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Vulliamy P, Armstrong PC. Platelets in Hemostasis, Thrombosis, and Inflammation After Major Trauma. Arterioscler Thromb Vasc Biol 2024; 44:545-557. [PMID: 38235557 DOI: 10.1161/atvbaha.123.318801] [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: 01/19/2024]
Abstract
Trauma currently accounts for 10% of the total global burden of disease and over 5 million deaths per year, making it a leading cause of morbidity and mortality worldwide. Although recent advances in early resuscitation have improved early survival from critical injury, the mortality rate in patients with major hemorrhage approaches 50% even in mature trauma systems. A major determinant of clinical outcomes from a major injury is a complex, dynamic hemostatic landscape. Critically injured patients frequently present to the emergency department with an acute traumatic coagulopathy that increases mortality from bleeding, yet, within 48 to 72 hours after injury will switch from a hypocoagulable to a hypercoagulable state with increased risk of venous thromboembolism and multiple organ dysfunction. This review will focus on the role of platelets in these processes. As effectors of hemostasis and thrombosis, they are central to each phase of recovery from injury, and our understanding of postinjury platelet biology has dramatically advanced over the past decade. This review describes our current knowledge of the changes in platelet behavior that occur following major trauma, the mechanisms by which these changes develop, and the implications for clinical outcomes. Importantly, supported by research in other disease settings, this review also reflects the emerging role of thromboinflammation in trauma including cross talk between platelets, innate immune cells, and coagulation. We also address the unresolved questions and significant knowledge gaps that remain, and finally highlight areas that with the further study will help deliver further improvements in trauma care.
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Affiliation(s)
- Paul Vulliamy
- Centre for Trauma Sciences (P.V.), Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, United Kingdom
| | - Paul C Armstrong
- Centre for Immunobiology (P.C.A.), Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, United Kingdom
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Zeng J, He J, Chen M, Li J. Association between mean platelet volume and obstructive sleep apnea-hypopnea syndrome: A systemic review and meta-analysis. PLoS One 2024; 19:e0297815. [PMID: 38363791 PMCID: PMC10871486 DOI: 10.1371/journal.pone.0297815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/12/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Despite polysomnography (PSG) being acknowledged being considered the gold standard for diagnosing obstructive sleep apnea-hypopnea syndrome (OSAHS), researchers have been seeking a biomarker that is less invasive, more practical in detection, and cost-effective for diagnosing and assessing the severity of the disease. To address this concern, the values of mean platelet volume (MPV) between patients with OSAHS and healthy controls were compared, and the relationship between MPV and multiple sleep monitoring parameters was analyzed in this study. METHODS A comprehensive search was conducted across medical databases, including PubMed, Web of Science, EMBASE, CNKI, and Wanfang, up until August 2, 2023, to identify published articles related to OSAHS. This study reviewed the literature regarding the values of MPV in individuals with OSAHS and control groups, the Pearson/Spearman correlation coefficients between MPV and sleep monitoring parameters, and the odds ratios (OR) of MPV concerning the occurrence of cardiovascular diseases (CVDs) in patients with OSAHS. Meta-analyses were performed using standardized mean difference (SMD), Fisher's z values correlation coefficients (ZCOR) and odds ratio (OR) as effect variables. A fixed-effect model was used if the heterogeneity was not significant (I2<50%); otherwise, a random-effect model was applied. We will also combine the treatment effect estimates of individual trials using fixed-effect and random-effects models. Statistical analysis was carried out by employing STATA 11.0 and R 4.1.3. RESULTS In total, 31 articles were selected for the final analysis. The study involved 3604 patients and 1165 control individuals. The MPV in the OSAHS group was considerably elevated in comparison to the healthy controls (SMD = 0.37, 95%CI = 0.21-0.53, P < 0.001), particularly among individuals with severe OSAHS (SMD = 0.57, 95%CI = 0.23-0.90, P = 0.001). Subgroup analysis based on ethnicity, mean body mass index (BMI), and study design type also revealed a considerably higher MPV in the OSAHS category in comparison to the healthy controls. Furthermore, MPV showed correlations with various sleep monitoring parameters. The elevation of MPV may be one of the risk factors for CVDs in individuals with OSAHS (adjusted OR = 1.72, 95%CI = 1.08-2.73, P = 0.022). CONCLUSION MPV is a relatively simple, cost-effective, and practical indicator of the severity of OSAHS, with its values being linked to the risk of CVDs in individuals with OSAHS.
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Affiliation(s)
- Jun Zeng
- Clinical Medical College of Chengdu Medical College, Chengdu, Sichuan, China
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
- Key Laboratory of Geriatric Respiratory Diseases of Sichuan Higher Education Institutes, Chengdu, Sichuan, China
| | - Jie He
- Clinical Medical College of Chengdu Medical College, Chengdu, Sichuan, China
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
- Key Laboratory of Geriatric Respiratory Diseases of Sichuan Higher Education Institutes, Chengdu, Sichuan, China
| | - MeiFeng Chen
- Clinical Medical College of Chengdu Medical College, Chengdu, Sichuan, China
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
- Key Laboratory of Geriatric Respiratory Diseases of Sichuan Higher Education Institutes, Chengdu, Sichuan, China
| | - Jia Li
- Clinical Medical College of Chengdu Medical College, Chengdu, Sichuan, China
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
- Key Laboratory of Geriatric Respiratory Diseases of Sichuan Higher Education Institutes, Chengdu, Sichuan, China
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Luo Q, Li X, Zhao Z, Zhao Q, Liu Z, Yang W. Nomogram for hospital-acquired venous thromboembolism among patients with cardiovascular diseases. Thromb J 2024; 22:15. [PMID: 38291419 PMCID: PMC10826242 DOI: 10.1186/s12959-024-00584-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 01/18/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Identifying venous thromboembolism (VTE) is challenging for patients with cardiovascular diseases due to similar clinical presentation. Most hospital-acquired VTE events are preventable, whereas the implementation of VTE prophylaxis in clinical practice is far from sufficient. There is a lack of hospital-acquired VTE prediction models tailored specifically designed for patients with cardiovascular diseases. We aimed to develop a nomogram predicting hospital-acquired VTE specifically for patients with cardiovascular diseases. MATERIAL AND METHODS Consecutive patients with cardiovascular diseases admitted to internal medicine of Fuwai hospital between September 2020 and August 2021 were included. Univariable and multivariable logistic regression were applied to identify risk factors of hospital-acquired VTE. A nomogram was constructed according to multivariable logistic regression, and internally validated by bootstrapping. RESULTS A total of 27,235 patients were included. During a median hospitalization of four days, 154 (0.57%) patients developed hospital-acquired VTE. Multivariable logistic regression identified that female sex, age, infection, pulmonary hypertension, obstructive sleep apnea, acute coronary syndrome, cardiomyopathy, heart failure, immobility, central venous catheter, intra-aortic balloon pump and anticoagulation were independently associated with hospital-acquired VTE. The nomogram was constructed with high accuracy in both the training set and validation (concordance index 0.865 in the training set, and 0.864 in validation), which was further confirmed in calibration. Compared to Padua model, the Fuwai model demonstrated significantly better discrimination ability (area under curve 0.865 vs. 0.786, net reclassification index 0.052, 95% confidence interval 0.012-0.091, P = 0.009; integrated discrimination index 0.020, 95% confidence interval 0.001-0.039, P = 0.051). CONCLUSION The incidence of hospital-acquired VTE in patients with cardiovascular diseases is relatively low. The nomogram exhibits high accuracy in predicting hospital-acquired VTE in patients with cardiovascular diseases.
