{"doi":"10.1210/clinem/dgad456","title":"Utility of Polygenic Scores for Differentiating Diabetes Diagnosis Among Patients With Atypical Phenotypes of Diabetes","abstract":"<jats:title>Abstract</jats:title>\n               <jats:sec>\n                  <jats:title>Context</jats:title>\n                  <jats:p>Misclassification of diabetes type occurs in people with atypical presentations of type 1 diabetes (T1D) or type 2 diabetes (T2D). Although current clinical guidelines suggest clinical variables and treatment response as ways to help differentiate diabetes type, they remain insufficient for people with atypical presentations.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Objective</jats:title>\n                  <jats:p>This work aimed to assess the clinical utility of 2 polygenic scores (PGSs) in differentiating between T1D and T2D.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Methods</jats:title>\n                  <jats:p>Patients diagnosed with diabetes in the UK Biobank were studied (N = 41 787), including 464 (1%) and 15 923 (38%) who met the criteria for classic T1D and T2D, respectively, and 25 400 (61%) atypical diabetes. The validity of 2 published PGSs for T1D (PGST1D) and T2D (PGST2D) in differentiating classic T1D or T2D was assessed using C statistic. The utility of genetic probability for T1D based on PGSs (GenProb-T1D) was evaluated in atypical diabetes patients.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Results</jats:title>\n                  <jats:p>The joint performance of PGST1D and PGST2D for differentiating classic T1D or T2D was outstanding (C statistic = 0.91), significantly higher than that of PGST1D alone (0.88) and PGST2D alone (0.70), both P less than .001. Using an optimal cutoff of GenProb-T1D, 23% of patients with atypical diabetes had a higher probability of T1D and its validity was independently supported by clinical presentations that are characteristic of T1D.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion</jats:title>\n                  <jats:p>PGST1D and PGST2D can be used to discriminate classic T1D and T2D and have potential clinical utility for differentiating these 2 types of diseases among patients with atypical diabetes.</jats:p>\n               </jats:sec>","journal":"The Journal of Clinical Endocrinology &amp; Metabolism","year":2023,"id":622518,"datarank":0.38474240361923057,"base_score":2.5649493574615367,"endowment":2.5649493574615367,"self_citation_contribution":0.38474240361923057,"citation_network_contribution":0.0,"self_endowment_contribution":0.38474240361923057,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":12,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1251947,"name":"Zhuqing Shi","orcid":"0000-0001-6321-950X","position":1,"is_corresponding":false},{"id":271520,"name":"Jun Wei","orcid":"0000-0001-8888-0417","position":2,"is_corresponding":false},{"id":1608496,"name":"Andrew S Rifkin","orcid":null,"position":3,"is_corresponding":false},{"id":1608497,"name":"S Lilly Zheng","orcid":null,"position":4,"is_corresponding":false},{"id":1608498,"name":"Brian T Helfand","orcid":null,"position":5,"is_corresponding":false},{"id":1608499,"name":"Nadim Ilbawi","orcid":null,"position":6,"is_corresponding":false},{"id":1608500,"name":"Henry M Dunnenberger","orcid":null,"position":7,"is_corresponding":false},{"id":1608501,"name":"Peter J Hulick","orcid":null,"position":8,"is_corresponding":false},{"id":260667,"name":"Arman Qamar","orcid":"0000-0003-0607-1240","position":9,"is_corresponding":false},{"id":33041,"name":"Jianfeng Xu","orcid":"0000-0002-1343-8752","position":10,"is_corresponding":false},{"id":1020192,"name":"Liana K. Billings","orcid":"0000-0001-7991-3010","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Utility of Polygenic Scores for Differentiating Diabetes Diagnosis Among Patients With Atypical Phenotypes of Diabetes","abstract":"<jats:title>Abstract</jats:title>\n               <jats:sec>\n                  <jats:title>Context</jats:title>\n                  <jats:p>Misclassification of diabetes type occurs in people with atypical presentations of type 1 diabetes (T1D) or type 2 diabetes (T2D). Although current clinical guidelines suggest clinical variables and treatment response as ways to help differentiate diabetes type, they remain insufficient for people with atypical presentations.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Objective</jats:title>\n                  <jats:p>This work aimed to assess the clinical utility of 2 polygenic scores (PGSs) in differentiating between T1D and T2D.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Methods</jats:title>\n                  <jats:p>Patients diagnosed with diabetes in the UK Biobank were studied (N = 41 787), including 464 (1%) and 15 923 (38%) who met the criteria for classic T1D and T2D, respectively, and 25 400 (61%) atypical diabetes. The validity of 2 published PGSs for T1D (PGST1D) and T2D (PGST2D) in differentiating classic T1D or T2D was assessed using C statistic. The utility of genetic probability for T1D based on PGSs (GenProb-T1D) was evaluated in atypical diabetes patients.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Results</jats:title>\n                  <jats:p>The joint performance of PGST1D and PGST2D for differentiating classic T1D or T2D was outstanding (C statistic = 0.91), significantly higher than that of PGST1D alone (0.88) and PGST2D alone (0.70), both P less than .001. Using an optimal cutoff of GenProb-T1D, 23% of patients with atypical diabetes had a higher probability of T1D and its validity was independently supported by clinical presentations that are characteristic of T1D.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion</jats:title>\n                  <jats:p>PGST1D and PGST2D can be used to discriminate classic T1D and T2D and have potential clinical utility for differentiating these 2 types of diseases among patients with atypical diabetes.</jats:p>\n               </jats:sec>","is_dataset_classified":null,"base_score":2.5649493574615367,"endowment":2.5649493574615367,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"37560999","pmcid":null,"openalex_id":"https://openalex.org/W4385715236","authors":[],"funders":[{"funder_name":"Auxiliary of NorthShore University HealthSystem","grant_id":"","title":null}],"total_grants":1,"fwci":2.5957,"citation_percentile":0.90426135,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":3},{"year":2025,"count":6},{"year":2026,"count":2}],"oa_status":"bronze","license":"https://academic.oup.com/pages/standard-publication-reuse-rights","oa_locations":[{"url":"https://academic.oup.com/jcem/article-pdf/109/1/107/54731767/dgad456.pdf","host_type":"journal"},{"url":"https://academic.oup.com/jcem/advance-article-pdf/doi/10.1210/clinem/dgad456/51114347/dgad456.pdf","host_type":"publisher"},{"url":"https://doi.org/10.1210/clinem/dgad456","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/37560999","host_type":"repository"}],"fields_of_study":["Genetic Associations and Epidemiology","Diabetes and associated disorders","Pancreatic function and diabetes","Humans","Diabetes Mellitus, Type 2","Diabetes Mellitus, Type 1","UK Biobank","Phenotype"],"mesh_terms":["UK Biobank","Diabetes Mellitus, Type 1","Diabetes Mellitus, Type 2","Humans","Phenotype"],"keywords":["Type 1 diabetes","Medicine","Type 2 diabetes","Diabetes mellitus","Biobank","Internal medicine","Bioinformatics","Endocrinology","Biology","Ketoacidosis","Microvascular Complications","Type 1 Diabetes (T1d)","Type 2 Diabetes (T2d)","Atypical Diabetes","Diabetes Heterogeneity","Polygenic Score (Pgs)"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Reduced inequalities"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-03T19:55:58.888971Z","pmid":null,"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":[]}