Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization
PurposeTo investigate the predictive value of leukocyte subsets and C-reactive protein (CRP) in coronary artery disease (CAD).MethodsWe conducted a Mendelian randomization analysis (MR) on leukocyte subsets, C-reactive protein (CRP) and CAD, incorporating data from 68,624 patients who underwent coro...
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Frontiers Media S.A.
2024-09-01
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| Series: | Frontiers in Cardiovascular Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2024.1442275/full |
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| author | Yuan Liu Yuan Liu Xin Yuan Xin Yuan Yu-Chan He Yu-Chan He Zhong-Hai Bi Zhong-Hai Bi Si-Yao Li Si-Yao Li Ye Li Ye Li Yan-Li Liu Yan-Li Liu Liu Miao Liu Miao |
| author_facet | Yuan Liu Yuan Liu Xin Yuan Xin Yuan Yu-Chan He Yu-Chan He Zhong-Hai Bi Zhong-Hai Bi Si-Yao Li Si-Yao Li Ye Li Ye Li Yan-Li Liu Yan-Li Liu Liu Miao Liu Miao |
| author_sort | Yuan Liu |
| collection | DOAJ |
| description | PurposeTo investigate the predictive value of leukocyte subsets and C-reactive protein (CRP) in coronary artery disease (CAD).MethodsWe conducted a Mendelian randomization analysis (MR) on leukocyte subsets, C-reactive protein (CRP) and CAD, incorporating data from 68,624 patients who underwent coronary angiography from 2010 to 2022. After initial screening, clinical data from 46,664 patients were analyzed. Techniques employed included propensity score matching (PSM), logistic regression, lasso regression, and random forest algorithms (RF). Risk factors were assessed, and the sensitivity and specificity of the models were evaluated using receiver operating characteristic (ROC) curves. Additionally, survival analysis was conducted based on a 36-month follow-up period.ResultsThe inverse variance weight (IVW) analysis showed that basophil count (OR 0.92, 95% CI: 0.84–1.00, P = 0.048), CRP levels (OR 0.87, 95% CI: 0.73–1.00, P = 0.040), and lymphocyte count (OR 1.10, 95% CI: 1.04–1.16, P = 0.001) are significant risk factors for CAD. Using LASSO regression, logistic regression, and RF analysis, both CRP and lymphocyte counts were consistently identified as risk factors for CAD, prior to and following PSM. The ROC curve analysis indicated that the combination of lymphocyte and CRP levels after PSM achieves a higher diagnostic value (0.85). Survival analysis revealed that high lymphocyte counts and low CRP levels are associated with a decreased risk of Major Adverse Cardiovascular Events (MACE) (P < 0.001). Conversely, a higher CRP level combined with lymphocyte counts correlates with a poorer prognosis.ConclusionThere is a causal relationship between lymphocytes, CRP and CAD. The combined assessment of CRP and lymphocytes offers diagnostic value for CAD. Furthermore, high CRP levels coupled with low lymphocyte counts are associated with a poor prognosis. |
| format | Article |
| id | doaj-art-6d3a3b21c0cb4fc2a1215e0fa2803394 |
| institution | OA Journals |
| issn | 2297-055X |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Cardiovascular Medicine |
| spelling | doaj-art-6d3a3b21c0cb4fc2a1215e0fa28033942025-08-20T01:55:14ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2024-09-011110.3389/fcvm.2024.14422751442275Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomizationYuan Liu0Yuan Liu1Xin Yuan2Xin Yuan3Yu-Chan He4Yu-Chan He5Zhong-Hai Bi6Zhong-Hai Bi7Si-Yao Li8Si-Yao Li9Ye Li10Ye Li11Yan-Li Liu12Yan-Li Liu13Liu Miao14Liu Miao15Department of Cardiology, Liuzhou People’s Hospital, Affiliated of Guangxi Medical University, Liuzhou, Guangxi, ChinaThe Key Laboratory of Coronary Atherosclerotic Disease Prevention and Treatment of Liuzhou, Liuzhou, Guangxi, ChinaDepartment of Cardiology, Liuzhou People’s Hospital, Affiliated of Guangxi Medical University, Liuzhou, Guangxi, ChinaThe Key Laboratory of Coronary Atherosclerotic Disease Prevention and Treatment of Liuzhou, Liuzhou, Guangxi, ChinaDepartment of Cardiology, Liuzhou People’s Hospital, Affiliated of Guangxi Medical University, Liuzhou, Guangxi, ChinaThe Key Laboratory of Coronary Atherosclerotic Disease Prevention and Treatment of Liuzhou, Liuzhou, Guangxi, ChinaDepartment of Cardiology, Liuzhou People’s