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Affiliation(s)
- Qin Luo
- Center for Pulmonary Vascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.167 Beilishi Rd, Xicheng DistrictBeijing, 100037, China
| | - Xin Li
- Center for Pulmonary Vascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.167 Beilishi Rd, Xicheng DistrictBeijing, 100037, China
| | - Zhihui Zhao
- Center for Pulmonary Vascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.167 Beilishi Rd, Xicheng DistrictBeijing, 100037, China
| | - Qing Zhao
- Center for Pulmonary Vascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.167 Beilishi Rd, Xicheng DistrictBeijing, 100037, China
| | - Zhihong Liu
- Center for Pulmonary Vascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.167 Beilishi Rd, Xicheng DistrictBeijing, 100037, China.
| | - Weixian Yang
- Department of Cardiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Cheng S, Gao H, Li Y, Shi X, Li X, Yang T, Teng D, Meng T, Shi J. Analysis of Risk Factors of Postoperative Lower Extremity Deep Venous Thrombosis in Patients With Cervical Cancer. Clin Appl Thromb Hemost 2024; 30:10760296241240747. [PMID: 38528746 DOI: 10.1177/10760296241240747] [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: 03/27/2024] Open
Abstract
Deep venous thrombosis (DVT) has a significant negative impact on surgical and tumor patient's safety and quality of life. There was no specific report on the incidence and risk factors of postoperative lower extremity DVT in cervical cancer patients. Analysis of the risk factors of postoperative DVT in patients with cervical cancer is of great clinical significance for prevention and treatment. We retrospectively analyzed 309 cervical cancer patients treated by the Hubei Cervical Cancer Prevention Center and used a logistic regression model to test the risk variables of postoperative lower extremity deep venous thrombosis in cervical cancer patients. By univariate analyses, the results of the study showed that the incidence of postoperative DVT was significantly increased in cervical cancer patients complicated with old age, obesity, high preoperative plasma D-dimer level, increased preoperative triglyceride level, chronic diseases (hypertension, diabetes, and cardiovascular disease), open surgery, long operation time, intraoperative blood transfusion, advanced tumor stage, and preoperative chemotherapy/radiotherapy. Advanced age, obesity, elevated preoperative D-dimer level, high preoperative triglyceride level, and open surgery were independent risk factors for postoperative lower extremity DVT in patients with cervical cancer by multivariate regression analyses (all P < .05). In gynecologic patients with cervical cancer, there is a high incidence of postoperative lower extremity DVT. Clinicians should develop systematic and comprehensive prevention and treatment measures for the risk factors to lower this morbidity and improve patient prognosis.
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Affiliation(s)
- Shiyu Cheng
- Medical College, Wuhan University of Science and Technology School of Medicine, Wuhan, China
| | - Han Gao
- Department of Gynecology, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yanli Li
- Department of Gynecology, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiuting Shi
- Medical College, Wuhan University of Science and Technology School of Medicine, Wuhan, China
| | - Xin Li
- Medical College, Wuhan University of Science and Technology School of Medicine, Wuhan, China
| | - Tianzhuo Yang
- Medical College, Wuhan University of Science and Technology School of Medicine, Wuhan, China
| | - Dan Teng
- Medical College, Wuhan University of Science and Technology School of Medicine, Wuhan, China
| | - Tingzhu Meng
- Medical College, Wuhan University of Science and Technology School of Medicine, Wuhan, China
| | - Jie Shi
- Department of Gynecology, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Sun B, Cheng X, Zhang M, Shi Q, Zhao X, Wang X, Zhang Y. Dynamic observation of circRNA and mRNA profiles in a rat model of deep vein thrombosis. Exp Ther Med 2023; 26:467. [PMID: 37664678 PMCID: PMC10469585 DOI: 10.3892/etm.2023.12166] [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: 01/31/2023] [Accepted: 07/20/2023] [Indexed: 09/05/2023] Open
Abstract
The goal of the present study was to identify different transcriptome expression profiles involved in the pathogenesis of deep vein thrombosis (DVT), and to illustrate the diagnostic and therapeutic potential of circular RNAs (circRNAs) and mRNAs in DVT progression. A Sprague-Dawley rat model of DVT was successfully established through the stenosis method and samples were sequenced at four time points (1, 6 and 12 h, and 3 days after ligation) to observe the dynamic changes in circRNAs and mRNAs during DVT progression. RNA sequencing was used to analyze the circRNA and mRNA expression profiles, and associated functions and pathways, in the blood of DVT rats at the four time points. In addition, Short Time Series Expression Miner (STEM) analysis was performed to explore temporal gene expression. Differential expression of 1,680, 4,018, 3,724, and 3,036 circRNAs, and 400, 1,176, 373, and 573 mRNAs was observed in the 1, 6 and 12 h, and 3-day groups, respectively, compared with the sham group (fold change >2.0 or <-2.0, P<0.05). Functional enrichment analysis indicated that differentially expressed mRNAs were associated with the following terms: Immune response, cell activation, blood stasis facilitated organelle, extracellular membrane-bounded organelle, and blood microparticle, oxygen transporter activity. STEM analysis indicated that the expression of 366 circRNAs in circRNA profile 45 and 270 mRNAs in mRNA profile 45 was consistent with thrombus progression. Enrichment analysis was performed on mRNA profile 45. The main Gene Ontology annotations were chromosome segregation, mitotic sister chromatid segregation, cell cycle process, and ligand-dependent nuclear receptor transcription coactivator activity. Pathway enrichment analysis identified the platelet-associated pathway, immune-associated pathway, and inflammation-relation pathway. According to the enriched platelet-associated pathways, four mRNAs and ten candidate circRNAs were selected for reverse transcription-quantitative PCR verification. The expression of nine of the ten circRNAs and all four mRNAs was consistent with the sequencing results. In summary, differentially expressed circRNAs and mRNAs are dynamically involved in DVT development. Dysregulated transcriptome profiles and the corresponding functions and pathways may provide mechanistic insights into DVT diagnosis and treatment.
