Detailed Information

Cited 0 time in webofscience Cited 25 time in scopus
Metadata Downloads

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

Full metadata record
DC FieldValueLanguage
dc.contributor.authorKwak, Soo Heon-
dc.contributor.authorChoi, Sung Hee-
dc.contributor.authorKim, Kyunga-
dc.contributor.authorJung, Hye Seung-
dc.contributor.authorCho, Young Min-
dc.contributor.authorLim, Soo-
dc.contributor.authorCho, Nam H.-
dc.contributor.authorKim, Seong Yeon-
dc.contributor.authorPark, Kyong Soo-
dc.contributor.authorJang, Hak C.-
dc.date.available2021-02-22T12:02:53Z-
dc.date.issued2013-12-
dc.identifier.issn0012-186X-
dc.identifier.issn1432-0428-
dc.identifier.urihttps://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/11166-
dc.description.abstractWomen 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. 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. 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 x 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 x 10(-5)). 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.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER-
dc.titlePrediction of type 2 diabetes in women with a history of gestational diabetes using a genetic risk score-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1007/s00125-013-3059-x-
dc.identifier.scopusid2-s2.0-84887987730-
dc.identifier.wosid000326599300003-
dc.identifier.bibliographicCitationDIABETOLOGIA, v.56, no.12, pp 2556 - 2563-
dc.citation.titleDIABETOLOGIA-
dc.citation.volume56-
dc.citation.number12-
dc.citation.startPage2556-
dc.citation.endPage2563-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasssci-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEndocrinology & Metabolism-
dc.relation.journalWebOfScienceCategoryEndocrinology & Metabolism-
dc.subject.keywordPlusASSOCIATION-
dc.subject.keywordPlusPREVENTION-
dc.subject.keywordPlusMELLITUS-
dc.subject.keywordAuthorGenetic risk score-
dc.subject.keywordAuthorGestational diabetes-
dc.subject.keywordAuthorRisk prediction-
dc.subject.keywordAuthorType 2 diabetes-
Files in This Item
There are no files associated with this item.
Appears in
Collections
이과대학 > 통계학과 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE