Continuity of temperament subgroup classifications from infancy to toddlerhood in the context of early autism traits.
Lacey ChetcutiMirko UljarevicKandice J VarcinMaryam BoutrusStefanie DimovSarah PillarJosephine BarbaroCheryl DissanayakeJonathan Michael GreenAndrew J O WhitehouseKristelle Hudrynull nullPublished in: Autism research : official journal of the International Society for Autism Research (2022)
Our previous cross-sectional investigation (Chetcuti et al., 2020) showed that infants with autism traits could be divided into distinct subgroups based on temperament. This longitudinal study builds on this existing work by exploring the continuity of temperament subgroup classifications and their associations with behavioral/clinical phenotypic features from infancy to toddlerhood. 103 infants (68% male) showing early signs of autism were referred to the study by community healthcare professionals and seen for assessments when aged around 12-months (Time 1), 18-months (Time 2), and 24-months (Time 3). Latent profile analysis revealed inhibited/low positive, active/negative reactive, and sociable/well-regulated subgroups at each timepoint, and a unique reactive/regulated subgroup at Time 3. Cross-tabulations indicated a significant likelihood of children having a recurrent subgroup classification from one timepoint to the next, and no apparent patterns to the movement of children who did change from one subgroup to another over time. Temperament subgroups were associated with concurrent child social-emotional functioning and autism traits, but unrelated to child age, sex, or developmental level. These findings suggest that temperament subgroup classifications might represent a reliable and very early indicator of autism characteristics and social-emotional functioning among infants/toddlers with autism traits.
Keyphrases
- autism spectrum disorder
- intellectual disability
- mental health
- genome wide
- phase iii
- healthcare
- cross sectional
- young adults
- transcription factor
- machine learning
- randomized controlled trial
- clinical trial
- deep learning
- magnetic resonance imaging
- weight gain
- magnetic resonance
- gene expression
- radiation therapy
- dna methylation