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Dong Y, Zhang Y, Liu P, Zhu S, Peng X, Hu X, Zhang X, Chen Y. A metal-organic framework signaling probe-mediated immunosensor for the economical and rapid determination of enrofloxacin in milk. Food Chem 2024; 449:139050. [PMID: 38581779 DOI: 10.1016/j.foodchem.2024.139050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 03/02/2024] [Accepted: 03/14/2024] [Indexed: 04/08/2024]
Abstract
Ensuring the safety of animal-derived foods requires the reliable and swift identification of enrofloxacin residues to monitor the presence of antibiotics. In this regard, we synthesized, tuned, and investigated the optical properties of a bimetallic metal-organic framework (Ce/Zr-UiO 66). The investigation was facilitated by employing a polydopamine-coated pipette tip with high adsorption efficiency, serving as an immunoreactive carrier. Subsequently, an immunofunctionalized variant of Ce/Zr-UiO 66, referred to as Ce/Zr-UiO 66@ Bovine serum albumin-enrofloxacin, was developed as an optical probe for the rapid and sensitive identification of enrofloxacin across a variety of samples. The method can accurately detect enrofloxacin at concentrations as low as 0.12 ng/mL, with a determination time of under 15 min; furthermore, it demonstrates exceptional efficacy when applied to food, environmental, and clinical samples. The implementation of this methodology offers a valuable means for cost-effective, rapid, and on-site enrofloxacin determination.
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Affiliation(s)
- Yiming Dong
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yu Zhang
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Puyue Liu
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Shiyi Zhu
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Xuewen Peng
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Xiaobo Hu
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Xiya Zhang
- College of Food Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China
| | - Yiping Chen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China; Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, Liaoning, China.
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Dong Y, Zhao J, Wu L, Chen Y. Cu(II)-induced magnetic resonance tuning and enhanced magnetic relaxation switching immunosensor for sensitive detection of chlorpyrifos and Salmonella. Food Chem 2024; 446:138847. [PMID: 38422644 DOI: 10.1016/j.foodchem.2024.138847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 02/19/2024] [Accepted: 02/21/2024] [Indexed: 03/02/2024]
Abstract
Magnetic relaxation switching (MRS) biosensors have been recognized as useful analytical tools for a range of targets; however, traditional MRS biosensors are limited by the "prozone effect", resulting in a narrow linear range and low sensitivity. Herein, we proposed a paramagnetic Cu2+-induced magnetic resonance tuning (MRET) strategy, based on which Cu2+ ions and magnetic nanoparticles (MNPs) were adopted to construct a Cu-MNP-mediated MRS (Cu-M-MRS) immunosensor with Cu2+ ions acting as a quencher and MNPs as an enhancer. An Fe3O4@polydopamine-secondary antibody conjugate was prepared and used to correlate the amount of Cu2+ ions to the target concentration through an immunoassay. Based on the immunoreaction, the Cu-M-MRS immunosensor enabled the sensitive detection of chlorpyrifos (0.05 ng/mL, a 77-fold enhancement in sensitivity compared with the traditional MRS immunosensor) and Salmonella (50 CFU/mL). The proposed MRET strategy effectively improved the sensitivity and accuracy of the MRS immunosensor, offering a promising and versatile platform for food safety detection.
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Affiliation(s)
- Yongzhen Dong
- State Key Laboratory of Marine Food Processing and Safety Control, Dalian Polytechnic University, Dalian 116034, Liaoning, China; Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, Liaoning, China
| | - Junpeng Zhao
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Long Wu
- School of Food Science and Engineering, Key Laboratory of Tropical and Vegetables Quality and Safety for State Market Regulation, Hainan University, Haikou 570228, China
| | - Yiping Chen
- State Key Laboratory of Marine Food Processing and Safety Control, Dalian Polytechnic University, Dalian 116034, Liaoning, China; Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, Liaoning, China.
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3
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Song S, Wu Z, Lv J, Yu C, Sun D, Pei P, Pan L, Yang L, Chen Y, Du H, Chen L, Schmidt D, Avery D, Duan L, Chen J, Chen Z, Li L, Pang Y. Dietary factors and patterns in relation to risk of later-onset ulcerative colitis in Chinese: A prospective study of 0.5 million people. Aliment Pharmacol Ther 2024; 59:1425-1434. [PMID: 38654428 DOI: 10.1111/apt.17963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 02/27/2024] [Accepted: 03/10/2024] [Indexed: 04/26/2024]
Abstract
BACKGROUND There is limited evidence on the associations of dietary factors and patterns with risk of later-onset ulcerative colitis (UC) in Chinese adults. AIMS To investigate the associations of dietary factors and patterns with risk of later-onset UC in Chinese. METHODS The prospective China Kadoorie Biobank cohort study recruited 512,726 participants aged 30-79. Dietary habits were assessed using food frequency questionnaires. Dietary patterns were derived by factor analysis with a principal component method. Cox regression analysis was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS During a median follow-up of 12.1 years, 312 cases of newly diagnosed UC were documented (median age of diagnosis 60.1 years). Egg consumption was associated with higher risk of UC (HR for daily vs. never or rarely: 2.29 [95% CI: 1.26-4.16]), while spicy food consumption was inversely associated with risk of UC (HR: 0.63 [0.45-0.88]). The traditional northern dietary pattern, characterised by high intake of wheat and low intake of rice, was associated with higher risk of UC (HR for highest vs. lowest quartile of score: 2.79 [1.93-4.05]). The modern dietary pattern, characterised by high intake of animal-origin foods and fruits, was associated with higher risk of UC (HR: 2.48 [1.63-3.78]). Population attributable fraction was 13.04% (7.71%-19.11%) for daily/almost daily consumption of eggs and 9.87% (1.94%-18.22%) for never/rarely consumption of spicy food. CONCLUSIONS The findings highlight the importance of evaluating dietary factors and patterns in the primary prevention of later-onset UC in Chinese adults.
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Affiliation(s)
- Shuyao Song
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zhiyu Wu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Pei Pei
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Lang Pan
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Lingli Chen
- Tongxiang Center for Disease Control and Prevention, Tongxiang, China
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liping Duan
- Department of Gastroenterology, Peking University Third Hospital, Beijing, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
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4
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Yao P, Iona A, Pozarickij A, Said S, Wright N, Lin K, Millwood I, Fry H, Kartsonaki C, Mazidi M, Chen Y, Bragg F, Liu B, Yang L, Liu J, Avery D, Schmidt D, Sun D, Pei P, Lv J, Yu C, Hill M, Bennett D, Walters R, Li L, Clarke R, Du H, Chen Z. Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes. Diabetes Care 2024; 47:1012-1019. [PMID: 38623619 DOI: 10.2337/dc23-2145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 03/09/2024] [Indexed: 04/17/2024]
Abstract
OBJECTIVE Integrated analyses of plasma proteomics and genetic data in prospective studies can help assess the causal relevance of proteins, improve risk prediction, and discover novel protein drug targets for type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS We measured plasma levels of 2,923 proteins using Olink Explore among ∼2,000 randomly selected participants from China Kadoorie Biobank (CKB) without prior diabetes at baseline. Cox regression assessed associations of individual protein with incident T2D (n = 92 cases). Proteomic-based risk models were developed with discrimination, calibration, reclassification assessed using area under the curve (AUC), calibration plots, and net reclassification index (NRI), respectively. Two-sample Mendelian randomization (MR) analyses using cis-protein quantitative trait loci identified in a genome-wide association study of CKB and UK Biobank for specific proteins were conducted to assess their causal relevance for T2D, along with colocalization analyses to examine shared causal variants between proteins and T2D. RESULTS Overall, 33 proteins were significantly associated (false discovery rate <0.05) with risk of incident T2D, including IGFBP1, GHR, and amylase. The addition of these 33 proteins to a conventional risk prediction model improved AUC from 0.77 (0.73-0.82) to 0.88 (0.85-0.91) and NRI by 38%, with predicted risks well calibrated with observed risks. MR analyses provided support for the causal relevance for T2D of ENTR1, LPL, and PON3, with replication of ENTR1 and LPL in Europeans using different genetic instruments. Moreover, colocalization analyses showed strong evidence (pH4 > 0.6) of shared genetic variants of LPL and PON3 with T2D. CONCLUSIONS Proteomic analyses in Chinese adults identified novel associations of multiple proteins with T2D with strong genetic evidence supporting their causal relevance and potential as novel drug targets for prevention and treatment of T2D.
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Affiliation(s)
- Pang Yao
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Andri Iona
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Alfred Pozarickij
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Saredo Said
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Neil Wright
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Kuang Lin
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Iona Millwood
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Hannah Fry
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Christiana Kartsonaki
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Mohsen Mazidi
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Yiping Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Fiona Bragg
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Bowen Liu
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Ling Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Junxi Liu
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Pei Pei
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Michael Hill
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Derrick Bennett
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Robin Walters
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Robert Clarke
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Huaidong Du
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
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Chai L, Chen Y, Yan X, Alcouffe P, Ganachaud F, Fleury E, Bernard J. Poly(vinyl alcohol)s and Their Glycoderivatives as Efficient Shell-Builders of Nanocapsules by Nanoprecipitation. Biomacromolecules 2024. [PMID: 38754095 DOI: 10.1021/acs.biomac.4c00213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2024]
Abstract
Poly(vinyl alcohol)s (PVAs) are very popular dispersants for the construction of colloids and common shell-constituents of microcapsules but remain mostly unexplored as building blocks for the design of nanocapsules through nanoprecipitation or other processes. Herein, we first show that model commercial PVAs and oils can be concomitantly engaged in solvent-shifting procedures to give rise to oil-filled nanocapsules in one step. Next, we report the synthesis of precisely defined water-soluble glyco-PVAs by reversible addition-fragmentation chain transfer (RAFT) copolymerization of 6-O-vinyladipoyl-d-glucopyranose and vinyl chloroacetate and selective alcoholysis reactions. We finally demonstrate that these glycopolymers are excellent candidates for the straightforward conception of oil- and drug-filled, surface- and/or core-tagged, stealth, and degradable nanocapsules by nanoprecipitation.
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Affiliation(s)
- Luxiao Chai
- Université de Lyon, CNRS, Université Claude Bernard Lyon 1, INSA Lyon, Université Jean Monnet, UMR 5223, Ingénierie des Matériaux Polymères, Villeurbanne, Cedex, F-69621, France
| | - Yiping Chen
- Université de Lyon, CNRS, Université Claude Bernard Lyon 1, INSA Lyon, Université Jean Monnet, UMR 5223, Ingénierie des Matériaux Polymères, Villeurbanne, Cedex, F-69621, France
| | - Xibo Yan
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
| | - Pierre Alcouffe
- Université de Lyon, CNRS, Université Claude Bernard Lyon 1, INSA Lyon, Université Jean Monnet, UMR 5223, Ingénierie des Matériaux Polymères, Villeurbanne, Cedex, F-69621, France
| | - Francois Ganachaud
- Université de Lyon, CNRS, Université Claude Bernard Lyon 1, INSA Lyon, Université Jean Monnet, UMR 5223, Ingénierie des Matériaux Polymères, Villeurbanne, Cedex, F-69621, France
| | - Etienne Fleury
- Université de Lyon, CNRS, Université Claude Bernard Lyon 1, INSA Lyon, Université Jean Monnet, UMR 5223, Ingénierie des Matériaux Polymères, Villeurbanne, Cedex, F-69621, France
| | - Julien Bernard
- Université de Lyon, CNRS, Université Claude Bernard Lyon 1, INSA Lyon, Université Jean Monnet, UMR 5223, Ingénierie des Matériaux Polymères, Villeurbanne, Cedex, F-69621, France
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Liu P, Dong Y, Li X, Zhang Y, Liu Z, Lu Y, Peng X, Zhai R, Chen Y. Multilayered Fe 3O 4@(ZIF-8) 3 combined with a computer-vision-enhanced immunosensor for chloramphenicol enrichment and detection. J Hazard Mater 2024; 470:134150. [PMID: 38552394 DOI: 10.1016/j.jhazmat.2024.134150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 03/24/2024] [Accepted: 03/26/2024] [Indexed: 04/25/2024]
Abstract
The misuse and overuse of chloramphenicol poses severe threats to food safety and human health. In this work, we developed a magnetic solid-phase extraction (MSPE) pretreatment material coated with a multilayered metal-organic framework (MOF), Fe3O4 @ (ZIF-8)3, for the separation and enrichment of chloramphenicol from fish. Furthermore, we designed an artificial-intelligence-enhanced single microsphere immunosensor. The inherent ultra-high porosity of the MOF and the multilayer assembly strategy allowed for efficient chloramphenicol enrichment (4.51 mg/g within 20 min). Notably, Fe3O4 @ (ZIF-8)3 exhibits a 39.20% increase in adsorption capacity compared to Fe3O4 @ZIF-8. Leveraging the remarkable decoding abilities of artificial intelligence, we achieved the highly sensitive detection of chloramphenicol using a straightforward procedure without the need for specialized equipment, obtaining a notably low detection limit of 46.42 pM. Furthermore, the assay was successfully employed to detect chloramphenicol in fish samples with high accuracy. The developed immunosensor offers a robust point-of-care testing tool for safeguarding food safety and public health.
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Affiliation(s)
- Puyue Liu
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yiming Dong
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Xiaoxuan Li
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yu Zhang
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Zhi Liu
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yingying Lu
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Xuewen Peng
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Ruifang Zhai
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
| | - Yiping Chen
- Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, Liaoning, China; College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China; State Key Laboratory of Marine Food Processing and Safety Control, Dalian Polytechnic University, Dalian 116034, Liaoning, China.
