ArticleFrontiers in molecular neuroscience2022
Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders.
Article in Frontiers in molecular neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Multimodal characterization of cortical hyperexcitability as a driver of cognitive decline in neurocognitive disorders: study protocol for the LENDÜLET Neurocognitive Research Project.Frontiers in aging neuroscience · 2026Article
- Autism Spectrum Disorder as a Multifactorial Disorder: The Interplay of Genetic Factors and Inflammation.International journal of molecular sciences · 2025Review
- Identification of Neurotransmission and Synaptic Biological Processes Disrupted in Autism Spectrum Disorder Using Interaction Networks and Community Detection Analysis.Biomedicines · 2023Article
- The molecular basis of p21-activated kinase-associated neurodevelopmental disorders: From genotype to phenotype.Frontiers in neuroscience · 2023Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation, variable severity, and multiple comorbidities. A complex underlying genetic architecture matches the clinical heterogeneity, and evidence indicates that several co-occurring brain disorders share a genetic component with ASD. In this study, we established a genetic similarity disease network approach to explore the shared genetics between ASD and frequent comorbid brain diseases (and subtypes), namely Intellectual Disability, Attention-Deficit/Hyperactivity Disorder, and Epilepsy, as well as other rarely co-occurring neuropsychiatric conditions in the Schizophrenia and Bipolar Disease spectrum. Using sets of disease-associated genes curated by the DisGeNET database, disease genetic similarity was estimated from the Jaccard coefficient between disease pairs, and the Leiden detection algorithm was used to identify network disease communities and define shared biological pathways. We identified a heterogeneous brain disease community that is genetically more similar to ASD, and that includes Epilepsy, Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder combined type, and some disorders in the Schizophrenia Spectrum. To identify loss-of-function rare
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