{"doi":"10.2337/dc24-1537","title":"Additive Value of Polygenic Risk Score to Family History for Type 2 Diabetes Prediction: Results From the All of Us Research Database","abstract":"OBJECTIVE: The goal of this study was to assess the additive value of considering type 2 diabetes (T2D) polygenic risk score (PRS) in addition to family history for T2D prediction. RESEARCH DESIGN AND METHODS: Data were obtained from the All of Us (AoU) research database. First-degree T2D family history was self-reported on the personal family history health questionnaire. A PRS was constructed from 1,289 variants identified from a large multiancestry genome-wide association study meta-analysis for T2D. Logistic regression models were run to generate odds ratios (ORs) and 95% CIs for T2D. All models were adjusted for age, sex, and BMI. RESULTS: A total of 109,958 AoU research participants were included in the analysis. The odds of T2D increased with 1 SD PRS (OR 1.75; 95% CI 1.71-1.79) and positive T2D family history (OR 2.32; 95% CI 2.20-2.43). In the joint model, both 1 SD PRS (OR 1.69; 95% CI 1.65-1.72) and family history (OR 2.06; 95% CI 1.98-2.15) were significantly associated with T2D, although the ORs were slightly attenuated. Predictive models that included both the PRS and family history (area under the curve [AUC] 0.794) performed better than models including only family history (AUC 0.763) or the PRS (AUC 0.785). CONCLUSIONS: In predicting T2D, inclusion of a T2D PRS in addition to family history of T2D (first-degree relatives) added statistical value. Further study is needed to determine whether consideration of both family history and a PRS would be useful for clinical T2D prediction.","journal":"Diabetes Care","year":2025,"id":530975,"datarank":0.42934222849106574,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.18792654162595068,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.18792654162595068,"corpus_percentile":56.65661019571439,"corpus_rank":5604,"citation_count":4,"citer_count":4,"citers_with_citation_signal":2,"citers_with_endowment":2,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.643,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":11262,"name":"Laura M. Raffield","orcid":"0000-0002-7892-193X","position":1,"is_corresponding":false},{"id":844808,"name":"Katherine Kolor","orcid":null,"position":2,"is_corresponding":false},{"id":849811,"name":"Alain K. Koyama","orcid":"0000-0002-1246-2937","position":3,"is_corresponding":false},{"id":49163,"name":"Ramal Moonesinghe","orcid":"0000-0001-5327-533X","position":4,"is_corresponding":false},{"id":88629,"name":"Meda E. Pavkov","orcid":"0000-0002-6203-1772","position":5,"is_corresponding":false},{"id":108737,"name":"Cassandra N. Spracklen","orcid":"0000-0003-3590-7182","position":6,"is_corresponding":false},{"id":526,"name":"Muin J. Khoury","orcid":"0000-0002-9887-443X","position":7,"is_corresponding":false},{"id":715073,"name":"Emily Drzymalla","orcid":"0009-0007-7258-3777","position":0,"is_corresponding":true}],"reference_count":26,"raw_metadata":null,"created_at":"2026-07-19T02:51:10.077559Z","pmid":"39841967","pmcid":"PMC11770167","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":[]}