한빛사논문
서울대학교 의과대학, 서울대학교 병원
Jaewon Choi 1,2, Hyunsuk Lee 3,4,5, Alan Kuang 6, Alicia Huerta-Chagoya 7,8, Denise M Scholtens 6, Daeho Choi 9, Minseok Han 9, William L Lowe Jr 10, Alisa K Manning 11,12,13, Hak Chul Jang 14, Kyong Soo Park 3,5,15, Soo Heon Kwak 1,3
1Division of Data Science Research, Innovative Biomedical Technology Research Institute, Seoul National University Hospital, Seoul, Republic of Korea.
2Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea.
3Department of Internal Medicine, Seoul National University Hospital and Seoul National University College of Medicine, Seoul, Republic of Korea.
4Department of Translational Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
5Genomic Medicine Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
6Department of Preventive Medicine (Biostatistics), Northwestern University Feinberg School of Medicine, Chicago, IL.
7Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.
8Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA.
9Seoul National University College of Medicine, Seoul, Republic of Korea.
10Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.
11Department of Medicine, Harvard Medical School, Boston, MA.
12Metabolism Program, The Broad Institute of MIT and Harvard, Cambridge, MA.
13Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA.
14Department of Internal Medicine, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seongnam, Republic of Korea.
15Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Corresponding author: Soo Heon Kwak
Abstract
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.
논문정보
관련 링크
연구자 키워드
관련분야 연구자보기
소속기관 논문보기
관련분야 논문보기
해당논문 저자보기