{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T10:07:58Z","timestamp":1789553278920,"version":"build-2803163510"},"reference-count":41,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"12","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2026,6,16]]},"abstract":"<jats:sec xml:lang=\"en\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p xml:lang=\"en\">Coronary artery disease (CAD) is a leading global cause of mortality, yet the predictive accuracy of conventional risk models is limited. Here, we integrate conventional risk factors, polygenic risk scores, and large\u2010scale proteomics to develop a unified model for enhanced CAD risk prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p xml:lang=\"en\">Using data from UK Biobank, participants with plasma proteomics and genetic risk data were included after excluding prevalent CAD. Participants from England were split into training (n=32\u2009330) and internal validation (n=13\u2009857) sets, and Scotland\/Wales participants formed an external validation set (n=5775). Incident CAD was ascertained from linked health records. A 202\u2010protein proteomic risk score was derived by least absolute shrinkage and selection operator Cox regression, and CatBoost models were trained using conventional risk factors alone and with incremental addition of polygenic risk scores and protein proteomic risk scores; Shapley Additive Explanations\u2010guided forward selection identified a compact protein panel.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p xml:lang=\"en\">Across cohorts, the median age was 58\u2009years and \u223c45% were men. Protein proteomic risk score was dose\u2010dependently associated with CAD risk. Compared with conventional risk factors alone, integrating polygenic risk scores and protein proteomic risk scores improved discrimination, with the area under the curve increasing from 0.750 (95% CI, 0.732\u20130.767) to 0.789 (95% CI, 0.772\u20130.805) in internal validation and from 0.717 (95% CI, 0.683\u20130.750) to 0.762 (95% CI, 0.732\u20130.791) in external validation. A 9\u2010protein panel (GDF15 [growth differentiation factor 15], MMP12 [matrix metalloproteinase 12], NPPB [natriuretic peptide B], PGF [placental growth factor], REN [renin], ADGRG2 [adhesion G\u2010protein coupled receptor], ACE2 [angiotensin\u2010converting enzyme 2], CDCP1 [CUB domain\u2010containing protein 1], CXCL17 [C\u2010X\u2010C motif chemokine ligand 17)]) captured most proteomic predictive information.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p xml:lang=\"en\">Our findings demonstrate that integrating conventional risk factors, polygenic risk scores, and proteomic data improves CAD risk prediction. This study highlights the utility of proteomics in precision cardiovascular medicine and simplified risk stratification tools.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/jaha.125.047248","type":"journal-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T12:14:59Z","timestamp":1781525699000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Machine Learning\u2010Driven Prediction of Coronary Artery Disease Risk Based on UK Biobank Plasma Proteomics"],"prefix":"10.1161","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0629-1456","authenticated-orcid":false,"given":"Yuezhong","family":"Huang","sequence":"first","affiliation":[{"name":"The Second Affiliated Hospital and Yuying Children\u2019s Hospital of Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"The Second Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoli","family":"Chen","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital and Yuying Children\u2019s Hospital of Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"The Second Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9202-7962","authenticated-orcid":false,"given":"Hao","family":"Zhang","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital and Yuying Children\u2019s Hospital of Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"The Second Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7764-2389","authenticated-orcid":false,"given":"Zhanpei","family":"Bai","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital and Yuying Children\u2019s Hospital of Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"The Second Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Shen","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital and Yuying Children\u2019s Hospital of Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"The Second Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daishan","family":"Zheng","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital and Yuying Children\u2019s Hospital of Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"The Second Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longyu","family":"Fang","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital and Yuying Children\u2019s Hospital of Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"The Second Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongzi","family":"Song","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital and Yuying Children\u2019s Hospital of Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"The Second Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0034-8475","authenticated-orcid":false,"given":"Hebei","family":"Gao","sequence":"additional","affiliation":[{"name":"The Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Eye Hospital, Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4709-4385","authenticated-orcid":false,"given":"Fan","family":"Lu","sequence":"additional","affiliation":[{"name":"The Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Eye Hospital, Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"Eye Hospital, Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7852-6358","authenticated-orcid":false,"given":"Xiu\u2010Feng","family":"Huang","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital and Yuying Children\u2019s Hospital of Wenzhou Medical University","place":["Wenzhou, China"]},{"name":"The Second Affiliated Hospital of Wenzhou Medical University","place":["Wenzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2020.11.010"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000000558"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000000678"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.i2416"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1605086"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajcnut.2023.08.002"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehx144"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamacardio.2018.1717"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06592-6"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.121.058303"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10654-024-01168-8"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCGEN.123.004053"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1038\/s43856-025-00872-0"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12986-025-01040-w"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(12)60404-8"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1001779"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06563-x"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06547-x"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v033.i01"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1101\/2022.06.16.22276246"},{"key":"e_1_3_2_22_2","first-page":"6639","volume-title":"Proceedings of the 32nd international conference on neural information processing systems","author":"Prokhorenkova L","year":"2018","unstructured":"Prokhorenkova L, Gusev G, Vorobev A, Dorogush AV, Gulin A. CatBoost: unbiased boosting with categorical features. Proceedings of the 32nd international conference on neural information processing systems. Montr\u00e9al, Canada: Curran Associates Inc; 2018:6639\u20136649."},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.2307\/2531595"},{"key":"e_1_3_2_24_2","first-page":"4768","volume-title":"Proceedings of the 31st international conference on neural information processing systems","author":"Lundberg SM","year":"2017","unstructured":"Lundberg SM, Lee S\u2010I. A unified approach to interpreting model predictions. Proceedings of the 31st international conference on neural information processing systems. Long Beach, California, USA: Curran Associates Inc; 2017:4768\u20134777."},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkg034"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamacardio.2023.0857"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurjpc\/zwad202"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1373\/clinchem.2016.255174"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.2174\/1573403x12666160111125304"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1161\/ATVBAHA.108.173898"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1126\/scisignal.2003825"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-022-04590-8"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-018-0183-z"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.5951"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwx016"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1038\/nri2675"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2011.04.005"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.atherosclerosis.2022.05.015"},{"key":"e_1_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11926-012-0313-z"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1038\/nri3793"},{"key":"e_1_3_2_41_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1538-7836.2009.03416.x"},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.1152\/physrev.00024.2005"}],"container-title":["Journal of the American Heart Association"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ahajournals.org\/doi\/full\/10.1161\/JAHA.125.047248","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T09:46:18Z","timestamp":1789551978000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ahajournals.org\/doi\/10.1161\/JAHA.125.047248"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,16]]},"references-count":41,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2026,6,16]]}},"alternative-id":["10.1161\/JAHA.125.047248"],"URL":"https:\/\/doi.org\/10.1161\/jaha.125.047248","relation":{},"ISSN":["2047-9980"],"issn-type":[{"value":"2047-9980","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,16]]},"assertion":[{"value":"2025-10-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-28","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-06-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e047248"}}