Clinical correlates of diagnostic certainty in children and youths with Autistic Disorder.

BACKGROUND: Clinicians diagnosing autism rely on diagnostic criteria and instruments in combination with an implicit knowledge based on clinical expertise of the specific signs and presentations associated with the condition. This implicit knowledge influences how diagnostic criteria are interpreted, but it cannot be directly observed. Instead, insight into clinicians' understanding of autism can be gained by investigating their diagnostic certainty. Modest correlations between the certainty of an autism diagnosis and symptom load have been previously reported. Here, we investigated the associations of diagnostic certainty with specific items of the ADOS as well as other clinical features including head circumference. METHODS: Phenotypic data from the Simons Simplex Collection was used to investigate clinical correlates of diagnostic certainty in individuals diagnosed with Autistic Disorder (n = 1511, age 4 to 18 years). Participants were stratified by the ADOS module used to evaluate them. We investigated how diagnostic certainty was associated with total ADOS scores, age, and ADOS module. We calculated the odds-ratios of being diagnosed with the highest possible certainty given the presence or absence of different signs during the ADOS evaluation. Associations between diagnostic certainty and other cognitive and clinical variables were also assessed. RESULTS: In each ADOS module, some items showed a larger association with diagnostic certainty than others. Head circumference was significantly higher for individuals with the highest certainty rating across all three ADOS modules. In turn, head circumference was positively correlated with some of the ADOS items that were associated with diagnostic certainty, and was negatively correlated with verbal/nonverbal IQ ratio among those assessed with ADOS module 2. LIMITATIONS: The investigated cohort was heterogeneous, e.g. in terms of age, IQ, language level, and total ADOS score, which could impede the identification of associations that only exist in a subgroup of the population. The variability of the certainty ratings in the sample was low, limiting the power to identify potential associations with other variables. Additionally, the scoring of diagnostic certainty may vary between clinicians. CONCLUSION: Some ADOS items may better capture the signs that are most associated with clinicians' implicit knowledge of Autistic Disorder. If replicated in future studies, new diagnostic instruments with differentiated weighting of signs may be needed to better reflect this, possibly resulting in better specificity in standardized assessments.

Genesis, modelling and methodological remedies to autism heterogeneity.

Diagnostic criteria used in autism research have undergone a shift towards the inclusion of a larger population, paralleled by increasing, but variable, estimates of autism prevalence across clinical settings and continents. A categorical diagnosis of autism spectrum disorder is now consistent with large variations in language, intelligence, comorbidity, and severity, leading to a heterogeneous sample of individuals, increasingly distant from the initial prototypical descriptions. We review the history of autism diagnosis and subtyping, and the evidence of heterogeneity in autism at the cognitive, neurological, and genetic levels. We describe two strategies to address the problem of heterogeneity: clustering, and truncated-compartmentalized enrollment strategy based on prototype recognition. The advances made using clustering methods have been modest. We present an alternative, new strategy for dissecting autism heterogeneity, emphasizing incorporation of prototypical samples in research cohorts, comparison of subgroups defined by specific ranges of values for the clinical specifiers, and retesting the generality of neurobiological results considered to be acquired from the entire autism spectrum on prototypical cohorts defined by narrow specifiers values.

Representativeness of autistic samples in studies recruiting through social media.

Survey-based research with recruitment through online channels is a convenient way to obtain large samples and has recently been increasingly used in autism research. However, sampling from online channels may be associated with a high risk of sampling bias causing findings not to be generalizable to the autism population. Here we examined autism studies that have sampled on social media for markers of sampling bias. Most samples showed one or more indicators of sampling bias, in the form of reversed sex ratio, higher employment rates, higher education level, lower fraction of individuals with intellectual disability, and later age of diagnosis than would be expected when comparing with for example population study results from published research. Findings from many of the included studies are therefore difficult to generalize to the broader autism population. Suggestions for how research strategies may be adapted to address some of the problems are discussed. LAY SUMMARY: Online surveys offer a convenient way to recruit large numbers of participants for autism research. However, the resulting samples may not fully reflect the autism population. Here we investigated the samples of 36 autism studies that recruited participants online and found that the demographic composition tended to deviate from what has been reported about the autism population in previous research. The results may thus not be generalizable to autism in general.

Childhood diagnoses in individuals identified as autistics in adulthood.

BACKGROUND: Autism is a developmental condition, where symptoms are expected to occur in childhood, but a significant number of individuals are diagnosed with autism for the first time in adulthood. Here, we examine diagnoses given in childhood among individuals that are diagnosed with autism in adulthood, to investigate whether the late autism diagnosis might be explained by misdiagnosis in childhood or diagnostic overshadowing. METHODS: Through the Danish National Patient Registry, we identified individuals diagnosed with autism in adulthood (N = 2199), as well as a control sample with no records of an autism diagnosis (N = 460,798) and calculated how many had received different psychiatric or neurological diagnoses in childhood. RESULTS: We found that most childhood diagnoses were overrepresented in those with an adult autism diagnosis, and attention-deficit hyperactivity disorder, affective disorders, anxiety, and stress disorders were the most prevalent childhood conditions in this group. However, 69% of males and 61% of females with adult autism diagnoses were not found to have received any of the investigated diagnoses before 18 years of age, and most childhood diagnoses were given after the age of 12. LIMITATIONS: Milder to moderate cases of psychiatric conditions that have been solely treated by family physicians or school psychologists may not be fully included in our dataset. The study is based on data from the Danish health care system, and further research is needed to assess whether the findings can be generalized to other countries. CONCLUSION: A majority of those with an adult autism diagnosis had no records of having received any of the investigated diagnoses in childhood. In these cases, the late autism diagnosis is therefore unlikely to be explained by either misdiagnosis or overshadowing. This result is at odds with the prevailing notion that autistic symptoms tend to diminish with age. Therefore, further research is warranted to examine how and if early signs of autism may have manifested among these individuals, and how similar they are to autistic people diagnosed earlier in their development.

