mental health problems in autism spectrum disorders (ASD). No twin studies to date have reported on individuals meeting diagnostic criteria of ASD. This twin study reports on the etiological overlap between the diagnosis of ASD and emotional symptoms, hyperactivity, and conduct problems measured with the Strengths and Difficulties Questionnaire. METHOD Genetic and environmental influences on the covariance between ASD and coexisting problems were estimated, in line with the correlated risks model prediction. Phenotypic causality models were also fitted to explore alternative explanations of comorbidity: namely, that coexisting problems are the result of or result in ASD symptoms; that they increase recognition of ASD; or that they arise due to an over-observation bias/confusion when differentiating between phenotypes. RESULTS More than 50% of twins with broad spectrum/ASD met the borderline/abnormal levels cut-off criteria for emotional symptoms or hyperactivity, and approximately 25% met these criteria for the 3 reported problems. In comparison, between 13% and 16% of unaffected twins scored above the cut-offs. The phenotypic correlation between ASD and emotional symptoms was explained entirely by genetic influences and accompanied by a moderate genetic correlation (0.42). The opposite was true for the overlap with conduct problems, as nonshared-environmental factors had the strongest impact. For hyperactivity, the best-fitting model suggested a unidirectional phenotypic influence of hyperactivity on ASD. CONCLUSION Our findings suggest a possible effect of hyperactivity on identification of ASD. The lack of genetic influences on conduct problems-ASD overlap further supports the genetic independence of these 2 phenotypes. Finally, the co-occurrence of emotional symptoms in ASD, compared to other co-occurring problems, is completely explained by common genetic effects.

Impact of ASD Traits on Treatment Outcomes of Eating Disorders in Girls

Evidence links high levels of Autism Spectrum Disorder Traits in women with chronicity of anorexia nervosa. This study reports through clinical audit the impact of ASD traits on treatment outcomes of girls who were referred for treatment in a specialist eating disorder service. Presence of current, but not early childhood, ASD traits was elevated in comparison with previously reported community samples. Current ASD traits were correlated with emotional disorders and with need for treatment augmentation (psychiatric inpatient or day patient admission), but this relationship was not significant after the contribution of depression had been controlled for. There was no difference in Morgan Russell Outcomes at discharge for those with high and low current ASD traits. Parent-reported ASD-related developmental difficulties were associated with attenuated change in self-reported cognitive symptoms of AN. This study highlights the need for further understanding of the aetiology, diagnostic significance and predictive utility for future relapse of elevated ASD traits in childhood eating disorders. Copyright

Screening for co-occurring conditions in adults with autism spectrum disorder using the Strengths and Difficulties Questionnaire: a pilot study

Adolescents and adults with autism spectrum disorder (ASD) are at elevated risk of co‐occurring mental health problems. These are often undiagnosed, can cause significant impairment, and place a very high burden on family and carers. Detecting co‐occurring disorders is extremely important. However, there is no validated screening tool for this purpose. The aim of this pilot study is to test the utility of the strengths and difficulties questionnaire (SDQ) to screen for co‐occurring emotional disorders and hyperactivity in adolescents and adults with ASD. The SDQ was completed by 126 parents and 98 individuals with ASD (in 79 cases both parent and self‐report were available from the same families). Inter‐rater reliability, test‐retest stability, internal consistency, and construct validity were examined. SDQ subscales were also compared to clinically utilized measures of emotional disorders and hyperactivity to establish the ability to predict risk of disorder. Inter‐rater reliability (r = 0.42), test‐retest stability (r = 0.64), internal consistency (α = 0.52–0.81) and construct validity (r = 0.42–0.57) for the SDQ subscales were comparable to general population samples. Parent‐ and self‐report SDQ subscales were significantly associated with measures of anxiety, depression and hyperactivity (62–74% correctly classified). Parent‐report performed significantly better than self‐report; adults with ASD under‐reported difficulties. The SDQ shows promise as a simple and efficient way to screen for emotional disorders and hyperactivity in adolescents and adults with ASD that could help reduce the impact of these disorders on individuals and their families. However, further more systematic attempts at validation are warranted. Autism Res 2016, 9: 1353–1363.