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Huang X, Han Y, Kim M. Mendelian Randomization Study on hs-CRP and Dyslipidemia in Koreans: Identification of Novel SNP rs76400217. Int J Mol Sci 2025; 26:506. [PMID: 39859220 PMCID: PMC11764716 DOI: 10.3390/ijms26020506] [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: 11/20/2024] [Revised: 01/03/2025] [Accepted: 01/08/2025] [Indexed: 01/27/2025] Open
Abstract
High-sensitivity C-reactive protein (hs-CRP) is a marker of systemic inflammation and is associated with developing dyslipidemia. However, the causality between hs-CRP and dyslipidemia remains unresolved. This study aimed to investigate the relationship between hs-CRP concentrations and dyslipidemia and to explore the potential causal link using Mendelian randomization (MR) analysis. A nested case-control study was conducted with 1174 participants, and genotype data were analyzed using the Korean Chip. A genome-wide association study (GWAS) identified rs76400217 as a suitable instrumental variable (IV) due to its significant association with hs-CRP (p < 10-8). Logistic regression models, adjusted for confounders, were used to evaluate the association between hs-CRP and dyslipidemia. An MR analysis was performed using a two-stage least squares (2SLS) method, with rs76400217 as the IV to assess causality. Logistic regression showed a significant association between hs-CRP concentrations and dyslipidemia (OR 2.08, 95% CI: 1.81-2.39, p < 0.001). This association remained significant after adjusting for factors such as age, sex, alcohol consumption, and BMI. The MR analysis using rs76400217 as the IV confirmed the strong associations with hs-CRP concentrations (p < 0.001) in all models, but the causality between hs-CRP and dyslipidemia was not statistically significant. Thus, no evidence of a causal relationship between hs-CRP and the risk of dyslipidemia was found in the Korean population. The strong association observed between hs-CRP and dyslipidemia may be due to other contributing factors rather than a direct cause.
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Affiliation(s)
- Ximei Huang
- Department of Food and Nutrition, College of Life Science and Nano Technology, Hannam University, Daejeon 34054, Republic of Korea;
| | - Youngmin Han
- Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul 03722, Republic of Korea;
| | - Minjoo Kim
- Department of Food and Nutrition, College of Life Science and Nano Technology, Hannam University, Daejeon 34054, Republic of Korea;
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Bian Z, Xu L, Wang Y, Tsai MK, Chu DTW, Tu H, Wen CP, Wu X. Association of the systemic inflammation and anthropometric measurements with cancer risk: a prospective study in MJ cohort. Front Oncol 2024; 14:1400893. [PMID: 39314636 PMCID: PMC11417304 DOI: 10.3389/fonc.2024.1400893] [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: 03/19/2024] [Accepted: 08/14/2024] [Indexed: 09/25/2024] Open
Abstract
Objective To investigate the specific role of inflammation in the connection between obesity and the overall incidence of cancer. Methods A total of 356,554 participants in MJ cohort study were included. Systemic inflammation markers from blood samples and anthropometric measurements were determined using professional instruments. The Cox model was adopted to evaluate the association. Results Over a median follow-up of 8.2 years, 9,048 cancer cases were identified. For individual systemic inflammation biomarkers, the overall cancer risk significantly escalated as blood C-reactive protein (CRP) (hazard ratio (HR)=1.036 (1.017-1.054)) and globulin (GLO) (HR=1.128 (1.105-1.152)) levels increased, and as hemoglobin (HEMO) (HR=0.863 (0.842-0.884)), albumin (ALB) (HR=0.846 (0.829-0.863)) and platelets (PLA) (HR=0.842 (0.827-0.858)) levels decreased. For composite indicators, most of them existed a significant relationship to the overall cancer risk. Most indicators were correlated with the overall cancer and obesity-related cancer risk, but there was a reduction of association with non-obesity related cancer risk. Most of indicators mediated the association between anthropometric measurements and overall cancer risk. Conclusions Systemic inflammatory state was significantly associated with increased risks of cancer risk. Inflammation biomarkers were found to partly mediate the association between obesity and cancer risk.