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7
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Lu Y, Wen J, Wang C, Wang M, Jiang F, Miao L, Xu M, Li Y, Chen X, Chen Y. Mesophilic Argonaute-Based Single Polystyrene Sphere Aptamer Fluorescence Platform for the Multiplexed and Ultrasensitive Detection of Non-Nucleic Acid Targets. Small 2024; 20:e2308424. [PMID: 38081800 DOI: 10.1002/smll.202308424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/13/2023] [Indexed: 01/04/2024]
Abstract
The rapid, simultaneous, and accurate identification of multiple non-nucleic acid targets in clinical or food samples at room temperature is essential for public health. Argonautes (Agos) are guided, programmable, target-activated, next-generation nucleic acid endonucleases that could realize one-pot and multiplexed detection using a single enzyme, which cannot be achieved with CRISPR/Cas. However, currently reported thermophilic Ago-based multi-detection sensors are mainly employed in the detection of nucleic acids. Herein, this work proposes a Mesophilic Argonaute Report-based single millimeter Polystyrene Sphere (MARPS) multiplex detection platform for the simultaneous analysis of non-nucleic acid targets. The aptamer is utilized as the recognition element, and a single millimeter-sized polystyrene sphere (PSmm) with a large concentration of guide DNA on the surface served as the microreactor. These are combined with precise Clostridium butyricum Ago (CbAgo) cleavage and exonuclease I (Exo I) signal amplification to achieve the efficient and sensitive recognition of non-nucleic acid targets, such as mycotoxins (<60 pg mL-1) and pathogenic bacteria (<102 cfu mL-1). The novel MARPS platform is the first to use mesophilic Agos for the multiplex detection of non-nucleic acid targets, overcoming the limitations of CRISPR/Cas in this regard and representing a major advancement in non-nucleic acid target detection using a gene-editing-based system.
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Affiliation(s)
- Yingying Lu
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Junping Wen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Chengming Wang
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Mengjiao Wang
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Feng Jiang
- Laboratory of Detection Technology of Focus Chemical Hazards in Animal-derived Food for State Market Regulation, Hubei Provincial Institute for Food Supervision and Test, Wuhan, 430075, China
| | - Lin Miao
- Department of Laboratory Medicine, General Hospital of Central Theater Command, Wuhan, 430070, China
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, 510515, China
| | - Minggao Xu
- Department of Laboratory Medicine, General Hospital of Central Theater Command, Wuhan, 430070, China
| | - Yingjun Li
- State Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xiaohua Chen
- Department of Laboratory Medicine, General Hospital of Central Theater Command, Wuhan, 430070, China
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, 510515, China
| | - Yiping Chen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
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Chen Y, Chan S, Bennett D, Chen X, Wu X, Ke Y, Lv J, Sun D, Pan L, Pei P, Yang L, Chen Y, Chen J, Chen Z, Li L, Du H, Yu C, Doherty A. Correction: Device-measured movement behaviours in over 20,000 China Kadoorie Biobank participants. Int J Behav Nutr Phys Act 2024; 21:50. [PMID: 38693505 PMCID: PMC11064345 DOI: 10.1186/s12966-024-01597-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024] Open
Affiliation(s)
- Yuanyuan Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Shing Chan
- Nufeld Department of Population Health, University of Oxford, Oxford, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Derrick Bennett
- Nufeld Department of Population Health, University of Oxford, Oxford, UK
- National Institute of Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Xiaofang Chen
- Department of Epidemiology and Statistics, Chengdu Medical College, Chengdu, Sichuan, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Yalei Ke
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
| | - Lang Pan
- Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
| | - Pei Pei
- Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nufeld Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nufeld Department of Population Health, University of Oxford, Oxford, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nufeld Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK.
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nufeld Department of Population Health, University of Oxford, Oxford, UK.
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
| | - Aiden Doherty
- Nufeld Department of Population Health, University of Oxford, Oxford, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
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9
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Zhu Z, Sun GK, He QR, Li ZY, Ma Y, Chen YP. [Diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2024; 42:276-281. [PMID: 38677991 DOI: 10.3760/cma.j.cn121094-20230309-00071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/29/2024]
Abstract
Objective: To explore the diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers by comparing the differences of whole blood cell parameters between occupational radiation injury population and occupational health examination population. Methods: In February 2023, 184 radiation workers who received occupational health examinations in our hospital and occurrenced chromosome aberration from July 2021 to July 2022 were retrospectively selected as the radiation injury group. And other 184 radiation workers encountered in the same period without chromosome aberration occurrence were selected as the control group. Collected whole blood cell parameters from two groups of research subjects, conducted comparative analysis, constructed a logistic regression model, and evaluated the diagnostic value of the logistic regression model for radiation injury on radiation workers by receiver operating characteristic curve (ROC) and area under curve (AUC) . In addition, with the same standard, 60 radiation workers with chromosome aberration and 60 radiation workers without chromosome aberration from August 2022 to January 2023 were included in the validation queue to validate the logistic regression model. Results: Neu_X, Neu_Y, Neu_Z, Lym_X, Lym_Y, Lym_Z, Mon_X, Mon_Y, Mon_Z, Micro, MCHC in the radiation injury group were significantly higher than those in the control group, and the difference was statistically significant (P<0.05) . And MCV and Macro in the radiation injury group were lower than those in the control group, and the difference was statistically significant (P<0.05) . Moreover, logistic regression analysis showed that Lym_X, Lym_Y, Lym_Z, MCHC, Micro were all independent risk factors for diagnosing radiation injury on radiation workers (OR=1.08、1.02、0.99、1.06、51.32, P<0.05) . ROC curve analysis showed that the AUC, sensitivity, specificity, and accuracy of the logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro in diagnosing radiation injury on radiation workers were 0.80, 85.9%, 65.8% and 75.9% respectively. The validation queue verified the logistic regression model and the AUC, sensitivity, specificity, and accuracy of the logistic regression model were 0.80, 81.7%, 71.7% and 76.7% respectively, the model fitted well. Conclusion: Radiation damage can cause changes in multiple whole blood cell parameters of radiation workers. The logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro showed good diagnosis ability and can be used for the screening of radiation injury on radiation workers.
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Affiliation(s)
- Z Zhu
- Laboratory Department of West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - G K Sun
- Laboratory Department of West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Q R He
- Laboratory Department of West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Z Y Li
- Technology Department of Chengdu Jiheng Zhixiang Technology Co. Ltd., Chengdu 610036, China
| | - Y Ma
- Laboratory Department of West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Y P Chen
- Laboratory Department of West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
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10
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Zhang Y, Ding Y, Yu C, Sun D, Pei P, Du H, Yang L, Chen Y, Schmidt D, Avery D, Chen J, Chen J, Chen Z, Li L, Lv J. Predictive value of 8-year blood pressure measures in intracerebral hemorrhage risk over 5 years. Eur J Prev Cardiol 2024:zwae147. [PMID: 38629743 DOI: 10.1093/eurjpc/zwae147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 03/21/2024] [Accepted: 04/16/2024] [Indexed: 05/07/2024]
Abstract
AIMS The relationships between long-term blood pressure (BP) measures and intracerebral hemorrhage (ICH), as well as their predictive ability on ICH, were unclear. We aimed to investigate the independent associations of multiple BP measures with subsequent 5-year ICH risk, as well as the incremental value of these measures over a single-point BP measurement in ICH risk prediction. METHODS We included 12,398 participants from the China Kadoorie Biobank (CKB) who completed three surveys every four to five years. The following long-term BP measures were calculated: mean, minimum, maximum, standard deviation, coefficient of variation, average real variability, and cumulative BP exposure (cumBP). Cox proportional hazard models were used to examine the associations between these measures and ICH. The potential incremental value of these measures in ICH risk prediction was assessed using Harrell's C statistics, continuous net reclassification improvement (cNRI), and relative integrated discrimination improvement (rIDI). RESULTS The hazard ratios (95% confidence intervals) of incident ICH associated with per SD increase in cumSBP and cumDBP were 1.62 (1.25, 2.10) and 1.59 (1.23, 2.07), respectively. When cumBP was added to the conventional 5-year ICH risk prediction model, the C-statistic change was 0.009 (-0.001, 0.019), the cNRI was 0.267 (0.070, 0.464), and the rIDI was 18.2% (5.8%, 30.7%). Further subgroup analyses revealed a consistent increase in cNRI and rIDI in men, rural residents, and participants without diabetes. Other long-term BP measures showed no statistically significant associations with incident ICH and generally did not improve model performance. CONCLUSION The nearly 10-year cumBP was positively associated with an increased 5-year risk of ICH and could significantly improve risk reclassification for the ICH risk prediction model that included single-point BP measurement.
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Affiliation(s)
- Yiqian Zhang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Yinqi Ding
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Jianwei Chen
- Liuyang Centers for Disease Control and Prevention, Liuyang, Changsha, Hunan, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University
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11
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Kong L, Hong F, Luan P, Chen Y, Feng Y, Zhu M. Novel competitive electrochemical impedance biosensor for the ultrasensitive detection of umami substances based on Pd/Cu-TCPP(Fe). Food Chem 2024; 438:137631. [PMID: 37983998 DOI: 10.1016/j.foodchem.2023.137631] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 09/12/2023] [Accepted: 09/28/2023] [Indexed: 11/22/2023]
Abstract
The development of biosensors capable of assessing umami intensity has elicited significant attention. However, the detection range of these biosensors is constrained by the sensing components and strategies used. In this study, we introduce a novel competitive, ultra-high-sensitivity impedance biosensor by utilizing composite nanomaterials and T1R1 as a composite signal probe. Pd/Cu-TCPP(Fe) had a substantial surface area, effectively enhancing the loading capacity of the T1R1 and thus augmenting the biosensor's recognition precision. Furthermore, the Pd/Cu-TCPP(Fe) elevated peroxidase-like activity catalyzed the formation of insoluble precipitates of 4-chloro-1-naphthol (4-CN), resulting in cascaded amplification of the impedance signal. The remarkable catalytic activity of the composite signal probe endowed the biosensor with exceptional analytical performance, featuring a limit of detection (LOD) of 0.86 pg/mL and a linear detection range spanning from 10 to 10,000 pg/mL. Successful application of the biosensor for umami detection in fish was demonstrated, signifying its substantial potential in food-flavor evaluation.
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Affiliation(s)
- Liqin Kong
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Feng Hong
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China; Key Laboratory of Environment Correlative Dietology, Huazhong Agricultural University, Ministry of Education, Wuhan, China
| | - Peng Luan
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yiping Chen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China; Key Laboratory of Environment Correlative Dietology, Huazhong Agricultural University, Ministry of Education, Wuhan, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan, Hubei, China; Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yaoze Feng
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China; Key Laboratory of Aquaculture Facilities Engineering, Ministry of Agriculture and Rural Affairs, Wuhan, Hubei, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan, Hubei, China; Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
| | - Ming Zhu
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China; Key Laboratory of Aquaculture Facilities Engineering, Ministry of Agriculture and Rural Affairs, Wuhan, Hubei, China
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12
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Kartsonaki C, Yao P, Butt J, Jeske R, de Martel C, Plummer M, Sun D, Clark S, Walters RG, Chen Y, Lv J, Yu C, Hill M, Peto R, Li L, Waterboer T, Chen Z, Millwood IY, Yang L. Infectious pathogens and risk of esophageal, gastric and duodenal cancers and ulcers in China: A case-cohort study. Int J Cancer 2024; 154:1423-1432. [PMID: 38108203 PMCID: PMC7615747 DOI: 10.1002/ijc.34814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 10/16/2023] [Accepted: 10/24/2023] [Indexed: 12/19/2023]
Abstract
Infection by certain pathogens is associated with cancer development. We conducted a case-cohort study of ~2500 incident cases of esophageal, gastric and duodenal cancer, and gastric and duodenal ulcer and a randomly selected subcohort of ~2000 individuals within the China Kadoorie Biobank study of >0.5 million adults. We used a bead-based multiplex serology assay to measure antibodies against 19 pathogens (total 43 antigens) in baseline plasma samples. Associations between pathogens and antigen-specific antibodies with risks of site-specific cancers and ulcers were assessed using Cox regression fitted using the Prentice pseudo-partial likelihood. Seroprevalence varied for different pathogens, from 0.7% for Hepatitis C virus (HCV) to 99.8% for Epstein-Barr virus (EBV) in the subcohort. Compared to participants seronegative for the corresponding pathogen, Helicobacter pylori seropositivity was associated with a higher risk of non-cardia (adjusted hazard ratio [HR] 2.73 [95% CI: 2.09-3.58]) and cardia (1.67 [1.18-2.38]) gastric cancer and duodenal ulcer (2.71 [1.79-4.08]). HCV was associated with a higher risk of duodenal cancer (6.23 [1.52-25.62]) and Hepatitis B virus was associated with higher risk of duodenal ulcer (1.46 [1.04-2.05]). There were some associations of antibodies again some herpesviruses and human papillomaviruses with risks of gastrointestinal cancers and ulcers but these should be interpreted with caution. This first study of multiple pathogens with risk of gastrointestinal cancers and ulcers demonstrated that several pathogens are associated with risks of gastrointestinal cancers and ulcers. This will inform future investigations into the role of infection in the etiology of these diseases.
