In their analysis of the accumulated data from the clinically ascertained Simons Simplex Collection (SSC), Hus et al. (2013) provide a large-scale clinical replication of previously reported associations (see Constantino, Hudziak & Todd, 2003) between quantitative autistic traits [as measured by the Social Responsiveness Scale (SRS)] and variation in behavior problem symptomatology, using one of the most widely used instruments in the world, the Child Behavior Checklist (CBCL). One of the more resounding affirmations of such an association comes from a recently published analysis of genetically informative data involving some 20,000 children and adults, demonstrating that the genetic influences on autistic syndromes substantially overlap with those influencing attention deficit hyperactivity disorder and other psychiatric syndromes (Lundstrom et al., 2011). Reexamination of the association between autistic traits and other behavioral symptoms in a large clinical sample affords a unique window of observation on the nature of overlap of neuropsychiatric syndromes. In this commentary, the authors address a central question that cannot be resolved by the design of the Hus et al. (2013) study, namely,whether the causal arrow points in the opposite direction, that is, the behavioral symptoms, which appear to "predict" autistic severity scores on the SRS, might actually be caused by the autistic syndrome. The authors also state that, beyond the issue of the direction of causality, the analyses presented in Hus et al. (2013) evoke several important caveats when evaluating overlap in psychopathology constructs. One the authors address is the purpose for which a given measurement instrument is most applicable within a given sample. Another is that the Hus et al. (2013) analyses raise additional psychometric and analytic issues, such as rater influences on construct measurement, evaluation of the magnitude of correlation in samples with wide versus narrow symptom ranges, and the effects of missing data on bivariate correlations and multivariate regressions. Another addressed by the authors concerns the potential trade-offs in specificity that are incurred by the implementation of brief measurement methods. The authors conclude by noting that time will tell what the boundaries of autism are and are not, and those boundaries are changing more rapidly than even the most judicious revisions to diagnostic instruments can keep pace with. In the meantime, ascertainment of severity in autism might best remain broadly conceived, flexible, and inclusive.