ArticleInternational journal of molecular medicine2018
Comprehensive literature data-mining analysis reveals a broad genetic network functionally associated with autism spectrum disorder.
Article in International journal of molecular medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Review of autism spectrum disorder databases for the identification of candidate genes.Database : the journal of biological databases and curation · 2025Review
- Significance of PPARA as a Treatment Target for Chronic Lymphocytic Leukemia.PPAR research · 2023Article
- Role of PPARG in Chemosensitivity-Regulating Network for Hypopharyngeal Squamous Cell Carcinoma.PPAR research · 2023Article
- Formaldehyde exposure and leukemia risk: a comprehensive review and network-based toxicogenomic approach.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2021Review
- Identification of a de novo FOXP1 mutation and incidental discovery of inherited genetic variants contributing to a case of autism spectrum disorder and epilepsy.Molecular genetics & genomic medicine · 2019Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Previous studies have indicated that genetic factors are the predominate cause of Autism spectrum disorder (ASD). Nevertheless, to the best of our knowledge, to date no systematic study has summarized these data and provided an objective, complete list of genes with demonstrated associations with ASD. The present study included a literature data mining analysis of >2,064 articles including publications from January 2000 to April 2016, which identified 488 ASD target genes. Gene set enrichment analysis (GSEA), sub‑network enrichment analysis (SNEA) and network connectivity analysis (NCA) were conducted to assess the functional profile and pathogenic significance of these genes. A total of 2 literature metrics were proposed to prioritize the curated ASD genes with specific significance. This approach resulted in the development of an ASD genetic database. Subsequent analysis indicated that 391 of the 488 genes were enriched in 97 biological pathways (P<1x10‑8), demonstrating significant functional associations with each other. The majority of these curated ASD genes also serve significant roles in the pathogenesis of other neuropsychiatric disorders. These results suggest that the genetic causes of ASD are within a large network composed of functionally‑associated genes. The genetic database, together with the metric scores developed in the present study, provides a basis for future biological/genetic modeling in the field.
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