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DOI 10.2337/dc24-0022

Медицинская библиотека · Diabetes care · 2024

Genome-Wide Polygenic Risk Score Predicts Incident Type 2 Diabetes in Women With History of Gestational Diabetes.

Choi Jaewon, Lee Hyunsuk, Kuang Alan, Huerta-Chagoya Alicia, Scholtens Denise M, Choi Daeho, Han Minseok, Lowe William L, Manning Alisa K, Jang Hak Chul, Park Kyong Soo, Kwak Soo Heon

СтатьяПоддержка исследования: вне правительства СШАПоддержка NIH: внешняя программаПеревод в очереди

Аннотация

OBJECTIVE

Women with a history of gestational diabetes mellitus (GDM) are at increased risk of developing type 2 diabetes (T2D). It remains unclear whether genetic information improves prediction of incident T2D in these women.

RESEARCH DESIGN AND

METHODS

Using five independent cohorts representing four different ancestries (n = 1,895), we investigated whether a genome-wide T2D polygenic risk score (PRS) is associated with increased risk of incident T2D. We also calculated the area under the receiver operating characteristics curve (AUROC) and continuous net reclassification improvement (NRI) following the incorporation of T2D PRS into clinical risk models to assess the diagnostic utility.

RESULTS

Among 1,895 women with previous history of GDM, 363 (19.2%) developed T2D in a range of 2 to 30 years. T2D PRS was higher in those who developed T2D (-0.08 vs. 0.31, P = 2.3 × 10-11) and was associated with an increased risk of incident T2D (odds ratio 1.52 per 1-SD increase, 95% CI 1.05-2.21, P = 0.03). In a model that includes age, family history of diabetes, systolic blood pressure, and BMI, the incorporation of PRS led to an increase in AUROC for T2D from 0.71 to 0.74 and an intermediate improvement of NRI (0.32, 95% CI 0.15-0.49, P = 3.0 × 10-4). Although there was variation, a similar trend was observed across study cohorts.

CONCLUSIONS

In cohorts of GDM women with diverse ancestry, T2D PRS was significantly associated with future development of T2D. A significant but small improvement was observed in AUROC when T2D PRS was integrated into clinical risk models to predict incident T2D.

Для цитирования: Choi Jaewon, Lee Hyunsuk, Kuang Alan, Huerta-Chagoya Alicia, Scholtens Denise M, Choi Daeho, Han Minseok, Lowe William L, Manning Alisa K, Jang Hak Chul, Park Kyong Soo, Kwak Soo Heon. Genome-Wide Polygenic Risk Score Predicts Incident Type 2 Diabetes in Women With History of Gestational Diabetes.. Diabetes care. 2024. DOI: 10.2337/dc24-0022.

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