Background And Objectives: Autism spectrum disorder (ASD) and gender dysphoria (GD) frequently cooccur. However, existing research has primarily used smaller samples, limiting generalizability and the ability to assess further demographic variation. The purpose of this study was to (1) examine the prevalence of cooccurring ASD and GD diagnoses among US adolescents aged 9 to 18 and (2) identify demographic differences in the prevalence of cooccurring ASD and GD diagnoses.
Methods: This secondary analysis used data from the PEDSnet learning health system network of 8 pediatric hospital institutions. Analyses included descriptive statistics and adjusted mixed logistic regression testing for associations between ASD and GD diagnoses and interactions between ASD diagnosis and demographic characteristics in the association with GD diagnosis.
Results: Among 919 898 patients, GD diagnosis was more prevalent among youth with an ASD diagnosis compared with youth without an ASD diagnosis (1.1% vs 0.6%), and adjusted regression revealed significantly greater odds of GD diagnosis among youth with an ASD diagnosis (adjusted odds ratio = 3.00, 95% confidence interval: 2.72-3.31). Cooccurring ASD/GD diagnoses were more prevalent among youth whose electronic medical record-reported sex was female and those using private insurance, and less prevalent among youth of color, particularly Black and Asian youth.
Conclusions: Results indicate that youth whose electronic medical record-reported sex was female and those using private insurance are more likely, and youth of color are less likely, to have cooccurring ASD/GD diagnoses. This represents an important step toward building services and supports that reduce disparities in access to care and improve outcomes for youth with cooccurring ASD/GD and their families.
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http://dx.doi.org/10.1542/peds.2023-061363 | DOI Listing |
BMC Pediatr
January 2025
Department of Developmental and Behavioral Pediatrics, Children's Medical Center, The First Hospital of Jilin University, Changchun, China.
Background: Most previous studies have focused on the clinical efficacy after intervention of ESDM, particularly in core symptoms. However, only a few have paid attention to the effectiveness of ESDM on emotional dysregulation and behavior problems in children with ASD. This study aimed to explore the effect of the ESDM on addressing emotional dysregulation and behavior problems in children with ASD in China, as well as its correlation with core symptoms of ASD.
View Article and Find Full Text PDFHum Genet
January 2025
Department of Biomedical Sciences, University of Padova, Padova, Italy.
The Genetics of Neurodevelopmental Disorders Lab in Padua provided a new intellectual disability (ID) Panel challenge for computational methods to predict patient phenotypes and their causal variants in the context of the Critical Assessment of the Genome Interpretation, 6th edition (CAGI6). Eight research teams submitted a total of 30 models to predict phenotypes based on the sequences of 74 genes (VCF format) in 415 pediatric patients affected by Neurodevelopmental Disorders (NDDs). NDDs are clinically and genetically heterogeneous conditions, with onset in infant age.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Background: Brain morphology changes due to both natural aging and various pathological conditions. We used magnetic resonance imaging (MRI) and artificial intelligence (AI) to derive three brain age gaps (Wen et al., 2023b) [gray matter (GM), white matter (WM), and functional connectivity (FC)-BAG] for brain aging and 9 dimensional neuroimaging endophenotypes (Wen et al.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Background: Brain morphology changes due to both natural aging and various pathological conditions. We used magnetic resonance imaging (MRI) and artificial intelligence (AI) to derive three brain age gaps (Wen et al., 2023b) [gray matter (GM), white matter (WM), and functional connectivity (FC)-BAG] for brain aging and 9 dimensional neuroimaging endophenotypes (Wen et al.
View Article and Find Full Text PDFHum Brain Mapp
January 2025
Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, China.
Insomnia disorder (ID) is a highly heterogeneous psychiatric disease, and the use of neuroanatomical data to objectively define biological subtypes is essential. We aimed to examine the neuroanatomical subtypes of ID by morphometric similarity network (MSN) and the association between MSN changes and specific transcriptional expression patterns. We recruited 144 IDs and 124 healthy controls (HC).
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