A radical change in our autism research strategy is needed: Back to prototypes.
Use expert-chosen prototype cases, not wide DSM lists, to shrink autism heterogeneity in your next study.
01Research in Context
What this study did
Mottron (2021) says autism research is stuck. Too many different kids get the same label.
The paper tells teams to stop using wide DSM nets. Instead, pick clear prototype cases chosen by expert clinicians.
What they found
The author shows that broad groups hide real brain mechanisms. Prototypes cut noise and boost study power.
How this fits with other research
Fein et al. (2021) extend the idea. They add ESSENCE screening and expert-consensus rules.
Constantino (2021) pushes back. They want to split autism by inherited early-risk markers, not symptom prototypes. Both papers want less noise but pick different paths.
Müller et al. (2017) warn keep the ASD label. They fear losing it will slow real-world use. The clash is practical, not scientific.
Why it matters
If you run studies, try pre-screening with clinician-rated prototypes before you enroll. You may see clearer effects with fewer kids. If you teach, know that the field is moving away from one-size-fits-all autism. Watch for new selection tools that mix expert judgment with quick risk markers.
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02At a glance
03Original abstract
The evolution of autism diagnosis, from its discovery to its current delineation using standardized instruments, has been paralleled by a steady increase in its prevalence and heterogeneity. In clinical settings, the diagnosis of autism is now too vague to specify the type of support required by the concerned individuals. In research, the inclusion of individuals categorically defined by over-inclusive, polythetic criteria in autism cohorts results in a population whose heterogeneity runs contrary to the advancement of scientific progress. Investigating individuals sharing only a trivial resemblance produces a large-scale type-2 error (not finding differences between autistic and dominant population) rather than detecting mechanistic differences to explain their phenotypic divergences. The dimensional approach of autism proposed to cure the disease of its categorical diagnosis is plagued by the arbitrariness of the dimensions under study. Here, we argue that an emphasis on the reliability rather than specificity of diagnostic criteria and the misuse of diagnostic instruments, which ignore the recognition of a prototype, leads to confound autism with the entire range of neurodevelopmental conditions and personality variants. We propose centering research on cohorts in which individuals are selected based on their expert judged prototypicality to advance the theoretical and practical pervasive issues pertaining to autism diagnostic thresholds. Reversing the current research strategy by giving more weight to specificity than reliability should increase our ability to discover the mechanisms of autism. LAY SUMMARY: Scientific research into the causes of autism and its mechanisms is carried out on large cohorts of people who are less and less different from the general population. This historical trend may explain the poor harvest of results obtained. Services and intervention are provided according to a diagnosis that now encompasses extremely different individuals. Last, we accept as a biological reality the constant increase over the years in the proportion of autistic people among the general population. These drifts are made possible by the attribution of a diagnosis of autism to people who meet vague criteria, rather than to people who experienced clinicians recognize as autistic. We propose to change our research strategy by focusing on the study of the latter, fewer in number, but more representative of the "prototype" of autism. To do this, it is necessary to clearly distinguish the population on which the research is carried out from that to which we provide support. People must receive services according to their needs, and not according to the clarity of their diagnosis.
Autism research : official journal of the International Society for Autism Research, 2021 · doi:10.1002/aur.2494