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Affiliation(s)
- Baolan Sun
- Department of Laboratory, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Xi Cheng
- Department of Gynecology and Obstetrics, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Mu Zhang
- Department of Ophthalmology, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Qin Shi
- Department of Gynecology and Obstetrics, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Xinxin Zhao
- Department of Gynecology and Obstetrics, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Xudong Wang
- Department of Laboratory, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Yuquan Zhang
- Department of Gynecology and Obstetrics, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
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Xu D, Hu X, Zhang H, Gao Q, Guo C, Liu S, Tang B, Zhang G, Zhang C, Tang M. Analysis of risk factors for deep vein thrombosis after spinal infection surgery and construction of a nomogram preoperative prediction model. Front Cell Infect Microbiol 2023; 13:1220456. [PMID: 37600944 PMCID: PMC10435901 DOI: 10.3389/fcimb.2023.1220456] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 07/20/2023] [Indexed: 08/22/2023] Open
Abstract
Objective To investigate the differences in postoperative deep venous thrombosis (DVT) between patients with spinal infection and those with non-infected spinal disease; to construct a clinical prediction model using patients' preoperative clinical information and routine laboratory indicators to predict the likelihood of DVT after surgery. Method According to the inclusion criteria, 314 cases of spinal infection (SINF) and 314 cases of non-infected spinal disease (NSINF) were collected from January 1, 2016 to December 31, 2021 at Xiangya Hospital, Central South University, and the differences between the two groups in terms of postoperative DVT were analyzed by chi-square test. The spinal infection cases were divided into a thrombotic group (DVT) and a non-thrombotic group (NDVT) according to whether they developed DVT after surgery. Pre-operative clinical information and routine laboratory indicators of patients in the DVT and NDVT groups were used to compare the differences between groups for each variable, and variables with predictive significance were screened out by least absolute shrinkage and operator selection (LASSO) regression analysis, and a predictive model and nomogram of postoperative DVT was established using multi-factor logistic regression, with a Hosmer- Lemeshow goodness-of-fit test was used to plot the calibration curve of the model, and the predictive effect of the model was evaluated by the area under the ROC curve (AUC). Result The incidence of postoperative DVT in patients with spinal infection was 28%, significantly higher than 16% in the NSINF group, and statistically different from the NSINF group (P < 0.000). Five predictor variables for postoperative DVT in patients with spinal infection were screened by LASSO regression, and plotted as a nomogram. Calibration curves showed that the model was a good fit. The AUC of the predicted model was 0.8457 in the training cohort and 0.7917 in the validation cohort. Conclusion In this study, a nomogram prediction model was developed for predicting postoperative DVT in patients with spinal infection. The nomogram included five preoperative predictor variables, which would effectively predict the likelihood of DVT after spinal infection and may have greater clinical value for the treatment and prevention of postoperative DVT.
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Affiliation(s)
- Dongcheng Xu
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaojiang Hu
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Hongqi Zhang
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Qile Gao
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Chaofeng Guo
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Shaohua Liu
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Bo Tang
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Guang Zhang
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Chengran Zhang
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Mingxing Tang
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- China for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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Wu D, Gu H, Tang Y, Peng L, Liu H, Jiang Y, Xu Z, Wei Q, Wang Y. Predictive factors on postoperative venous thromboembolism after minimally invasive colorectal cancer surgery: a retrospective observational study. BMC Surg 2023; 23:85. [PMID: 37041489 PMCID: PMC10091640 DOI: 10.1186/s12893-023-01992-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 04/06/2023] [Indexed: 04/13/2023] Open
Abstract
BACKGROUND Venous thromboembolism (VTE) is a serious and preventable postoperative complication. However, the predictive significance of perioperative biochemical parameters for VTE after minimally invasive colorectal cancer surgery remains unclear. METHODS A total of 149 patients undergoing minimally invasive colorectal cancer surgery were collected between October 2021 and October 2022. Biochemical parameters related to preoperative and postoperative day 1, day 3, and day 5 were collected, including D-Dimer, mean platelet volume (MPV), and maximum amplitude (MA) of thromboelastography (TEG). Receiver operating characteristic (ROC) curves were used to explore the predictive powers of meaningful biochemical parameters for postoperative VTE, and calibration curves were used to assess predictive accuracy. RESULTS The overall cumulative incidence of VTE was 8.1% (12/149). The preoperative and postoperative day 3 D-Dimer, postoperative day 3, and day 5 MPV, and postoperative day 1, day 3, and day 5 TEG-MA was significantly higher in the VTE group than in the non-VTE group (P < 0.05). The results of both the ROC curve and the calibration curve indicated that these meaningful D-Dimer, MPV, and TEG-MA had moderate discrimination and consistency for postoperative VTE. CONCLUSIONS D-Dimer, MPV, and TEG-MA may predict postoperative VTE in patients undergoing minimally invasive surgery for colorectal cancer at specific times in the perioperative period.
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Affiliation(s)
- Dabin Wu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Haitao Gu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Yunhao Tang
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Linglong Peng
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Hang Liu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Yahui Jiang
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Zhiquan Xu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Qi Wei
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Yaxu Wang
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
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Xu Y, Guo Y. Platelet indices and blood pressure: a multivariable mendelian randomization study. Thromb J 2023; 21:31. [PMID: 36941692 PMCID: PMC10026509 DOI: 10.1186/s12959-023-00475-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 03/10/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Platelet indices are blood-based parameters reflecting the activation of platelets. Previous studies have identified an association between platelet indices and blood pressure (BP). However, causal inferences are prone to bias by confounding effects and reverse causation. We performed a Mendelian randomization (MR) study to compare the causal roles between genetically determined platelet indices and BP levels. METHODS Single-nucleotide polymorphisms (SNPs) associated with platelet count (PLT), plateletcrit (PCT), mean platelet volume (MPV), platelet distribution width (PDW), and BP at the level of genome-wide significance (p < 5 × 10- 8) in the UK Biobank were used as instrumental variables. In bidirectional univariable MR analyses, inverse variance-weighted (IVW), MR‒Egger, and weighted median methods were used to obtain estimates for individual causal power. In addition, heterogeneity and sensitivity analyses were performed to examine the pleiotropy of effect estimates. Finally, multivariable MR analyses were undertaken to disentangle the comparative effects of four platelet indices on BP. RESULTS In the univariable MR analyses, increased levels of PLT and PCT were associated with higher BP, and PDW was associated with higher DBP alone. In the reverse direction, SBP had a minor influence on PLT and PCT. In multivariable MR analysis, PDW and PLT revealed an independent effect, whereas the association for PCT and MPV was insignificant after colinear correction. CONCLUSION These findings suggest that platelets and BP may affect each other. PDW and PLT are independent platelet indices influencing BP. Increased platelet activation and aggregation may be involved in the pathogenesis of hypertension, which may provide insights into evaluating thromboembolic events in people with high BP. The necessity of initiating antiplatelet therapy among hypertension groups needs further investigation.
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Affiliation(s)
- Yuhan Xu
- School of Medicine, Southeast University, Nanjing, Jiangsu Province, 210009, China
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Yijing Guo
- School of Medicine, Southeast University, Nanjing, Jiangsu Province, 210009, China.
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China.
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Humic Acids Inhibit Platelet Activation to Reduce Venous Thromboembolism in Mice. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:6606423. [PMID: 36588591 PMCID: PMC9797308 DOI: 10.1155/2022/6606423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 11/17/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022]
Abstract
Objective We aimed to investigate the effects of the natural product humic acids (HA) on platelet activation and development of venous thromboembolism (VTE) in mice and further explore the relevant mechanism. Methods Eight-week C57BL/6 mice were randomly assigned to three groups: sham operation group (n = 7), VTE group (n = 8), and VTE + HA group (n = 10). Thrombi were harvested to hematoxylin-eosin staining to evaluate the thrombolysis and recanalization of the thrombus. In addition, flow cytometry was performed to detect the expression levels of protein disulfide isomerase on endothelial-derived exosomes and glycoprotein IIb/IIIa on the surface of the activated platelets surface in plasma. Furthermore, the protein expression level of glycoprotein IIb/IIIa in thrombus was determined by immunohistochemistry and immunofluorescence. Results The length of thrombosis in the VTE + HA group was significantly shorter than that in the VTE group (P = 0.040). No significant differences were observed in thrombolysis and recanalization between the VTE + HA group and the VTE group (P > 0.05). The content of protein disulfide isomerase carried by endothelial-derived exosomes was significantly increased in the VTE group (P = 0.008) but significantly reduced by native humic acids (P = 0.012). Compared with the VTE group, the expression of glycoprotein IIb/IIIa on activated platelet surface in the VTE + HA group was significantly decreased (P = 0.002). The concentration of plasmatic P-selectin in the VTE group was significantly higher than that in the VTE + HA group (P < 0.001). Conclusion We demonstrate that HA possess a pharmacological property that decreases venous thrombus formation in mice. The underlying mechanism is that HA could inhibit the expression of glycoprotein IIb/IIIa on the activated platelets surface by suppressing endothelial-derived exosomes carrying on protein disulfide isomerase, thereby blocking platelet activation.