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Affiliation(s)
- Christiana Kartsonaki
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Pang Yao
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Julia Butt
- Infections and Cancer Epidemiology Division, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rima Jeske
- Infections and Cancer Epidemiology Division, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Catherine de Martel
- Early Detection, Prevention and Infections Branch, International Agency for Research on Cancer, Lyon, France
| | - Martyn Plummer
- Department of Statistics, University of Warwick, Coventry, UK
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing 100191, China
| | - Sarah Clark
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G. Walters
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing 100191, China
| | - Michael Hill
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Richard Peto
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing 100191, China
| | - Tim Waterboer
- Infections and Cancer Epidemiology Division, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y. Millwood
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
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13
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Dong Y, Feng N, Liu P, Wei Q, Peng X, Jiang F, Chen Y. Dual-Track Multifunctional Bimetallic Metal-Organic Frameworks for Antibiotic Enrichment and Detection. Small 2024:e2309075. [PMID: 38597772 DOI: 10.1002/smll.202309075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 11/28/2023] [Indexed: 04/11/2024]
Abstract
The improper use and overuse of antibiotics have led to significant burdens and detrimental effects on the environment, food supply, and human health. Herein, a magnetic solid-phase extraction program and an optical immunosensor based on bimetallic Ce/Zr-UiO 66 for the detection of antibiotics are developed. A magnetic Fe3O4@SiO2@Ce/Zr-UiO 66 metal-organic framework (MOF) is prepared to extract and enrich chloramphenicol from fish, wastewater, and urine samples, and a horseradish peroxidase (HRP)-Ce/Zr-UiO 66@bovine serum protein-chloramphenicol probe is used for the sensitive detection of chloramphenicol based on the dual-effect catalysis of Ce and HRP. In this manner, the application of Ce/Zr-UiO 66 in integrating sample pretreatment and antibiotic detection is systematically investigated and the associated mechanisms are explored. It is concluded that Ce/Zr-UiO 66 is a versatile dual-track material exhibiting high enrichment efficiency (6.37 mg g-1) and high sensitivity (limit of detection of 51.3 pg mL-1) for chloramphenicol detection and serving as a multifunctional MOF for safeguarding public health and hygiene.
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Affiliation(s)
- Yiming Dong
- Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian, Liaoning, 116034, China
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Niu Feng
- Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian, Liaoning, 116034, China
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Puyue Liu
- Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian, Liaoning, 116034, China
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Qiaoling Wei
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Xuewen Peng
- Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian, Liaoning, 116034, China
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Feng Jiang
- Key Laboratory of Detection Technology of Focus Chemical Hazards in Animal-derived Food for State Market Regulation, Wuhan, Hubei, 430075, China
| | - Yiping Chen
- Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian, Liaoning, 116034, China
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
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14
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Lou Y, Li Y, Chen Y. The palliative care needs and experiences of patients with advanced Parkinson's disease: a qualitative scoping review. Front Med (Lausanne) 2024; 11:1362828. [PMID: 38660425 PMCID: PMC11039912 DOI: 10.3389/fmed.2024.1362828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 03/26/2024] [Indexed: 04/26/2024] Open
Abstract
Aim To determine the experiences and needs of palliative care in patients with advanced Parkinson's disease (PD). Methods A scoping literature review methodology, as described by the Joanna Briggs Institute, was employed to search for relevant literature. An electronic search of studies published in English was conducted across five databases from inception to 10 September 2023. Results The search yielded a total of 1,205 articles, with 20 meeting the inclusion criteria. The findings were organized into four themes: (1) unmet emotional and informational needs; (2) needs for effective coordination of care; (3) planning for the future; and (4) symptom management. This scoping review highlights the intricate nature of palliative care for patients with PD and sheds light on issues within current palliative care healthcare systems. The findings emphasize the necessity for individualized interventions and services to address the diverse unmet palliative care needs of people with PD. Conclusion The study reveals the complex landscape of palliative care for individuals with advanced PD, emphasizing the inadequacies within existing healthcare systems. The identified themes underscore the importance of tailored interventions to address the varied unmet palliative care needs of this population.
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Affiliation(s)
- Yan Lou
- School of Nursing, Hangzhou Normal University, Hangzhou, Zhejiang, China
- Zhejiang Haining Health School, Haining City, Zhejiang, China
| | - Yiting Li
- School of Nursing, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Yiping Chen
- School of Nursing, Shanxi Medical University, Taiyuan, Shanxi, China
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15
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Levy M, Buckell J, Clarke R, Wu N, Pei P, Sun D, Avery D, Zhang H, Lv J, Yu C, Li L, Chen Z, Yip W, Chen Y, Mihaylova B. Association between health insurance cost-sharing and choice of hospital tier for cardiovascular diseases in China: a prospective cohort study. Lancet Reg Health West Pac 2024; 45:101020. [PMID: 38380231 PMCID: PMC10876671 DOI: 10.1016/j.lanwpc.2024.101020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 12/13/2023] [Accepted: 01/16/2024] [Indexed: 02/22/2024]
Abstract
Background Hospitals in China are classified into tiers (1, 2 or 3), with the largest (tier 3) having more equipment and specialist staff. Differential health insurance cost-sharing by hospital tier (lower deductibles and higher reimbursement rates in lower tiers) was introduced to reduce overcrowding in higher tier hospitals, promote use of lower tier hospitals, and limit escalating healthcare costs. However, little is known about the effects of differential cost-sharing in health insurance schemes on choice of hospital tiers. Methods In a 9-year follow-up of a prospective study of 0.5 M adults from 10 areas in China, we examined the associations between differential health insurance cost-sharing and choice of hospital tiers for patients with a first hospitalisation for stroke or ischaemic heart disease (IHD) in 2009-2017. Analyses were performed separately in urban areas (stroke: n = 20,302; IHD: n = 19,283) and rural areas (stroke: n = 21,130; IHD: n = 17,890), using conditional logit models and adjusting for individual socioeconomic and health characteristics. Findings About 64-68% of stroke and IHD cases in urban areas and 27-29% in rural areas chose tier 3 hospitals. In urban areas, higher reimbursement rates in each tier and lower tier 3 deductibles were associated with a greater likelihood of choosing their respective hospital tiers. In rural areas, the effects of cost-sharing were modest, suggesting a greater contribution of other factors. Higher socioeconomic status and greater disease severity were associated with a greater likelihood of seeking care in higher tier hospitals in urban and rural areas. Interpretation Patient choice of hospital tiers for treatment of stroke and IHD in China was influenced by differential cost-sharing in urban areas, but not in rural areas. Further strategies are required to incentivise appropriate health seeking behaviour and promote more efficient hospital use. Funding Wellcome Trust, Medical Research Council, British Heart Foundation, Cancer Research UK, Kadoorie Charitable Foundation, China Ministry of Science and Technology, and National Natural Science Foundation of China.
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Affiliation(s)
- Muriel Levy
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, UK
| | - John Buckell
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, UK
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, UK
| | - Nina Wu
- School of Public Health, Capital Medical University, Beijing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Dianjianyi Sun
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Hua Zhang
- NCDs Prevention and Control Department, Qingdao Centre for Disease Control and Prevention, Qingdao, China
| | - Jun Lv
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Canqing Yu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Liming Li
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Winnie Yip
- Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, UK
| | - Borislava Mihaylova
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, UK
- Health Economics and Policy Research Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
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Zhou C, Huang C, Zhang H, Yang W, Jiang F, Chen G, Liu S, Chen Y. Machine-learning-driven optical immunosensor based on microspheres-encoded signal transduction for the rapid and multiplexed detection of antibiotics in milk. Food Chem 2024; 437:137740. [PMID: 37871421 DOI: 10.1016/j.foodchem.2023.137740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 10/01/2023] [Accepted: 10/10/2023] [Indexed: 10/25/2023]
Abstract
Antibiotic residues are the most common contaminants in milk and other related dairy products. Simultaneous, convenient, and stable detection of antibiotic residues in foods is vital to secure public health. Herein, we proposed an optical immunosensor with easily-functionalized polystyrene nanoparticles differing in size and quantity, and bearing multiplex signal probes for the simultaneous detection of multiple antibiotics through a simple one-step signal conversion reaction. After the integration of the machine-learning-based transcoding analysis, this sensor is suitable for multiplexed detection of antibiotics in a broad linear range from pg/mL to ng/mL within 30 min, with an overall accuracy of >99 %. Compared to the conventional standard chemiluminescence immunoassays, this immunosensor is suitable for the accurate quantification of multiple antibiotics in milk, with improved accuracy, reduced costs, and simplified procedure. This ensures its applications in food safety monitoring when simultaneous detection of multiple hazardous substances in food matrices is needed.
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Affiliation(s)
- Cuiyun Zhou
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Chenxi Huang
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China; Department of Food Science, Cornell University, Ithaca, NY, 14853, USA
| | - Hongyu Zhang
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Weihai Yang
- Qingdao Customs District P.R.China, Qingdao 266000, Shandong, China
| | - Feng Jiang
- Key Laboratory of Detection Technology of Focus Chemical Hazards in Animal-derived Food for State Market Regulation, Wuhan 430075, Hubei, China
| | - Guoxun Chen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
| | - Shanmei Liu
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
| | - Yiping Chen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China; Shenzhen Institute of Food Nutrition and Health, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
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17
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Elbasheer MMA, Bohrmann B, Chen Y, Lv J, Sun D, Wu X, Yang X, Avery D, Li L, Chen Z, Kartsonaki C, Chan KH, Yang L. Reproductive factors and risk of lung cancer among 300,000 Chinese female never-smokers: evidence from the China Kadoorie Biobank study. BMC Cancer 2024; 24:384. [PMID: 38532314 PMCID: PMC10964706 DOI: 10.1186/s12885-024-12133-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Accepted: 03/17/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND Lung cancer is the leading cause of cancer mortality among Chinese females despite the low smoking prevalence among this population. This study assessed the roles of reproductive factors in lung cancer development among Chinese female never-smokers. METHODS The prospective China Kadoorie Biobank (CKB) recruited over 0.5 million Chinese adults (0.3 million females) from 10 geographical areas in China in 2004-2008 when information on socio-demographic/lifestyle/environmental factors, physical measurements, medical history, and reproductive history collected through interviewer-administered questionnaires. Cox proportional hazard regression was used to estimate adjusted hazard ratios (HRs) of lung cancer by reproductive factors. Subgroup analyses by menopausal status, birth year, and geographical region were performed. RESULTS During a median follow-up of 11 years, 2,284 incident lung cancers occurred among 282,558 female never-smokers. Ever oral contraceptive use was associated with a higher risk of lung cancer (HR = 1.16, 95% CI: 1.02-1.33) with a significant increasing trend associated with longer duration of use (p-trend = 0.03). Longer average breastfeeding duration per child was associated with a decreased risk (0.86, 0.78-0.95) for > 12 months compared with those who breastfed for 7-12 months. No statistically significant association was detected between other reproductive factors and lung cancer risk. CONCLUSION Oral contraceptive use was associated with an increased risk of lung cancer in Chinese female never-smokers. Further studies are needed to assess lung cancer risk related to different types of oral contraceptives in similar populations.
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Affiliation(s)
- Marwa M A Elbasheer
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Bastian Bohrmann
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council (MRC) Population Health Research Unit (MRC PHRU), University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Xia Wu
- Pengzhou Centre for Disease Control and Prevention (CDC), Pengzhou, China
| | - Xiaoming Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council (MRC) Population Health Research Unit (MRC PHRU), University of Oxford, Oxford, UK
| | - Christiana Kartsonaki
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council (MRC) Population Health Research Unit (MRC PHRU), University of Oxford, Oxford, UK
| | - Ka Hung Chan
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Oxford BHF Centre of Research Excellence, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
- Medical Research Council (MRC) Population Health Research Unit (MRC PHRU), University of Oxford, Oxford, UK.
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18
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Hong F, Zhao Y, Pan S, Ren L, Jiang F, Wu L, Chen Y. Click Reaction-Mediated Fluorescent Immunosensor Based on Cu-MOF Nanoparticles for Ultrasensitive and High-Throughput Detection of Aflatoxin B 1 in Food Samples. J Agric Food Chem 2024; 72:5975-5982. [PMID: 38462975 DOI: 10.1021/acs.jafc.3c09730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Due to the high toxicity of aflatoxin B1 and its risks to human health, we developed a click reaction-mediated automated fluorescent immunosensor (CAFI) for sensitive detection of aflatoxin B1 based on the Cu(I)-catalyzed click reaction. With its large specific surface area, a copper-based metal-organic framework (Cu-MOF) was synthesized to adsorb and enrich the copper ion (Cu(II)) and then load the complete antigen (BSA-AFB1). After the immunoreaction, Cu(II) inside the Cu-MOF-Antigen conjugate would be reduced to Cu(I) in the presence of sodium ascorbate, which triggered the click reaction between the fluorescent donor-modified DNA and the receptor-modified complementary DNA to lead to a fluorescence signal readout. The whole reaction steps were finished by the self-developed automated immunoreaction device. This CAFI method showed a limit of detection (LOD) of 0.48 pg/mL as well as a 670-fold enhancement in sensitivity compared to conventional ELISA, revealing its great potential in practical applications and automated detection.
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Affiliation(s)
- Feng Hong
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yongkun Zhao
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, China
| | - Shixing Pan
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Liangqiong Ren
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Feng Jiang
- Key Laboratory of Detection Technology of Focus Chemical Hazards in Animal-derived Food for State Market Regulation, Hubei Provincial Institute for Food Supervision and Test, Wuhan 430075, China
| | - Long Wu
- School of Food Science and Engineering, Key Laboratory of Tropical and Vegetables Quality and Safety for State Market Regulation, Hainan University, Haikou 570228, China
| | - Yiping Chen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
- State Key Laboratory of Marine Food Processing and Safety Control, Dalian Polytechnic University, Dalian 116034, Liaoning, China
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19
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Lu P, Zhan C, Huang C, Miao L, Chen R, Zhao Y, Xianyu Y, Chen X, Chen Y. A Wash-Free Spheres-on-Sphere Strategy for On-Site and Multiplexed Biosensing. ACS Nano 2024; 18:8270-8282. [PMID: 38451231 DOI: 10.1021/acsnano.3c12289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Respiratory infections and food contaminants pose severe challenges to global health and the economy. A rapid on-site platform for the simultaneous detection of multiple pathogens is crucial for accurate diagnosis, appropriate treatment, and a reduced healthcare burden. Herein, we present a spheres-on-sphere (SOS) platform for multiplexed detection using a portable Coulter counter, which employs millimeter- and micron-sized spheres coupled with antibodies as multitarget probes. The assay allows for quantitative detection of multiple analytes within 20 min by simple mixing, enabling on-site detection. The platform shows high accuracy in identifying three respiratory viruses (SARS-CoV-2, influenza A virus, and parainfluenza virus) from throat swab samples, with LOD of 50.7, 32.4, and 49.1 pg/mL. It also demonstrates excellent performance in quantifying three mycotoxins (aflatoxin B1, deoxynivalenol, and ochratoxin A) from food samples. The SOS platform offers a rapid on-site approach with high sensitivity and specificity for applications in resource-limited settings.
