Although initially described as an inborn disorder of affective contact, information on autism as it exists in infants has been limited. Delays in diagnosis, lack of information about the condition, and reliance on retrospective research strategies have been problematic. An awareness of the increased risk for siblings is now allowing the development of new, prospective approaches. Consistent with Kanner's original hypothesis, the available information strongly suggests a fundamental difficulty in the earliest social processes, which, in turn, impacts many other areas of development. New approaches to screening have lowered the age of initial diagnosis; this presents new challenges for early intervention. Directions for future research are highlighted.
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http://dx.doi.org/10.1146/annurev.psych.56.091103.070159 | DOI Listing |
Pediatr Res
January 2025
Thompson Center for Autism and Neurodevelopment, University of Missouri-Columbia, Columbia, MO, USA.
Background: Identification of prodromal indicators of autism in infancy has the potential to identify behaviors relevant to early autism screening.
Methods: We report on data from a prospective general population birth cohort with maternal reported measures at 9 and 12 months: the Survey of Well-Being of Young Children (SWYC; general developmental surveillance) and the First Year Inventory-Lite v3.1b (FYI-Lite; autism specific parent report research tool).
Case Rep Genet
January 2025
Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, University of California, 2825 50th Street, Davis, Sacramento 95817, California, USA.
Fragile X syndrome (FXS) presents with autism spectrum disorder (ASD), intellectual disability, developmental delay, seizures, hypotonia during infancy, joint laxity, behavioral issues, and characteristic facial features. The predominant mechanism is due to CGG trinucleotide repeat expansion of more than 200 repeats in the 5'UTR (untranslated region) of (Fragile X Messenger Ribonucleoprotein 1) causing promoter methylation and transcriptional silencing. However, not all patients presenting with the characteristic phenotype and point/frameshift mutations with deletions in have been described in the literature.
View Article and Find Full Text PDFJ Autism Dev Disord
January 2025
Faculty of Psychology, University of Warsaw, Warsaw, Poland.
Infants at elevated likelihood for or later diagnosed with autism typically have smaller vocabularies than their peers, as shown by the Mullen Scales of Early Learning (MSEL) and the MacArthur-Bates Communicative Developmental Inventory (CDI). However, the extent to which MSEL and CDI scores align remains unclear, especially across clinical and non-clinical populations. This study examined whether the concurrent validity of the MSEL and CDI differs based on autism likelihood and diagnosis.
View Article and Find Full Text PDFFront Child Adolesc Psychiatry
January 2024
National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark.
Introduction: Regulatory problems of eating, sleeping, and crying in infancy may index mental health vulnerability in older ages, and knowledge is needed to inform strategies to break the developmental trajectories of dysregulation in early childhood. In this study, we examined the prospective associations between infant regulatory problems at the age of 8-10 months identified by community health nurses (CHN) and mental disorders diagnosed in hospital settings in children aged 1-8 years.
Methods: From a cohort of all newborn children in 15 municipalities in the Capital Region of Copenhagen ( = 43,922) we included all children who were examined by CHNs at the scheduled home visit at the age of 8-10 months ( = 36,338).
Commun Med (Lond)
January 2025
Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Leibniz ScienceCampus Primate Cognition and German Center for Child and Adolescent Health (DZKJ), Göttingen, Germany.
Background: To assess the integrity of the developing nervous system, the Prechtl general movement assessment (GMA) is recognized for its clinical value in diagnosing neurological impairments in early infancy. GMA has been increasingly augmented through machine learning approaches intending to scale-up its application, circumvent costs in the training of human assessors and further standardize classification of spontaneous motor patterns. Available deep learning tools, all of which are based on single sensor modalities, are however still considerably inferior to that of well-trained human assessors.
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