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Affiliation(s)
- Zilong Bian
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Luopiao Xu
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuting Wang
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Min-Kuang Tsai
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | | | - Huakang Tu
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chi-Pang Wen
- National Institute for Data Science in Health and Medicine, Zhejiang University, Hangzhou, China
| | - Xifeng Wu
- Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- National Institute for Data Science in Health and Medicine, Zhejiang University, Hangzhou, China
- School of Medicine and Health Science, George Washington University, Washington DC, United States
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3
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Wang G, Zhu Z, Wang Y, Zhang Q, Sun Y, Pang G, Ge W, Ma Z, Ma H, Gong L, Ma H, Shao F, Zhu M. The association between METS-IR, an indirect index for insulin resistance, and lung cancer risk. Eur J Public Health 2024; 34:800-805. [PMID: 38300233 PMCID: PMC11293818 DOI: 10.1093/eurpub/ckad234] [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] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND Insulin resistance has been reported to increase the risk of breast, prostate and colorectal cancer. However, the role of insulin resistance and its interaction with genetic risk in the development of lung cancer remains controversial. Therefore, we aimed to explore the association between a novel metabolic score for insulin resistance (METS-IR) and lung cancer risk. METHODS A total of 395 304 participants without previous cancer at baseline were included. The Cox proportional hazards regression model was performed to investigate the association between METS-IR and lung cancer risk. In addition, a Mendelian randomization analysis was also performed to explore the causal relationship. The joint effects and additive interactions between METS-IR and polygenetic risk score (PRS) of lung cancer were also investigated. RESULTS During a median follow-up of 11.03 years (Inter-quartile range (IQR): 10.30-11.73), a total of 3161 incident lung cancer cases were diagnosed in 395 304 participants. There was a significant association between METS-IR and lung cancer risk, with an HR of 1.28 (95% CI: 1.17-1.41). Based on the Mendelian randomization analysis, however, no causal associations were observed. We observed a joint effect but no interaction between METS-IR and genetic risk. The lung cancer incidence was estimated to be 100.42 (95% CI: 91.45-109.38) per 100 000 person-year for participants with a high METS-IR and PRS, while only 42.76 (95% CI: 36.94-48.59) with low METS-IR and PRS. CONCLUSIONS High METS-IR was significantly associated with an increased risk of lung cancer. Keeping a low level of METS-IR might help reduce the long-term incident risk of lung cancer.
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Affiliation(s)
- Guoqing Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Zhaopeng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yi Wang
- Department of Respiratory Disease, Nanjing Chest Hospital, Nanjing Medical University, Nanjing, China
| | - Qiang Zhang
- Department of Thoracic Surgery, Nanjing Chest Hospital, Nanjing Medical University, Nanjing, China
| | - Yungang Sun
- Department of Thoracic Surgery, Nanjing Chest Hospital, Nanjing Medical University, Nanjing, China
| | - Guanlian Pang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Wenjing Ge
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Zhimin Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Huimin Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Linnan Gong
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Feng Shao
- Department of Thoracic Surgery, Nanjing Chest Hospital, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
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Shi J, Wen W, Long J, Xue H, Yang Y, Tao R, Pan W, Shu XO, Cai Q. Genetic correlation and causal associations between circulating C-reactive protein levels and lung cancer risk. Cancer Causes Control 2024; 35:897-906. [PMID: 38332239 DOI: 10.1007/s10552-024-01855-7] [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] [Received: 06/13/2023] [Accepted: 01/16/2024] [Indexed: 02/10/2024]
Abstract
PURPOSE We aimed to characterize genetic correlations and causal associations between circulating C-reactive protein (CRP) levels and the risk of lung cancer (LC). METHODS Leveraging summary statistics from genome-wide association studies of circulating CRP levels among 575,531 individuals of European ancestry, and LC risk among 29,266 cases and 56,450 controls, we investigated genetic associations of circulating CRP levels with the risk of overall lung cancer and its histological subtypes, by using linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) analyses. RESULTS Significant positive genetic correlations between circulating CRP levels and the risk of LC and its histological subtypes were identified from LDSC regression, with correlation coefficients ranging from 0.12 to 0.26, and all false discovery adjusted p < 0.05. Univariable MR demonstrated a nominal association between CRP levels and an increased risk of lung squamous cell carcinoma (SCC) (inverse variance-weighted OR = 1.15, 95% CI 1.01-1.30). However, this association disappeared when multivariable MR included cigarettes per day and/or body mass index. By using our recently developed constrained maximum likelihood-based MR method, we identified significant associations of CRP levels with the risk of overall LC (OR 1.06, 95% CI 1.03-1.09), SCC (OR 1.06, 95% CI 1.02-1.09), and small cell lung cancer (SCLC, OR 1.09, 95% CI 1.03-1.15). Moreover, most univariable and multivariable MR analyses also revealed consistent CRP-SCLC associations. CONCLUSION There may be a genetic and causal association between circulating CRP levels and the risk of SCLC, which is in line with previous population-based observational studies.
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Affiliation(s)
- Jiajun Shi
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37023, USA
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37023, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37023, USA
| | - Haoran Xue
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Yaohua Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37023, USA
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37023, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, 37023, USA
| | - Wei Pan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37023, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37023, USA.
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Liang D, Liu C, Yang M. The association between C-reactive protein levels and the risk of kidney stones: a population-based study. BMC Nephrol 2024; 25:39. [PMID: 38281018 PMCID: PMC10822160 DOI: 10.1186/s12882-024-03476-3] [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: 08/10/2023] [Accepted: 01/21/2024] [Indexed: 01/29/2024] Open
Abstract
OBJECTIVES The relationship between C-reactive protein (CRP) and the risk of developing kidney stones is unclear, and we aimed to assess the association between CRP and kidney stones in US adults. METHODS We used data from NHANES 2007-2010, and we excluded participants who were under 18 years of age and lacked data on CRP and kidney stones. Finally, we included a total of 11,033 participants and performed weighted multivariate regression analysis and subgroup analysis to assess the independent relationship between CRP and kidney stones. RESULTS The mean prevalence of kidney stones among the participants was 9.8%. Notably, as CRP levels increased, the prevalence of kidney stones exhibited a corresponding rise across quartiles (Kidney stones: Quartile 1: 7.59%; Quartile 2: 8.77%; Quartile 3: 9.64%; Quartile 4: 10.89%). CRP was positively associated with the risk of kidney stones (Model 1: OR = 1.09, 95% CI: 1.01-1.18, p = 0.03; Model 2: OR = 1.09, 95% CI: 1.00-1.18, p = 0.03, Model 3: OR = 1.14, 95%CI: 1.02-1.26, p = 0.04). Participants in the highest CRP quartile experienced a 69% increased risk of kidney stones compared to those in the lowest quartile (OR = 1.64, 95% CI: 1.04-2.59, p = 0.03). Notably, interaction tests revealed that gender, BMI, diabetes, hypertension, CKD and smoking or alcohol consumption status did not significantly influence the association between CRP and kidney stones. CONCLUSIONS Our findings reveal a significant association between higher CRP levels and an increased risk of kidney stones. In clinical practice, heightened awareness of CRP as a potential biomarker could aid in risk assessment and management strategies for kidney stone patients.