Autism comorbidities show elevated female-to-male odds ratios and are associated with the age of first autism diagnosis.

OBJECTIVE: To investigate the association between the comorbidity rates in autism and sex, birth year and the age at which autism was first diagnosed and compare the relative impact of each. METHOD: Using the Danish National Patient Registry, cumulative incidences up to the age of 16 for 11 comorbid conditions (psychosis, affective disorders, anxiety disorders, conduct disorder, eating disorders, obsessive-compulsive disorder, attention-deficit hyperactivity disorder, epilepsy, tic disorders, sleep disorders or intellectual disability) were calculated for individuals with autism (N = 16,126) and non-autism individuals (N = 654,977). Individuals were further stratified based on the age at the first autism diagnoses and comorbid diagnoses up to the age of 16 were compared. RESULTS: Most comorbidities were significantly associated with birth year and sex. Female/male odds ratios for 8 of 11 comorbid conditions were up to 67% higher than the corresponding odds ratios in the non-autism population, including conditions that are generally more common in males than in females as well as conditions that are more common in females. All comorbidity rates were significantly associated with the age at the first autism diagnosis, which was a stronger predictor than sex and birth year for 8 conditions. CONCLUSIONS: Comorbidity rates for females exceed what would be expected based on the sex ratios among non-autistic individuals, indicating that the association between autism and comorbidity is stronger in females. Comorbidity rates are also highly dependent on the age at the first autism diagnosis, which may contribute to autism heterogeneity in research and clinical practice.

An opposite pattern of cognitive performance in autistic individuals with and without alexithymia.

Oakley, Brewer, Bird, and Catmur (2016) investigated whether the Reading the Minds in the Eyes Test (RMET) measures emotion recognition rather than theory of mind (ToM). To explore this, 19 participants with autism and 23 controls, matched on alexithymia traits, were tested with the RMET, as well as the ToM Movie for Assessment of Social Cognition (MASC). The authors found a significant difference between the two groups on the MASC but not on the RMET, but dividing the groups based on alexithymia resulted in a significantly lower performance on the RMET but not on the MASC for the alexithymia group. Therefore, they conclude that difficulties on the RMET are associated with alexithymia, not autism, while difficulties on the MASC are associated with autism, not alexithymia. Here we investigated what seems to be opposite patterns of performance on the two cognitive tasks within the autism group, which modified the authors' interpretation of their data. This was examined by correlating the alexithymia scores with the RMET and a subscale of the MASC scores, referred to as the cognitive MASC. We found a negative correlation between the alexithymia score and the RMET score while also finding a positive correlation between the alexithymia score and the cognitive MASC score in the autism group. Such an opposite pattern of performance suggests the presence of distinct patterns of ToM difficulties within the autism group. This also indicates that, contrary to what is reported by Oakley et al., there is an association between alexithymia and the MASC within the autism group. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Temporal Changes in Effect Sizes of Studies Comparing Individuals With and Without Autism: A Meta-analysis.

Importance: The definition and nature of autism have been highly debated, as exemplified by several revisions of the DSM (DSM-III, DSM-IIIR, DSM-IV, and DSM-5) criteria. There has recently been a move from a categorical view toward a spectrum-based view. These changes have been accompanied by a steady increase in the prevalence of the condition. Changes in the definition of autism that may increase heterogeneity could affect the results of autism research; specifically, a broadening of the population with autism could result in decreasing effect sizes of group comparison studies. Objective: To examine the correlation between publication year and effect size of autism-control group comparisons across several domains of published autism neurocognitive research. Data Sources: This meta-analysis investigated 11 meta-analyses obtained through a systematic search of PubMed for meta-analyses published from January 1, 1966, through January 27, 2019, using the search string autism AND (meta-analysis OR meta-analytic). The last search was conducted on January 27, 2019. Study Selection: Meta-analyses were included if they tested the significance of group differences between individuals with autism and control individuals on a neurocognitive construct. Meta-analyses were only included if the tested group difference was significant and included data with a span of at least 15 years. Data Extraction and Synthesis: Data were extracted and analyzed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline using fixed-effects models. Main Outcomes and Measures: Estimated slope of the correlation between publication year and effect size, controlling for differences in methods, sample size, and study quality. Results: The 11 meta-analyses included data from a total of 27 723 individuals. Demographic data such as sex and age were not available for the entire data set. Seven different psychological and neurologic constructs were analyzed based on data from these meta-analyses. Downward temporal trends for effect size were found for all constructs (slopes: -0.067 to -0.003), with the trend being significant in 5 of 7 cases: emotion recognition (slope: -0.028 [95% CI, -0.048 to -0.007]), theory of mind (-0.045 [95% CI, -0.066 to -0.024]), planning (-0.067 [95% CI, -0.125 to -0.009]), P3b amplitude (-0.048 [95% CI, -0.093 to -0.004]), and brain size (-0.047 [95% CI, -0.077 to -0.016]). In contrast, 3 analogous constructs in schizophrenia, a condition that is also heterogeneous but with no reported increase in prevalence, did not show a similar trend. Conclusions and Relevance: The findings suggest that differences between individuals with autism and those without the diagnosis have decreased over time and that possible changes in the definition of autism from a narrowly defined and homogenous population toward an inclusive and heterogeneous population may reduce our capacity to build mechanistic models of the condition.