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Affiliation(s)
- Peng Lu
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Chen Zhan
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Chenxi Huang
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Lin Miao
- The First School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Rui Chen
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yongkun Zhao
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yunlei Xianyu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China
| | - Xiaohua Chen
- The First School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Yiping Chen
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
- State Key Laboratory of Marine Food Processing and Safety Control, Dalian Polytechnic University, Dalian 116034, Liaoning, China
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20
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Zhao Y, Wang X, Pan S, Hong F, Lu P, Hu X, Jiang F, Wu L, Chen Y. Bimetallic nanozyme-bioenzyme hybrid material-mediated ultrasensitive and automatic immunoassay for the detection of aflatoxin B 1 in food. Biosens Bioelectron 2024; 248:115992. [PMID: 38184942 DOI: 10.1016/j.bios.2023.115992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 12/12/2023] [Accepted: 12/28/2023] [Indexed: 01/09/2024]
Abstract
Aflatoxin B1 (AFB1) is one of the most prevalent and dangerous biotoxin in crops and feedstuff, which poses a great threat to human health and also cause significant financial losses. Therefore, there is an urgent need to develop an effective method for AFB1 detection. In this work, we developed an automatic reaction equipment and nanozyme-enhanced immunosorbent assay (Auto-NEISA) for sensitive and accurate detection of AFB1 by combining the highly effective signal probes with a self-designed automated immunoreactive equipment. Wherein, polystyrene (PS) nanoparticles were used as signal carriers for loading a massive in situ-synthesized platinum and palladium bimetallic nanozyme, which could enrich horseradish peroxidase-labeled goat anti-mouse antibody (HRP-Ab2) on the nanozyme surface to form a bimetallic nanozyme-bioenzyme hybrid material for multiple signal amplification. The entire reaction could be automatically completed by the self-developed immunoreactive equipment. The Auto-NEISA method realized the sensitive detection of AFB1 with a wide linear detection range of 10-104 pg/mL, at a low limit of detection (LOD) of 5.52 pg/mL. The LOD was 65-fold lower than that of the enzyme-linked immunosorbent assay (ELISA). Additionally, Auto-NEISA was successfully applied to detect AFB1 in real food samples, demonstrating that it has considerable potential for detecting food contaminants with high accuracy and efficiency.
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Affiliation(s)
- Yongkun Zhao
- College of Engineering, Huazhong Agricultural University, Wuhan, 430070, PR China
| | - Xufeng Wang
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, 430070, PR China
| | - Shixing Pan
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, 430070, PR China
| | - Feng Hong
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, 430070, PR China
| | - Peng Lu
- College of Engineering, Huazhong Agricultural University, Wuhan, 430070, PR China
| | - Xiaobo Hu
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan, 430070, PR China
| | - Feng Jiang
- Key Laboratory of Detection Technology of Focus Chemical Hazards in Animal-derived Food for State Market Regulation, Wuhan, 430075, PR China
| | - Long Wu
- School of Food Science and Engineering, Key Laboratory of Tropical and Vegetables Quality and Safety for State Market Regulation, Hainan University, Haikou, 570228, PR China
| | - Yiping Chen
- Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian, 116034, Liaoning, PR China; Key Laboratory of Detection Technology of Focus Chemical Hazards in Animal-derived Food for State Market Regulation, Wuhan, 430075, PR China.
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21
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Zhao J, Han M, Ma A, Jiang F, Chen R, Dong Y, Wang X, Ruan S, Chen Y. A machine vision-assisted Argonaute-mediated fluorescence biosensor for the detection of viable Salmonella in food without convoluted DNA extraction and amplification procedures. J Hazard Mater 2024; 466:133648. [PMID: 38306835 DOI: 10.1016/j.jhazmat.2024.133648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/17/2024] [Accepted: 01/26/2024] [Indexed: 02/04/2024]
Abstract
The precise identification viable pathogens hold paramount significance in the prevention of foodborne diseases outbreaks. In this study, we integrated machine vision and learning with single microsphere to develop a phage and Clostridium butyricum Argonaute (CbAgo)-mediated fluorescence biosensor for detecting viable Salmonella typhimurium (S. typhimurium) without convoluted DNA extraction and amplification procedures. Phage and lysis buffer was utilized to capture and lyse viable S. typhimurium, respectively. Subsequently, CbAgo can cleave the bacterial DNA to obtain target DNA that guides a newly targeted cleavage of fluorescent probes. After that, the resulting fluorescent signal accumulates on the streptavidin-modified single microsphere. The overall detection process is then analyzed and interpreted by machine vision and learning algorithms, achieving highly sensitive detection of S. typhimurium with a limit of detection at 40.5 CFU/mL and a linear range of 50-107 CFU/mL. Furthermore, the proposed biosensor demonstrates standard recovery rates and coefficients of variation at 93.22% - 106.02% and 1.47% - 12.75%, respectively. This biosensor exhibits exceptional sensitivity and selectivity, presenting a promising method for the rapid and effective detection of foodborne pathogens. ENVIRONMENTAL IMPLICATION: Bacterial pathogens exist widely in the environment and seriously threaten the safety of human life. In this study, we developed a phage and Clostridium butyricum Argonaute-mediated fluorescence biosensor for the detection of viable Salmonella typhimurium in environmental water and food samples. Compared with other Salmonella detection methods, this method does not need complex DNA extraction and amplification steps, which reduces the use of chemical reagents and experimental consumables in classic DNA extraction kit methods.
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Affiliation(s)
- Junpeng Zhao
- College of Food Science and Technology, Huazhong Agricultural University, Shizishan Street, Hongshan District, Wuhan 430070, Hubei, China
| | - Minjie Han
- College of Food Science and Technology, Huazhong Agricultural University, Shizishan Street, Hongshan District, Wuhan 430070, Hubei, China
| | - Aimin Ma
- College of Food Science and Technology, Huazhong Agricultural University, Shizishan Street, Hongshan District, Wuhan 430070, Hubei, China
| | - Feng Jiang
- Key Laboratory of Detection Technology of Focus Chemical Hazards in Animal-derived Food for State Market Regulation, Wuhan 430075, Hubei, China
| | - Rui Chen
- College of Food Science and Technology, Huazhong Agricultural University, Shizishan Street, Hongshan District, Wuhan 430070, Hubei, China
| | - Yongzhen Dong
- State Key Laboratory of Marine Food Processing and Safety Control, Dalian Polytechnic University, Dalian 116034, Liaoning, China
| | - Xufeng Wang
- College of Food Science and Technology, Huazhong Agricultural University, Shizishan Street, Hongshan District, Wuhan 430070, Hubei, China
| | - Shilong Ruan
- Daye Public Inspection and Test Center, Daye 435100, Hubei, China
| | - Yiping Chen
- State Key Laboratory of Marine Food Processing and Safety Control, Dalian Polytechnic University, Dalian 116034, Liaoning, China.
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Wang Z, Liu Y, Zhang A, Yang L, Wei C, Chen Y, Liu Z, Li Z. Occurrence characteristics, environmental trend, and source analysis of polycyclic aromatic hydrocarbons in the water environment of industrial zones. Environ Res 2024; 245:118053. [PMID: 38160976 DOI: 10.1016/j.envres.2023.118053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/11/2023] [Accepted: 12/25/2023] [Indexed: 01/03/2024]
Abstract
The middle reaches of the Yellow River are rich in energy resources, with the Kuye River, a first-class river in this region, serving as a vital hub for the coal chemical industry within China. This study investigated the occurrence patterns, environmental trends, and ecological risks associated with polycyclic aromatic hydrocarbons (PAHs) in the Kuye River Basin, offering insights into the environmental dynamics of regions. The findings indicated that the river sediments primarily contained PAHs with medium to high-molecular weights, exhibiting levels ranging from 402.92 ng/g dw to 16,783.72 ng/g dw, while water bodies predominantly featured PAHs with low to medium molecular weights, ranging from 299.34 ng/L to 10,930.9 ng/L. The source analysis of PAHs indicated that industrial and traffic exhaust emissions were the primary contributors to PAHs in the Kuye basin, with sediments serving as a secondary release source based on fugacity fraction. The content of PAHs in sediment correlated closely with the environmental factors, and the PAHs inventory of the basin was 19.97 tons. The increased overall PAH concentration in the basin posed significant ecological and public health concerns, necessitating urgent attention.
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Affiliation(s)
- Zhu Wang
- School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Yan Ta Road. No.13, Xi'an, 710055, China; Key Lab of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Yongjun Liu
- School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Yan Ta Road. No.13, Xi'an, 710055, China; Key Lab of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China.
| | - Aining Zhang
- School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Yan Ta Road. No.13, Xi'an, 710055, China; Key Lab of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Lu Yang
- School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Yan Ta Road. No.13, Xi'an, 710055, China; Key Lab of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Chunxiao Wei
- School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Yan Ta Road. No.13, Xi'an, 710055, China; Key Lab of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Yiping Chen
- Institute of Earth Environment, Chinese Academy of Sciences, Yan Xiang Road. No.97, Xi'an, 710061, China
| | - Zhe Liu
- School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Yan Ta Road. No.13, Xi'an, 710055, China; Key Lab of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Zhihua Li
- School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Yan Ta Road. No.13, Xi'an, 710055, China; Key Lab of Northwest Water Resource, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an, 710055, China
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Zhang Y, Sun Q, Yu C, Sun D, Pang Y, Pei P, Du H, Yang L, Chen Y, Yang X, Chen X, Chen J, Chen Z, Li L, Lv J. Associations of traditional cardiovascular risk factors with 15-year blood pressure change and trajectories in Chinese adults: a prospective cohort study. J Hypertens 2024:00004872-990000000-00438. [PMID: 38525868 DOI: 10.1097/hjh.0000000000003717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2024]
Abstract
OBJECTIVE How traditional cardiovascular disease (CVD) risk factors are related to long-term blood pressure change (BPC) or trajectories remain unclear. We aimed to examine the independent associations of these factors with 15-year BPC and trajectories in Chinese adults. METHODS We included 15 985 participants who had attended three surveys, including 2004-2008 baseline survey, and 2013-2014 and 2020-2021 resurveys, over 15 years in the China Kadoorie Biobank (CKB). We measured systolic and diastolic blood pressure (SBP and DBP), height, weight, and waist circumference (WC). We asked about the sociodemographic characteristics and lifestyle factors, including smoking, alcohol drinking, intake of fresh vegetables, fruits, and red meat, and physical activity, using a structured questionnaire. We calculated standard deviation (SD), cumulative blood pressure (cumBP), coefficient of variation (CV), and average real variability (ARV) as long-term BPC proxies. We identified blood pressure trajectories using the latent class growth model. RESULTS Most baseline sociodemographic and lifestyle characteristics were associated with cumBP. After adjusting for other characteristics, the cumSBP (mmHg × year) increased by 116.9 [95% confidence interval (CI): 111.0, 122.7] for every 10 years of age. The differences of cumSBP in heavy drinkers of ≥60 g pure alcohol per day and former drinkers were 86.7 (60.7, 112.6) and 48.9 (23.1, 74.8) compared with less than weekly drinkers. The cumSBP in participants who ate red meat less than weekly was 29.4 (12.0, 46.8) higher than those who ate red meat daily. The corresponding differences of cumSBP were 127.8 (120.7, 134.9) and 70.2 (65.0, 75.3) for BMI per 5 kg/m2 and WC per 10 cm. Most of the findings of other BPC measures by baseline characteristics were similar to the cumBP, but the differences between groups were somewhat weaker. Alcohol drinking was associated with several high-risk trajectories of SBP and DBP. Both BMI and WC were independently associated with all high-risk blood pressure trajectories. CONCLUSIONS Several traditional CVD risk factors were associated with unfavorable long-term BPC or blood pressure trajectories in Chinese adults.
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Affiliation(s)
- Yiqian Zhang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
| | - Qiufen Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Yuanjie Pang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Xiaoming Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | | | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University
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24
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Zhu Y, Zhuang Z, Lv J, Sun D, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Liu F, Stevens R, Chen J, Chen Z, Li L, Yu C. A genome-wide association study based on the China Kadoorie Biobank identifies genetic associations between snoring and cardiometabolic traits. Commun Biol 2024; 7:305. [PMID: 38461358 PMCID: PMC10924953 DOI: 10.1038/s42003-024-05978-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 02/27/2024] [Indexed: 03/11/2024] Open
Abstract
Despite the high prevalence of snoring in Asia, little is known about the genetic etiology of snoring and its causal relationships with cardiometabolic traits. Based on 100,626 Chinese individuals, a genome-wide association study on snoring was conducted. Four novel loci were identified for snoring traits mapped on SLC25A21, the intergenic region of WDR11 and FGFR, NAA25, ALDH2, and VTI1A, respectively. The novel loci highlighted the roles of structural abnormality of the upper airway and craniofacial region and dysfunction of metabolic and transport systems in the development of snoring. In the two-sample bi-directional Mendelian randomization analysis, higher body mass index, weight, and elevated blood pressure were causal for snoring, and a reverse causal effect was observed between snoring and diastolic blood pressure. Altogether, our results revealed the possible etiology of snoring in China and indicated that managing cardiometabolic health was essential to snoring prevention, and hypertension should be considered among snorers.
