Tania Sharma , Akiko Maehara , Michael Maeng , Lars Kjøller-Hansen , Thomas Engstrøm , Ori Ben-Yehuda , Mitsuaki Matsumura , Ole Fröbert , Jonas Persson , Rune Wiseth , Alf Inge Larsen , Sasha Koul , Rebecca Rylance , Gary S. Mintz , Ziad A. Ali , Stefan K. James , Gregg W. Stone , David Erlinge
{"title":"循环蛋白生物标志物及其与易损斑块特征的关联——PROSPECT II亚研究","authors":"Tania Sharma , Akiko Maehara , Michael Maeng , Lars Kjøller-Hansen , Thomas Engstrøm , Ori Ben-Yehuda , Mitsuaki Matsumura , Ole Fröbert , Jonas Persson , Rune Wiseth , Alf Inge Larsen , Sasha Koul , Rebecca Rylance , Gary S. Mintz , Ziad A. Ali , Stefan K. James , Gregg W. Stone , David Erlinge","doi":"10.1016/j.ijcrp.2025.200440","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>In the PROSPECT-II study, near infrared spectroscopy (NIRS) and intravascular ultrasound (IVUS) was used to characterize atherosclerotic plaques in the coronary arteries. NIRS-derived lipid core burden index (LCBI) and IVUS-derived plaque burden (PB) were able to identify plaques strongly associated with adverse cardiovascular events.</div></div><div><h3>Aim</h3><div>Our aim was to identify biomarkers associated with LCBI or PB in the coronary arteries.</div></div><div><h3>Methods</h3><div>898 patients with recent myocardial infarction underwent percutaneous coronary intervention. Blood samples to analyze plasma levels of 179 proteins associated with cardiovascular disease were procured and a combined NIRS-IVUS catheter was used to analyze the coronary arteries. Adjusted linear regression models were calculated between the biomarkers and the outcomes of interest, adjusted for multiplicity testing. Kaplan-Meier survival curves of biomarkers divided by median were assessed with the log-rank test. Adjusted Cox proportional models were calculated for major adverse cardiovascular events.</div></div><div><h3>Results</h3><div>A total of 24 proteins were associated with PB and 28 proteins with LCBI. Eight of these biomarkers were associated with both increased pan-coronary LCBI and PB; IL-18R1, CSF-1, VEGFA, EN-RAGE, cathepsin D, PCSK9, transferrin receptor protein 1 and OPN. After adjusting for multiplicity, angiopoietin like 3 (ANGPTL3) retained its association with LCBI, and IL-18R1 and CSF-1 retained their association with PB.</div></div><div><h3>Conclusion</h3><div>We were able to identify distinct biomarker patterns associated with PB and LCBI. IL-18R1 and CSF-1 had a strong relationship with PB. ANGPTL3 was associated with lipid rich plaques but not with PB, supporting its role in lipid accumulation and development of vulnerable plaques.</div></div>","PeriodicalId":29726,"journal":{"name":"International Journal of Cardiology Cardiovascular Risk and Prevention","volume":"26 ","pages":"Article 200440"},"PeriodicalIF":2.1000,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Circulating protein biomarkers and their association with vulnerable plaque characteristics – a PROSPECT II substudy\",\"authors\":\"Tania Sharma , Akiko Maehara , Michael Maeng , Lars Kjøller-Hansen , Thomas Engstrøm , Ori Ben-Yehuda , Mitsuaki Matsumura , Ole Fröbert , Jonas Persson , Rune Wiseth , Alf Inge Larsen , Sasha Koul , Rebecca Rylance , Gary S. Mintz , Ziad A. Ali , Stefan K. James , Gregg W. Stone , David Erlinge\",\"doi\":\"10.1016/j.ijcrp.2025.200440\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>In the PROSPECT-II study, near infrared spectroscopy (NIRS) and intravascular ultrasound (IVUS) was used to characterize atherosclerotic plaques in the coronary arteries. NIRS-derived lipid core burden index (LCBI) and IVUS-derived plaque burden (PB) were able to identify plaques strongly associated with adverse cardiovascular events.</div></div><div><h3>Aim</h3><div>Our aim was to identify biomarkers associated with LCBI or PB in the coronary arteries.