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Subtype-specific plasma signatures of platelet-related protein releasate in acute pulmonary embolism. Thromb Res 2022; 220:75-87. [DOI: 10.1016/j.thromres.2022.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/21/2022] [Accepted: 10/07/2022] [Indexed: 11/17/2022]
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Thibord F, Klarin D, Brody JA, Chen MH, Levin MG, Chasman DI, Goode EL, Hveem K, Teder-Laving M, Martinez-Perez A, Aïssi D, Daian-Bacq D, Ito K, Natarajan P, Lutsey PL, Nadkarni GN, de Vries PS, Cuellar-Partida G, Wolford BN, Pattee JW, Kooperberg C, Braekkan SK, Li-Gao R, Saut N, Sept C, Germain M, Judy RL, Wiggins KL, Ko D, O’Donnell CJ, Taylor KD, Giulianini F, De Andrade M, Nøst TH, Boland A, Empana JP, Koyama S, Gilliland T, Do R, Huffman JE, Wang X, Zhou W, Soria JM, Souto JC, Pankratz N, Haessler J, Hindberg K, Rosendaal FR, Turman C, Olaso R, Kember RL, Bartz TM, Lynch JA, Heckbert SR, Armasu SM, Brumpton B, Smadja DM, Jouven X, Komuro I, Clapham KR, Loos RJ, Willer CJ, Sabater-Lleal M, Pankow JS, Reiner AP, Morelli VM, Ridker PM, van Hylckama Vlieg A, Deleuze JF, Kraft P, Rader DJ, Lee KM, Psaty BM, Skogholt AH, Emmerich J, Suchon P, Rich SS, Vy HMT, Tang W, Jackson RD, Hansen JB, Morange PE, Kabrhel C, Trégouët DA, Damrauer SM, Johnson AD, Smith NL. Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors. Circulation 2022; 146:1225-1242. [PMID: 36154123 PMCID: PMC10152894 DOI: 10.1161/circulationaha.122.059675] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 08/09/2022] [Indexed: 01/24/2023]
Abstract
BACKGROUND Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources. METHODS We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations. RESULTS In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. CONCLUSIONS Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.
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Affiliation(s)
- Florian Thibord
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, 73 Mt. Wayte Ave, Suite #2, Framingham, MA, 01702, USA
- The Framingham Heart Study, Boston University and NHLBI, 73 Mt. Wayte Ave, Suite #2, Framingham, MA, 01702, USA
| | - Derek Klarin
- Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, 94305, USA
- VA Palo Alto Healthcare System, Palo Alto, CA, 94550, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA
| | - Ming-Huei Chen
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, 73 Mt. Wayte Ave, Suite #2, Framingham, MA, 01702, USA
- The Framingham Heart Study, Boston University and NHLBI, 73 Mt. Wayte Ave, Suite #2, Framingham, MA, 01702, USA
| | - Michael G. Levin
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women’s Hospital, 900 Commonwealth Ave, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Ellen L. Goode
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Kristian Hveem
- HUNT Research Center, Department of Public Health and Nursing, Norwegian University of Science and Technology, Forskningsvegen 2, Levanger, 7600, Norway
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Håkon Jarls gate 11, Trondheim, 7030, Norway
| | - Maris Teder-Laving
- Institute of Genomics, University of Tartu, Riia 23b, Tartu, Tartu, 51010, Estonia
| | - Angel Martinez-Perez
- Genomics of Complex Disease Unit, Institut d’Investigació Biomèdica Sant Pau (IIB SANT PAU), St Quinti 77-79, Barcelona, 8041, Spain
| | - Dylan Aïssi
- Bordeaux Population Health Research Center, University of Bordeaux, 146 rue Léo Saignat, Bordeaux, 33076, France
- UMR1219, INSERM, 146 rue Léo Saignat, Bordeaux, 33076, France
| | - Delphine Daian-Bacq
- Centre National de Recherche en Génomique Humaine, CEA, Université Paris-Saclay, 2 Rue Gaston Crémieux, Evry, 91057, France
- Laboratory of Excellence on Medical Genomics, GenMed, France
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehirocho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Pradeep Natarajan
- Cardiovascular Research Center, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA, 02446, USA
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard & MIT, 75 Ames St, Cambridge, MA, 02142, USA
- Department of Medicine, Harvard Medical School, Shattuck St, Boston, MA, 02115, USA
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, 1300 South Second Street, Minneapolis, MN, 55454, USA
| | - Girish N. Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1 Gu stave L. Levy Pl, New York, NY, 10029, USA
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, 1200 Pressler St, Houston, TX, 77030, USA
| | | | - Brooke N. Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jack W. Pattee
- Division of Biostatistics, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
- Center for Innovative Design & Analysis and Department of Biostatistics & Informatics, Colorado School of Public Health, 13001 East 17th Place, Aurora, CO, 80045, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, 98109, USA
| | - Sigrid K. Braekkan
- Thrombosis Research Center (TREC), UiT - The Arctic University of Norway, Universitetsvegen 57, Tromsø, 9037, Norway
- Division of internal medicine, University Hospital of North Norway, Tromsø, 9038, Norway
| | - Ruifang Li-Gao
- Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, Leiden, 2300 RC, The Netherlands
| | - Noemie Saut
- Hematology Laboratory, La Timone University Hospital of Marseille, 264 Rue Saint-Pierre, Marseille, 13385, France
| | - Corriene Sept
- Department of Epidemiology, Harvard TH Chan Harvard School of Public Health, 655 Huntington Ave., Building II, Boston, MA, 02115, USA
| | - Marine Germain
- Bordeaux Population Health Research Center, University of Bordeaux, 146 rue Léo Saignat, Bordeaux, 33076, France
- UMR1219, INSERM, 146 rue Léo Saignat, Bordeaux, 33076, France
- Laboratory of Excellence on Medical Genomics, GenMed, France
| | - Renae L. Judy
- Surgery, University of Pennsylvania, 3401 Walnut Street, Philadelphia, PA, 19104, USA
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA
| | - Darae Ko
- The Framingham Heart Study, Boston University and NHLBI, 73 Mt. Wayte Ave, Suite #2, Framingham, MA, 01702, USA
- Section of Cardiovascular Medicine, Boston University School of Medicine, 85 East Newton Street, Boston, MA, 02118, USA
| | - Christopher J. O’Donnell
- Cardiology Section, Department of Medicine, VA Boston Healthcare System, Boston, MA, 02132, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation, 1124 W Carson St., Torrance, CA, 90502, USA
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women’s Hospital, 900 Commonwealth Ave, Boston, MA, 02215, USA
| | - Mariza De Andrade
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Therese H. Nøst
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Håkon Jarls gate 11, Trondheim, 7030, Norway
| | - Anne Boland
- Centre National de Recherche en Génomique Humaine, CEA, Université Paris-Saclay, 2 Rue Gaston Crémieux, Evry, 91057, France
- Laboratory of Excellence on Medical Genomics, GenMed, France
| | - Jean-Philippe Empana
- Integrative Epidemiology of cardiovascular diseases, Université Paris Cité, Paris Cardiovascular Research Center (PARCC), 56 rue Leblanc, Paris, 75015, France
- Department of Cardiology, APHP, Hopital Européen Georges Pompidou, 20 rue Leblanc, Paris, 75015, France
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehirocho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
- Cardiovascular Research Center, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA, 02446, USA