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Affiliation(s)
- Yunqing Zhu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Zhenhuang Zhuang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Fang Liu
- Suzhou Centers for Disease Control, NO.72 Sanxiang Road, Gusu District, Suzhou, 215004, Jiangsu, China
| | - Rebecca Stevens
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, 100022, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China.
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25
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Wang X, Li J, Nong J, Deng X, Chen Y, Wu P, Huang X. Curcumol Attenuates Portal Hypertension and Collateral Shunting Via Inhibition of Extrahepatic Angiogenesis in Cirrhotic Rats. Biochem Genet 2024:10.1007/s10528-024-10684-x. [PMID: 38438779 DOI: 10.1007/s10528-024-10684-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 01/03/2024] [Indexed: 03/06/2024]
Abstract
Liver cirrhosis can cause disturbances in blood circulation in the liver, resulting in impaired portal blood flow and ultimately increasing portal venous pressure. Portal hypertension induces portal-systemic collateral formation and fatal complications. Extrahepatic angiogenesis plays a crucial role in the development of portal hypertension. Curcumol is a sesquiterpenoid derived from the rhizome of Curcumae Rhizoma and has been confirmed to alleviate liver fibrosis by inhibiting angiogenesis. Therefore, our study was designed to explore the effects of curcumol on extrahepatic angiogenesis and portal hypertension. To induce cirrhosis, Sprague Dawley rats underwent bile duct ligation (BDL) surgery. Rats received oral administration with curcumol (30 mg/kg/d) or vehicle (distilled water) starting on day 15 following surgery, when BDL-induced liver fibrosis had developed. The effect of curcumol was assessed on day 28, which is the typical time of BDL-induced cirrhosis. The results showed that curcumol markedly reduced portal pressure in cirrhotic rats. Curcumol inhibited abnormal splanchnic inflow, mitigated liver injury, improved liver fibrosis, and attenuated portal-systemic collateral shunting in cirrhotic rats. These protective effects were partially attributed to the inhibition on mesenteric angiogenesis by curcumol. Mechanically, curcumol partially reversed the BDL-induced activation of the JAK2/STAT3 signaling pathway in cirrhotic rats. Collectively, curcumol attenuates portal hypertension in liver cirrhosis by suppressing extrahepatic angiogenesis through inhibiting the JAK2/STAT3 signaling pathway.
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Affiliation(s)
- Xinyuan Wang
- Development of Planning Division, Guangxi University of Chinese Medicine, Nanning, 530000, China
| | - Juan Li
- Development of Pediatric, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning, 530000, China
| | - Jiao Nong
- Development of Education, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning, 530000, China
| | - Xin Deng
- Basic Medical College, Guangxi University of Chinese Medicine, Nanning, 530000, China
| | - Yiping Chen
- Development of Emergency, The First Affiliated Hospital of Guangxi University of Chinese Medicine, No.28 Wangyuan Road, Qingxiu District, Nanning, 530000, China
| | - Peibin Wu
- Achievement Transformation and Social Service Office, Guangxi University of Chinese Medicine, Nanning, 530000, China
| | - Xiabing Huang
- Development of Emergency, The First Affiliated Hospital of Guangxi University of Chinese Medicine, No.28 Wangyuan Road, Qingxiu District, Nanning, 530000, China.
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26
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Liu G, Zhang CM, Li Y, Sun JY, Cheng YB, Chen YP, Wang ZH, Ren H, Liu CF, Jin YP, Chen S, Wang XM, Xu F, Xu XZ, Zhu QJ, Wang XD, Liu XH, Liu Y, Hu Y, Wang W, Ai Q, Dang HX, Gao HM, Fan CN, Qian SY. [Respiratory virus infection and its influence on outcome in children with septic shock]. Zhonghua Er Ke Za Zhi 2024; 62:211-217. [PMID: 38378281 DOI: 10.3760/cma.j.cn112140-20231014-00286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Objective: To investigate respiratory virus infection in children with septic shock in pediatric care units (PICU) in China and its influence on clinical outcomes. Methods: The clinical data of children with septic shock in children's PICU from January 2018 to December 2019 in 10 Chinese hospitals were retrospectively collected. They were divided into the pre-COVID-19 and post-COVID-19 groups according to the onset of disease, and the characteristics and composition of respiratory virus in the 2 groups were compared. Matching age, malignant underlying diseases, bacteria, fungi and other viruses, a new database was generated using 1∶1 propensity score matching method. The children were divided into the respiratory virus group and non-respiratory virus group according to the presence or absence of respiratory virus infection; their clinical characteristics, diagnosis, and treatment were compared by t-test, rank sum test and Chi-square test. The correlation between respiratory virus infection and the clinical outcomes was analyzed by logistic regression. Results: A total of 1 247 children with septic shock were included in the study, of them 748 were male; the age was 37 (11, 105) months. In the pre-and post-COVID-19 groups, there were 530 and 717 cases of septic shock, respectively; the positive rate of respiratory virus was 14.9% (79 cases) and 9.8% (70 cases); the seasonal distribution of septic shock was 28.9% (153/530) and 25.9% (185/717) in autumn, and 30.3% (161/530) and 28.3% (203/717) in winter, respectively, and the corresponding positive rates of respiratory viruses were 19.6% (30/153) and 15.7% (29/185) in autumn, and 21.1% (34/161) and 15.3% (31/203) in winter, respectively. The positive rates of influenza virus and adenovirus in the post-COVID-19 group were lower than those in the pre-COVID-19 group (2.1% (15/717) vs. 7.5% (40/530), and 0.7% (5/717) vs. 3.2% (17/530), χ2=21.51 and 11.08, respectively; all P<0.05). Rhinovirus virus were higher than those in the pre-Covid-19 group (1.7% (12/717) vs. 0.2% (1/530), χ2=6.51, P=0.011). After propensity score matching, there were 147 cases in both the respiratory virus group and the non-respiratory virus group. Rate of respiratory failure, acute respiratory distress, rate of disseminated coagulation dysfunction, and immunoglobulin usage of the respiratory virus group were higher than those of non-respiratory virus group (77.6% (114/147) vs. 59.2% (87/147), 17.7% (26/147) vs. 4.1% (6/147), 15.6% (25/147) vs. 4.1% (7/147), and 35.4% (52/147) vs. 21.4% (32/147); χ2=11.07, 14.02, 11.06 and 6.67, all P<0.05); and PICU hospitalization of the former was longer than that of the later (7 (3, 16) vs. 3 (1, 7)d, Z=5.01, P<0.001). Univariate logistic regression analysis showed that the presence of respiratory viral infection was associated with respiratory failure, disseminated coagulation dysfunction, the use of mechanical ventilation, and the use of immunoglobulin and anti-respiratory viral drugs (OR=2.42, 0.22, 0.25, 0.56 and 1.12, all P<0.05). Conclusions: The composition of respiratory virus infection in children with septic shock is different between pre and post-COVID-19. Respiratory viral infection is associated with organ dysfunction in children with septic shock. Decreasing respiratory viral infection through respiratory protection may improve the clinical outcome of these children.
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Affiliation(s)
- G Liu
- Department of Pediatric Intensive Care Unit, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - C M Zhang
- Department of Pediatric Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - Y Li
- Department of Pediatric Intensive Care Unit, Children's Hospital Affiliated to Soochow University, Suzhou 215025, China
| | - J Y Sun
- Department of Pediatric Critical Care, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - Y B Cheng
- Department of Pediatric Intensive Care Unit, Henan Children's Hospital, Zhengzhou 450018, China
| | - Y P Chen
- Department of Pediatric Intensive Care Unit, Baoding Children's Hospital, Baoding 071051, China
| | - Z H Wang
- Department of Pediatric Intensive Care Unit, Baoding Children's Hospital, Baoding 071051, China
| | - H Ren
- Department of Pediatric Intensive Care Unit, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - C F Liu
- Department of Pediatric Intensive Care Unit, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Y P Jin
- Department of Pediatric Intensive Care Unit, Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - S Chen
- Department of Pediatric Intensive Care Unit, Tianjin Children's Hospital, Tianjin 300074, China
| | - X M Wang
- Department of Hematology, Tianjin Children's Hospital, Tianjin 300074, China
| | - F Xu
- Department of Pediatric Critical Care, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - X Z Xu
- Department of Pediatric Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - Q J Zhu
- Department of Pediatric Intensive Care Unit, Children's Hospital Affiliated to Soochow University, Suzhou 215025, China
| | - X D Wang
- Department of Pediatric Intensive Care Unit, Henan Children's Hospital, Zhengzhou 450018, China
| | - X H Liu
- Department of Pediatric Intensive Care Unit, Baoding Children's Hospital, Baoding 071051, China
| | - Y Liu
- Department of Pediatric Intensive Care Unit, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Y Hu
- Department of Pediatric Intensive Care Unit, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - W Wang
- Department of Pediatric Intensive Care Unit, Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Q Ai
- Department of Hematology, Tianjin Children's Hospital, Tianjin 300074, China
| | - H X Dang
- Department of Pediatric Critical Care, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - H M Gao
- Department of Pediatric Intensive Care Unit, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - C N Fan
- Department of Pediatric Intensive Care Unit, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - S Y Qian
- Department of Pediatric Intensive Care Unit, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
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Zhu Y, Zhuang Z, Lv J, Sun D, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Wu X, Schmidt D, Avery D, Chen J, Chen Z, Li L, Yu C. Causal association between snoring and stroke: a Mendelian randomization study in a Chinese population. Lancet Reg Health West Pac 2024; 44:101001. [PMID: 38304719 PMCID: PMC10832459 DOI: 10.1016/j.lanwpc.2023.101001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 11/24/2023] [Accepted: 12/19/2023] [Indexed: 02/03/2024]
Abstract
Background Previous observational studies established a positive relationship between snoring and stroke. We aimed to investigate the causal effect of snoring on stroke. Methods Based on 82,339 unrelated individuals with qualified genotyping data of Asian descent from the China Kadoorie Biobank (CKB), we conducted a Mendelian randomization (MR) analysis of snoring and stroke. Genetic variants identified in the genome-wide association analysis (GWAS) of snoring in CKB and UK Biobank (UKB) were selected for constructing genetic risk scores (GRS). A two-stage method was applied to estimate the associations of the genetically predicted snoring with stroke and its subtypes. Besides, MR analysis among the non-obese group (body mass index, BMI <24.0 kg/m2), as well as multivariable MR (MVMR), were performed to control for potential pleiotropy from BMI. In addition, the inverse-variance weighted (IVW) method was applied to estimate the causal association with genetic variants identified in CKB GWAS. Findings Positive associations were found between snoring and total stroke, hemorrhagic stroke (HS), and ischemic stroke (IS). With GRS of CKB, the corresponding HRs (95% CIs) were 1.56 (1.15, 2.12), 1.50 (0.84, 2.69), 2.02 (1.36, 3.01), and the corresponding HRs (95% CIs) using GRS of UKB were 1.78 (1.30, 2.43), 1.94 (1.07, 3.52), and 1.74 (1.16, 2.61). The associations remained stable in the MR among the non-obese group, MVMR analysis, and MR analysis using the IVW method. Interpretation This study suggests that, among Chinese adults, genetically predicted snoring could increase the risk of total stroke, IS, and HS, and the causal effect was independent of BMI. Funding National Natural Science Foundation of China, Kadoorie Charitable Foundation Hong Kong, UK Wellcome Trust, National Key R&D Program of China, Chinese Ministry of Science and Technology.
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Affiliation(s)
- Yunqing Zhu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Zhenhuang Zhuang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Iona Y. Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Robin G. Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Xianping Wu
- Suzhou Centers for Disease Control, NO.72 Sanxiang Road, Gusu District, Suzhou, 215004, Jiangsu, China
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, 100022, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
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28
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Shi K, Zhu Y, Lv J, Sun D, Pei P, Du H, Chen Y, Yang L, Han B, Stevens R, Chen J, Chen Z, Li L, Yu C. Association of physical activity with risk of chronic kidney disease in China: A population-based cohort study. J Sport Health Sci 2024; 13:204-211. [PMID: 37532222 PMCID: PMC10980896 DOI: 10.1016/j.jshs.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/29/2023] [Accepted: 07/06/2023] [Indexed: 08/04/2023]
Abstract
BACKGROUND Information on the association between physical activity (PA) and the risk of chronic kidney disease (CKD) is limited. We aimed to explore the associations of total, domain-specific, and intensity-specific PA with CKD and its subtypes in China. METHODS The study included 475,376 adults from the China Kadoorie Biobank aged 30-79 years during 2004-2008 at baseline. An interviewer-administered questionnaire was used to collect the information about PA, which was quantified as metabolic equivalent of task hours per day (MET-h/day) and categorized into 4 groups based on quartiles. Cox regression was used to analyze the association between PA and CKD risk. RESULTS During a median follow-up of 12.1 years, 5415 incident CKD cases were documented, including 1159 incident diabetic kidney disease (DKD) cases and 362 incident hypertensive nephropathy (HTN) cases. Total PA was inversely associated with CKD risk, with an adjusted hazard ratio (HR, 95% confidence interval (95%CI)) of 0.83 (0.75-0.92) for incident CKD in the highest quartile of total PA as compared with participants in the lowest quartile. Similar results were observed for risk of DKD and HTN, and the corresponding HRs (95%CIs) were 0.75 (0.58-0.97) for DKD risk and 0.56 (0.37-0.85) for HTN risk. Increased nonoccupational PA, low-intensity PA, and moderate-to-vigorous-intensity PA were significantly associated with a decreased risk of CKD, with HRs (95%CIs) of 0.80 (0.73-0.88), 0.85 (0.77-0.94), and 0.85 (0.76-0.95) in the highest quartile, respectively. CONCLUSION PA, including nonoccupational PA, low-intensity PA, and moderate-to-vigorous-intensity PA, was inversely associated with the risk of CKD, including DKD, HTN, and other CKD, and such associations were dose dependent.
