Background: Sensorimotor impairments are common in autism spectrum disorder (ASD) and evident in unaffected first-degree relatives, suggesting that they may serve as important endophenotypes associated with inherited risk. We tested the familiality of sensorimotor impairments in ASD across multiple motor behaviors and effector systems and in relation to parental broader autism phenotypic (BAP) characteristics.
Methods: Fifty-eight autistic individuals (probands), 109 parents, and 89 control participants completed tests of manual motor and oculomotor control. Sensorimotor tests varied in their involvement of , feedforward control and , sensory feedback control processes. Subgroup analyses compared families with at least one parent showing BAP traits (BAP+) and those in which neither parent showed BAP traits (BAP-).
Results: Probands with BAP- parents (BAP- probands) showed rapid manual motor and oculomotor deficits, while BAP+ probands showed sustained motor impairments compared to controls. BAP- parents showed impaired rapid oculomotor and sustained manual motor abilities relative to BAP+ parents and controls. Atypical rapid oculomotor impairments also were familial.
Limitations: Larger samples of ASD families including greater samples of probands with BAP+ parents are needed. Genetic studies also are needed to link sensorimotor endophenotype findings directly to genes.
Conclusions: Results indicate rapid sensorimotor behaviors are selectively impacted in BAP- probands and their parents and may reflect familial liabilities for ASD that are independent of familial autistic traits. Sustained sensorimotor behaviors were affected in BAP+ probands and BAP- parents re ecting familial traits that may only confer risk when combined with parental autistic trait liabilities. These findings provide new evidence that rapid and sustained sensorimotor alterations represent strong but separate familial pathways of ASD risk that demonstrate unique interactions with mechanisms related to parental autistic traits.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246285 | PMC |
| http://dx.doi.org/10.21203/rs.3.rs-2973214/v1 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Development, Measurement Properties and Reference Values of the Upper Extremity Motor Coordination Test: A New Motor Coordination Test of the Upper Limbs.
Physiother Res Int
January 2025
Department of Physiotherapy, Centro Universitário FUNCESI, Itabira, Brazil.
Background And Purpose: To develop a new test to assess the motor coordination of the upper limbs, and to investigate the test-retest and inter-rater reliability, construct validity, standard error of measurement (SEM), minimum detectable change (MDC), and the reference values.
Methods: The Upper Extremity Motor Coordination Test (UEMOCOT)was applied for 20 s, with the individual touching two targets (one right and one left) as quickly as possible, first with the hand (manual task) and then with the index finger (finger task). To test-retest reliability, the UEMOCOT was administered two times.
Transforming literature screening: The emerging role of large language models in systematic reviews.
Proc Natl Acad Sci U S A
January 2025
Department of Health Economics and Health Services Research, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany.
Systematic reviews (SR) synthesize evidence-based medical literature, but they involve labor-intensive manual article screening. Large language models (LLMs) can select relevant literature, but their quality and efficacy are still being determined compared to humans. We evaluated the overlap between title- and abstract-based selected articles of 18 different LLMs and human-selected articles for three SR.
View Article and Find Full Text PDFAtypical development of sequential manual motor planning and visuomotor integration in children with autism at early school-age: A longitudinal kinematic study.
Autism
January 2025
Department of Psychology, Umeå University, Sweden.
Many children with autism struggle with movement difficulties, yet the causes of these difficulties remain unclear. One possible explanation is atypical motor planning and integration of visual and motoric information. Before performing a goal-directed movement, the brain creates a prediction of the movement based on visual and sensory information and previous experience, forming a "blueprint" of the motor steps needed to achieve the goal.
View Article and Find Full Text PDFA scoping review of the motor impairments in autism spectrum disorder.
Neurosci Biobehav Rev
January 2025
Laboratory of Cognitive Neurophysiology (LabNeuro), Institute of Biological Sciences, Department of Biophysics and Physiology, Federal University of Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil; Post-Graduation Program in Rehabilitation Sciences and Physical-Functional Performance, Federal University of Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil. Electronic address:
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder mainly defined by impairments in communication and socialization. Although motor symptoms are not typically considered central to the disease, their high frequency and early onset have been recurrently reported in the literature. Therefore, this scoping review provides a broad description of these motor impairments across all ages, as well as a discussion of their relevance and relation to other clinical aspects of ASD.
View Article and Find Full Text PDFN2GNet tracks gait performance from subthalamic neural signals in Parkinson's disease.
NPJ Digit Med
January 2025
Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Adaptive deep brain stimulation (DBS) provides individualized therapy for people with Parkinson's disease (PWP) by adjusting the stimulation in real-time using neural signals that reflect their motor state. Current algorithms, however, utilize condensed and manually selected neural features which may result in a less robust and biased therapy. In this study, we propose Neural-to-Gait Neural network (N2GNet), a novel deep learning-based regression model capable of tracking real-time gait performance from subthalamic nucleus local field potentials (STN LFPs).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!