{"doi":"10.3389/fcvm.2024.1478600","title":"Plasma proteomics and carotid intima-media thickness in the UK biobank cohort","abstract":"Background and aims Ultrasound derived carotid intima-media thickness (cIMT) is valuable for cardiovascular risk stratification. We assessed the relative importance of traditional atherosclerosis risk factors and plasma proteins in predicting cIMT measured nearly a decade later. Method We examined 6,136 UK Biobank participants with 1,461 proteins profiled using the proximity extension assay applied to their baseline blood draw who subsequently underwent a cIMT measurement. We implemented linear regression, stepwise Akaike Information Criterion-based, and the least absolute shrinkage and selection operator (LASSO) models to identify potential proteomic as well as non-proteomic predictors. We evaluated our model performance using the proportion variance explained ( R 2 ). Result The mean time from baseline assessment to cIMT measurement was 9.2 years. Age, blood pressure, and anthropometric related variables were the strongest predictors of cIMT with fat-free mass index of the truncal region being the strongest predictor among adiposity measurements. A LASSO model incorporating variables including age, assessment center, genetic risk factors, smoking, blood pressure, trunk fat-free mass index, apolipoprotein B, and Townsend deprivation index combined with 97 proteins achieved the highest R 2 (0.308, 95% C.I. 0.274, 0.341). In contrast, models built with proteins alone or non-proteomic variables alone explained a notably lower R 2 (0.261, 0.228–0.294 and 0.260, 0.226–0.293, respectively). Chromogranin b (CHGB), Cystatin-M/E (CST6), leptin (LEP), and prolargin (PRELP) were the proteins consistently selected across all models. Conclusion Plasma proteins add to the clinical and genetic risk factors in predicting a cIMT measurement. Our findings implicate blood pressure and extracellular matrix-related proteins in cIMT pathophysiology.","journal":"Frontiers in Cardiovascular Medicine","year":2024,"id":452353,"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":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.5922,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":305531,"name":"Pik Fang Kho","orcid":"0000-0001-7831-6062","position":1,"is_corresponding":false},{"id":11257,"name":"Rodrigo Guarischi-Sousa","orcid":"0000-0002-3614-9996","position":2,"is_corresponding":false},{"id":777258,"name":"Jiayan Zhou","orcid":"0000-0001-5974-087X","position":3,"is_corresponding":false},{"id":556967,"name":"Daniel J. Panyard","orcid":"0000-0001-5480-4803","position":4,"is_corresponding":false},{"id":964340,"name":"Zahra Azizi","orcid":"0000-0002-7897-0934","position":5,"is_corresponding":false},{"id":1274122,"name":"Trisha Gupte","orcid":"0000-0003-3695-3244","position":6,"is_corresponding":false},{"id":905245,"name":"Kathleen Watson","orcid":"0000-0001-7202-8553","position":7,"is_corresponding":false},{"id":504420,"name":"Fahim Abbasi","orcid":"0000-0002-3932-8375","position":8,"is_corresponding":false},{"id":7147,"name":"Themistocles L. Assimes","orcid":"0000-0003-2349-0009","position":9,"is_corresponding":false},{"id":1274594,"name":"Ming-Li Chen","orcid":null,"position":0,"is_corresponding":true}],"reference_count":47,"raw_metadata":null,"created_at":"2026-07-19T02:02:50.407779Z","pmid":"39416432","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":[]}