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Affiliation(s)
- Dan Liang
- Department of Endocrine, People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China
| | - Chang Liu
- School of Medicine, Nankai University, Tianjin, China
| | - Mei Yang
- Department of Endocrine, People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China.
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Hsu WL, Hsieh YT, Chen WM, Chien MH, Luo WJ, Chang JH, Devlin K, Su KY. High-fat diet induces C-reactive protein secretion, promoting lung adenocarcinoma via immune microenvironment modulation. Dis Model Mech 2023; 16:dmm050360. [PMID: 37929799 PMCID: PMC10651111 DOI: 10.1242/dmm.050360] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 10/12/2023] [Indexed: 11/07/2023] Open
Abstract
To understand the effects of a high-fat diet (HFD) on lung cancer progression and biomarkers, we here used an inducible mutant epidermal growth factor receptor (EGFR)-driven lung cancer transgenic mouse model fed a regular diet (RD) or HFD. The HFD lung cancer (LC-HFD) group exhibited significant tumor formation and deterioration, such as higher EGFR activity and proliferation marker expression, compared with the RD lung cancer (LC-RD) group. Transcriptomic analysis of the lung tissues revealed that the significantly changed genes in the LC-HFD group were highly enriched in immune-related signaling pathways, suggesting that an HFD alters the immune microenvironment to promote tumor growth. Cytokine and adipokine arrays combined with a comprehensive analysis using meta-database software indicated upregulation of C-reactive protein (CRP) in the LC-HFD group, which presented with increased lung cancer proliferation and metastasis; this was confirmed experimentally. Our results imply that an HFD can turn the tumor growth environment into an immune-related pro-tumorigenic microenvironment and demonstrate that CRP has a role in promoting lung cancer development in this microenvironment.
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Affiliation(s)
- Wei-Lun Hsu
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Yun-Ting Hsieh
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Wei-Ming Chen
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Min-Hui Chien
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Wei-Jia Luo
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Jung-Hsuan Chang
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Kevin Devlin
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Kang-Yi Su
- Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei 10055, Taiwan
- Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei 10617, Taiwan
- Department of Laboratory Medicine, National Taiwan University Hospital, Taipei 10055, Taiwan
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7
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Wang H, Yang R, Zhou K, Wang S, Cheng C, Liu D, Li W. Association between pretreatment C-reactive protein level and survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis. Int Immunopharmacol 2023; 124:110937. [PMID: 37757636 DOI: 10.1016/j.intimp.2023.110937] [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: 06/27/2023] [Revised: 08/24/2023] [Accepted: 09/09/2023] [Indexed: 09/29/2023]
Abstract
BACKGROUND Current evidence suggests that C-reactive protein (CRP) levels may affect cancer prognosis. However, the effect of CRP has not been validated in immunotherapy recipients with non-small cell lung cancer (NSCLC). Therefore, we performed a meta-analysis to explore the prognostic value of CRP level in patients with NSCLC treated with immune checkpoint inhibitors. METHODS PubMed, Web of Science, Embase, and Scopus databases were systematically retrieved for eligible publications, and hazard ratios (HRs) with corresponding 95% confidence intervals (95%CIs) were extracted and merged to evaluate the correlation between pretreatment CRP levels and overall survival (OS) and progression-free survival (PFS). Subgroup and sensitivity analyses were conducted to confirm these findings. RESULTS Thirty-five cohorts consisting of 4698 patients were included in the primary analysis. Pooled results demonstrated that a higher pretreatment CRP level is associated with worse OS and PFS (OS: HR = 1.13, 95 %CI:1.09-1.18; PFS: HR = 1.16, 95 %CI:1.10-1.22). These findings remained robust after further statistical analyses. CONCLUSION Pretreatment CRP level could be a promising biomarker for NSCLC immunotherapy. However, prospective studies are required to validate these findings.
