Endophenotype trait domains for advancing gene discovery in autism spectrum disorder

Matthew W. Mosconi, Cassandra J. Stevens, Kathryn E. Unruh, Robin Shafer, Jed T. Elison

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations


Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of “endophenotype trait domains” (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.

Original languageEnglish (US)
Article number41
JournalJournal of neurodevelopmental disorders
Issue number1
StatePublished - Dec 2023

Bibliographical note

Publisher Copyright:
© 2023, The Author(s).

PubMed: MeSH publication types

  • Journal Article
  • Review
  • Research Support, N.I.H., Extramural


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