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Differential diagnosis of autism is very complex. Best practice guidelines in the US encourage the use of specialized tools by a highly trained provider. The need for this comprehensive evaluation, coupled with the increase in autism prevalence and awareness, has led to alarmingly long wait times for diagnostic evaluations. Several solutions are currently being researched to remedy this problem and relieve the pressure, including testing new devices or procedures that can speed up the diagnostic process. Creative solutions are welcomed; however, we urge caution in the use of new devices and methods without being fully vetted. Moreover, a quality assessment provides much more than just a designation of whether or not autism is present. Thus, even in cases when alternative means could be used to more quickly arrive at a diagnosis, a comprehensive assessment with a trained clinician is needed to guide recommendations and ongoing care.

Autism Spectrum Disorder (ASD or autism) is a heterogeneous neurodevelopmental disorder. We are now at a critical juncture in autism research where we have the knowledge base and expertise to begin to think about studies that view heterogeneity, not as 'statistical noise' that can be 'accounted for' using data-reduction techniques (such as group trajectories), but rather as 'informative variance' that can help form a more precise and dynamic picture of autism. In this Editorial we coin a new term and introduce the concept of 'chronogeneity' for the study of autism heterogeneity in relation to the dimension of time (chrono). Using examples of ongoing research and analytical advances we build the case for the potential utility of the concept of 'chronogeneity' and argue that a refined approach to the longitudinal investigation of autism (and other neurodevelopmental disorders) may move us closer to more precise and adaptive models of care for the children and youth affected by these disorders.

Background: The Social Responsiveness Scale (SRS) is a parent-completed screening questionnaire often used to measure autism spectrum disorders (ASD) severity. Although child characteristics are known to influence scores from other ASD-symptom measures, as well as parent-questionnaires more broadly, there has been limited consideration of how non-ASD-specific factors may affect interpretation of SRS scores. Previous studies have explored effects of behavior problems on SRS specificity, but have not addressed influences on the use of the SRS as a quantitative measure of ASD-symptoms. Method: Raw scores (SRS-Raw) from parent-completed SRS were analyzed for 2,368 probands with ASD and 1,913 unaffected siblings. Regression analyses were used to assess associations between SRS scores and demographic, language, cognitive, and behavior measures. Results: For probands, higher SRS-Raw were associated with greater non-ASD behavior problems, higher age, and more impaired language and cognitive skills, as well as scores from other parent report measures of social development and ASD-symptoms. For unaffected siblings, having more behavior problems predicted higher SRS-Raw; male gender, younger age, and poorer adaptive social and expressive communication skills also showed small, but significant effects. Conclusions: When using the SRS as a quantitative phenotype measure, the influence of behavior problems, age, and expressive language or cognitive level on scores must be considered. If effects of non-ASD-specific factors are not addressed, SRS scores are more appropriately interpreted as indicating general levels of impairment, than as severity of ASDspecific symptoms or social impairment. Additional research is needed to consider how these factors influence the SRS’ sensitivity and specificity in large, clinical samples including individuals with disorders other than ASD. Keywords: Social Responsiveness Scale, autism spectrum disorder, behavior problems, age, language level.