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Affiliation(s)
- Haoyu Wang
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China; Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Ruiyuan Yang
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Ke Zhou
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Suyan Wang
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Cheng Cheng
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Dan Liu
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Weimin Li
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China; Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
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Mouliou DS. C-Reactive Protein: Pathophysiology, Diagnosis, False Test Results and a Novel Diagnostic Algorithm for Clinicians. Diseases 2023; 11:132. [PMID: 37873776 PMCID: PMC10594506 DOI: 10.3390/diseases11040132] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 09/15/2023] [Accepted: 09/19/2023] [Indexed: 10/25/2023] Open
Abstract
The current literature provides a body of evidence on C-Reactive Protein (CRP) and its potential role in inflammation. However, most pieces of evidence are sparse and controversial. This critical state-of-the-art monography provides all the crucial data on the potential biochemical properties of the protein, along with further evidence on its potential pathobiology, both for its pentameric and monomeric forms, including information for its ligands as well as the possible function of autoantibodies against the protein. Furthermore, the current evidence on its potential utility as a biomarker of various diseases is presented, of all cardiovascular, respiratory, hepatobiliary, gastrointestinal, pancreatic, renal, gynecological, andrological, dental, oral, otorhinolaryngological, ophthalmological, dermatological, musculoskeletal, neurological, mental, splenic, thyroid conditions, as well as infections, autoimmune-supposed conditions and neoplasms, including other possible factors that have been linked with elevated concentrations of that protein. Moreover, data on molecular diagnostics on CRP are discussed, and possible etiologies of false test results are highlighted. Additionally, this review evaluates all current pieces of evidence on CRP and systemic inflammation, and highlights future goals. Finally, a novel diagnostic algorithm to carefully assess the CRP level for a precise diagnosis of a medical condition is illustrated.
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Hogea P, Tudorache E, Fira-Mladinescu O, Marc M, Manolescu D, Bratosin F, Rosca O, Mavrea A, Oancea C. The Association of IFN-γ, TNF-α, and Interleukins in Bronchoalveolar Lavage Fluid with Lung Cancer: A Prospective Analysis. J Pers Med 2023; 13:968. [PMID: 37373957 DOI: 10.3390/jpm13060968] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/04/2023] [Accepted: 06/06/2023] [Indexed: 06/29/2023] Open
Abstract
Lung cancer is a leading cause of cancer-related mortality worldwide. Identifying novel diagnostic and prognostic biomarkers is essential for improving patient outcomes. This study aimed to investigate the predictive role of cytokines from bronchoalveolar lavage fluid (BALF) in lung cancer diagnosis and prognosis. A prospective study was conducted on 33 patients with suspected lung cancer, divided into inflammatory and non-inflammatory BALF groups. Inflammatory markers in BALF were assessed, and their association with lung cancer risk was analyzed using receiver operating characteristic (ROC) plot analysis, sensitivity and specificity percentages, and regression analysis. Statistically significant differences were observed between the inflammatory and non-inflammatory groups for several inflammatory markers, including IFN-gamma, IL-1b, IL-2, IL-6, IL-10, and IL-12p70. In the follow-up analysis, significant differences persisted for IFN-gamma, IL-1b, IL-2, IL-4, and IL-6. ROC plot analysis revealed that IL-12p70 had the highest area under the curve (AUC) value (0.702), followed by IL-2 (0.682), IL-6 (0.620), IL-4 (0.611), TNF-alpha (0.609), IL-10 (0.604), IL-1b (0.635), and IFN-gamma (0.521). IL-6 showed the highest sensitivity (73%), and IL-1b had the highest specificity (69%). Regression analysis demonstrated that IL-6 (cut-off = 25 pg/mL) and IL-12p70 (cut-off = 30 pg/mL) had the highest odds ratios for lung cancer risk, at 5.09 (95% CI: 2.38-9.24, p < 0.001) and 4.31 (95% CI: 1.85-8.16, p < 0.001), respectively. Cytokines from BALF, particularly IL-6 and IL-12p70, show potential as diagnostic and prognostic biomarkers for lung cancer. Further studies with larger cohorts are warranted to confirm these findings and elucidate the clinical implications of these markers in lung cancer management.
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Affiliation(s)
- Patricia Hogea
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania
- Doctoral School, Faculty of General Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania
| | - Emanuela Tudorache
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania
- First Pulmonology Clinic, Clinical Hospital of Infectious Diseases and Pulmonology, "Victor Babes", Gheorghe Adam Street 13, 300310 Timisoara, Romania
| | - Ovidiu Fira-Mladinescu
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania
- Second Pulmonology Clinic, Clinical Hospital of Infectious Diseases and Pulmonology, "Victor Babes", Gheorghe Adam Street 13, 300310 Timisoara, Romania
| | - Monica Marc
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania
- Second Pulmonology Clinic, Clinical Hospital of Infectious Diseases and Pulmonology, "Victor Babes", Gheorghe Adam Street 13, 300310 Timisoara, Romania
| | - Diana Manolescu
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania
- Discipline of Radiology, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square 2, 300041 Timisoara, Romania
| | - Felix Bratosin
- Discipline of Infectious Diseases, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square 2, 300041 Timisoara, Romania
| | - Ovidiu Rosca
- Discipline of Infectious Diseases, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square 2, 300041 Timisoara, Romania
| | - Adelina Mavrea
- Department of Internal Medicine I, Cardiology Clinic, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square 2, 300041 Timisoara, Romania
| | - Cristian Oancea
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania
- First Pulmonology Clinic, Clinical Hospital of Infectious Diseases and Pulmonology, "Victor Babes", Gheorghe Adam Street 13, 300310 Timisoara, Romania
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10
