Billets de Michelle Dawson

Billet publié sur Bluesky le 10/07/2025 12:01

Bluesky Publication avec DOI crossref Extrait cité dans le billet Question posée par Dawson dans le billet Lien intégré au billet Termes sur l’autisme

Authors create 4 classes of autism?--"Social/behavioral" (37%), "Mixed ASD with DD" (19%), "Moderate challenges" (34%), "Broadly affected" (10%)? www.nature.com/articles/s41... based on SCQ, CBCL, & RBS-R scores & developmental milestones, in N=5392 autistics aged 4-18 years, free

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Publication avec DOI Récupéré Publication crossref

Aviya Litman, Natalie Sauerwald, LeeAnne Green Snyder, Jennifer Foss-Feig, Christopher Y. Park, Yun Hao, Ilan Dinstein, Chandra L. Theesfeld, et al. (2025). Decomposition of phenotypic heterogeneity in autism reveals underlying genetic programs. Nature Genetics, 57(7), 1611-1619. Springer Science and Business Media LLC.

Date de publication
09/07/2025
Identifiant
10.1038/s41588-025-02224-z
Auteurs
Aviya Litman, Natalie Sauerwald, LeeAnne Green Snyder, Jennifer Foss-Feig, Christopher Y. Park, Yun Hao, Ilan Dinstein, Chandra L. Theesfeld, Olga G. Troyanskaya
Source
Nature Genetics
Détails
57(7), 1611-1619
Type de référence
article
Éditeur
Springer Science and Business Media LLC
Source de métadonnées
crossref

Résumé

Abstract Unraveling the phenotypic and genetic complexity of autism is extremely challenging yet critical for understanding the biology, inheritance, trajectory and clinical manifestations of the many forms of the condition. Using a generative mixture modeling approach, we leverage broad phenotypic data from a large cohort with matched genetics to identify robust, clinically relevant classes of autism and their patterns of core, associated and co-occurring traits, which we further validate and replicate in an independent cohort. We demonstrate that phenotypic and clinical outcomes correspond to genetic and molecular programs of common, de novo and inherited variation and further characterize distinct pathways disrupted by the sets of mutations in each class. Remarkably, we discover that class-specific differences in the developmental timing of affected genes align with clinical outcome differences. These analyses demonstrate the phenotypic complexity of children with autism, identify genetic programs underlying their heterogeneity, and suggest specific biological dysregulation patterns and mechanistic hypotheses.

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