</div></div><div><h3>Methods</h3><div>898 patients with recent myocardial infarction underwent percutaneous coronary intervention. Blood samples to analyze plasma levels of 179 proteins associated with cardiovascular disease were procured and a combined NIRS-IVUS catheter was used to analyze the coronary arteries. Adjusted linear regression models were calculated between the biomarkers and the outcomes of interest, adjusted for multiplicity testing. Kaplan-Meier survival curves of biomarkers divided by median were assessed with the log-rank test. Adjusted Cox proportional models were calculated for major adverse cardiovascular events.</div></div><div><h3>Results</h3><div>A total of 24 proteins were associated with PB and 28 proteins with LCBI. Eight of these biomarkers were associated with both increased pan-coronary LCBI and PB; IL-18R1, CSF-1, VEGFA, EN-RAGE, cathepsin D, PCSK9, transferrin receptor protein 1 and OPN. After adjusting for multiplicity, angiopoietin like 3 (ANGPTL3) retained its association with LCBI, and IL-18R1 and CSF-1 retained their association with PB.</div></div><div><h3>Conclusion</h3><div>We were able to identify distinct biomarker patterns associated with PB and LCBI. IL-18R1 and CSF-1 had a strong relationship with PB. ANGPTL3 was associated with lipid rich plaques but not with PB, supporting its role in lipid accumulation and development of vulnerable plaques.</div></div>\",\"PeriodicalId\":29726,\"journal\":{\"name\":\"International Journal of Cardiology Cardiovascular Risk and Prevention\",\"volume\":\"26 \",\"pages\":\"Article 200440\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Cardiology Cardiovascular Risk and Prevention\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772487525000789\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PERIPHERAL VASCULAR DISEASE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Cardiology Cardiovascular Risk and Prevention","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772487525000789","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PERIPHERAL VASCULAR DISEASE","Score":null,"Total":0}
Circulating protein biomarkers and their association with vulnerable plaque characteristics – a PROSPECT II substudy
Background
In the PROSPECT-II study, near infrared spectroscopy (NIRS) and intravascular ultrasound (IVUS) was used to characterize atherosclerotic plaques in the coronary arteries. NIRS-derived lipid core burden index (LCBI) and IVUS-derived plaque burden (PB) were able to identify plaques strongly associated with adverse cardiovascular events.
Aim
Our aim was to identify biomarkers associated with LCBI or PB in the coronary arteries.
Methods
898 patients with recent myocardial infarction underwent percutaneous coronary intervention. Blood samples to analyze plasma levels of 179 proteins associated with cardiovascular disease were procured and a combined NIRS-IVUS catheter was used to analyze the coronary arteries. Adjusted linear regression models were calculated between the biomarkers and the outcomes of interest, adjusted for multiplicity testing. Kaplan-Meier survival curves of biomarkers divided by median were assessed with the log-rank test. Adjusted Cox proportional models were calculated for major adverse cardiovascular events.
Results
A total of 24 proteins were associated with PB and 28 proteins with LCBI. Eight of these biomarkers were associated with both increased pan-coronary LCBI and PB; IL-18R1, CSF-1, VEGFA, EN-RAGE, cathepsin D, PCSK9, transferrin receptor protein 1 and OPN. After adjusting for multiplicity, angiopoietin like 3 (ANGPTL3) retained its association with LCBI, and IL-18R1 and CSF-1 retained their association with PB.
Conclusion
We were able to identify distinct biomarker patterns associated with PB and LCBI. IL-18R1 and CSF-1 had a strong relationship with PB. ANGPTL3 was associated with lipid rich plaques but not with PB, supporting its role in lipid accumulation and development of vulnerable plaques.