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Wong JY, Blechter B, Bassig BA, Dai Y, Vermeulen R, Hu W, Rahman ML, Duan H, Niu Y, Downward GS, Leng S, Ji BT, Fu W, Xu J, Meliefste K, Zhou B, Yang J, Ren D, Ye M, Jia X, Meng T, Bin P, Hosgood HD, Rothman N, Silverman DT, Zheng Y, Lan Q. Alterations to biomarkers related to long-term exposure to diesel exhaust at concentrations below occupational exposure limits in the European Union and the USA. Occup Environ Med 2023; 80:260-267. [PMID: 36972977 PMCID: PMC10337808 DOI: 10.1136/oemed-2022-108719] [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: 10/28/2022] [Accepted: 03/04/2023] [Indexed: 03/29/2023]
Abstract
BACKGROUND We previously found that occupational exposure to diesel engine exhaust (DEE) was associated with alterations to 19 biomarkers that potentially reflect the mechanisms of carcinogenesis. Whether DEE is associated with biological alterations at concentrations under existing or recommended occupational exposure limits (OELs) is unclear. METHODS In a cross-sectional study of 54 factory workers exposed long-term to DEE and 55 unexposed controls, we reanalysed the 19 previously identified biomarkers. Multivariable linear regression was used to compare biomarker levels between DEE-exposed versus unexposed subjects and to assess elemental carbon (EC) exposure-response relationships, adjusted for age and smoking status. We analysed each biomarker at EC concentrations below the US Mine Safety and Health Administration (MSHA) OEL (<106 µg/m3), below the European Union (EU) OEL (<50 µg/m3) and below the American Conference of Governmental Industrial Hygienists (ACGIH) recommendation (<20 µg/m3). RESULTS Below the MSHA OEL, 17 biomarkers were altered between DEE-exposed workers and unexposed controls. Below the EU OEL, DEE-exposed workers had elevated lymphocytes (p=9E-03, false discovery rate (FDR)=0.04), CD4+ count (p=0.02, FDR=0.05), CD8+ count (p=5E-03, FDR=0.03) and miR-92a-3p (p=0.02, FDR=0.05), and nasal turbinate gene expression (first principal component: p=1E-06, FDR=2E-05), as well as decreased C-reactive protein (p=0.02, FDR=0.05), macrophage inflammatory protein-1β (p=0.04, FDR=0.09), miR-423-3p (p=0.04, FDR=0.09) and miR-122-5p (p=2E-03, FDR=0.02). Even at EC concentrations under the ACGIH recommendation, we found some evidence of exposure-response relationships for miR-423-3p (ptrend=0.01, FDR=0.19) and gene expression (ptrend=0.02, FDR=0.19). CONCLUSIONS DEE exposure under existing or recommended OELs may be associated with biomarkers reflective of cancer-related processes, including inflammatory/immune response.
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Affiliation(s)
- Jason Yy Wong
- Epidemiology and Community Health Branch, National Heart Lung and Blood Institute, Bethesda, Maryland, USA
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Batel Blechter
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Bryan A Bassig
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Yufei Dai
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Roel Vermeulen
- The Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Wei Hu
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Mohammad L Rahman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Huawei Duan
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yong Niu
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - George S Downward
- The Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Shuguang Leng
- Division of Epidemiology, Biostatistics, and Preventive Medicine, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, New Mexico, USA
- Cancer Control and Population Sciences, University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico, USA
| | - Bu-Tian Ji
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Wei Fu
- Chaoyang Center for Disease Control and Prevention, Chaoyang, Lianing, China
| | - Jun Xu
- Division of Community Medicine and Public Health Practice, Hong Kong University, Hong Kong, Hong Kong, China
| | - Kees Meliefste
- The Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Baosen Zhou
- China Medical University, Liaoning, Shenyang, China
| | - Jufang Yang
- Chaoyang Center for Disease Control and Prevention, Chaoyang, Lianing, China
| | - Dianzhi Ren
- Chaoyang Center for Disease Control and Prevention, Chaoyang, Lianing, China
| | - Meng Ye
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaowei Jia
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tao Meng
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ping Bin
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - H Dean Hosgood
- Division of Epidemiology, Yeshiva University Albert Einstein College of Medicine, Bronx, New York, USA
| | - Nathaniel Rothman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Debra T Silverman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Yuxin Zheng
- School of Public Health, Qingdao University, Qingdao, China
| | - Qing Lan
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
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11
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Derived Neutrophil-Lymphocyte Ratio and C-Reactive Protein as Prognostic Factors for Early-Stage Non-Small Cell Lung Cancer Treated with Stereotactic Body Radiation Therapy. Diagnostics (Basel) 2023; 13:diagnostics13020313. [PMID: 36673123 PMCID: PMC9857614 DOI: 10.3390/diagnostics13020313] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 12/27/2022] [Accepted: 01/05/2023] [Indexed: 01/18/2023] Open
Abstract
Objectives: To explore the relationship between peripheral blood inflammation parameters and overall survival (OS) and progression-free survival (PFS) of early-stage non-small cell lung cancer patients who underwent stereotactic body radiotherapy (SBRT). Patients and methods: In this study, eligible patients treated with SBRT from 2013 to 2018, and both serum complete blood count and blood biochemical results were available prior to (within 60 days) radiotherapy were included. Results: A review of hospital registries identified 148 patients, and the 5-year OS and PFS of the entire cohort were 69.8% and 65.6%, respectively, with the median follow-up time was 52.8 months. Multivariable analysis showed that derived neutrophil-lymphocyte ratio (dNLR) ≥1.4 and C-reactive protein (CRP) ≥2.9 were statistically and independently associated with worse OS (HR = 4.62, 95% CI 1.89-11.27, p = 0.001; HR = 2.92, 95% CI 1.49-5.70, p = 0.002, respectively). The 5-year OS for patients with dNLR below and equal to or above the 1.4 were 85.3% and 62.9% (p = 0.002), respectively, and 76.7% for the low CRP group versus 58.5% for the high CRP group (p = 0.030). Higher serum level of post-treatment CRP also independent parameters for inferior PFS (HR = 4.83, 95% CI 1.28-18.25, p = 0.020). Conclusions: Our results demonstrate that dNLR and CRP are associated with the outcomes of early-stage NSCLC patients treated with SBRT, which may assist in selecting optimal nursing care and therapeutic scheme for every individual.
