AIMS/HYPOTHESIS: Women with a history of gestational diabetes mellitus (GDM) are at increased risk of future development of type 2 diabetes. Recently, over 65 genetic variants have been confirmed to be associated with diabetes. We investigated whether this genetic information could improve the prediction of future diabetes in women with GDM. METHODS: This was a prospective cohort study consisting of 395 women with GDM who were followed annually with an OGTT. A weighted genetic risk score (wGRS), consisting of 48 variants, was assessed for improving discrimination (C statistic) and risk reclassification (continuous net reclassification improvement [NRI] index) when added to clinical risk factors. RESULTS: Among the 395 women with GDM, 116 (29.4%) developed diabetes during a median follow-up period of 45 months. Women with GDM who went on to develop diabetes had a significantly higher wGRS than those who did not (9.36 ± 0.92 vs 8.78 ± 1.07; p < 1.56 × 10(-7)). In a complex clinical model adjusted for age, prepregnancy BMI, family history of diabetes, blood pressure, fasting glucose and fasting insulin concentration, the C statistic marginally improved from 0.741 without the wGRS to 0.775 with the wGRS (p = 0.015). The addition of the wGRS to the clinical model resulted in a modest improvement in reclassification (continuous NRI 0.430 [95% CI 0.218, 0.642]; p = 7.0 × 10(-5)). CONCLUSIONS/ INTERPRETATION: In women with GDM, who are at high risk of diabetes, the wGRS was significantly associated with the future development of diabetes. Furthermore, it improved prediction over clinical risk factors.
AIMS/HYPOTHESIS: Women with a history of gestational diabetes mellitus (GDM) are at increased risk of future development of type 2 diabetes. Recently, over 65 genetic variants have been confirmed to be associated with diabetes. We investigated whether this genetic information could improve the prediction of future diabetes in women with GDM. METHODS: This was a prospective cohort study consisting of 395 women with GDM who were followed annually with an OGTT. A weighted genetic risk score (wGRS), consisting of 48 variants, was assessed for improving discrimination (C statistic) and risk reclassification (continuous net reclassification improvement [NRI] index) when added to clinical risk factors. RESULTS: Among the 395 women with GDM, 116 (29.4%) developed diabetes during a median follow-up period of 45 months. Women with GDM who went on to develop diabetes had a significantly higher wGRS than those who did not (9.36 ± 0.92 vs 8.78 ± 1.07; p < 1.56 × 10(-7)). In a complex clinical model adjusted for age, prepregnancy BMI, family history of diabetes, blood pressure, fasting glucose and fasting insulin concentration, the C statistic marginally improved from 0.741 without the wGRS to 0.775 with the wGRS (p = 0.015). The addition of the wGRS to the clinical model resulted in a modest improvement in reclassification (continuous NRI 0.430 [95% CI 0.218, 0.642]; p = 7.0 × 10(-5)). CONCLUSIONS/ INTERPRETATION: In women with GDM, who are at high risk of diabetes, the wGRS was significantly associated with the future development of diabetes. Furthermore, it improved prediction over clinical risk factors.
Authors: Mustafa Kanat; Diedre Winnier; Luke Norton; Nazik Arar; Chris Jenkinson; Ralph A Defronzo; Muhammad A Abdul-Ghani Journal: Diabetes Care Date: 2011-02-23 Impact factor: 19.112
Authors: Soo Heon Kwak; Sung Hee Choi; Hye Seung Jung; Young Min Cho; Soo Lim; Nam H Cho; Seong Yeon Kim; Kyong Soo Park; Hak C Jang Journal: J Clin Endocrinol Metab Date: 2013-03-07 Impact factor: 5.958
Authors: Valeriya Lyssenko; Anna Jonsson; Peter Almgren; Nicoló Pulizzi; Bo Isomaa; Tiinamaija Tuomi; Göran Berglund; David Altshuler; Peter Nilsson; Leif Groop Journal: N Engl J Med Date: 2008-11-20 Impact factor: 91.245
Authors: Philippa J Talmud; Aroon D Hingorani; Jackie A Cooper; Michael G Marmot; Eric J Brunner; Meena Kumari; Mika Kivimäki; Steve E Humphries Journal: BMJ Date: 2010-01-14
Authors: Mark O Goodarzi; Nicholette D Palmer; Jinrui Cui; Xiuqing Guo; Yii-Der I Chen; Kent D Taylor; Leslie J Raffel; Lynne E Wagenknecht; Thomas A Buchanan; Willa A Hsueh; Jerome I Rotter Journal: J Clin Endocrinol Metab Date: 2020-04-01 Impact factor: 5.958
Authors: Raziel Rojas-Rodriguez; Rachel Ziegler; Tiffany DeSouza; Sana Majid; Aylin S Madore; Nili Amir; Veronica A Pace; Daniel Nachreiner; David Alfego; Jomol Mathew; Katherine Leung; Tiffany A Moore Simas; Silvia Corvera Journal: Sci Transl Med Date: 2020-11-25 Impact factor: 17.956