Integrative analysis of γδT cells and dietary factors reveals predictive values for autism spectrum disorder in children

Abstract

Background: Autism spectrum disorder (ASD) includes a range of multifactorial neurodevelopmental disabilities characterized by a variable set of neuropsychiatric symptoms. Immunological abnormalities have been considered to play important roles in the pathogenesis of ASD, but it is still unknown which abnormalities are more prominent.

Methods: A total of 105 children with ASD and 105 age and gender-matched typically developing (TD) children were recruited. An eating and mealtime behavior questionnaire, dietary habits, and the Bristol Stool Scale were investigated. The immune cell profiles in peripheral blood were analyzed by flow cytometry, and cytokines (IFN-γ, IL-8, IL-10, IL-17A, and TNF-α) in plasma were examined by Luminex assay. The obtained results were further validated using an external validation cohort including 82 children with ASD and 51 TD children.

Results: Compared to TD children, children with ASD had significant eating and mealtime behavioral changes and gastrointestinal symptoms characterized by increased food fussiness and emotional eating, decreased fruit and vegetable consumption, and increased stool astriction. The proportion of γδT cells was significantly higher in children with ASD than TD children (β: 0.156; 95% CI: 0.888 ∼ 2.135, p < 0.001) even after adjusting for gender, eating and mealtime behaviors, and dietary habits. In addition, the increased γδT cells were evident in all age groups (age < 48 months: β: 0.288; 95% CI: 0.420 ∼ 4.899, p = 0.020; age ≥ 48 months: β: 0.458; 95% CI: 0.694 ∼ 9.352, p = 0.024), as well as in boys (β: 0.174; 95% CI: 0.834 ∼ 2.625, p < 0.001) but not in girls. These findings were also confirmed by an external validation cohort. Furthermore, IL-17, but not IFN-γ, secretion by the circulating γδT cells was increased in ASD children. Machine learning revealed that the area under the curve in nomogram plots for increased γδT cells combined with eating behavior/dietary factors was 0.905, which held true in both boys and girls and in all the age groups of ASD children. The decision curves showed that children can receive significantly higher diagnostic benefit within the threshold probability range from 0 to 1.0 in the nomogram model.

Conclusions: Children with ASD present with divergent eating and mealtime behaviors and dietary habits as well as gastrointestinal symptoms. In peripheral blood, γδT cells but not αβT cells are associated with ASD. The increased γδT cells combined with eating and mealtime behavior/dietary factors have a high value for assisting in the diagnosis of ASD.

Keywords: Autism spectrum disorders; Diet; Immunity; Machine learning; γδT cell.