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12
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Yin J, Wang G, Wu Z, Lyu Z, Su K, Li F, Feng X, Guo LW, Chen Y, Xie S, Cui H, Li J, Ren J, Shi JF, Chen S, Wu S, Dai M, Li N, He J. Association Between Baseline C-Reactive Protein and the Risk of Lung Cancer: A Prospective Population-Based Cohort Study. Cancer Prev Res (Phila) 2022; 15:747-754. [PMID: 35896151 DOI: 10.1158/1940-6207.capr-21-0533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 03/21/2022] [Accepted: 07/22/2022] [Indexed: 01/31/2023]
Abstract
C-reactive protein (CRP), a systemic marker of diagnosing chronic inflammation, has been associated with the incidence of multiple types of cancer. However, little is known about the impact of CRP on lung cancer incidence in Chinese population. A total of 97,950 participants without cancer at baseline (2006-2007) of the Kailuan Cohort Study were followed up. The concentration of plasma high-sensitivity CRP (hsCRP) was tested for all participants at baseline interview. Multivariable Cox proportional hazards regression models were used to assess the association between levels of hsCRP and incident lung cancer. During 8.7-year follow-up, 890 incident lung cancer cases occurred and were divided into three groups according to the level of hsCRP. The risk of incident lung cancer was significantly increased with elevated levels of hsCRP [HRMedium/Low, 1.21; 95% confidence interval (CI), 1.03-1.42; HRHigh/Low, 1.42, 95% CI, 1.20-1.68; Ptrend < 0.001], compared with the low group after adjusting confounders. Moreover, after stratifying by BMI, the significantly positive associations between the hsCRP level and the risk of lung cancer were found among those with BMI < 24 (HRHigh/Low, 1.51; 95% CI, 1.18-1.94; Ptrend = 0.001) and BMI = 24-28 (HRHigh/Low, 1.47; 95% CI, 1.13-1.92; Ptrend = 0.003), but not among those with BMI ≥ 28 (HRHigh/Low, 1.01; 95% CI, 0.64-1.57; Ptrend = 0.991). There was an antagonistic interaction between hsCRP levels and BMI that contributed to development of lung cancer (Pinteraction = 0.049). In conclusion, these findings indicate a dose-dependent relationship between hsCRP and lung cancer risk among Chinese population, especially in nonobese participants, suggesting that CRP could serve as a potential biomarker for prediction of lung cancer risk and identification of high-risk population. PREVENTION RELEVANCE In this prospective population-based cohort study, we found an association between higher plasma hsCRP and an increased risk of developing lung cancer, with stronger associations observed among nonobese participants.
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Affiliation(s)
- Jian Yin
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Gang Wang
- Department of Oncology, Kailuan General Hospital, Tangshan, China
| | - Zheng Wu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Zhangyan Lyu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Kai Su
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fang Li
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaoshuang Feng
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Lan-Wei Guo
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
- Henan Office for Cancer Control and Research, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China
| | - Yuheng Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Shuanghua Xie
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Hong Cui
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Jiang Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Jiansong Ren
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Ju-Fang Shi
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Shuohua Chen
- Health Department of Kailuan (group), Tangshan, China
| | - Shouling Wu
- Health Department of Kailuan (group), Tangshan, China
| | - Min Dai
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Jie He
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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13
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Zhu M, Ma Z, Zhang X, Hang D, Yin R, Feng J, Xu L, Shen H. C-reactive protein and cancer risk: a pan-cancer study of prospective cohort and Mendelian randomization analysis. BMC Med 2022; 20:301. [PMID: 36117174 PMCID: PMC9484145 DOI: 10.1186/s12916-022-02506-x] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 08/01/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Although observational studies have reported associations between serum C-reactive protein (CRP) concentration and risks of lung, breast, and colorectal cancer, inconsistent or absent evidences were showed for other cancers. We conducted a pan-cancer analysis to comprehensively assess the role of CRP, including linearity and non-linearity associations. METHODS We analyzed 420,964 cancer-free participants from UK Biobank cohort. Multivariable-adjusted Cox proportional hazards model was conducted to evaluate the observed correlation of CRP with overall cancer and 21 site-specific cancer risks. Furthermore, we performed linear and non-linear Mendelian randomization analyses to explore the potential causal relation between them. RESULTS During a median follow-up period of 7.1 years (interquartile range: 6.3, 7.7), 34,979 incident cancer cases were observed. Observational analyses showed higher CRP concentration was associated with increased risk of overall cancer (hazard ratio (HR) = 1.02, 95% CI: 1.01, 1.02 per 1mg/L increase, P < 0.001). There was a non-linear association between CRP and overall cancer risk with inflection point at 3mg/L (false-discovery rate adjust (FDR-adjusted) Poverall < 0.001 and FDR-adjusted Pnon-linear < 0.001). For site-specific cancer, we observed positive linear associations for cancers of esophagus and stomach (FDR-adjusted Poverall < 0.050 and FDR-adjusted Pnon-linear > 0.050). In addition, we also observed three different patterns of non-linear associations, including "fast-to-low increase" (head and neck, colorectal, liver, lung, kidney cancer, and non-Hodgkin lymphoma), "increase-to-decrease" (breast cancer), and "decrease-to-platform" (chronic lymphocytic leukemia). Furthermore, the inflection points of non-linear association patterns were consistently at around 3mg/L. By contrast, there was no evidence for linear or non-linear associations between genetically predicted CRP and risks of overall cancer or site-specific cancers. CONCLUSIONS Our results indicated that CRP was a potential biomarker to assess risks of overall cancer and 12 site-specific cancers, while no association were observed for genetically-predicted CRP and cancer risks.
