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Dai Q, Zhao S, Li W, Liu K, Tao X, Liu C, Yao H, Mu F, Chen S, Li J, Wei P, Gao F, Xi M. Pharmacodynamics and Mechanism of Astragali Radix and Anemarrhenae Rhizoma in Treating Chronic Heart Failure by Inhibiting Complement Activation. Rejuvenation Res 2024; 27:61-74. [PMID: 38386515 DOI: 10.1089/rej.2023.0068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2024] Open
Abstract
Astragali radix (AR) and anemarrhenae rhizoma (AAR) are used clinically in Chinese medicine for the treatment of chronic heart failure (CHF), but the exact therapeutic mechanism is unclear. In this study, a total of 60 male C57BL/6 mice were divided into 5 groups, namely sham, model, AR, AAR, and AR-AAR. In the sham group, the chest was opened without ligation. In the other groups, the chest was opened and the transverse aorta was ligated to construct the transverse aortic constriction model. After 8 weeks of feeding, mice were given medicines by gavage for 4 weeks. Left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS) were detected by echocardiography. Heart weight index (HWI) and wheat germ agglutinin staining were used to evaluate cardiac hypertrophy. Hematoxylin-eosin staining was used to observe the pathological morphology of myocardial tissue. Masson staining was used to evaluate myocardial fibrosis. The content of serum brain natriuretic peptide (BNP) was detected by enzyme-linked immunosorbent assay kit. The content of serum immunoglobulin G (IgG) was detected by immunoturbidimetry. The mechanism of AR-AAR in the treatment of CHF was explored by proteomics. Western blot was used to detect the protein expressions of complement component 1s (C1s), complement component 9 (C9), and terminal complement complex 5b-9 (C5b-9). The results show that AR-AAR inhibits the expression of complement proteins C1s, C9, and C5b-9 by inhibiting the production of IgG antibodies from B cell activation, which further inhibits the complement activation, attenuates myocardial fibrosis, reduces HWI and cardiomyocyte cross-sectional area, improves cardiomyocyte injury, reduces serum BNP release, elevates LVEF and LVFS, improves cardiac function, and exerts myocardial protection.
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Affiliation(s)
- Qi Dai
- College of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang, China
- TANK Medicinal Biology Institute of Xi'an, Xi'an, China
| | - Shi Zhao
- TANK Medicinal Biology Institute of Xi'an, Xi'an, China
| | - Weihong Li
- TANK Medicinal Biology Institute of Xi'an, Xi'an, China
- College of Life Sciences, Northwestern University, Xi'an, China
| | - Kedi Liu
- TANK Medicinal Biology Institute of Xi'an, Xi'an, China
| | - Xingru Tao
- TANK Medicinal Biology Institute of Xi'an, Xi'an, China
- Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Chengzhao Liu
- College of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang, China
- TANK Medicinal Biology Institute of Xi'an, Xi'an, China
| | - Hong Yao
- College of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang, China
- TANK Medicinal Biology Institute of Xi'an, Xi'an, China
| | - Fei Mu
- Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Sha Chen
- YouYi Clinical Laboratories of Shaanxi, Xi'an, China
| | - Jing Li
- YouYi Clinical Laboratories of Shaanxi, Xi'an, China
| | - Peifeng Wei
- College of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang, China
- National Drug Clinical Trial Institute, The Second Affiliated Hospital, Shaanxi University of Chinese Medicine, Xi'an, China
| | - Feng Gao
- College of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang, China
| | - Miaomiao Xi
- TANK Medicinal Biology Institute of Xi'an, Xi'an, China
- National Drug Clinical Trial Institute, The Second Affiliated Hospital, Shaanxi University of Chinese Medicine, Xi'an, China
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Klimentova J, Rehulka P, Stulik J, Vozandychova V, Rehulkova H, Jurcova I, Lazarova M, Aiglova R, Dokoupil J, Hrecko J, Pudil R. Proteomic Profiling of Dilated Cardiomyopathy Plasma Samples ─ Searching for Biomarkers with Potential to Predict the Outcome of Therapy. J Proteome Res 2024; 23:971-984. [PMID: 38363107 PMCID: PMC10913098 DOI: 10.1021/acs.jproteome.3c00691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/30/2024] [Accepted: 02/05/2024] [Indexed: 02/17/2024]
Abstract
