{"doi":"10.1210/clinem/dgaa087","title":"Plasma Glycated CD59 Predicts Early Gestational Diabetes and Large for Gestational Age Newborns","abstract":"CONTEXT: Gestational diabetes mellitus (GDM) diagnosed in early pregnancy is a health care challenge because it increases the risk of adverse outcomes. Plasma-glycated CD59 (pGCD59) is an emerging biomarker for diabetes and GDM. The aim of this study was to assess the performance of pGCD59 as a biomarker of early GDM and its association with delivering a large for gestational age (LGA) infant. OBJECTIVES: To assess the performance of pGCD59 to identify women with GDM in early pregnancy (GDM < 20) and assess the association of pGCD59 with LGA and potentially others adverse neonatal outcomes linked to GDM. METHODS: Blood levels of pGCD59 were measured in samples from 693 obese women (body mass index > 29) undergoing a 75-g, 2-hour oral glucose tolerance test (OGTT) at <20 weeks' gestation in the Vitamin D and Lifestyle Intervention study: the main analyses included 486 subjects who had normal glucose tolerance throughout the pregnancy, 207 who met criteria for GDM at <20 weeks, and 77 diagnosed with GDM at pregnancy weeks 24 through 28. Reference tests were 75-g, 2-hour OGTT adjudicated based on International Association of Diabetes and Pregnancy Study Group criteria. The index test was a pGCD59 ELISA. RESULTS: Mean pGCD59 levels were significantly higher (P < 0.001) in women with GDM < 20 (3.9 ± 1.1 standard peptide units [SPU]) than in those without (2.7 ± 0.7 SPU). pGCD59 accurately identified GDM in early pregnancy with an area under the curve receiver operating characteristic curves of 0.86 (95% confidence interval [CI], 0.83-0.90). One-unit increase in maternal pGCD59 level was associated with 36% increased odds of delivering an LGA infant (odds ratio for LGA vs non-LGA infant: 1.4; 95% CI, 1.1-1.8; P = 0.016). CONCLUSION: Our results indicate that pGCD59 is a simple and accurate biomarker for detection of GDM in early pregnancy and risk assessment of LGA.","journal":"The Journal of Clinical Endocrinology & Metabolism","year":2020,"id":94642,"datarank":1.1046125257276551,"base_score":3.6375861597263857,"endowment":3.6375861597263857,"self_citation_contribution":0.5456379239589579,"citation_network_contribution":0.5589746017686971,"self_endowment_contribution":0.5456379239589579,"citer_contribution":0.5589746017686971,"corpus_percentile":null,"corpus_rank":null,"citation_count":37,"citer_count":22,"citers_with_citation_signal":18,"citers_with_endowment":18,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9602,"is_data_producer":true,"deposit_databanks":{"ISRCTN":["ISRCTN70595832"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":378993,"name":"Miguel Ángel Luque-Fernández","orcid":"0000-0001-6683-5164","position":1,"is_corresponding":false},{"id":274327,"name":"Delia Bogdanet","orcid":"0000-0001-6127-5049","position":2,"is_corresponding":false},{"id":471383,"name":"Gernot Desoyé","orcid":"0000-0002-5715-3230","position":3,"is_corresponding":false},{"id":274331,"name":"Fidelma Dunne","orcid":"0000-0003-3682-9403","position":4,"is_corresponding":false},{"id":413447,"name":"José A. Halperin","orcid":"0000-0003-4749-5285","position":5,"is_corresponding":false},{"id":471382,"name":"Dong-Dong Ma","orcid":"0000-0001-7125-9587","position":0,"is_corresponding":true}],"reference_count":43,"raw_metadata":null,"created_at":"2026-07-18T22:33:00.770265Z","pmid":"32069353","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}