Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Cho SB

PROVIDER: S-EPMC8024163 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Rationale: Sleep-disordered breathing (SDB) is associated with increased risk of adverse pregnancy outcomes, including gestational diabetes mellitus (GDM). GDM is a significant cause of maternal and infant morbidities. Assessing these risk factors concurrently may facilitate both the identification of women at GDM risk and the initiation of GDM prevention strategies.Objectives: To investigate whether SDB events, including SDB in rapid eye movement (REM) sleep and other sleep parameters, are associated with increased risk of GDM and to evaluate the performance of the models investigating associations between breathing and sleep parameters and GDM risk.Methods: In this case-control study, 46 women with newly diagnosed GDM and 46 healthy control subjects, who were individually matched for age, gestational age, body mass index, race, and parity, completed overnight polysomnographic studies and sleep questionnaires after being screened for GDM during the late-second to mid-third trimesters. Conditional logistic regression analysis was used to identify models investigating associations between risk factors and GDM risk. The Bayesian information criterion (BIC) was employed to compare models; the model with the lowest BIC is preferred.Results: Obstructive sleep apnea (OSA; defined as an apnea-hypopnea index [AHI] >5 events/h) was present in 22% of subjects with GDM and 9% of control subjects (P < 0.001). Women with OSA had a higher GDM risk (odds ratio [OR], 4.71; 95% confidence interval [CI], 1.05-21.04). In individual models, GDM risk was also significantly higher among women with higher overall AHI (events/h OR, 1.81; 95% CI, 1.01-3.27), higher AHI in REM (events/h OR, 2.09; 95% CI, 1.02-4.31), higher oxygen desaturation index greater than or equal to 4% (ODI4; events/h OR, 2.21; 95% CI, 1.03-4.73), and higher Sleep Apnea Symptom Score (OR, 2.72; 95% CI, 1.11-6.69). The percentage of non-REM sleep was significantly associated with decreased risk of GDM (percentage of non-REM sleep OR, 0.88; 95% CI, 0.78-0.99). The BIC supports the conclusion that there is a strong association between AHI in REM and GDM risk compared with the other significant models.Conclusions: SDB events, including REM-related OSA, are linked to increased GDM risk. GDM risk is also influenced by intercorrelated sleep variables.

Project description:Six oral medication classes have been approved by the Food and Drug Administration for the treatment of type 2 diabetes. Although all of these agents effectively lower blood glucose, the evidence supporting their impact on other clinical events is variable. There also are substantial cost differences between agents. We aimed to evaluate temporal trends in the use of specific drugs for the initial management of type 2 diabetes and to estimate the economic consequences of non-recommended care.We studied a cohort of 254,973 patients, aged 18 to 100 years, who were newly initiated on oral hypoglycemic monotherapy between January 1, 2006, and December 31, 2008, by using prescription claims data from a large pharmacy benefit manager. Linear regression models were used to assess whether medication initiation patterns changed over time. Multivariate logistic regression models were constructed to identify independent predictors of receiving initial therapy with metformin. We then measured the economic consequences of prescribing patterns by drug class for both patients and the insurer.Over the course of the study period, the proportion of patients initially treated with metformin increased from 51% to 65%, whereas those receiving sulfonylureas decreased from 26% to 18% (P<.001 for both). There was a significant decline in the use of thiazolidinediones (20.1%-8.3%, P<.001) and an increase in prescriptions for dipeptidyl peptidase-4 inhibitors (0.4%-7.3%, P<.001). Younger patients, women, and patients receiving drug benefits through Medicare were least likely to initiate treatment with metformin. Combined patient and insurer spending for patients who were initiated on alpha-glucosidase inhibitors, thiazolidinediones, meglitinides, or dipeptidyl peptidase-4 inhibitors was $677 over a 6-month period compared with $116 and $118 for patients initiated on metformin or a sulfonylurea, respectively, a cost difference of approximately $1120 annually per patient.Approximately 35% of patients initiating an oral hypoglycemic drug did not receive recommended initial therapy with metformin. These practice patterns also have substantial implications for health care spending.