IDGenetics: a comprehensive database for genes and mutations of intellectual disability related disorders. (15th October 2018) - Chen, Chong; Chen, Denghui; Xue, Huangqi; Liu, Xinting; Zhang, Tao; Tang, Shaohua; Li, Wei; Xu, Xueqin
Highlights: This study developed IDGenetics, the comprehensive and freely available genetic database for ID, with versatile browsing and searching functionalities. It holds the following functions: 1) integration and annotation of cumulative to date 815 known ID genes and 17102 variants related to 3001 clinical phenotypes from 3822 publications; 2) 1478 candidate genes were prioritized by adopting the annotations of 12 functional prediction tools and own algorithm; 3) functional analysis based on the known genes to explore pattern of associations between genes and phenotypes; 4) overlap analysis addressing the comorbidity of the other neuropsychiatric disorders based on the shared genes, common phenotypes and enriched pathways; 5) dynamically visualizing the distribution of mutations, and graphically displaying the network between two genes or phenotypes. In conclusion, IDGenetics (http://www.ccgenomics.cn/IDGenetics/ ) could be widely used by researchers intending to unravel the genetic basis of ID. ABSTRACT: Intellectual disability (ID) is one of the most prevalent chronic developmental brain disorders or phenotype of syndromic ID, affecting nearly 1-2% of the general population worldwide. Over recent decades, tremendous effort and high-throughput platforms have been devised to explore the complex heterogeneity, numerous genes and variants have been associated with the ID, especially de novo mutations and copy number variants. An organized resource containing the increasing genetic data is imperative to assist ID research. In this study, the integrative and annotated intellectual disability database has been developed, named 'IDGenetics', which contains known information about ID, including 815 genes and 17102 variants associated with 918 clinical diseases (3001 clinical phenotype) collected from 3822 publications and ID-related databases. Furthermore, in-depth data mining was performed to obtain an understanding of each entry, including functional annotation, gene/disease/phenotype network establishment and overlap analysis focusing on comorbidity. 1478 candidate genes (483 high-confidence and 995 low-confidence) were collected and prioritized by adopting the annotations of 12 functional prediction tools and algorithm. In addition, IDGenetics database provides concise search methods, convenient browsing functions, intuitive graphical displays and constantly updated features. IDGenetics will be a valuable and integrative resource for deciphering the genetic and functional architecture of ID and the improvement of clinical diagnosis, intervention and treatment.