Determination of the prognosis and treatment outcomes of dilated cardiomyopathy is a serious problem due to the lack of valid specific protein markers. Using in-depth proteome discovery analysis, we compared 49 plasma samples from patients suffering from dilated cardiomyopathy with plasma samples from their healthy counterparts. In total, we identified 97 proteins exhibiting statistically significant dysregulation in diseased plasma samples. The functional enrichment analysis of differentially expressed proteins uncovered dysregulation in biological processes like inflammatory response, wound healing, complement cascade, blood coagulation, and lipid metabolism in dilated cardiomyopathy patients. The same proteome approach was employed in order to find protein markers whose expression differs between the patients well-responding to therapy and nonresponders. In this case, 45 plasma proteins revealed statistically significant different expression between these two groups. Of them, fructose-1,6-bisphosphate aldolase seems to be a promising biomarker candidate because it accumulates in plasma samples obtained from patients with insufficient treatment response and with worse or fatal outcome. Data are available via ProteomeXchange with the identifier PXD046288.
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Affiliation(s)
- Jana Klimentova
- Faculty
of Military Health Sciences, Department of Molecular Pathology and
Biology, University of Defence, Trebesska 1575, Hradec Kralove 50001, Czech Republic
- The
first Department of Internal Medicine − Cardioangiology, Medical Faculty of Charles University in Hradec Kralove
and University Hospital Hradec Kralove, Sokolska 581, Hradec Kralove 50005, Czech Republic
| | - Pavel Rehulka
- Faculty
of Military Health Sciences, Department of Molecular Pathology and
Biology, University of Defence, Trebesska 1575, Hradec Kralove 50001, Czech Republic
| | - Jiri Stulik
- Faculty
of Military Health Sciences, Department of Molecular Pathology and
Biology, University of Defence, Trebesska 1575, Hradec Kralove 50001, Czech Republic
- Charles
University, Faculty of Medicine in Hradec Kralove, Simkova 870, Hradec Kralove 50003, Czech Republic
| | - Vera Vozandychova
- Faculty
of Military Health Sciences, Department of Molecular Pathology and
Biology, University of Defence, Trebesska 1575, Hradec Kralove 50001, Czech Republic
- The
first Department of Internal Medicine − Cardioangiology, Medical Faculty of Charles University in Hradec Kralove
and University Hospital Hradec Kralove, Sokolska 581, Hradec Kralove 50005, Czech Republic
| | - Helena Rehulkova
- Faculty
of Military Health Sciences, Department of Molecular Pathology and
Biology, University of Defence, Trebesska 1575, Hradec Kralove 50001, Czech Republic
- The
first Department of Internal Medicine − Cardioangiology, Medical Faculty of Charles University in Hradec Kralove
and University Hospital Hradec Kralove, Sokolska 581, Hradec Kralove 50005, Czech Republic
| | - Ivana Jurcova
- Institute
for Clinical and Experimental Medicine (IKEM), Videnska 1958/9, Prague 14021, Czech Republic
| | - Marie Lazarova
- Department
of Internal Medicine I − Cardiology, Faculty of Medicine and
Dentistry, Palacky University and University
Hospital Olomouc, Zdravotniku 248/7, Olomouc 77900, Czech Republic
| | - Renata Aiglova
- Department
of Internal Medicine I − Cardiology, Faculty of Medicine and
Dentistry, Palacky University and University
Hospital Olomouc, Zdravotniku 248/7, Olomouc 77900, Czech Republic
| | - Jiri Dokoupil
- The
first Department of Internal Medicine − Cardioangiology, Medical Faculty of Charles University in Hradec Kralove
and University Hospital Hradec Kralove, Sokolska 581, Hradec Kralove 50005, Czech Republic
| | - Juraj Hrecko
- The
first Department of Internal Medicine − Cardioangiology, Medical Faculty of Charles University in Hradec Kralove
and University Hospital Hradec Kralove, Sokolska 581, Hradec Kralove 50005, Czech Republic
| | - Radek Pudil
- The
first Department of Internal Medicine − Cardioangiology, Medical Faculty of Charles University in Hradec Kralove
and University Hospital Hradec Kralove, Sokolska 581, Hradec Kralove 50005, Czech Republic
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Ren K, Feng J, Yang X, Ren B, Guo Y. Efficacy of metoprolol combined with torasemide in elderly patients with degenerative valvular heart disease and heart failure and its influence on NT-proBNP levels. Pak J Med Sci 2023; 39:945-949. [PMID: 37492298 PMCID: PMC10364288 DOI: 10.12669/pjms.39.4.7465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 12/23/2022] [Accepted: 05/20/2023] [Indexed: 07/27/2023] Open
