TY - JOUR
T1 - Comprehensive literature data-mining analysis reveals a broad genetic network functionally associated with Autism spectrum disorder
AU - Xu, Cheng
AU - Cao, Hongbao
AU - Zhang, Fuquan
AU - Cheadle, Chris
N1 - Publisher Copyright:
© 2018 Spandidos Publications. All rights reserved.
PY - 2018/11
Y1 - 2018/11
N2 - 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.
AB - 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.
KW - Autism spectrum disorder
KW - Gene set enrichment analysis
KW - Literature data mining
KW - Sub-network enrichment analysis
UR - http://www.scopus.com/inward/record.url?scp=85053381073&partnerID=8YFLogxK
U2 - 10.3892/ijmm.2018.3845
DO - 10.3892/ijmm.2018.3845
M3 - Artículo
C2 - 30226572
AN - SCOPUS:85053381073
SN - 1107-3756
VL - 42
SP - 2353
EP - 2362
JO - International Journal of Molecular Medicine
JF - International Journal of Molecular Medicine
IS - 5
ER -