Prediction of type 2 diabetes in women with a history of gestational diabetes using a genetic risk score

Soo Heon Kwak,
Sung Hee Choi,
Kyunga Kim,
Hye Seung Jung,
Young Min Cho,
Soo Lim,
Nam H. Cho,
Seong Yeon Kim,
Kyong Soo Park,
Hak C. Jang
Abstract

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.

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