{"doi":"10.1016/j.kint.2023.03.017","title":"Association of polygenic scores with chronic kidney disease phenotypes in a longitudinal study of older adults","abstract":"Risk of chronic kidney disease (CKD) is influenced by environmental and genetic factors and increases sharply in individuals 70 years and older. Polygenic scores (PGS) for kidney disease-related traits have shown promise but require validation in well-characterized cohorts. Here, we assessed the performance of recently developed PGSs for CKD-related traits in a longitudinal cohort of healthy older individuals enrolled in the Australian ASPREE randomized controlled trial of daily low-dose aspirin with CKD risk at baseline and longitudinally. Among 11,813 genotyped participants aged 70 years or more with baseline eGFR measures, we tested associations between PGSs and measured eGFR at baseline, clinical phenotype of CKD, and longitudinal rate of eGFR decline spanning up to six years of follow-up per participant. A PGS for eGFR was associated with baseline eGFR, with a significant decrease of 3.9 mL/min/1.73m2 (95% confidence interval -4.17 to -3.68) per standard deviation (SD) increase of the PGS. This PGS, as well as a PGS for CKD stage 3 were both associated with higher risk of baseline CKD stage 3 in cross-sectional analysis (Odds Ratio 1.75 per SD, 95% confidence interval 1.66-1.85, and Odds Ratio 1.51 per SD, 95% confidence interval 1.43-1.59, respectively). Longitudinally, two separate PGSs for eGFR slope were associated with significant kidney function decline during follow-up. Thus, our study demonstrates that kidney function has a considerable genetic component in older adults, and that new PGSs for kidney disease-related phenotypes may have potential utility for CKD risk prediction in advanced age. Risk of chronic kidney disease (CKD) is influenced by environmental and genetic factors and increases sharply in individuals 70 years and older. Polygenic scores (PGS) for kidney disease-related traits have shown promise but require validation in well-characterized cohorts. Here, we assessed the performance of recently developed PGSs for CKD-related traits in a longitudinal cohort of healthy older individuals enrolled in the Australian ASPREE randomized controlled trial of daily low-dose aspirin with CKD risk at baseline and longitudinally. Among 11,813 genotyped participants aged 70 years or more with baseline eGFR measures, we tested associations between PGSs and measured eGFR at baseline, clinical phenotype of CKD, and longitudinal rate of eGFR decline spanning up to six years of follow-up per participant. A PGS for eGFR was associated with baseline eGFR, with a significant decrease of 3.9 mL/min/1.73m2 (95% confidence interval -4.17 to -3.68) per standard deviation (SD) increase of the PGS. This PGS, as well as a PGS for CKD stage 3 were both associated with higher risk of baseline CKD stage 3 in cross-sectional analysis (Odds Ratio 1.75 per SD, 95% confidence interval 1.66-1.85, and Odds Ratio 1.51 per SD, 95% confidence interval 1.43-1.59, respectively). Longitudinally, two separate PGSs for eGFR slope were associated with significant kidney function decline during follow-up. Thus, our study demonstrates that kidney function has a considerable genetic component in older adults, and that new PGSs for kidney disease-related phenotypes may have potential utility for CKD risk prediction in advanced age. Lay SummaryThe sum of multiple small genetics contributors to a trait such as kidney function can be captured by polygenic risk scores (PGSs), derived from large-scale genome-wide association studies; however, the clinical significance of these scores is still being understood. We tested several recently developed PGSs for kidney traits in 11,813 European Australians, aged >70 years, from the ASPirin in Reducing Events in the Elderly population, with a mean estimated glomerular filtration rate (eGFR) of 72.9 ml/min per 1.73 m2. We validated multiple PGSs for both eGFR and decline in eGFR. At a population level, those with higher PGSs had the lowest mean eGFR of 57 ml/min per 1.73 m2, with significant individual variability. ","journal":"Kidney International","year":2023,"id":332288,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":25,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9533,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1058371,"name":"Julia Jefferis","orcid":"0000-0003-3362-8139","position":1,"is_corresponding":false},{"id":264293,"name":"Rory Wolfe","orcid":"0000-0002-2126-1045","position":2,"is_corresponding":false},{"id":447430,"name":"James B. Wetmore","orcid":"0000-0003-1380-8597","position":3,"is_corresponding":false},{"id":264297,"name":"John J. McNeil","orcid":"0000-0002-1049-5129","position":4,"is_corresponding":false},{"id":104607,"name":"Anne M. Murray","orcid":"0000-0002-2787-8433","position":5,"is_corresponding":false},{"id":48623,"name":"Kevan R. Polkinghorne","orcid":"0000-0002-9851-002X","position":6,"is_corresponding":false},{"id":480797,"name":"Andrew Mallett","orcid":"0000-0002-8752-2551","position":7,"is_corresponding":false},{"id":301792,"name":"Paul Lacaze","orcid":"0000-0002-0902-6798","position":8,"is_corresponding":false},{"id":374280,"name":"Andrew Bakshi","orcid":"0000-0001-5650-7036","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T01:09:30.139849Z","pmid":"37001602","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":[]}