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Affiliation(s)
- Kexiang Shi
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
| | - Yunqing Zhu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Huaidong Du
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - Yiping Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - Ling Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - Bing Han
- NCDs Prevention and Control Department, Henan Center for Disease Control and Prevention, Zhengzhou 450016, China
| | - Rebecca Stevens
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China.
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Shen J, Hao C, Yuan S, Chen W, Tong T, Chen Y, Shahzad Aslam M, Yan S, Li J, Zeng J, Liu S, Chen Y, Jiang Y, Li P, Meng X. Acupuncture alleviates CUMS-induced depression-like behaviors of rats by regulating oxidative stress, neuroinflammation and ferroptosis. Brain Res 2024; 1826:148715. [PMID: 38142722 DOI: 10.1016/j.brainres.2023.148715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/08/2023] [Accepted: 12/11/2023] [Indexed: 12/26/2023]
Abstract
BACKGROUND The treatment of depression with acupuncture has been documented. The mechanism behind acupuncture's curative and preventative effects is still unknown. METHODS The current study examined the effects of acupuncture on depression-like behaviors in a rat model of chronic unpredictable mild stress (CUMS), while also exploring its potential mechanisms. A total of six groups of rats were randomly assigned: control, CUMS, acupuncture, fluoxetine, acupoint catgut embedding and sham acupoint catgut embedding. Fluoxetine (2.1 mg/kg) and acupoint catgut embedding were used for comparative research to acupuncture. The modelling evaluation is measured by body weight and behavior tests. Western blotting and reverse transcription-polymerase chain reaction were used to detect the proteins and mRNA expression of Silent information regulator 1 (Sirt1)/ nuclear factor-erythroid 2-related factor 2 (Nrf2)/ heme oxygenase-1 (HO-1)/ Glutathione peroxidase 4 (GPX4) pathway in the hippocampus. The expression of oxidative stress (OS)-related proteins and inflammatory cytokines in the serum was detected with ELISA. Immunofluorescence showed microglia and astrocytes activity in the hippocampus. RESULTS Acupuncture and fluoxetine could alleviate CUMS-induced depression-like behaviors. Acupuncture was also found to effectively reverse the levels of MDA, SOD, GSH, GSH-PX and T-AOC, IL-1β, IL-6 and TNF-α in the serum of CUMS-induced rats. Rats with CUMS showed decreased levels of Sirt1, Nrf2, HO-1 and GPX4 in the hippocampus, while acupuncture treatment could partly reverse the diminished effects. In addition, acupuncture treatment significantly reduced the activation of hippocampal microglia and astrocytes in CUMS-induced rats. CONCLUSION The study's findings indicate that acupuncture has the potential to mitigate depression-like behaviors in rats induced with CUMS by mitigating OS and reducing neuroinflammation.
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Affiliation(s)
- Junliang Shen
- Department of Traditional Chinese Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, PR China
| | - Chongyao Hao
- Second Clinical College, Shanxi University of Traditional Chinese Medicine, Taiyuan, Shanxi, PR China
| | - Shiwei Yuan
- Longyan Hospital of Traditional Chinese Medicine Affiliated Xiamen University, Longyan, Fujian, PR China
| | - Wenjie Chen
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, PR China
| | - Tao Tong
- Second Clinical College, Shanxi University of Traditional Chinese Medicine, Taiyuan, Shanxi, PR China
| | - Yiping Chen
- First Clinical College, Yunnan University of Chinese Medicine, Kunming, Yunnan, PR China
| | | | - Simin Yan
- Department of Traditional Chinese Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, PR China
| | - Jianguo Li
- Second Clinical College, Shanxi University of Traditional Chinese Medicine, Taiyuan, Shanxi, PR China
| | - Jingyu Zeng
- Department of Traditional Chinese Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, PR China
| | - Siyu Liu
- Longyan Hospital of Traditional Chinese Medicine Affiliated Xiamen University, Longyan, Fujian, PR China
| | - Yiwen Chen
- Department of Traditional Chinese Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, PR China
| | - Yanqin Jiang
- Department of Traditional Chinese Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, PR China
| | - Peng Li
- Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, PR China.
| | - Xianjun Meng
- Department of Traditional Chinese Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, PR China.
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30
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Wei X, Sun D, Gao J, Zhang J, Zhu M, Yu C, Ma Z, Fu Y, Ji C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Jin G, Chen Z, Hu Z, Li L, Shen H, Lv J, Ma H. Development and evaluation of a polygenic risk score for lung cancer in never-smoking women: A large-scale prospective Chinese cohort study. Int J Cancer 2024; 154:807-815. [PMID: 37846649 DOI: 10.1002/ijc.34765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 08/30/2023] [Accepted: 09/13/2023] [Indexed: 10/18/2023]
Abstract
The proportion of lung cancer in never smokers is rising, especially among Asian women, but there is no effective early detection tool. Here, we developed a polygenic risk score (PRS), which may help to identify the population with higher risk of lung cancer in never-smoking women. We first performed a large GWAS meta-analysis (8595 cases and 8275 controls) to systematically identify the susceptibility loci for lung cancer in never-smoking Asian women and then generated a PRS using GWAS datasets. Furthermore, we evaluated the utility and effectiveness of PRS in an independent Chinese prospective cohort comprising 55 266 individuals. The GWAS meta-analysis identified eight known loci and a novel locus (5q11.2) at the genome-wide statistical significance level of P < 5 × 10-8 . Based on the summary statistics of GWAS, we derived a polygenic risk score including 21 variants (PRS-21) for lung cancer in never-smoking women. Furthermore, PRS-21 had a hazard ratio (HR) per SD of 1.29 (95% CI = 1.18-1.41) in the prospective cohort. Compared with participants who had a low genetic risk, those with an intermediate (HR = 1.32, 95% CI: 1.00-1.72) and high (HR = 2.09, 95% CI: 1.56-2.80) genetic risk had a significantly higher risk of incident lung cancer. The addition of PRS-21 to the conventional risk model yielded a modest significant improvement in AUC (0.697 to 0.711) and net reclassification improvement (24.2%). The GWAS-derived PRS-21 significantly improves the risk stratification and prediction accuracy for incident lung cancer in never-smoking Asian women, demonstrating the potential for identification of high-risk individuals and early screening.
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Affiliation(s)
- Xiaoxia Wei
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Jiaxin Gao
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jing Zhang
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Zhimin Ma
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yating Fu
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chen Ji
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Guangfu Jin
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Zhibin Hu
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Hongbing Shen
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Hongxia Ma
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
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Turnbull I, Camm CF, Halsey J, Du H, Bennett DA, Chen Y, Yu C, Sun D, Liu X, Li L, Chen Z, Clarke R. Correlates and consequences of atrial fibrillation in a prospective study of 25 000 participants in the China Kadoorie Biobank. Eur Heart J Open 2024; 4:oeae021. [PMID: 38572088 PMCID: PMC10989653 DOI: 10.1093/ehjopen/oeae021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 02/08/2024] [Accepted: 02/15/2024] [Indexed: 04/05/2024]
Abstract
Aims The prevalence of atrial fibrillation (AF) is positively correlated with prior cardiovascular diseases (CVD) and CVD risk factors but is lower in Chinese than Europeans despite their higher burden of CVD. We examined the prevalence and prognosis of AF and other electrocardiogram (ECG) abnormalities in the China Kadoorie Biobank. Methods and results A random sample of 25 239 adults (mean age 59.5 years, 62% women) had a 12-lead ECG recorded and interpreted using a Mortara VERITAS™ algorithm in 2013-14. Participants were followed up for 5 years for incident stroke, ischaemic heart disease, heart failure (HF), and all CVD, overall and by CHA2DS2-VASc scores, age, sex, and area. Overall, 1.2% had AF, 13.6% had left ventricular hypertrophy (LVH), and 28.1% had ischaemia (two-thirds of AF cases also had ischaemia or LVH). The prevalence of AF increased with age, prior CVD, and levels of CHA₂DS₂-VASc scores (0.5%, 1.3%, 2.1%, 2.9%, and 4.4% for scores <2, 2, 3, 4, and ≥5, respectively). Atrial fibrillation was associated with two-fold higher hazard ratios (HR) for CVD (2.15; 95% CI, 1.71-2.69) and stroke (1.88; 1.44-2.47) and a four-fold higher HR for HF (3.79; 2.21-6.49). The 5-year cumulative incidence of CVD was comparable for AF, prior CVD, and CHA₂DS₂-VASc scores ≥ 2 (36.7% vs. 36.2% vs. 37.7%, respectively) but was two-fold greater than for ischaemia (19.4%), LVH (18.0%), or normal ECG (14.1%), respectively. Conclusion The findings highlight the importance of screening for AF together with estimation of CHA₂DS₂-VASc scores for prevention of CVD in Chinese adults.
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Affiliation(s)
- Iain Turnbull
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Christian Fielder Camm
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Jim Halsey
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Huaidong Du
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Derrick A Bennett
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Yiping Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Dianyianji Sun
- Department of Epidemiology and Biostatistics, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Xiaohong Liu
- Medical Records Archive, Pengzhou Traditional Medicine Hospital, Penzhou, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Robert Clarke
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
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Chen S, Ban CR, Zhang XT, Chen YP, Ren CH, Chen H. [Expression of programmed cell death ligand 1 and clinicopathological and immunological characteristics in fumarate hydratase-deficient renal cell carcinoma]. Zhonghua Bing Li Xue Za Zhi 2024; 53:155-161. [PMID: 38281783 DOI: 10.3760/cma.j.cn112151-20230905-00132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
Objective: To investigate the expression of programmed cell death ligand 1 (PD-L1), clinicopathologic features, immunohistochemical expression and molecular characteristics in fumarate hydratase (FH)-deficient renal cell carcinoma and to explore the potential application of immunotherapy in the patients. Methods: There were six patients with FH-deficient renal cell carcinoma treated at the First Affiliated Hospital of Fujian Medical University between January 2020 and October 2022. The clinical data, histological morphology, immunophenotype, PD-L1 expression and next-generation sequencing results were tabulated and analyzed. Results: There were 6 patients, all male, age ranged from 37 to 72 years (mean 45.7 years). Four cases were high-grade (WHO/ISUP grade3-4) with 2 or more histologic patterns, including papillary (most common), glandular, tubular, vesicular, ethmoid, nest-like, cystic and solid structures. Two cases were low-grade which showed nest-like, glandular, or tubular arrangement with eosinophilic flocculent cytoplasm and small intracellular vacuoles. Immunohistochemical analysis revealed strong expression of 2SC in all 6 cases, negative expression of FH in 5 cases, and positive expression of GATA3 in 5 cases. In high-grade cases, the mean values of CD4 and CD8 positive T-lymphocytes in advanced tumor invasion were 180.3/mm2 and 130.5/mm2, respectively. PD-L1 combined positive scores (CPS) were 20, 50, 5 and 30, respectively. The Ki-67 proliferative index were 20%, 20%, 10% and 30%, respectively. In low-grade cases, the mean values of CD4 and CD8 positive T-lymphocytes were 123.0/mm2 and 100.5/mm2, respectively. The PD-L1 CPS score was 1, and the Ki-67 proliferation index was 3%. High-throughput sequencing showed FH gene somatic mutation in 3 cases, FH gene germline mutation in 2 cases, and FH gene mutation was not detected in one case. Conclusion: FH-deficient renal cell carcinoma is more commonly high-grade than low grade. FH and 2SC are immunohistochemical markers used in the diagnosis of FH-deficient renal cell carcinoma, and GATA3 positivity is supportive of the diagnosis. The tumor infiltration of high-grade FH-deficient renal cell carcinoma shows an increase in CD4 and CD8 positive T-lymphocytes, and high expression of PD-L1; thus, anti-PD-L1 immunotherapy can be used as a treatment option.
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Affiliation(s)
- S Chen
- Department of Pathology, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
| | - C R Ban
- Department of Pathology, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
| | - X T Zhang
- Department of Pathology, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
| | - Y P Chen
- Department of Pathology, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
| | - C H Ren
- Department of Pathology, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
| | - H Chen
- Department of Pathology, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
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Wang Z, Feng N, Zhou Y, Cheng X, Zhou C, Ma A, Wang Q, Li Y, Chen Y. Mesophilic Argonaute-Mediated Polydisperse Droplet Biosensor for Amplification-Free, One-Pot, and Multiplexed Nucleic Acid Detection Using Deep Learning. Anal Chem 2024; 96:2068-2077. [PMID: 38259216 DOI: 10.1021/acs.analchem.3c04426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Detection of nucleic acids from a single multiplexed and amplification-free test is critical for ensuring food safety, clinical diagnostics, and environmental monitoring. In this study, we introduced a mesophilic Argonaute protein from Clostridium butyricum (CbAgo), which exhibits nucleic acid endonuclease activity, to achieve a programmable, amplification-free system (PASS) for rapid nucleic acid quantification at ambient temperatures in one pot. By using CbAgo-mediated binding with specific guide DNA (gDNA) and subsequent targeted cleavage of wild-type target DNAs complementary to gDNA, PASS can detect multiple foodborne pathogen DNA (<102 CFU/mL) simultaneously. The fluorescence signals were then transferred to polydisperse emulsions and analyzed by using deep learning. This simplifies the process and increases the suitability of polydisperse emulsions compared to traditional digital PCR, which requires homogeneous droplets for accurate detection. We believe that PASS has the potential to become a next-generation point-of-care digital nucleic acid detection method.
