A network analysis framework of genetic and nongenetic risks for type 2 diabetes.
|
| Abstract |
Both genetic and nongenetic factors have been found to be associated with type 2 diabetes, however, the correlation between them is still unclear. In the present study, we aimed to fully decipher the nongenetic and genetic factor association network for type 2 diabetes. We identified risk factors for type 2 diabetes by systematically searching for related meta-analyses and genome-wide association studies (GWAS) database. Among a total of 27,822 studies screened, 202 articles were eligible, from which 174 nongenetic factors and 210 genetic factors associated with type 2 diabetes were identified. Then, we obtained 584 associations between the nongenetic and genetic factors of type 2 diabetes, based on which a risk factor association network was conducted. The nongenetic factors could be classified into seven categories according to the Global Burden of Diseases (GBD). Of these seven categories of nongenetic factors, five were found to be correlated with genes associated with type 2 diabetes, including environmental risks, behavioral risks, metabolic risks, related disease of type 2 diabetes, and treatments. Specifically, air pollutants of environmental risks, alcohol using of behavioral risks, obesity of metabolic risks, rheumatoid arthritis of related disease risk, and simvastatin of treatment was correlated with the largest number of genes. In summary, the correlation between genetic factors and nongenetic factors identified in this study indicates that there is a common phenotype-genotype association in type 2 diabetes, with the combinations of genotypes ("genetic signature") clustering in phenotypes related to type 2 diabetes. Thus, we should take a systematic approach to explore the relationship of various factors for type 2 diabetes, as well as other noncommunicable diseases.
|
|---|---|
| Authors | Yuan Zhang, Shu Li, Zhi Cao, Yangyang Cheng, Chenjie Xu, Hongxi Yang, Li Sun, Hongxiao Jiao, Ju Wang, Wei-Dong Li, Yaogang Wang |
| Journal | Reviews in endocrine & metabolic disorders (Rev Endocr Metab Disord) Vol. 22 Issue 2 Pg. 461-469 (06 2021) ISSN: 1573-2606 [Electronic] Germany |
| PMID | 32926312 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't, Review) |
| Topics |
|
Join CureHunter, for free Research Interface BASIC access!
Realize the full power of the drug-disease research graph!