{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T13:00:55Z","timestamp":1790773255350,"version":"4.1.0"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"National Hospital"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Diabetologia"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims\/hypothesis<\/jats:title>\n                    <jats:p>Women with previous gestational diabetes mellitus (GDM) have an increased risk of developing both type 1 and type 2 diabetes. However, predicting the risk on a personal level is challenging. Polygenic scores (PGSs), which capture an individual's genetic susceptibility to disease, may improve risk prediction. We aimed to examine the utility of PGSs for type 1 diabetes (T1D-PGS) and type 2 diabetes (T2D-PGS) to predict overt diabetes in women with previous GDM, with a median follow-up time of 30 years after index pregnancy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted an observational study including 370 women diagnosed with GDM between 1978 and 1996. Development of type 1 and type 2 diabetes was identified using national registry data comprising ICD-10 diagnosis codes on diabetes until 2019, combined with a glucose tolerance test performed in 2000\u20132002. The predictive ability of T1D-PGS and T2D-PGS and clinical risk factors during index pregnancy for type 1 and type 2 diabetes, including maternal age at delivery, pre-pregnancy BMI, fasting plasma glucose, insulin treatment and family history of diabetes, was evaluated using receiver operating characteristic area under the curve (AUC).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      During a median follow-up of 30 years, 200 (54.1%) women were diagnosed with diabetes: 30 (8.1%) with type 1 diabetes, 157 (42.4%) with type 2 diabetes and 13 (3.5%) carried monogenic diabetes variants. The mean T1D-PGS was higher in women with type 1 diabetes compared with those without (13.6 vs 11.5,\n                      <jats:italic>p<\/jats:italic>\n                      &lt;0.001), while the T2D-PGS was similar between women with and without type 2 diabetes (52.9 vs 52.8,\n                      <jats:italic>p<\/jats:italic>\n                      =0.16). The T1D-PGS and clinical risk factors during pregnancy were discriminative of type 1 diabetes with AUCs of 0.788 and 0.839, respectively, while a combined model yielded an AUC of 0.887. The T2D-PGS and clinical risk factors during pregnancy yielded AUCs of 0.539 and 0.745, respectively. The combined model had an AUC of 0.752.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions\/interpretation<\/jats:title>\n                    <jats:p>In women with previous GDM, the T1D-PGS showed good predictive ability for the development of type 1 diabetes, especially when combined with clinical risk factors during pregnancy, and may have potential to guide targeted follow-up and early treatment interventions. The T2D-PGS showed no predictive ability for type 2 diabetes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00125-026-06824-0","type":"journal-article","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T14:45:37Z","timestamp":1785854737000},"page":"3261-3272","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting future risk of type 1 and type 2 diabetes after gestational diabetes mellitus using polygenic scores: a cohort study"],"prefix":"10.1007","volume":"69","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9868-7629","authenticated-orcid":false,"given":"Isabella L.","family":"J\u00f8rgensen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2067-5246","authenticated-orcid":false,"given":"Peter","family":"Damm","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8227-1469","authenticated-orcid":false,"given":"Mette K.","family":"Andersen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0135-8218","authenticated-orcid":false,"given":"Pauline K.","family":"Reim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0120-2638","authenticated-orcid":false,"given":"Lana R. 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Laboratory assistance was provided by T. H. Lorentzen at the Novo Nordisk Foundation Center for Basic Metabolic Research. HPC facilities and technical expertise were provided by the Data Analytics Platform, including Staff Scientist C. F. Rundsten, at the Novo Nordisk Foundation Center for Basic Metabolic Research.","order":1,"name":"Ethics","label":"Acknowledgements","group":{"name":"EthicsHeading","label":"Ethics"}},{"value":"The data contain sensitive personal information and are thus not openly available due to data protection regulations. Access to the register data is governed and provided by Statistics Denmark and can be granted to researchers affiliated with authorised research institutions following approval from relevant Danish Authorities (Danish Data Protection Agency). Access to genetic and phenotypic data requires approval from the Danish Data Protection Agency and Scientific Ethical Committee and a data processor agreement must be signed between the data processor and data controller and may not be processed for purposes other than statistical and scientific studies.","order":2,"name":"Ethics","label":"Data availability","group":{"name":"EthicsHeading","label":"Ethics"}},{"value":"This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. ILJ is part of a clinical research and implementation project, TRANSLATE, supported by the Innovation Foundation (9090-00078B). ACBT is supported by the Novo Nordisk Foundation (NNF17OC0028328) and the BRIDGE \u2013 Translational Excellence Programme (bridge.ku.dk) at the Faculty of Health and Medical Sciences, University of Copenhagen, funded by the Novo Nordisk Foundation (NNF20SA0064340). The Novo Nordisk Foundation Center for Basic Metabolic Research is supported by an unrestricted grant from the Novo Nordisk Foundation (NNF23SA0084103).","order":3,"name":"Ethics","label":"Funding","group":{"name":"EthicsHeading","label":"Ethics"}},{"value":"LR serves as the chairperson of the Diabetic Pregnancy Study Group (unpaid); has received grants from Novo Nordisk A\/S (grant number: U1111-1209-6358) for the CopenFast trial, an investigator sponsored study, and from the Novo Nordisk Foundation (grant number: NNF24OC0091713) for an investigator sponsored randomised controlled trial; and participated in the European Association for the Study of Diabetes annual meeting 2023 as an invitee by Novo Nordisk. PD and ERM are involved in clinical studies on the use of insulin in pregnant women with pre-existing diabetes in collaboration with Novo Nordisk, but no personal honorarium is received. TH owns stocks in Novo Nordisk. The authors declare that there are no other relationships or activities that might bias, or be perceived to bias, their work.","order":4,"name":"Ethics","label":"Authors\u2019 relationships and activities","group":{"name":"EthicsHeading","label":"Ethics"}},{"value":"The study was conceived by ILJ, PD, TH and ACBT. The study was designed by ILJ, PD, TH, ACBT and PKR. ILJ, PD, JL and LRFM collected data. ILJ performed statistical analysis and prepared the first draft of the manuscript. All co-authors took part in interpreting data and revising the manuscript, and approved the final version to be published. ILJ is the guarantor of this work.","order":5,"name":"Ethics","label":"Contribution statement","group":{"name":"EthicsHeading","label":"Ethics"}}]}}