Abstract
Objective To investigate the efficacy of metoprolol combined with torasemide in elderly patients with degenerative valvular heart disease (DVHD) and heart failure and its influence on N-terminal pro-B-type natriuretic peptide (NT-proBNP) concentrations. Methods The records of 129 DVHD patients ≥60 years old with heart failure diagnosed and treated in our hospital from January 2020 to February 2022 were retrospectively selected. According to the treatment records, 62 patients received metoprolol treatment (Control-group), and 67 patients received metoprolol combined with torasemide treatment (Observation-group). The changes in cardiac function, NT-proBNP and inflammatory factor concentrations and clinical efficacy were analyzed and compared between the two groups before and after treatment. Results After treatment, left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDD) and the mitral ratio of peak early to late diastolic filling velocity (E/A) were lower, with a greater decrease in the Observation-group compared to the Control-group (P<0.05). After treatment, NT-proBNP and interleukin-1beta (IL-1β), tumor necrosis factor-alpha (TNF-α), interleukin 6 (IL-6) concentrations were lower in both groups, with a greater decrease in the Observation-group compared to the Control-group (P<0.05). The total clinical efficacy of the Observation-group was significantly higher than the Control-group (P<0.05). There was no significant difference in the total incidence of adverse drug reactions between the two groups (P>0.05). Conclusion Metoprolol combined with torasemide has a significant therapeutic effect on DVHD patients with heart failure. This drug combination improved cardiac function, reduced NT-proBNP concentrations and has good safety.
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Affiliation(s)
- Kai Ren
- Kai Ren Department of Cardiology, Tianjin Chest Hospital, Tianjin 300222, P.R. China
| | - Jinping Feng
- Jinping Feng Department of Cardiology, Tianjin Chest Hospital, Tianjin 300222, P.R. China
| | - Xuwen Yang
- Xuwen Yang Department of Recovery Unit, Tianjin Chest Hospital, Tianjin 300222, P.R. China
| | - Bei Ren
- Bei Ren Department of Cardiology, Tianjin Chest Hospital, Tianjin 300222, P.R. China
| | - Yujun Guo
- Yujun Guo Department of Cardiology, Tianjin Chest Hospital, Tianjin 300222, P.R. China
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Zhang L, Lin Y, Wang K, Han L, Zhang X, Gao X, Li Z, Zhang H, Zhou J, Yu H, Fu X. Multiple-model machine learning identifies potential functional genes in dilated cardiomyopathy. Front Cardiovasc Med 2023; 9:1044443. [PMID: 36712235 PMCID: PMC9874116 DOI: 10.3389/fcvm.2022.1044443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 12/22/2022] [Indexed: 01/12/2023] Open
Abstract
Introduction Machine learning (ML) has gained intensive popularity in various fields, such as disease diagnosis in healthcare. However, it has limitation for single algorithm to explore the diagnosing value of dilated cardiomyopathy (DCM). We aim to develop a novel overall normalized sum weight of multiple-model MLs to assess the diagnosing value in DCM. Methods Gene expression data were selected from previously published databases (six sets of eligible microarrays, 386 samples) with eligible criteria. Two sets of microarrays were used as training; the others were studied in the testing sets (ratio 5:1). Totally, we identified 20 differently expressed genes (DEGs) between DCM and control individuals (7 upregulated and 13 down-regulated). Results We developed six classification ML methods to identify potential candidate genes based on their overall weights. Three genes, serine proteinase inhibitor A3 (SERPINA3), frizzled-related proteins (FRPs) 3 (FRZB), and ficolin 3 (FCN3) were finally identified as the receiver operating characteristic (ROC). Interestingly, we found all three genes correlated considerably with plasma cells. Importantly, not only in training sets but also testing sets, the areas under the curve (AUCs) for SERPINA3, FRZB, and FCN3 were greater than 0.88. The ROC of SERPINA3 was significantly high (0.940 in training and 0.918 in testing sets), indicating it is a potentially functional gene in DCM. Especially, the plasma levels in DCM patients of SERPINA3, FCN, and FRZB were significant compared with healthy control. Discussion SERPINA3, FRZB, and FCN3 might be potential diagnosis targets for DCM, Further verification work could be implemented.