Hospital, Affiliated of Guangxi Medical University, Liuzhou, Guangxi, ChinaThe Key Laboratory of Coronary Atherosclerotic Disease Prevention and Treatment of Liuzhou, Liuzhou, Guangxi, ChinaDepartment of Cardiology, Liuzhou People’s Hospital, Affiliated of Guangxi Medical University, Liuzhou, Guangxi, ChinaThe Key Laboratory of Coronary Atherosclerotic Disease Prevention and Treatment of Liuzhou, Liuzhou, Guangxi, ChinaDepartment of Cardiology, Liuzhou People’s Hospital, Affiliated of Guangxi Medical University, Liuzhou, Guangxi, ChinaThe Key Laboratory of Coronary Atherosclerotic Disease Prevention and Treatment of Liuzhou, Liuzhou, Guangxi, ChinaDepartment of Cardiology, Liuzhou People’s Hospital, Affiliated of Guangxi Medical University, Liuzhou, Guangxi, ChinaThe Key Laboratory of Coronary Atherosclerotic Disease Prevention and Treatment of Liuzhou, Liuzhou, Guangxi, ChinaDepartment of Cardiology, Liuzhou People’s Hospital, Affiliated of Guangxi Medical University, Liuzhou, Guangxi, ChinaThe Key Laboratory of Coronary Atherosclerotic Disease Prevention and Treatment of Liuzhou, Liuzhou, Guangxi, ChinaPurposeTo investigate the predictive value of leukocyte subsets and C-reactive protein (CRP) in coronary artery disease (CAD).MethodsWe conducted a Mendelian randomization analysis (MR) on leukocyte subsets, C-reactive protein (CRP) and CAD, incorporating data from 68,624 patients who underwent coronary angiography from 2010 to 2022. After initial screening, clinical data from 46,664 patients were analyzed. Techniques employed included propensity score matching (PSM), logistic regression, lasso regression, and random forest algorithms (RF). Risk factors were assessed, and the sensitivity and specificity of the models were evaluated using receiver operating characteristic (ROC) curves. Additionally, survival analysis was conducted based on a 36-month follow-up period.ResultsThe inverse variance weight (IVW) analysis showed that basophil count (OR 0.92, 95% CI: 0.84–1.00, P = 0.048), CRP levels (OR 0.87, 95% CI: 0.73–1.00, P = 0.040), and lymphocyte count (OR 1.10, 95% CI: 1.04–1.16, P = 0.001) are significant risk factors for CAD. Using LASSO regression, logistic regression, and RF analysis, both CRP and lymphocyte counts were consistently identified as risk factors for CAD, prior to and following PSM. The ROC curve analysis indicated that the combination of lymphocyte and CRP levels after PSM achieves a higher diagnostic value (0.85). Survival analysis revealed that high lymphocyte counts and low CRP levels are associated with a decreased risk of Major Adverse Cardiovascular Events (MACE) (P < 0.001). Conversely, a higher CRP level combined with lymphocyte counts correlates with a poorer prognosis.ConclusionThere is a causal relationship between lymphocytes, CRP and CAD. The combined assessment of CRP and lymphocytes offers diagnostic value for CAD. Furthermore, high CRP levels coupled with low lymphocyte counts are associated with a poor prognosis.https://www.frontiersin.org/articles/10.3389/fcvm.2024.1442275/fullcoronary artery diseaselymphocytesCRPMendelian randomizationretrospective analysis |
| spellingShingle | Yuan Liu Yuan Liu Xin Yuan Xin Yuan Yu-Chan He Yu-Chan He Zhong-Hai Bi Zhong-Hai Bi Si-Yao Li Si-Yao Li Ye Li Ye Li Yan-Li Liu Yan-Li Liu Liu Miao Liu Miao Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization Frontiers in Cardiovascular Medicine coronary artery disease lymphocytes CRP Mendelian randomization retrospective analysis |
| title | Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization |
| title_full | Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization |
| title_fullStr | Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization |
| title_full_unstemmed | Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization |
| title_short | Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization |
| title_sort | exploring the predictive values of crp and lymphocytes in coronary artery disease based on a machine learning and mendelian randomization |
| topic | coronary artery disease lymphocytes CRP Mendelian randomization retrospective analysis |
| url | https://www.frontiersin.org/articles/10.3389/fcvm.2024.1442275/full |
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