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Affiliation(s)
- Zhipan Wang
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Niu Feng
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yanan Zhou
- State Key Laboratory of Agricultural Microbiology and College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Xinrui Cheng
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Cuiyun Zhou
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Aimin Ma
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Qinyu Wang
- Department of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430000, Hubei China
| | - Yingjun Li
- State Key Laboratory of Agricultural Microbiology and College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yiping Chen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
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Guo YH, Chen YP, Dou QH, Liu Q, Yang JH, Seng MH, Lyu YY, Wang CS, Lu MX, Xu J, Zhang YY, Zhao DY. [Seroepidemiological analysis of hepatitis B virus infection among adolescents aged 0-14 years in Henan Province and preliminary evaluation of the effectiveness of childhood hepatitis B vaccine immunization program]. Zhonghua Yu Fang Yi Xue Za Zhi 2024; 58:202-207. [PMID: 38387951 DOI: 10.3760/cma.j.cn112150-20231127-00378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Objective: To analyze the seroepidemiological characteristics of hepatitis B virus (HBV) infection among adolescents aged 0-14 years in Henan Province and to evaluate the effectiveness of the childhood hepatitis B vaccine (HepB) immunization program. Methods: From September 2021 to March 2022, a total of 4 883 adolescents aged 0-14 years were selected from 25 villages or communities of 18 provincial-level cities in Henan Province by using the multi-stage random cluster sampling method. Demographic data were collected through questionnaires. The 3 ml of blood samples were collected from individuals aged 0-4 years and 5 ml of blood samples were collected from individuals aged 5-14 years to test HBsAg, HBcAb and HBsAb. Data on vaccination were collected through Henan Provincial Immunization Information System and hepatitis B cases in Henan Province were collected through China Infectious Disease Reporting System. The effectiveness of the childhood HepB immunization program was analyzed. Results: The average age of 4 883 subjects was (7.32±2.81) years old. The positive rates of HBsAg and HBcAb were 0.1% (7/4 883) and 1.0% (50/4 883), and the population standardized rates were 0.3% and 1.7%. In 2002, the positive rate of HBsAg among adolescents aged 0-14 years in Henan Province was 3.39%. Compared with that in 2002, the number of chronic HBV infections among adolescents in Henan Province in 2022 decreased by about 0.7 million. In 2002, the vaccination rate of newborns who completed all three doses of vaccine was 6.26%. In 2003, the vaccination rate of the hepatitis B vaccine rose rapidly, reaching 90% in 2013 for the first time. After 2014, the vaccination rate in Henan Province continued to remain above 95%. The proportion of cases among children aged 1-4 years in clinical reports decreased from 0.43% (1 108/256 566) in 2006 to 0.01% (78/80 655) in 2021. The proportion of cases among adolescents aged 5-19 years decreased from 18.21% (46 710/256 566) in 2006 to 1.1% (827/80 655) in 2021. Conclusions: From 2002 to 2022, the positive rate of HBsAg among adolescents aged 0-14 years has decreased significantly in Henan Province. The effectiveness of the HepB immunization program for children is good.
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Affiliation(s)
- Y H Guo
- Henan Immunoprophylaxis Key Laboratory of Medical Science, Zhengzhou 450016, China
| | - Y P Chen
- Office of Teaching and Graduate Management, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Q H Dou
- Henan Immunoprophylaxis Key Laboratory of Medical Science, Zhengzhou 450016, China
| | - Q Liu
- Henan Immunoprophylaxis Key Laboratory of Medical Science, Zhengzhou 450016, China
| | - J H Yang
- Henan Immunoprophylaxis Key Laboratory of Medical Science, Zhengzhou 450016, China
| | - M H Seng
- Henan Immunoprophylaxis Key Laboratory of Medical Science, Zhengzhou 450016, China
| | - Y Y Lyu
- Henan Immunoprophylaxis Key Laboratory of Medical Science, Zhengzhou 450016, China
| | - C S Wang
- Immunization Program, Henan Provincial Center for Disease Control and Prevention, Zhengzhou 450016, China
| | - M X Lu
- Immunization Program, Henan Provincial Center for Disease Control and Prevention, Zhengzhou 450016, China
| | - J Xu
- Henan Immunoprophylaxis Key Laboratory of Medical Science, Zhengzhou 450016, China
| | - Y Y Zhang
- Henan Immunoprophylaxis Key Laboratory of Medical Science, Zhengzhou 450016, China
| | - D Y Zhao
- Henan Immunoprophylaxis Key Laboratory of Medical Science, Zhengzhou 450016, China
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Zhao W, Zhang M, Zhang L, Deng X, Wang Y, Chen Y, Weng S. Carbon Dots with Antioxidant Capacity for Detecting Glucose by Fluorescence and Repairing High-Glucose Damaged Glial Cells. J Fluoresc 2024:10.1007/s10895-024-03599-8. [PMID: 38300482 DOI: 10.1007/s10895-024-03599-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 01/23/2024] [Indexed: 02/02/2024]
Abstract
Diabetic mellitus management extends beyond blood glucose monitoring to the essential task of mitigating the overexpression of reactive oxygen species (ROS), particularly vital for cellular repair, especially within the nervous system. Herein, antioxidant carbon dots (Arg-CDs) were designed and prepared using anhydrous citric acid, L-arginine, and ethylenediamine as sources through a hydrothermal method. Arg-CDs exhibited excellent scavenging ability to 2,2-Diphenyl-1-picrylhydrazyl (DPPH∙), and fluorescence response to hydroxyl radicals (∙OH), a characteristic representative of reactive oxygen species (ROS). Assisted by glucose oxidase and Fe2+, Arg-CDs showed a sensitive and selective response to glucose. The quenching mechanism of Arg-CDs by formed ∙OH was based on the static quenching effect (SQE). The analytical performance of this method for glucose detection encompassed a wide linear range (0.3-15 μM), a low practical limit of detection (0.1 μM) and practical applicability for blood glucose monitoring. In an in vitro model employing glial cells (BV2 cells), it was observed that high glucose medium led to notable cellular damage ascribed to the excessive ROS production from hyperglycemia. The diminished and apoptotic glial cells were gradually recovered by adding increased contents of Arg-CDs. This work illustrates a promising area that designs effective carbon dots with antioxidant capacity for the dual applications of detection and cell repairing based on the utilization of antioxidant activity.
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Affiliation(s)
- Wenlong Zhao
- Department of Neurology, Institute of Neurology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China
| | - Menghan Zhang
- Department of Pharmaceutical Analysis, School of Pharmacy, Fujian Medical University, Fuzhou, 350122, China
| | - Liang Zhang
- Department of Pharmaceutical Analysis, School of Pharmacy, Fujian Medical University, Fuzhou, 350122, China
- Department of Pharmacy, Fujian Provincial Geriatric Hospital, Teaching Hospital of Fujian Medical University, Fuzhou, 350003, China
| | - Xiaoqin Deng
- Department of Pharmaceutical Analysis, School of Pharmacy, Fujian Medical University, Fuzhou, 350122, China
| | - Yao Wang
- Department of Pharmaceutical Analysis, School of Pharmacy, Fujian Medical University, Fuzhou, 350122, China
| | - Yiping Chen
- Department of Interventional Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China.
| | - Shaohuang Weng
- Department of Pharmaceutical Analysis, School of Pharmacy, Fujian Medical University, Fuzhou, 350122, China.
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Pang Y, Lv J, Wu T, Yu C, Guo Y, Chen Y, Yang L, Millwood IY, Walters RG, Yang X, Stevens R, Clarke R, Chen J, Li L, Chen Z, Kartsonaki C. Associations of diabetes, circulating protein biomarkers, and risk of pancreatic cancer. Br J Cancer 2024; 130:504-510. [PMID: 38129526 PMCID: PMC10844301 DOI: 10.1038/s41416-023-02533-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 11/21/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Type 2 diabetes (T2D) is associated with higher risk of pancreatic cancer (PC), but the underlying mechanisms are not fully understood. METHODS We conducted a case-subcohort study involving 610 PC cases and 623 subcohort participants with 92 protein biomarkers measured in baseline plasma samples. Genetically-instrumented T2D was derived using 86 single-nucleotide polymorphisms (SNPs), including insulin resistance (IR) SNPs. RESULTS In observational analyses of 623 subcohort participants (mean age, 52 years; 61% women), T2D was positively associated with 13 proteins (SD difference: IL6: 0.52 [0.23-0.81]; IL10: 0.41 [0.12-0.70]), of which 8 were nominally associated with incident PC. The 8 proteins potentially mediated 36.9% (18.7-75.0%) of the association between T2D and PC. In MR, no associations were observed for genetically-determined T2D with proteins, but there were positive associations of genetically-determined IR with IL6 and IL10 (SD difference: 1.23 [0.05-2.41] and 1.28 [0.31-2.24]). In two-sample MR, fasting insulin was associated with both IL6 and PC, but no association was observed between IL6 and PC. CONCLUSIONS Proteomics were likely to explain the association between T2D and PC, but were not causal mediators. Elevated fasting insulin driven by insulin resistance might explain the associations of T2D, proteomics, and PC.
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Affiliation(s)
- Yuanjie Pang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, 100191, Beijing, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, 100191, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Ting Wu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, 100191, Beijing, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, 100191, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Yu Guo
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Beijing, China
- Fuwai Hospital, Chinese Academy of Medical Sciences, 167 Beilishi Road, Xicheng District, 100037, Beijing, China
| | - Yiping Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xiaoming Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK
| | - Rebecca Stevens
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK
| | - Robert Clarke
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK
| | - Junshi Chen
- National Center for Food Safety Risk Assessment, 37 Guangqu Road, 100021, Beijing, China
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, 100191, Beijing, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China.
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Christiana Kartsonaki
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK
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Chen Y, Li W, Zhang X, Cheng H, Tian Y, Yang H. Association between social capital and quality of life in older adults with subjective cognitive decline: A cross-sectional study. Appl Nurs Res 2024; 75:151773. [PMID: 38490797 DOI: 10.1016/j.apnr.2024.151773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 08/02/2023] [Accepted: 02/18/2024] [Indexed: 03/17/2024]
Abstract
BACKGROUND Subjective cognitive decline (SCD) is increasingly recognized as a clinical and medical risk factor for mild cognitive impairment (MCI) and dementia. Currently, there is little evidence regarding the quality of life (QoL) in older adults with SCD and the impact of social capital on their QoL. AIMS To examine the perceptions of social capital and QoL among older adults with SCD. METHODS A total of 325 participants (92.9 % response rate) with a self-reported diagnosis of SCD completed the Chinese version of the 36-item Short-Form Health Survey, the Chinese Shortened Social Capital Scale and the Generalized Anxiety Disorder Scale. A t-test was used to compare the QoL score of our sample with the Chinese norm. Pearson correlation analysis and multivariate linear regression analysis were used to assess the association of social capital with QoL. RESULTS Social capital were strongly correlated with the total QoL, as well as its physical component summary and mental component summary. The QoL score of older adults with SCD was significantly lower than the Chinese norm (P < 0.001). Multivariate analysis showed that social capital, physical activity, nutrition and anxiety symptoms were factors associated with QoL among older SCD population (P < 0.05). CONCLUSION The findings of the current study suggest that older adults with SCD may experience lower QoL. Social capital is associated with the QoL in older adults with SCD. These findings have implications for clinicians who work with older adults with SCD.
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Affiliation(s)
- Yiping Chen
- Shanxi Medical University, Shanxi Province, China
| | - Wei Li
- Peking Union Medical College Hospital, Beijing, China
| | - Xin Zhang
- Tsinghua University, Shenzhen City, Guangdong Province, China
| | - Hui Cheng
- Shanxi Medical University, Shanxi Province, China
| | - Yuling Tian
- First Hospital of Shanxi Medical University, China
| | - Hui Yang
- First Hospital of Shanxi Medical University, China.
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Chen Y, Li Y, Li W, Tian Y, Yang H. Physical activity trajectories and their associations with health outcomes in older adults with mild cognitive impairment or dementia: a national cohort study. Aging Clin Exp Res 2024; 36:15. [PMID: 38291179 PMCID: PMC10827827 DOI: 10.1007/s40520-023-02667-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 11/17/2023] [Indexed: 02/01/2024]
Abstract
BACKGROUND Physical activity (PA) is a promising non-pharmacological intervention for this population. However, few studies have investigated their PA trajectories, influencing factors, and their relationship with health outcomes. AIMS The aim was to identify latent trajectories in PA and their determinants in older adults with mild cognitive impairment (MCI) or dementia, as well as to assess the associations between PA trajectories and health outcomes based on the capability-opportunity-motivation behavior model. METHODS This is a cohort study. Data were obtained from a national cohort study and included participants aged 60 years and older with MCI or dementia. PA trajectories were identified using group-based trajectory modelling. Multinomial logistic regression was conducted to identify the predictors of PA trajectories. Linear regression models were used to assess the associations between PA trajectories and health outcomes. This study adhered to the STROBE checklist for reporting. RESULTS Three distinct PA trajectories were identified: high-decreasing and rebound class (9.34%), moderate-decreasing class (10.31%), and low-increasing class (80.34%). The logistic regression showed that age, sex, education level, body mass index, residence, depressive symptoms, mobility activities of daily life score, frequency of social activities score were PA predictors. Adjusting for sociodemographic variables, only the high-decreasing and rebound class remained significantly associated with worse self-rated health. DISCUSSION This study revealed three PA trajectories among older adults with MCI/dementia. Besides sociodemographic variables, addressing physical function and mental health, providing social support are vital for promoting PA in this population.
