Heterogeneity thwarts autism explanatory power: A proposal for endophenotypes.
Ditch the single 'autism' label and screen for shared trait clusters that point to real treatment targets.
01Research in Context
What this study did
Waterhouse (2022) wrote a position paper. It says the word 'autism' hides too many kinds of kids. The paper urges teams to stop using the single label and to hunt for smaller, shared traits called endophenotypes.
These traits can show up in autism, ADHD, or language disorder. Finding them could show who will really benefit from which treatment.
What they found
The paper did not test kids. Instead it argues that the wide spread of symptoms blocks new treatments. Until we split the wide group into smaller, trait-based buckets, trials will keep failing.
How this fits with other research
Provenzani et al. (2020) counted 327 different outcome tools in 406 autism trials. That mess is the exact problem Waterhouse says endophenotypes could tidy up.
Dubuque (2015) warned that biomarker tests for 'autism' were rushed and possibly harmful. Waterhouse agrees biomarkers are premature but offers endophenotypes as a safer next step.
Rutter (2013) already asked the field to rethink autism. Waterhouse turns that old call into a concrete plan: screen across diagnoses and cluster by shared traits.
Why it matters
If you write protocols, intake forms, or treatment plans, stop relying only on the autism checkbox. Add broad screens for language, attention, and sensory traits that cross labels. Push your team to record the same core measures each time so your data can join future endophenotype work.
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Add one transdiagnostic question set (attention, language, sensory) to your intake and track scores for future grouping.
02At a glance
03Original abstract
Many researchers now believe that autism heterogeneity is likely to include many disorders, but most research is based on samples defined by the DSM-5 Autism Spectrum Disorder (ASD) criteria. However, individuals diagnosed with autism have complex and varied biological causes for their symptoms. Therefore, autism is not a unitary biological entity. And although autism is significantly different from typical development, autism is not a unitary clinical disorder because diagnosed individuals vary in symptom patterns, comorbidities, biomarkers, and gene variants. The DSM-5 ASD criteria were designed to reduce heterogeneity, and there have been many other efforts to reduce autism heterogeneity including using more stringent clinical criteria, dividing autism into low and high functioning groups, creating subgroups, and by studying larger samples. However, to date these efforts have not been successful. Heterogeneity is extensive and remains unexplained, and no autism pathophysiology has been discovered. Most importantly, heterogeneity has hindered the explanatory power of the autism diagnosis to discover drug regimens and effective behavioral treatments. The paper proposes that possible transdiagnostic endophenotypes may reduce autism heterogeneity. Searching for transdiagnostic endophenotypes requires exploring autism symptoms outside of the framework of the DSM-5 autism diagnosis. This paper proposes that researchers relax diagnostic criteria to increase the range of phenotypes to support the search for transdiagnostic endophenotypes. The paper proposes possible candidates for transdiagnostic endophenotypes. These candidates are taken from DSM-5 ASD criteria, from concepts that have resulted from researched theories, and from symptoms that are the result of subtyping. The paper then sketches a possible basis for a future transdiagnostic endophenotypes screening tool that includes symptoms of autism and other neurodevelopmental disorders.
Frontiers in Psychiatry, 2022 · doi:10.3389/fpsyt.2022.947653