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard & MIT, 75 Ames St, Cambridge, MA, 02142, USA
| | - Thomas Gilliland
- Cardiovascular Research Center, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA, 02446, USA
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard & MIT, 75 Ames St, Cambridge, MA, 02142, USA
- Department of Medicine, Harvard Medical School, Shattuck St, Boston, MA, 02115, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1 Gu stave L. Levy Pl, New York, NY, 10029, USA
- BioMe Phenomics Center, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA
| | - Jennifer E. Huffman
- MAVERIC, VA Boston Heathcare System, 2 Avenue de Lafayette, Boston, MA, 02111, USA
| | - Xin Wang
- 23andMe, Inc., 223 N Mathilda Ave, Sunnyvale, CA, 94086, USA
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, 02114, USA
| | - Jose Manuel Soria
- Genomics of Complex Disease Unit, Institut d’Investigació Biomèdica Sant Pau (IIB SANT PAU), St Quinti 77-79, Barcelona, 8041, Spain
| | - Juan Carlos Souto
- Genomics of Complex Disease Unit, Institut d’Investigació Biomèdica Sant Pau (IIB SANT PAU), St Quinti 77-79, Barcelona, 8041, Spain
- Unit of Thrombosis and Hemostasis, Hospital de la Santa Creu i Sant Pau, St Quinti 89, Barcelona, 8041, Spain
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| | - Jeffery Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, 98109, USA
| | - Kristian Hindberg
- Thrombosis Research Center (TREC), UiT - The Arctic University of Norway, Universitetsvegen 57, Tromsø, 9037, Norway
| | - Frits R. Rosendaal
- Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, Leiden, 2300 RC, The Netherlands
| | - Constance Turman
- Department of Epidemiology, Harvard TH Chan Harvard School of Public Health, 655 Huntington Ave., Building II, Boston, MA, 02115, USA
| | - Robert Olaso
- Centre National de Recherche en Génomique Humaine, CEA, Université Paris-Saclay, 2 Rue Gaston Crémieux, Evry, 91057, France
- Laboratory of Excellence on Medical Genomics, GenMed, France
| | - Rachel L. Kember
- Psychiatry, University of Pennsylvania, 3401 Walnut Street, Philadelphia, PA, 19104, USA
| | - Traci M. Bartz
- Cardiovascular Health Research Unit, Departments of Biostatistics and Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA
| | - Julie A. Lynch
- VA Informatics & Computing Infrastructure, VA Salt Lake City Healthcare System, 500 Foothills Drive, Salt Lake City, UT, 84148, USA
- Epidemiology, University of Utah, 500 Foothills Drive, Salt Lake City, UT, 84148, USA
| | - Susan R. Heckbert
- Department of Epidemiology, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA
| | - Sebastian M. Armasu
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Ben Brumpton
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Håkon Jarls gate 11, Trondheim, 7030, Norway
| | - David M. Smadja
- Hematology Department and Biosurgical Research Lab (Carpentier Foundation), European Georges Pompidou Hospital, Assistance Publique Hôpitaux de Paris, 20 rue Leblanc, Paris, 75015, France
- Innovative Therapies in Haemostasis, INSERM, Université de Paris, 4 avenue de l’Observatoire, Paris, 75270, France
| | - Xavier Jouven
- Integrative Epidemiology of cardiovascular diseases, Université Paris Descartes, Sorbonne Paris Cité, 56 rue Leblanc, Paris, 75015, France
- Paris Cardiovascular Research Center, Inserm U970, Université Paris Descartes, Sorbonne Paris Cité, 20 rue Leblanc, Paris, 75015, France
| | - Issei Komuro
- Department of Cardiovascular Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Tokyo, 113-8655, Japan
| | - Katharine R. Clapham
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard & MIT, 75 Ames St, Cambridge, MA, 02142, USA
- Department of Medicine, Harvard Medical School, Shattuck St, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, 900 Commonwealth Ave, Boston, MA, 02215, USA
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA
| | - Cristen J. Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Maria Sabater-Lleal
- Genomics of Complex Disease Unit, Institut d’Investigació Biomèdica Sant Pau (IIB SANT PAU), St Quinti 77-79, Barcelona, 8041, Spain
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institutet, Center for Molecular Medicine, Stockholm, 17176, Sweden
| | - James S. Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, 1300 South Second Street, Minneapolis, MN, 55454, USA
| | - Alexander P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, 98109, USA
- Department of Epidemiology, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA
| | - Vania M. Morelli
- Thrombosis Research Center (TREC), UiT - The Arctic University of Norway, Universitetsvegen 57, Tromsø, 9037, Norway
- Division of internal medicine, University Hospital of North Norway, Tromsø, 9038, Norway
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women’s Hospital, 900 Commonwealth Ave, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Astrid van Hylckama Vlieg
- Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, Leiden, 2300 RC, The Netherlands
| | - Jean-François Deleuze
- Centre National de Recherche en Génomique Humaine, CEA, Université Paris-Saclay, 2 Rue Gaston Crémieux, Evry, 91057, France
- Laboratory of Excellence on Medical Genomics, GenMed, France
- Centre D’Etude du Polymorphisme Humain, Fondation Jean Dausset, 27 rue Juliette Dodu, Paris, 75010, France
| | - Peter Kraft
- Department of Epidemiology, Harvard TH Chan Harvard School of Public Health, 655 Huntington Ave., Building II, Boston, MA, 02115, USA
| | - Daniel J. Rader
- Departments of Medicine and Genetics and Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19104, USA
| | | | | | | | | | | | - Kyung Min Lee
- VA Informatics & Computing Infrastructure, VA Salt Lake City Healthcare System, 500 Foothills Drive, Salt Lake City, UT, 84148, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA
- Department of Epidemiology, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA
- Department of Health Systems and Population Heath, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA
| | - Anne Heidi Skogholt
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Håkon Jarls gate 11, Trondheim, 7030, Norway
| | - Joseph Emmerich
- Department of vascular medicine, Paris Saint-Joseph Hospital Group, University of Paris, 185 rue Raymond Losserand, Paris, 75674, France
- UMR1153, INSERM CRESS, 185 rue Raymond Losserand, Paris, 75674, France
| | - Pierre Suchon
- Hematology Laboratory, La Timone University Hospital of Marseille, 264 Rue Saint-Pierre, Marseille, 13385, France
- C2VN, INSERM, INRAE, Aix-Marseille University, 27, bd Jean Moulin, Marseille, 13385, France
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, 3242 West Complex, Charlottesville, VA, 22908-0717, USA
| | - Ha My T. Vy
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1 Gu stave L. Levy Pl, New York, NY, 10029, USA
| | - Weihong Tang
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, 1300 South Second Street, Minneapolis, MN, 55454, USA
| | - Rebecca D. Jackson
- College of Medicine, Ohio State University, 376 W. 10th Ave, Columbus, OH, 43210, USA
| | - John-Bjarne Hansen
- Thrombosis Research Center (TREC), UiT - The Arctic University of Norway, Universitetsvegen 57, Tromsø, 9037, Norway
- Division of internal medicine, University Hospital of North Norway, Tromsø, 9038, Norway
| | - Pierre-Emmanuel Morange
- Hematology Laboratory, La Timone University Hospital of Marseille, 264 Rue Saint-Pierre, Marseille, 13385, France
- C2VN, INSERM, INRAE, Aix-Marseille University, 27, bd Jean Moulin, Marseille, 13385, France
