A sensory signature of unaffected biological parents predicts the risk of autism in their offspring

Chenyi Chen, Yawei Cheng, Chien Te Wu, Chung Hsin Chiang, Ching Ching Wong, Chih Mao Huang, Róger Marcelo Martínez, Ovid J.L. Tzeng, Yang Teng Fan

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Aim: Despite the emphasis on sensory dysfunction phenotypes in the revised diagnostic criteria for autism spectrum disorder (ASD), there has been limited research, particularly in the field of neurobiology, investigating the concordance in sensory features between individuals with ASD and their genetic relatives. Therefore, our objective was to examine whether neurobehavioral sensory patterns could serve as endophenotypic markers for ASD. Methods: We combined questionnaire- and lab-based sensory evaluations with sensory fMRI measures to examine the patterns of sensory responsivity in 30 clinically diagnosed with ASD, 26 matched controls (CON), and 48 biological parents for both groups (27 parents of individuals with ASD [P-ASD] and 21 for individuals with CON [P-CON]). Results: The ASD and P-ASD groups had higher sensory responsivity and rated sensory stimuli as more unpleasant than the CON and P-CON groups, respectively. They also exhibited greater hemodynamic responses within the sensory cortices. Overlapping activations were observed within these sensory cortices in the ASD and P-ASD groups. Using a machine learning approach with robust prediction models across cohorts, we demonstrated that the sensory profile of biological parents accurately predicted the likelihood of their offspring having ASD, achieving a prediction accuracy of 71.4%. Conclusions: These findings provide support for the hereditary basis of sensory alterations in ASD and suggest a potential avenue to improve ASD diagnosis by utilizing the sensory signature of biological parents, especially in families with a high risk of ASD. This approach holds promising prospects for early detection, even before the birth of the offspring.

Original languageEnglish
Pages (from-to)60-68
Number of pages9
JournalPsychiatry and Clinical Neurosciences
Volume78
Issue number1
DOIs
Publication statusPublished - Jan 2024

Keywords

  • autism spectrum disorder
  • endophenotype
  • machine learning
  • parent–child dyads
  • sensory responsivity

ASJC Scopus subject areas

  • General Neuroscience
  • Neurology
  • Clinical Neurology
  • Psychiatry and Mental health

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