Background: Autism spectrum disorder (ASD) is a complex neurological condition with increasing prevalence. Few tools accurately predict the developmental trajectory of children with ASD. Such tools would allow clinicians to provide accurate prognoses and track the efficacy of therapeutic interventions. Salivary RNAs that reflect the genetic-environmental interactions underlying ASD may provide objective measures of symptom severity and developmental outcomes. This study investigated whether salivary RNAs previously identified in childhood ASD remain perturbed in older children. We also explored whether RNA candidates changed with therapeutic intervention.
Method: A case-control design was used to characterize levels of 78 saliva RNA candidates among 96 children (48 ASD, 48 non-ASD, mean age: 11 years). Thirty-one children (22 ASD, 9 non-ASD developmental delay, mean age: 4 years) were followed longitudinally to explore changes of RNA candidates during early intervention. Saliva RNA and standardized behavioral assessments were collected for each participant. Associations between candidate RNAs and behavioral scores were determined in both groups via Spearman Correlation. Changes in candidate RNAs across two time-points were assessed in the younger cohort via Wilcoxon rank-sum test.
Results: Seven RNAs were associated with VABS-II and BASC scores in the older group ([R] >0.25, FDR< 0.15). Within the younger cohort, 12 RNAs displayed significant changes over time (FDR< 0.05). Three microRNAs were associated with behavioral scores and changed over time (miR-182-5p, miR-146b-5p, miR-374a-5p).
Conclusion: Several salivary RNAs are strongly associated with autistic behaviors in older individuals with ASD and change as early as three months after therapy initiation in younger children. These molecules could be used to track treatment effectiveness and provide prognoses. Further validation is necessary.
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http://dx.doi.org/10.1016/j.rasd.2021.101788 | DOI Listing |
Netw Neurosci
December 2024
Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea.
The study of large-scale brain connectivity is increasingly adopting unsupervised approaches that derive low-dimensional spatial representations from high-dimensional connectomes, referred to as gradient analysis. When translating this approach to study interindividual variations in connectivity, one technical issue pertains to the selection of an appropriate group-level template to which individual gradients are aligned. Here, we compared different group-level template construction strategies using functional and structural connectome data from neurotypical controls and individuals with autism spectrum disorder (ASD) to identify between-group differences.
View Article and Find Full Text PDFNetw Neurosci
December 2024
McLean Imaging Center, McLean Hospital, Harvard Medical School, Belmont, MA, USA.
The atypical static brain functions related to the executive control network (ECN), default mode network (DMN), and salience network (SN) in people with autism spectrum disorder (ASD) has been widely reported. However, their transient functions in ASD are not clear. We aim to identify transient network states (TNSs) using coactivation pattern (CAP) analysis to characterize the age-related atypical transient functions in ASD.
View Article and Find Full Text PDFMed J Armed Forces India
December 2024
Professor (Microbiology), Director, MAHE-FAIMER Institute, Manipal Academy of Higher Education, Manipal, India.
Background: Protocols instituted for behavioral treatment and skills training programs for the management of autism spectrum disorder (ASD) suffer from lack of collaborative approaches. The tenets of interprofessional collaborative practice (IPCP) focus on preparing a panel of health care professionals (HCPs) from different professions who can work together to enable the common goal of ensuring that children with ASD can participate in society. This study was designed to pilot this approach through an IPCP training module on ASD for care providers from multiple professions.
View Article and Find Full Text PDFFront Neurosci
December 2024
School of Education Science, Jiangsu Normal University, Xuzhou, China.
Background: Autism spectrum disorder is a distinctive developmental condition which is caused by an interaction between genetic vulnerability and environmental factors. Biomarkers play a crucial role in understanding disease characteristics for diagnosis, prognosis, and treatment. This study employs bibliometric analysis to identify and review the 100 top-cited articles' characteristics, current research hotspots and future directions of autism biomarkers.
View Article and Find Full Text PDFChemosphere
December 2024
Department of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1057, New York, NY, 10029, USA. Electronic address:
Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by social deficits and repetitive behaviors. Environmental pollutants may contribute to the etiology of ASD, but studies of perfluoroalkyl substances (PFAS) have shown conflicting results.
Objectives: We assessed associations between cord blood concentrations of PFAS with autistic traits at age seven years in a Singaporean birth cohort.
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