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Affiliation(s)
- Meng Zhu
- Department of Thoracic Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China
| | - Zhimin Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China.,Department of Epidemiology, School of Public Health, Southeast University, Nanjing, China
| | - Xu Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China
| | - Dong Hang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China
| | - Rong Yin
- Department of Thoracic Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, China
| | - Jifeng Feng
- Department of Medical Oncology, Jiangsu Cancer Hospital &Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, China.
| | - Lin Xu
- Department of Thoracic Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, China.
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China.
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14
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Shao F, Chen Y, Xu H, Chen X, Zhou J, Wu Y, Tang Y, Wang Z, Zhang R, Lange T, Ma H, Hu Z, Shen H, Christiani DC, Chen F, Zhao Y, You D. Metabolic Obesity Phenotypes and Risk of Lung Cancer: A Prospective Cohort Study of 450,482 UK Biobank Participants. Nutrients 2022; 14:3370. [PMID: 36014876 PMCID: PMC9414360 DOI: 10.3390/nu14163370] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 08/13/2022] [Accepted: 08/14/2022] [Indexed: 12/24/2022] Open
Abstract
(1) Background: The association between metabolic obesity phenotypes and incident lung cancer (LC) remains unclear. (2) Methods: Based on the combination of baseline BMI categories and metabolic health status, participants were categorized into eight groups: metabolically healthy underweight (MHUW), metabolically unhealthy underweight (MUUW), metabolically healthy normal (MHN), metabolically unhealthy normal (MUN), metabolically healthy overweight (MHOW), metabolically unhealthy overweight (MUOW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). The Cox proportional hazards model and Mendelian randomization (MR) were applied to assess the association between metabolic obesity phenotypes with LC risk. (3) Results: During a median follow-up of 9.1 years, 3654 incident LC patients were confirmed among 450,482 individuals. Compared with participants with MHN, those with MUUW had higher rates of incident LC (hazard ratio (HR) = 3.24, 95% confidence interval (CI) = 1.33-7.87, p = 0.009). MHO and MHOW individuals had a 24% and 18% lower risk of developing LC, respectively (MHO: HR = 0.76, 95% CI = 0.61-0.95, p = 0.02; MHO: HR = 0.82, 95% CI = 0.70-0.96, p = 0.02). No genetic association of metabolic obesity phenotypes and LC risk was observed in MR analysis. (4) Conclusions: In this prospective cohort study, individuals with MHOW and MHO phenotypes were at a lower risk and MUUW were at a higher risk of LC. However, MR failed to reveal any evidence that metabolic obesity phenotypes would be associated with a higher risk of LC.
