- Genetics
- Exome Chip Analysis of 14,026 Koreans Reveals Known and Newly Discovered Genetic Loci Associated with Type 2 Diabetes Mellitus
-
Seong Beom Cho, Jin Hwa Jang, Myung Guen Chung, Sang Cheol Kim
-
Diabetes Metab J. 2021;45(2):231-240. Published online July 28, 2020
-
DOI: https://doi.org/10.4093/dmj.2019.0163
-
-
6,784
View
-
204
Download
-
6
Web of Science
-
6
Crossref
-
 Graphical Abstract
 Abstract
 PDF Supplementary Material PubReader  ePub
 -
Background
Most loci associated with type 2 diabetes mellitus (T2DM) discovered to date are within noncoding regions of unknown functional significance. By contrast, exonic regions have advantages for biological interpretation.
Methods
We analyzed the association of exome array data from 14,026 Koreans to identify susceptible exonic loci for T2DM. We used genotype information of 50,543 variants using the Illumina exome array platform.
Results
In total, 7 loci were significant with a Bonferroni adjusted P=1.03×10−6. rs2233580 in paired box gene 4 (PAX4) showed the highest odds ratio of 1.48 (P=1.60×10−10). rs11960799 in membrane associated ring-CH-type finger 3 (MARCH3) and rs75680863 in transcobalamin 2 (TCN2) were newly identified loci. When we built a model to predict the incidence of diabetes with the 7 loci and clinical variables, area under the curve (AUC) of the model improved significantly (AUC=0.72, P<0.05), but marginally in its magnitude, compared with the model using clinical variables (AUC=0.71, P<0.05). When we divided the entire population into three groups—normal body mass index (BMI; <25 kg/m2), overweight (25≤ BMI <30 kg/m2), and obese (BMI ≥30 kg/m2) individuals—the predictive performance of the 7 loci was greatest in the group of obese individuals, where the net reclassification improvement was highly significant (0.51; P=8.00×10−5).
Conclusion
We found exonic loci having a susceptibility for T2DM. We found that such genetic information is advantageous for predicting T2DM in a subgroup of obese individuals.
-
Citations
Citations to this article as recorded by  - Polygenic Risk Score, Lifestyles, and Type 2 Diabetes Risk: A Prospective Chinese Cohort Study
Jia Liu, Lu Wang, Xuan Cui, Qian Shen, Dun Wu, Man Yang, Yunqiu Dong, Yongchao Liu, Hai Chen, Zhijie Yang, Yaqi Liu, Meng Zhu, Hongxia Ma, Guangfu Jin, Yun Qian
Nutrients.2023; 15(9): 2144. CrossRef - Celebrities in the heart, strangers in the pancreatic beta cell: Voltage‐gated potassium channels Kv7.1 and Kv11.1 bridge long QT syndrome with hyperinsulinaemia as well as type 2 diabetes
Anniek F. Lubberding, Christian R. Juhl, Emil Z. Skovhøj, Jørgen K. Kanters, Thomas Mandrup‐Poulsen, Signe S. Torekov
Acta Physiologica.2022;[Epub] CrossRef - Substitution of Carbohydrates for Fats and Risk of Type 2 Diabetes among Korean Middle-Aged Adults: Findings from the Korean Genome and Epidemiology Study
Hye-Ah Lee, Hyesook Park
Nutrients.2022; 14(3): 654. CrossRef - Ethnic-Specific Type 2 Diabetes Risk Factor PAX4 R192H Is Associated with Attention-Specific Cognitive Impairment in Chinese with Type 2 Diabetes
Su Fen Ang, Serena Low, Tze Pin Ng, Clara S.H. Tan, Keven Ang, Ziliang Lim, Wern Ee Tang, Tavintharan Subramaniam, Chee Fang Sum, Su Chi Lim, Nagaendran Kandiah
Journal of Alzheimer's Disease.2022; 88(1): 241. CrossRef - TrustGWAS: A full-process workflow for encrypted GWAS using multi-key homomorphic encryption and pseudorandom number perturbation
Meng Yang, Chuwen Zhang, Xiaoji Wang, Xingmin Liu, Shisen Li, Jianye Huang, Zhimin Feng, Xiaohui Sun, Fang Chen, Shuang Yang, Ming Ni, Lin Li, Yanan Cao, Feng Mu
Cell Systems.2022; 13(9): 752. CrossRef - Sex Differences in the Effects of CDKAL1 Variants on Glycemic Control in Diabetic Patients: Findings from the Korean Genome and Epidemiology Study
Hye Ah Lee, Hyesook Park, Young Sun Hong
Diabetes & Metabolism Journal.2022; 46(6): 879. CrossRef
|
KDA
