0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessBackground: Women with prior gestational diabetes (GDM) are at exceptionally high risk for type 2 diabetes (T2D). Yet, little is known about genetic determinants for the progression to T2D from GDM. Further, inference from existing data is hindered by small sample size. In a large study based on two independent populations, we examined a genetic risk score (GRS) for T2D in relation to the progression risk. Methods: This study included white women in the Diabetes and Women’s Health Study, which followed women with GDM from the Nurses’ Health Study II (NHSII, N = 1998) and the Danish National Birth Cohort (DNBC, N = 550). A GRS of T2D was calculated using 59 T2D SNPs (GRS59) from genome-wide association studies in European populations. GRS scores for beta-cell function (GRSBC) and insulin resistance (GRSIR) were derived based on subsets of these SNPs. The relative risks (RRs) of progression to T2D were estimated using log-binomial regression. RRs from the two cohorts were meta-analyzed using fixed effects models. Results: During the study follow-ups of more than 10 years after the index pregnancy, 416 (20.8%) in NHSII and 155 (28.2%) women in DNBC developed T2D. GRS59 was positively related to the risk of progression to T2D. RRs (95% CI) for increasing quartiles of GRS59 were 1.00, 0.99 (0.79, 1.23), 1.26 (1.03, 1.55), and 1.25 (1.01, 1.53), respectively (p-trend = 0.008). The associations were significantly stronger among lean (pre-pregnant BMI < 25 kg/m2) than overweight or obese women (p-interaction < 0.001). Further, GRSIR, but not GRSBC, was related to the risk of T2D. RRs (95% CI) for increasing quartiles of GRSIR were 1.00, 1.25 (1.02, 1.55), 1.32 (1.07, 1.64), and 1.29 (1.05, 1.58), respectively (p-trend = 0.02). The results were generally consistent across the two cohorts. Conclusion: In this large prospective study of women with prior GDM, greater GRS of T2D, especially GRS of insulin resistance, was associated with greater risk of progression to T2D. Disclosure M. Li: None. M.L. Rahman: None. J. Wu: None. M. Ding: None. J.E. Chavarro: None. Y. Lin: None. S.H. Ley: None. L. Grunnet: None. S. Hinkle: None. A. Thuesen: None. E. Yeung: None. R.E. Gore-Langton: None. S.J. Sherman: None. L. Hjort: None. F.B. Kampmann: None. P. Damm: Advisory Panel; Self; Novo Nordisk A/S. Other Relationship; Self; Novo Nordisk A/S. F. Tekola-Ayele: None. A. Liu: None. J. Mills: None. A.A. Vaag: Employee; Self; AstraZeneca. S.F. Olsen: None. F. Hu: None. C. Zhang: None. Funding Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institutes of Health; March of Dimes Birth Defects Foundation; Innovation Fund Denmark; Health Foundation; Heart Foundation; European Union
Mengying Li, Mohammad L. Rahman, Jing Wu, Ming Ding, Jorge E. Chavarro, Yuan Lin, Sylvia H. Ley, Louise Groth Grunnet, Stefanie N. Hinkle, Anne Cathrine B. Thuesen, Edwina Yeung, Robert E. Gore‐Langton, Seth Sherman, Line Hjort, Freja Bach Kampmann, Peter Damm, Fasil Tekola‐Ayele, Aiyi Liu, James L. Mills, Allan Vaag, Sjúrđur F. Olsen, Frank B Hu, CUILIN ZHANG (2019). 1705-P: Genetic Risk Score of Type 2 Diabetes and Progression Risk from Gestational Diabetes to Type 2 Diabetes: Results from Two Independent Populations. , 68(Supplement_1), DOI: https://doi.org/10.2337/db19-1705-p.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2019
Authors
23
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.2337/db19-1705-p
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access