| | - Christopher Kabrhel
- Emergency Medicine, Massachusetts General Hospital, Zero Emerson Place, Suite 3B, Boston, MA, 02114, USA
- Emergency Medicine, Harvard Medical School, Zero Emerson Place, Suite 3B, Boston, MA, 02114, USA
| | - David-Alexandre Trégouët
- Bordeaux Population Health Research Center, University of Bordeaux, 146 rue Léo Saignat, Bordeaux, 33076, France
- UMR1219, INSERM, 146 rue Léo Saignat, Bordeaux, 33076, France
- Laboratory of Excellence on Medical Genomics, GenMed, France
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz Philadelphia VA Medical Center, 3900 Woodland Ave, Philadelphia, PA, 19104, USA
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Andrew D. Johnson
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, 73 Mt. Wayte Ave, Suite #2, Framingham, MA, 01702, USA
- The Framingham Heart Study, Boston University and NHLBI, 73 Mt. Wayte Ave, Suite #2, Framingham, MA, 01702, USA
| | - Nicholas L. Smith
- Department of Epidemiology, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, 98101, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, 98108, USA
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Chen J, Gao X, Shen S, Xu J, Sun Z, Lin R, Dai Z, Su L, Christiani DC, Chen F, Zhang R, Wei Y. Association of longitudinal platelet count trajectory with ICU mortality: A multi-cohort study. Front Immunol 2022; 13:936662. [PMID: 36059447 PMCID: PMC9437551 DOI: 10.3389/fimmu.2022.936662] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 07/15/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectivePlatelet (PLT) engages in immune and inflammatory responses, all of which are related to the prognosis of critically ill patients. Although thrombocytopenia at ICU admission contributes to in-hospital mortality, PLT is repeatedly measured during ICU hospitalization and the role of longitudinal PLT trajectory remains unclear. We aimed to identify dynamic PLT trajectory patterns and evaluate their relationships with mortality risk and thrombocytopenia.MethodsWe adopted a three-phase, multi-cohort study strategy. Firstly, longitudinal PLT trajectory patterns within the first four ICU days and their associations with 28-day survival were tested in the eICU Collaborative Research Database (eICU-CRD) and independently validated in the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Secondly, the relationships among PLT trajectory patterns, thrombocytopenia, and 28-day mortality were explored and validated. Finally, a Mortality GRade system for ICU dynamically monitoring patients (Mortality-GRID) was developed to quantify the mortality risk based on longitudinal PLT, which was further validated in the Molecular Epidemiology of Acute Respiratory Distress Syndrome (MEARDS) cohort.ResultsA total of 35,332 ICU patients were included from three cohorts. Trajectory analysis clustered patients into ascending (AS), stable (ST), or descending (DS) PLT patterns. DS patients with high baseline PLT decline quickly, resulting in poor prognosis. AS patients have low baseline PLT but recover quickly, favoring a better prognosis. ST patients maintain low PLT, having a moderate prognosis in between (HRSTvsAS = 1.26, 95% CI: 1.14–1.38, P = 6.15 × 10−6; HRDSvsAS = 1.58, 95% CI: 1.40–1.79, P = 1.41 × 10−13). The associations remained significant in patients without thrombocytopenia during the entire ICU hospitalization and were robust in sensitivity analyses and stratification analyses. Further, the trajectory pattern was a warning sign of thrombocytopenia, which mediated 27.2% of the effects of the PLT trajectory on 28-day mortality (HRindirect = 1.11, 95% CI: 1.06–1.17, P = 9.80 × 10−6). Mortality-GRID well predicts mortality risk, which is in high consistency with that directly estimated in MEARDS (r = 0.98, P = 1.30 × 10−23).ConclusionLongitudinal PLT trajectory is a complementary predictor to baseline PLT for patient survival, even in patients without risk of thrombocytopenia. Mortality-GRID could identify patients at high mortality risk.
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Affiliation(s)
- Jiajin Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xi Gao
- Department of Immunology, School of Clinical Medicine, Nanjing Medical University, Nanjing, China
| | - Sipeng Shen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jingyuan Xu
- Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zhe Sun
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ruilang Lin
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Zhixiang Dai
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Li Su
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - David C. Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Feng Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ruyang Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- *Correspondence: Ruyang Zhang, ; Yongyue Wei,
| | - Yongyue Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- *Correspondence: Ruyang Zhang, ; Yongyue Wei,
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Navarrete S, Solar C, Tapia R, Pereira J, Fuentes E, Palomo I. Pathophysiology of deep vein thrombosis. Clin Exp Med 2022:10.1007/s10238-022-00829-w. [PMID: 35471714 DOI: 10.1007/s10238-022-00829-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 03/31/2022] [Indexed: 12/29/2022]
Abstract
Deep venous thrombosis is a frequent, multifactorial disease and a leading cause of morbidity and mortality. Most of the time deep venous thrombosis is triggered by the interaction between acquired risk factors, such as hip fracture, pregnancy, and immobility, and hereditary risk factors such as thrombophilias. The mechanisms underlying deep venous thrombosis are not fully elucidated; however, in recent years, important advances have shed light on the role of venous flow, endothelium, platelets, leukocytes, and the interaction between inflammation and hemostasis. It has been described that the alteration of venous blood flow produces endothelial activation, favoring the adhesion of platelets and leukocytes, which, through tissue factor expression and neutrophil extracellular traps formation, contribute to the activation of coagulation, trapping more cells, such as red blood cells. Thus, the concerted interaction of these phenomena allows the formation and growth of the thrombus. In this work, the main mechanisms involved in the pathophysiology of deep vein thrombosis will be described.
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Affiliation(s)
- Simón Navarrete
- Thrombosis Research Center, Medical Technology School, Department of Clinical Biochemistry and Immunohaematology, Faculty of Health Sciences, Universidad de Talca, Av. Lircay s/n, 3460000, Talca, Chile
| | - Carla Solar
- Thrombosis Research Center, Medical Technology School, Department of Clinical Biochemistry and Immunohaematology, Faculty of Health Sciences, Universidad de Talca, Av. Lircay s/n, 3460000, Talca, Chile
| | | | - Jaime Pereira
- Department of Hematology-Oncology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Eduardo Fuentes
- Thrombosis Research Center, Medical Technology School, Department of Clinical Biochemistry and Immunohaematology, Faculty of Health Sciences, Universidad de Talca, Av. Lircay s/n, 3460000, Talca, Chile
| | - Iván Palomo
- Thrombosis Research Center, Medical Technology School, Department of Clinical Biochemistry and Immunohaematology, Faculty of Health Sciences, Universidad de Talca, Av. Lircay s/n, 3460000, Talca, Chile.
