Exome Chip Analysis of 14,026 Koreans Reveals Known and Newly Discovered Genetic Loci Associated with Type 2 Diabetes Mellitus

BackgroundMost 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.MethodsWe 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. ResultsIn 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, PPP=8.00×10−5).ConclusionWe 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.

Exome Chip Analysis of 14,026 Koreans Reveals Known and Newly Discovered Genetic Loci Associated with Type 2 Diabetes Mellitus

BackgroundMost 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.MethodsWe 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. ResultsIn 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, PPP=8.00×10−5).ConclusionWe 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.

Exome Chip Analysis of 14,026 Koreans Reveals Known and Newly Discovered Genetic Loci Associated with Type 2 Diabetes Mellitus

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.

AKAPDB: A-Kinase Anchoring Proteins Database

A-kinase-anchoring proteins (AKAPs) are scaffold proteins which compartmentalize protein kinase A (PKA, cAMP-dependent protein kinase) and other enzymes to specific subcellular sites. The spatiotemporal control of these enzymes by AKAPs is important for cellular function like cell growth and development etc. Hence, it is important to understand the basic function of AKAPs and their functional domains. However, diverse names, function, cellular localizations and many members of AKAPs increase difficulties when researchers search appropriate AKAPs for their experimental purpose. Nevertheless, there was no previous AKAPs-related database regardless of their important cellular functions and difficulty of finding appropriate AKAPs. So, we developed AKAPs database (AKAPDB), which contains their sequence information, functions and other information derived from prediction programs and other databases. Therefore, we propose that AKAPDB can be an important tool to researchers in the related fields. AKAPDB is available via the internet at http://plaza3.snu.ac.kr/akapdb/