Autism Subtypes and Research

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The practice of categorizing autistic people into subtypes based on similarities in their traits and abilities is divisive. Subtypes can have negative connotations, evoking images of stereotyping and marginalization.

For decades, the autism spectrum was, by definition, a collection of subtypes, including Asperger syndrome and pervasive developmental disorder-not otherwise specified. But there was no clear clinical distinction between the subtypes, and they did not fully capture the inherent variation among people on the spectrum. So the fifth and most recent edition of the Diagnostic and Statistical Manual of Mental Disorders, to which clinicians refer to make diagnoses, retired them from use in 2013.

That said, there are often good reasons for subtyping. Identifying subtypes of people who share particular genetic variants may be useful, because these variants may be associated with specific medical issues. Subtyping analysis can also be used to demonstrate the nonexistence of certain subtypes. Or it can help researchers to identify who benefits most from a particular kind of support, without focusing on etiology or ontology.

For these reasons, we should not categorically stop conducting subtyping analyses. But research should focus on the discovery of meaningful subtypes of autism. To seek consensus among scientists on the number and nature of subtypes, we conducted a systematic review of the autism subtyping literature. We limited our search to articles published since 2001 that had used a statistical or machine-learning method to discover subtypes of autistic people.

We identified 156 articles that met our criteria. Of these, 82 percent found that two to four subtypes described their data well. But these subtypes reflected a highly diverse set of measures, including levels of inflammatory markers, scores on autism trait and sensory sensitivity questionnaires, tests of language skills, hormone levels and patterns of facial features, and this diversity made it difficult to find consensus or draw any firm conclusions.

Furthermore, we noticed that few studies took additional steps to validate their subtype results and support their claims.

In our review, published in the July issue of Clinical Psychology Review, we outline seven ways to provide convincing supporting evidence for subtyping analyses. We also provide a “Subtyping Validation Checklist” that researchers can use. These validation strategies call for more analysis, more measurements or more participants but can make any subtyping results all the more interpretable and valuable.

The prototypical form of validation is independent replication, in which the entire recruitment, measurement and analysis procedure is repeated with a second group of participants. Only 9 percent of the articles we reviewed included an independent replication sample, however.

Most articles — 88 percent — used a strategy called external validation, which involves comparing subtypes on additional variables not used in the original analysis.

To improve this situation, we have two additional recommendations. First, we ask that researchers describe which validation strategies they have used in their studies and explain their rationale for choosing these approaches.

Second, and more importantly, we ask researchers to explicitly state the goal of their subtyping analysis.