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14
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Panova-Noeva M, Wagner B, Nagler M, Koeck T, Ten Cate V, Eggebrecht L, Prochaska JH, Meyer I, Gerdes C, Spronk HM, Lackner KJ, Ten Cate H, Leineweber K, Heitmeier S, Konstantinides S, Wild PS. Variation of platelet function in clinical phenotypes of acute venous thromboembolism - Results from the GMP-VTE project. J Thromb Haemost 2022; 20:705-715. [PMID: 34784445 DOI: 10.1111/jth.15595] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 11/12/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND The role of platelets in the pathogenesis of venous thromboembolism (VTE) is receiving increasing attention; however, limited information is available on platelet function in the acute phase of the disease. OBJECTIVE To characterize platelet function according to VTE phenotypes. PATIENTS/METHODS In total, 154 subjects (isolated pulmonary embolism [iPE], n = 28; isolated deep vein thrombosis [iDVT], n = 35; DVT+PE, n = 91) were included. In this study platelet function analyzer (PFA)-200, light transmission aggregometry (LTA), thrombin generation (TG) in presence (PRP) and absence (PFP) of platelets and platelet flow cytometry were investigated. LASSO regression was used to select clinical and platelet biomarkers that distinguish between VTE phenotypes. RESULTS PFA-200 results did not differ between VTE phenotypes. LTA from DVT+PE subjects showed lowest maximum aggregation after epinephrine and adenosine diphosphate compared to iPE and iDVT. Lower % of PAC-1-positive platelets after in-vitro trigger were present in DVT+PE and iPE compared to iDVT. TG in PRP had lower peak height and velocity in DVT+PE and iPE against iDVT. The results of LASSO regression for the distinction between DVT+PE vs iDVT identified 18 variables (AUC =0.93) of which 72% were platelet biomarkers. For distinction between iPE and iDVT, 10 variables were selected (AUC = 0.96) of which 50% were platelet-related. Obesity was the only variable weakly discriminating between DVT+PE vs iPE (AUC = 0.66). CONCLUSION This explorative study suggests an important distinction between PE-related phenotypes and iDVT when considering clinical and platelet function data. Lower platelet-dependent TG along with reduced platelet reactivity suggest higher platelet degranulation in PE-dependent phenotypes compared to iDVT.
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Affiliation(s)
- Marina Panova-Noeva
- Center for Thrombosis and Hemostasis (CTH), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Preventive Cardiology and Preventive Medicine, Center for Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site RhineMain, Mainz, Germany
| | - Bianca Wagner
- Preventive Cardiology and Preventive Medicine, Center for Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Markus Nagler
- Preventive Cardiology and Preventive Medicine, Center for Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Thomas Koeck
- Preventive Cardiology and Preventive Medicine, Center for Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Vincent Ten Cate
- Preventive Cardiology and Preventive Medicine, Center for Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Lisa Eggebrecht
- Preventive Cardiology and Preventive Medicine, Center for Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Jürgen H Prochaska
- Center for Thrombosis and Hemostasis (CTH), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Preventive Cardiology and Preventive Medicine, Center for Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site RhineMain, Mainz, Germany
| | | | | | - Henri M Spronk
- Laboratory for Clinical Thrombosis and Hemostasis, Department of Internal Medicine, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, The Netherlands
| | - Karl J Lackner
- DZHK (German Center for Cardiovascular Research), Partner Site RhineMain, Mainz, Germany
- Institute for Clinical Chemistry and Laboratory Medicine, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Hugo Ten Cate
- Laboratory for Clinical Thrombosis and Hemostasis, Department of Internal Medicine, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, The Netherlands
| | | | | | - Stavros Konstantinides
- Center for Thrombosis and Hemostasis (CTH), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Philipp S Wild
- Center for Thrombosis and Hemostasis (CTH), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Preventive Cardiology and Preventive Medicine, Center for Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site RhineMain, Mainz, Germany
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15
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Sanchez ZAC, Vijayananda V, Virassammy DM, Rosenfeld L, Ramasubramanian AK. The interaction of vortical flows with red cells in venous valve mimics. BIOMICROFLUIDICS 2022; 16:024103. [PMID: 35282036 PMCID: PMC8896891 DOI: 10.1063/5.0078337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 02/08/2022] [Indexed: 06/14/2023]
Abstract
The motion of cells orthogonal to the direction of main flow is of importance in natural and engineered systems. The lateral movement of red blood cells (RBCs) distal to sudden expansion is considered to influence the formation and progression of thrombosis in venous valves, aortic aneurysms, and blood-circulating devices and is also a determining parameter for cell separation applications in flow-focusing microfluidic devices. Although it is known that the unique geometry of venous valves alters the blood flow patterns and cell distribution in venous valve sinuses, the interactions between fluid flow and RBCs have not been elucidated. Here, using a dilute cell suspension in an in vitro microfluidic model of a venous valve, we quantified the spatial distribution of RBCs by microscopy and image analysis, and using micro-particle image velocimetry and 3D computational fluid dynamics simulations, we analyzed the complex flow patterns. The results show that the local hematocrit in the valve pockets is spatially heterogeneous and is significantly different from the feed hematocrit. Above a threshold shear rate, the inertial separation of streamlines and lift forces contribute to an uneven distribution of RBCs in the vortices, the entrapment of RBCs in the vortices, and non-monotonic wall shear stresses in the valve pockets. Our experimental and computational characterization provides insights into the complex interactions between fluid flow, RBC distribution, and wall shear rates in venous valve mimics, which is of relevance to understanding the pathophysiology of thrombosis and improving cell separation efficiency.
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16
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Wang Z, Chen X, Wu J, Zhou Q, Liu H, Wu Y, Liu S, Liu Y. Low Mean Platelet Volume is Associated with Deep Vein Thrombosis in Older Patients with Hip Fracture. Clin Appl Thromb Hemost 2022; 28:10760296221078837. [PMID: 35157546 PMCID: PMC8848069 DOI: 10.1177/10760296221078837] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
This study aimed to explore the association between mean platelet volume (MPV) and preoperative deep vein thrombosis (DVT) in older patients with hip fracture. A total of 352 consecutive older patients with hip fracture were included from January 2014 to December 2020. MPV values were measured on admission, and color Doppler ultrasonography was performed for DVT screening before the planned surgery. The receiver operating characteristic (ROC) curve was used to establish the optimal cut-off value for the prediction of DVT. Univariate and multivariate logistic regression analysis were used to examine the association between factors and DVT. The overall prevalence of preoperative DVT was 15.1%, and patients with DVT had a lower value of MPV than non-DVT patients (11.6 ± 1.2 fL vs 12.3 ± 1.4 fL, P < .01). The cut-off point according to the ROC curve for MPV was 13.3 fL, and multivariate logistic regression analysis showed that MPV level < 13.3 fL was significantly associated with an increased risk of DVT (OR = 4.857, 95% CI: 1.091-21.617, P = .038), and with every 1.0 fL decrease in MPV, the risk increased by 27.7% (OR = 1.277, 95% CI: 1.001-1.629, P = .047). Our findings indicate that a low MPV level is associated with DVT in older patients with hip fracture. As MPV is a simple indicator that can be calculated from the blood routine test, it may be a potential biomarker of DVT with the combination of other tests, further studies are needed to confirm these results.
