Background: Little is known about the extent to which neurodevelopmental trajectories in infancy predict a later diagnosis of autism spectrum disorder (ASD).
Methods: We investigated the association between the neurodevelopmental trajectory classes identified using a latent class growth analysis and the distal clinical outcome. Participants included 952 infants from the Hamamatsu Birth Cohort for Mothers and Children (HBC study). Neurodevelopment was measured using the Mullen Scales of Early Learning, which contains five subscales (gross motor, fine motor, visual reception, receptive language, and expressive language), at seven time points from 1 to 24 months of age. ASD was diagnosed in 3.1% of the children at 32 months of age. The clinical outcome was included in our analysis model.
Results: Five neurodevelopmental classes were identified: high normal (11.5%), normal (49.2%), low normal (21.2%), delayed (14.1%), and markedly delayed (4.0%). The probability of a diagnosis of ASD in the markedly delayed class was highest (32.6%) when compared with the other classes. The probabilities of receiving a diagnosis of ASD in the delayed and low normal classes were 6.4% and 4.0%, respectively, whereas the probabilities in the normal and high normal classes were both 0%.
Conclusions: A diagnosis of ASD may be predicted by the neurodevelopmental trajectories during infancy, which can be evaluated both routinely and objectively in clinical settings. In this representative population, children diagnosed with ASD showed early signs in neurodevelopmental domains during the first 2 years of life.