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Affiliation(s)
- Fang Shao
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yina Chen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Hongyang Xu
- Department of Critical Care Medicine, Wuxi People’s Hospital Affiliated to Nanjing Medical University, Wuxi 214023, China
| | - Xin Chen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Jiawei Zhou
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yaqian Wu
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yingdan Tang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zhongtian Wang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Ruyang Zhang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
- The Center of Biomedical Big Data and the Laboratory of Biomedical Big Data, Nanjing Medical University, Nanjing 211166, China
| | - Theis Lange
- Section of Biostatistics, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, ØsterFarimagsgade 5, 1353 Copenhagen, Denmark
| | - Hongxia Ma
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Zhibin Hu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Hongbing Shen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - David C. Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02115, USA
| | - Feng Chen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
- The Center of Biomedical Big Data and the Laboratory of Biomedical Big Data, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Yang Zhao
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
- The Center of Biomedical Big Data and the Laboratory of Biomedical Big Data, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Dongfang You
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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15
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Jotic A, Milovanovic J, Savic-Vujovic K, Radin Z, Medic B, Folic M, Pavlovic B, Vujovic A, Dundjerovic D. Immune Cell and Biochemical Biomarkers in Advanced Laryngeal Cancer. Dose Response 2022; 20:15593258221115537. [PMID: 35898723 PMCID: PMC9309787 DOI: 10.1177/15593258221115537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Objective The aim of this study was to evaluate cell and biochemical biomarkers and
establish their prognostic value in patients with advanced laryngeal
cancer. Material and Methods A prospective study included 52 patients with advanced laryngeal carcinoma
surgically treated at the tertiary referral center. Tumor tissue was
immunohistochemically stained for T-cell markers (CD4 and CD8), and levels
of cytokines (IL-6 and IL-8) and C-reactive protein were analyzed from blood
samples. Results Overall 3-year survival (OS) of patients included in the study was 69.2% and
the disease specific survival (DSS) 72.5%. Higher expression of
CD4+ and CD8+ were significant prognostic factors
with positive impact on both OS and DSS in univariate analysis, but not in
multivariate analysis. Levels of IL-8 were a significant predictor of 3-year
OS and DSS survival in patients with advanced laryngeal cancer but not
levels of IL-6 and CRP values. Conclusion Though high expression of CD4 and CD8 were demonstrated in the tumor tissue,
but their prognostic role was not established. Higher values of IL-8 proved
to be significant negative predictor of DSS. This could further collaborate
the inclusion of combination of biomarkers in assessment of favorable
treatment choice in patients with advanced laryngeal carcinoma.
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Affiliation(s)
- Ana Jotic
- Clinic for Otorhinolaryngology and Maxillofacial Surgery, Clinical Center of Serbia, Belgrade, Serbia.,Medical Faculty, University of Belgrade, Belgrade, Serbia
| | - Jovica Milovanovic
- Clinic for Otorhinolaryngology and Maxillofacial Surgery, Clinical Center of Serbia, Belgrade, Serbia.,Medical Faculty, University of Belgrade, Belgrade, Serbia
| | - Katarina Savic-Vujovic
- Department of Pharmacology, Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Zorana Radin
- Ear, Nose and Throat Clinic, Clinical Hospital Center Zvezdara, Belgrade, Serbia
| | - Branislava Medic
- Department of Pharmacology, Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Miljan Folic
- Clinic for Otorhinolaryngology and Maxillofacial Surgery, Clinical Center of Serbia, Belgrade, Serbia.,Medical Faculty, University of Belgrade, Belgrade, Serbia
| | - Bojan Pavlovic
- Clinic for Otorhinolaryngology and Maxillofacial Surgery, Clinical Center of Serbia, Belgrade, Serbia.,Medical Faculty, University of Belgrade, Belgrade, Serbia
| | - Aleksandar Vujovic
- ENT Hospital, Clinical Hospital Center ''Dr Dragisa Misovic-Dedinje'' Belgrade, Serbia
| | - Dusko Dundjerovic
- Institute of Pathology, Medical Faculty, University of Belgrade, Belgrade, Serbia
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Wu T, Zhang H, Tian X, Cao Y, Wei D, Wu X. Neutrophil-to-Lymphocyte Ratio Better Than High-Sensitivity C-Reactive Protein in Predicting Stroke-Associated Pneumonia in Afebrile Patients. Neuropsychiatr Dis Treat 2021; 17:3589-3595. [PMID: 34916795 PMCID: PMC8668255 DOI: 10.2147/ndt.s340189] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 11/30/2021] [Indexed: 12/12/2022] Open
Abstract
PURPOSE To evaluate the association between neutrophil-to-lymphocyte ratio (NLR) and stroke-associated pneumonia (SAP) in patients with acute ischemic stroke (AIS) without fever and to clarify whether NLR has an advantage over high-sensitivity C-reactive protein (hs-CRP) in predicting SAP. PATIENTS AND METHODS A total of 434 patients with AIS without fever were assessed in this study. Multivariable analysis was used to evaluate the relationship between NLR and SAP, and the receiver operating characteristic (ROC) curve was used to compare the predictive value of NLR and hs-CRP. RESULTS Among the total patients, 18 (4.1%) developed SAP. After adjusting for confounders, NLR (adjusted odds ratio [aOR] = 1.60; 95% confidence interval [CI], 1.30-1.96; p < 0.001) remained independently associated with an increased risk of SAP. In addition, the area under the curve (AUC) of NLR (0.862 [0.826-0.893]) was higher than that of hs-CRP (0.738 [0.694-0.779]). CONCLUSION We found that compared with hs-CRP, NLR was significantly associated with the occurrence of SAP in patients with AIS without fever and showed a more effective predictive value for SAP.
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Affiliation(s)
- Ti Wu
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, People's Republic of China
| | - Haipeng Zhang
- Department of Clinical Laboratory, The Second Hospital of Tianjin Medical University, Tianjin, People's Republic of China
| | - Xiaolin Tian
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, People's Republic of China
| | - Yang Cao
- Department of Clinical Laboratory, The Second Hospital of Tianjin Medical University, Tianjin, People's Republic of China
| | - Dianjun Wei
- Department of Clinical Laboratory, Hebei Yanda Hospital, Langfang, Hebei, People's Republic of China
| | - Xiangkun Wu
- Department of Clinical Laboratory, Hebei Yanda Hospital, Langfang, Hebei, People's Republic of China
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