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Affiliation(s)
- Lin Zhang
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yexiang Lin
- Biomedical Engineering, Imperial College London, London, United Kingdom
| | - Kaiyue Wang
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Lifeng Han
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xue Zhang
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xiumei Gao
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Zheng Li
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | | | - Jiashun Zhou
- Tianjin Jinghai District Hospital, Tianjin, China
| | - Heshui Yu
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China,*Correspondence: Heshui Yu,
| | - Xuebin Fu
- Department of Cardiovascular-Thoracic Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States,Department of Pediatrics, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, United States,Xuebin Fu,
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Wang J, Xie S, Cheng Y, Li X, Chen J, Zhu M. Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy. Front Cardiovasc Med 2022; 9:972274. [PMID: 36082132 PMCID: PMC9445158 DOI: 10.3389/fcvm.2022.972274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Accepted: 08/05/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveInflammation plays an important role in the pathophysiology of ischemic cardiomyopathy (ICM). We aimed to identify potential biomarkers of inflammation-related genes for ICM and build a model based on the potential biomarkers for the diagnosis of ICM.Materials and methodsThe microarray datasets and RNA-Sequencing datasets of human ICM were downloaded from the Gene Expression Omnibus database. We integrated 8 microarray datasets via the SVA package to screen the differentially expressed genes (DEGs) between ICM and non-failing control samples, then the differentially expressed inflammation-related genes (DEIRGs) were identified. The least absolute shrinkage and selection operator, support vector machine recursive feature elimination, and random forest were utilized to screen the potential diagnostic biomarkers from the DEIRGs. The potential biomarkers were validated in the RNA-Sequencing datasets and the functional experiment of the ICM rat, respectively. A nomogram was established based on the potential biomarkers and evaluated via the area under the receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), and Clinical impact curve (CIC).Results64 DEGs and 19 DEIRGs were identified, respectively. 5 potential biomarkers (SERPINA3, FCN3, PTN, CD163, and SCUBE2) were ultimately selected. The validation results showed that each of these five potential biomarkers showed good discriminant power for ICM, and their expression trends were consistent with the bioinformatics results. The results of AUC, calibration curve, DCA, and CIC showed that the nomogram demonstrated good performance, calibration, and clinical utility.ConclusionSERPINA3, FCN3, PTN, CD163, and SCUBE2 were identified as potential biomarkers associated with the inflammatory response to ICM. The proposed nomogram could potentially provide clinicians with a helpful tool to the diagnosis and treatment of ICM from an inflammatory perspective.
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Affiliation(s)
- Jianru Wang
- Department of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
- Central Laboratory, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
| | - Shiyang Xie
- Department of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
- Central Laboratory, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
| | - Yanling Cheng
- Department of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
| | - Xiaohui Li
- Department of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
| | - Jian Chen
- Department of Vascular Disease, Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Vascular Anomalies, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
- *Correspondence: Jian Chen,
| | - Mingjun Zhu
- Department of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
- Mingjun Zhu,
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