{"doi":"10.1101/2022.03.08.22271868","title":"The influence of genetic predisposition and physical activity on risk of Gestational Diabetes Mellitus in the nuMoM2b cohort","abstract":"Abstract Importance Polygenic risk scores (PRS) for Type II Diabetes Mellitus (T2DM) can improve risk prediction for Gestational Diabetes Mellitus (GDM), yet the strength of the relationship between genetic and lifestyle risk factors has not been quantified. Objective To assess the effects of PRS and physical activity on existing GDM risk models and identify patient subgroups who may receive the most benefits from receiving a PRS or activity intervention. Design, Settings, and Participants The Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b) study was established to study individuals without previous pregnancy lasting 20 weeks or more (nulliparous) and to elucidate factors associated with adverse pregnancy outcomes. A sub-cohort of 3,533 participants with European ancestry were used for risk assessment and performance evaluation. Exposures Self-reported total physical activity in early pregnancy was quantified as metabolic equivalent of tasks (METs) in hours/week. Polygenic risk scores were calculated for T2DM using contributions of 85 single nucleotide variants, weighted by their association in the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium data. Main Outcomes and Measures Prediction of the development of GDM from clinical, genetic, and environmental variables collected in early pregnancy. The risk model is assessed using measures of model discrimination and calibration. Odds ratio and positive likelihood ratio were used for evaluating the effect of PRS and physical activity on GDM risk. Results In high-risk population subgroups (body mass index ≥ 25 or age ≥ 35), individuals with PRS in the top 25 th percentile or METs below 450 have significantly increased odds of GDM diagnosis. Participants with both high PRS and low METs have three times higher odds of GDM diagnosis than the population. Conversely, participants with high PRS and METs ≥ 450 do not exhibit increased odds of GDM diagnosis, and those with low METs and low PRS have reduced odds of GDM. The relationship between PRS and METs was found to be nonadditive. Conclusions and Relevance In high-risk patient subgroups the addition of PRS resulted in increased risk of GDM diagnosis, suggesting the benefits of targeted PRS ascertainment to encourage early intervention. Increased physical activity is associated with decreased risk of GDM, particularly among individuals genetically predisposed to T2DM. Key Points Question Do genetic predisposition to diabetes and physical activity in early pregnancy cooperatively impact risk of Gestational Diabetes Mellitus (GDM) among nulliparas? Findings Risk of GDM diagnosis increases significantly for nulliparas with high polygenic risk score (PRS) and with low physical activity. The odds ratio of developing GDM with high PRS was estimated to be 2.2, 1.6 with low physical activity, and 3.5 in combination. Meaning Physical activity in early pregnancy is associated with reduced risk of GDM and reversal of excess risk in genetically predisposed individuals. The interaction between PRS and physical activity may identify subjects for targeted interventions.","journal":"medRxiv","year":2022,"id":302872,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.958,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":72853,"name":"Hoyin Chu","orcid":"0000-0001-8630-3667","position":1,"is_corresponding":false},{"id":908339,"name":"Rashika Ramola","orcid":"0000-0002-4970-5242","position":2,"is_corresponding":false},{"id":908340,"name":"Rafael F. 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Hahn","orcid":"0000-0002-5731-8808","position":11,"is_corresponding":false},{"id":572505,"name":"Sriraam Natarajan","orcid":"0000-0001-9889-6260","position":12,"is_corresponding":false},{"id":331592,"name":"David M. Haas","orcid":"0000-0002-8379-0743","position":13,"is_corresponding":false},{"id":17057,"name":"PREDRAG RADIVOJAC","orcid":"0000-0002-6769-0793","position":14,"is_corresponding":false},{"id":108027,"name":"Kymberleigh A. Pagel","orcid":"0000-0001-8544-9250","position":0,"is_corresponding":true}],"reference_count":29,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:32:20.348385Z","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":[]}