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Affiliation(s)
- Zhicong Wang
- Department of Orthopedics, Deyang People's Hospital, Deyang, Sichuan, China
| | - Xi Chen
- Department of Orthopedics, Deyang People's Hospital, Deyang, Sichuan, China
| | - Jijun Wu
- Department of Cardiology, Deyang People's Hospital, Deyang, Sichuan, China
| | - Qing Zhou
- Department of Orthopedics, Deyang People's Hospital, Deyang, Sichuan, China
| | - Hailong Liu
- Department of Orthopedics, Deyang People's Hospital, Deyang, Sichuan, China
| | - Yuxuan Wu
- Department of Orthopedics, Deyang People's Hospital, Deyang, Sichuan, China
| | - Shuping Liu
- Department of Orthopedics, Deyang People's Hospital, Deyang, Sichuan, China
| | - Yuehong Liu
- Department of Orthopedics, Deyang People's Hospital, Deyang, Sichuan, China
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17
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Thrombo-Inflammation: A Focus on NTPDase1/CD39. Cells 2021; 10:cells10092223. [PMID: 34571872 PMCID: PMC8469976 DOI: 10.3390/cells10092223] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/24/2021] [Accepted: 08/24/2021] [Indexed: 12/13/2022] Open
Abstract
There is increasing evidence for a link between inflammation and thrombosis. Following tissue injury, vascular endothelium becomes activated, losing its antithrombotic properties whereas inflammatory mediators build up a prothrombotic environment. Platelets are the first elements to be activated following endothelial damage; they participate in physiological haemostasis, but also in inflammatory and thrombotic events occurring in an injured tissue. While physiological haemostasis develops rapidly to prevent excessive blood loss in the endothelium activated by inflammation, hypoxia or by altered blood flow, thrombosis develops slowly. Activated platelets release the content of their granules, including ATP and ADP released from their dense granules. Ectonucleoside triphosphate diphosphohydrolase-1 (NTPDase1)/CD39 dephosphorylates ATP to ADP and to AMP, which in turn, is hydrolysed to adenosine by ecto-5'-nucleotidase (CD73). NTPDase1/CD39 has emerged has an important molecule in the vasculature and on platelet surfaces; it limits thrombotic events and contributes to maintain the antithrombotic properties of endothelium. The aim of the present review is to provide an overview of platelets as cellular elements interfacing haemostasis and inflammation, with a particular focus on the emerging role of NTPDase1/CD39 in controlling both processes.
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18
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Baidildinova G, Nagy M, Jurk K, Wild PS, Ten Cate H, van der Meijden PEJ. Soluble Platelet Release Factors as Biomarkers for Cardiovascular Disease. Front Cardiovasc Med 2021; 8:684920. [PMID: 34235190 PMCID: PMC8255615 DOI: 10.3389/fcvm.2021.684920] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 05/24/2021] [Indexed: 12/19/2022] Open
Abstract
Platelets are the main players in thrombotic diseases, where activated platelets not only mediate thrombus formation but also are involved in multiple interactions with vascular cells, inflammatory components, and the coagulation system. Although in vitro reactivity of platelets provides information on the function of circulating platelets, it is not a full reflection of the in vivo activation state, which may be relevant for thrombotic risk assessment in various disease conditions. Therefore, studying release markers of activated platelets in plasma is of interest. While this type of study has been done for decades, there are several new discoveries that highlight the need for a critical assessment of the available tests and indications for platelet release products. First, new insights have shown that platelets are not only prominent players in arterial vascular disease, but also in venous thromboembolism and atrial fibrillation. Second, knowledge of the platelet proteome has dramatically expanded over the past years, which contributed to an increasing array of tests for proteins released and shed from platelets upon activation. Identification of changes in the level of plasma biomarkers associated with upcoming thromboembolic events allows timely and individualized adjustment of the treatment strategy to prevent disease aggravation. Therefore, biomarkers of platelet activation may become a valuable instrument for acute event prognosis. In this narrative review based on a systematic search of the literature, we summarize the process of platelet activation and release products, discuss the clinical context in which platelet release products have been measured as well as the potential clinical relevance.
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Affiliation(s)
- Gaukhar Baidildinova
- Departments of Biochemistry and Internal Medicine, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, Netherlands.,Center for Thrombosis and Hemostasis, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Magdolna Nagy
- Departments of Biochemistry and Internal Medicine, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, Netherlands
| | - Kerstin Jurk
- Center for Thrombosis and Hemostasis, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.,DZHK (German Center for Cardiovascular Research), Partner Site RhineMain, Mainz, Germany
| | - Philipp S Wild
- Center for Thrombosis and Hemostasis, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.,DZHK (German Center for Cardiovascular Research), Partner Site RhineMain, Mainz, Germany.,Preventive Cardiology and Preventive Medicine, Center for Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Hugo Ten Cate
- Departments of Biochemistry and Internal Medicine, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, Netherlands.,Center for Thrombosis and Hemostasis, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.,Thrombosis Expertise Center, Heart and Vascular Center, Maastricht University Medical Center, Maastricht, Netherlands
| | - Paola E J van der Meijden
- Departments of Biochemistry and Internal Medicine, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, Netherlands.,Thrombosis Expertise Center, Heart and Vascular Center, Maastricht University Medical Center, Maastricht, Netherlands
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19
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Llorente-Chávez A, Martín-Nares E, Núñez-Álvarez C, Hernández-Molina G. Thrombosis and thrombocytopenia in antiphospholipid syndrome: their association with mean platelet volume and hematological ratios. Thromb Res 2021; 203:12-17. [PMID: 33895567 DOI: 10.1016/j.thromres.2021.04.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 03/11/2021] [Accepted: 04/12/2021] [Indexed: 02/06/2023]
Abstract
OBJECTIVE To assess the mean platelet volume (MPV), platelet-to-lymphocyte ratio (PLR), the neutrophil-to-lymphocyte ratio (NLR) and the MPV-to-lymphocyte ratio, and to test them according to the clinical/serological status, shift through time and other comorbidities in APS. METHODS We included 96 primary APS patients according to the Sydney classification criteria and/or patients with thrombocytopenia and/or autoimmune hemolytic anemia who also fulfilled the serological criteria. We tested aCL, anti-β2GP-I and aPS/PT antibodies and LA. We first registered the MPV and the aforementioned ratios within at least 6 months after an event of thrombosis or thrombocytopenia/AIHA (baseline determination), and during thrombosis/thrombocytopenia/AIHA onset when available (acute event). RESULTS A lower baseline MPV and a higher PLR characterized the thrombotic group (n = 74). The AUC for baseline PLR was 0.82 (p < 0.001): SE of 69%, SP 91%, PPV 96%, NPV 74%, LR+ 13.67 and LR- 0.19. During the acute event, both variables increased. The thrombocytopenic group (n = 66) had a higher baseline MPV and a lower PLR, and during an acute event the PLR decreased more deeply. The AUC for MPV was 0.64 (p = 0.02): SE 44%, SP 92%, PPV 86%, NPV 40%, LR+ 3.3 and LR- 0.85. These findings were not related with the aPL antibody profile status, titers or comorbidities. CONCLUSION Basal MPV and PLR might help to identify APS patients according to their thrombotic or thrombocytopenic phenotype. These variables change during the acute events and might be the reflex of physiopathological or compensatory mechanisms in APS.
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Affiliation(s)
- Amaya Llorente-Chávez
- Internal Medicine Service, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Vasco de Quiroga 15, Colonia Belisario Domínguez Sección XVI, CP 14080 Ciudad de México, Mexico
| | - Eduardo Martín-Nares
- Department of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Vasco de Quiroga 15, Colonia Belisario Domínguez Sección XVI, CP 14080 Ciudad de México, Mexico
| | - Carlos Núñez-Álvarez
- Department of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Vasco de Quiroga 15, Colonia Belisario Domínguez Sección XVI, CP 14080 Ciudad de México, Mexico
| | - Gabriela Hernández-Molina
- Department of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Vasco de Quiroga 15, Colonia Belisario Domínguez Sección XVI, CP 14080 Ciudad de México, Mexico.
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