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Affiliation(s)
- Yiping Chen
- Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Yao Li
- Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Wei Li
- Peking Union Medical College Hospital, Beijing, China
| | - Yuling Tian
- First Hospital of Shanxi Medical University, No.56, Xinjian South Road, Yingze District, Taiyuan, Shanxi Province, China.
| | - Hui Yang
- First Hospital of Shanxi Medical University, No.56, Xinjian South Road, Yingze District, Taiyuan, Shanxi Province, China.
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Wang X, Chen L, Shi K, Lv J, Sun D, Pei P, Yang L, Chen Y, Du H, Liu J, Yang X, Barnard M, Chen J, Chen Z, Li L, Yu C. Diabetes and chronic kidney disease in Chinese adults: a population-based cohort study. BMJ Open Diabetes Res Care 2024; 12:e003721. [PMID: 38267203 PMCID: PMC10823934 DOI: 10.1136/bmjdrc-2023-003721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 12/05/2023] [Indexed: 01/26/2024] Open
Abstract
INTRODUCTION Cohort evidence of the association of diabetes mellitus (DM) with chronic kidney disease (CKD) is limited. Previous studies often describe patients with kidney disease and diabetes as diabetic kidney disease (DKD) or CKD, ignoring other subtypes. The present study aimed to assess the prospective association of diabetes status (no diabetes, pre-diabetes, screened diabetes, previously diagnosed controlled/uncontrolled diabetes with/without antidiabetic treatment) and random plasma glucose (RPG) with CKD risk (including CKD subtypes) among Chinese adults. RESEARCH DESIGN AND METHODS The present study included 472 545 participants from the China Kadoorie Biobank, using baseline information on diabetes and RPG. The incident CKD and its subtypes were collected through linkage with the national health insurance system during follow-up. Cox regression models were used to calculate the HR and 95% CI. RESULTS During 11.8 years of mean follow-up, 5417 adults developed CKD. Screened plus previously diagnosed diabetes was positively associated with CKD (HR=4.52, 95% CI 4.23 to 4.83), DKD (HR=33.85, 95% CI 29.56 to 38.76), and glomerulonephritis (HR=1.66, 95% CI 1.40 to 1.97). In those with previously diagnosed diabetes, participants with uncontrolled diabetes represented higher risks of CKD, DKD, and glomerulonephritis compared with those with controlled RPG. The risk of DKD was found to rise in participants with pre-diabetes and increased with the elevated RPG level, even in those without diabetes. CONCLUSIONS Among Chinese adults, diabetes was positively associated with CKD, DKD, and glomerulonephritis. Screen-detected and uncontrolled DM had a high risk of CKD, and pre-diabetes was associated with a greater risk of DKD, highlighting the significance of lifelong glycemic management.
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Affiliation(s)
- Xue Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Lu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Kexiang Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jiaqiu Liu
- NCDs Prevention and Control Department, Pengzhou CDC, Pengzhou, China
| | - Xiaoming Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Maxim Barnard
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
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Han K, Chen Y, Li M, Cui L. Using a Mixed-Method Approach to Explore the Factors Influencing the Family Resilience of Stroke Survivors in China. J Multidiscip Healthc 2024; 17:275-287. [PMID: 38264410 PMCID: PMC10804964 DOI: 10.2147/jmdh.s439737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 01/09/2024] [Indexed: 01/25/2024] Open
Abstract
Background Stroke is a critical public health issue in China that necessitates a closer examination of family resilience (defined here as the collective capacity of individuals, families and communities to effectively navigate challenges, recover from adverse events and foster positive adaptation). Amid rising stroke incidence, this study addresses the dearth of research on family resilience among stroke survivors in China, aiming to assess its level, identify influencing factors and establish coping strategies for family caregivers. Methods This mixed-methods research employed a sequential explanatory design. Questionnaires were distributed to 258 stroke survivors and their family members at outpatient follow-up visits. In the first stage (ie the quantitative research stage), the research tools for data collection included a general demographic sociological data questionnaire, the Family Resilience Assessment Scale (FRAS), the Self-Efficacy for Managing Chronic Disease 6-Item Scale, the Caregiver Burden Scale, the Family Functioning Scale and the Social Support Rating Scale. Quantitative data were analysed using IBM SPSS 26.0 software, utilising descriptive statistics for summarising sociodemographic characteristics and conducting analyses, such as independent-sample t-tests, one-way analysis of variance and Spearman correlation analysis. The second stage (ie the qualitative research stage) involved complementing and validating the data, developing a quantitative-qualitative interview framework and selecting participants for interviews. Colaizzi's seven-step analysis was applied to analyse interview data. In the third stage, the quantitative and qualitative research results were integrated, and a comprehensive analysis was performed to obtain an accurate conclusion. Results A total of 242 families responded to the questionnaire (response rate: 93.8%). In total, the mean age of stroke survivors was 61.86 ± 8.76 years old, and 69.8% were male. The quantitative results showed that the FRAS mean score was (185.33 ± 24.78), which was above the medium level. The multiple linear regression analysis confirmed that family function was the strongest influencing factor on family resilience (β = 0.948, p < 0.01). The qualitative analysis revealed four themes of family adaptation experience: loss of independence and certainty, facing threats and challenges, seeking family advantage resources and adopting coping strategies. Conclusion This hybrid study sheds light on the adaptation process of the families of stroke survivors, revealing family function as the primary influencer of resilience. Recognising that eliminating risk factors is challenging, our suggestion is for clinical practitioners to emphasise family strengths and implement resilience-oriented interventions. Focusing on enhancing coping abilities and fostering adaptation within families can aid in the rehabilitation process, promoting the well-being and growth of both the family unit and individual members, while alleviating caregiver burden.
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Affiliation(s)
- Kunjing Han
- Department of Nursing, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, People’s Republic of China
| | - Yiping Chen
- School of Nursing, Shanxi Medical University, Jinzhong, Shanxi Province, People’s Republic of China
| | - Min Li
- School of Nursing, Shanxi Medical University, Jinzhong, Shanxi Province, People’s Republic of China
| | - Liping Cui
- Department of Nursing, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, People’s Republic of China
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Holmes MV, Kartsonaki C, Boxall R, Lin K, Reeve N, Yu C, Lv J, Bennett DA, Hill MR, Yang L, Chen Y, Du H, Turnbull I, Collins R, Clarke RJ, Tobin MD, Li L, Millwood IY, Chen Z, Walters RG. PCSK9 genetic variants and risk of vascular and non-vascular diseases in Chinese and UK populations. Eur J Prev Cardiol 2024:zwae009. [PMID: 38198221 DOI: 10.1093/eurjpc/zwae009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 12/15/2023] [Accepted: 01/08/2024] [Indexed: 01/12/2024]
Abstract
AIM Lowering low-density lipoprotein cholesterol (LDL-C) through PCSK9 inhibition represents a new therapeutic approach to preventing and treating cardiovascular disease (CVD). Phenome-wide analyses of PCSK9 genetic variants in large biobanks can help to identify unexpected effects of PCSK9 inhibition. METHODS In the prospective China Kadoorie Biobank, we constructed a genetic score using three variants at the PCSK9 locus associated with directly-measured LDL-C (PCSK9-GS). Logistic regression gave estimated odds ratios (ORs) for PCSK9-GS associations with CVD and non-CVD outcomes, scaled to 1SD lower LDL-C. RESULTS PCSK9-GS was associated with lower risks of carotid plaque (n=8340 cases; OR=0.61 [95%CI: 0.45-0.83]; P=0.0015), major occlusive vascular events (n=15,752; 0.80 [0.67-0.95]; P=0.011), and ischaemic stroke (n=11,467; 0.80 [0.66-0.98]; P=0.029). However, PCSK9-GS was also associated with higher risk of hospitalisation with chronic obstructive pulmonary disease (COPD: n=6836; 1.38 [1.08-1.76]; P=0.0089), and with even higher risk of fatal exacerbations among individuals with pre-existing COPD (n=730; 3.61 [1.71-7.60]; P=7.3x10-4). We also replicated associations for a PCSK9 variant, reported in UK Biobank, with increased risks of acute upper respiratory tract infection (URTI) (pooled OR after meta-analysis of 1.87 ([1.38-2.54]; P=5.4x10-5) and self-reported asthma (pooled OR 1.17 ([1.04-1.30]; P=0.0071). There was no association of a polygenic LDL-C score with COPD hospitalisation, COPD exacerbation, or URTI. CONCLUSIONS LDL-C-lowering PCSK9 genetic variants are associated with lower risk of subclinical and clinical atherosclerotic vascular disease, but higher risks of respiratory diseases. Pharmacovigilance studies may be required to monitor patients treated with therapeutic PCSK9 inhibitors for exacerbations of respiratory diseases or respiratory tract infections.
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Affiliation(s)
- Michael V Holmes
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Christiana Kartsonaki
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ruth Boxall
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kuang Lin
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Nicola Reeve
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Derrick A Bennett
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Michael R Hill
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iain Turnbull
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robert J Clarke
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Martin D Tobin
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health and Care Research, Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
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Chen Y, Li W, Yang H. Determinants of physical activity behavior among older adults with subjective cognitive decline based on the capability, opportunity, motivation, and behavior model: mediating and moderating effects. Front Public Health 2024; 11:1338665. [PMID: 38264244 PMCID: PMC10805022 DOI: 10.3389/fpubh.2023.1338665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 12/19/2023] [Indexed: 01/25/2024] Open
Abstract
Background PA is vital for secondary prevention in older adults with subjective cognitive decline (SCD), but their physical activity (PA) levels are low, and the underlying interaction pathways among associated factors are poorly understood. This study aims to identify mediating and moderating effects of determinants on PA behavior in older adults with SCD using the capability, opportunity, motivation, and behavior model. Methods Following the STROBE checklist, we conducted a cross-sectional survey among 289 older adults with SCD. Path regression, mediation effects, and moderation effects were used to explore the associated factors of PA behavior and the associations among these variables. Results The prevalence of physical inactivity among older adults with SCD was high (40.3%). The path model fit indices were χ2/df = 1.145, GFI = 0.968, CFI = 0.988, and RMSEA = 0.022. Path regression revealed that frailty, physical and social support, PA motivation, and fall history had significant direct association with PA behavior. PA motivation not only partially mediates between frailty and PA behavior but also partially mediates between physical and social support and PA behavior. Additionally, fall history moderated the relationship between frailty and PA behavior. Conclusion PA behavior in older adults with SCD requires improvement. Healthcare professionals should devise more effective interventions to boost PA behavior by enhancing motivation. Screening for frailty and addressing fall history, while providing sufficient physical and social support, is crucial.
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Affiliation(s)
- Yiping Chen
- School of Nursing, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Wei Li
- International Medical Department, Peking Union Medical College Hospital (CAMS), Beijing, China
| | - Hui Yang
- School of Nursing, Shanxi Medical University, Taiyuan, Shanxi, China
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Yao DY, Chen YP, Ding F, Hu XS, Liang ZZ, Xing B, Cao YF, Zhang TQ, Wang XL, Liao YT, Yang J, Lyu HK. [Immunogenicity, safety and immune persistence of the sequential booster with the recombinant protein-based COVID-19 vaccine (CHO cell) in healthy people aged 18-84 years]. Zhonghua Yu Fang Yi Xue Za Zhi 2024; 58:25-32. [PMID: 38228546 DOI: 10.3760/cma.j.cn112150-20230423-00317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
Objective: To evaluate the immunogenicity, safety, and immune persistence of the sequential booster with the recombinant protein-based COVID-19 vaccine (CHO cell) in healthy people aged 18-84 years. Methods: An open-label, multi-center trial was conducted in October 2021. The eligible healthy individuals, aged 18-84 years who had completed primary immunization with the inactivated COVID-19 vaccine 3 to 9 months before, were recruited from Shangyu district of Shaoxing and Kaihua county of Quzhou, Zhejiang province. All participants were divided into three groups based on the differences in prime-boost intervals: Group A (3-4 months), Group B (5-6 months) and Group C (7-9 months), with 320 persons per group. All participants received the recombinant COVID-19 vaccine (CHO cell). Blood samples were collected before the vaccination and after receiving the booster at 14 days, 30 days, and 180 days for analysis of GMTs, antibody positivity rates, and seroconversion rates. All adverse events were collected within one month and serious adverse events were collected within six months. The incidences of adverse reactions were analyzed after the booster. Results: The age of 960 participants was (52.3±11.5) years old, and 47.4% were males (455). The GMTs of Groups B and C were 65.26 (54.51-78.12) and 60.97 (50.61-73.45) at 14 days after the booster, both higher than Group A's 44.79 (36.94-54.30) (P value<0.05). The GMTs of Groups B and C were 23.95 (20.18-28.42) and 27.98 (23.45-33.39) at 30 days after the booster, both higher than Group A's 15.71 (13.24-18.63) (P value <0.05). At 14 days after the booster, the antibody positivity rates in Groups A, B, and C were 91.69% (276/301), 94.38% (302/320), and 93.95% (295/314), respectively. The seroconversion rates in the three groups were 90.37% (272/301), 93.75% (300/320), and 93.31% (293/314), respectively. There was no significant difference among these rates in the three groups (all P values >0.05). At 30 days after the booster, antibody positivity rates in Groups A, B, and C were 79.60% (238/299), 87.74% (279/318), and 90.48% (285/315), respectively. The seroconversion rates in the three groups were 76.92% (230/299), 85.85% (273/318), and 88.25% (278/315), respectively. There was a significant difference among these rates in the three groups (all P values <0.001). During the sequential booster immunization, the incidence of adverse events in 960 participants was 15.31% (147/960), with rates of about 14.38% (46/320), 17.50% (56/320), and 14.06% (45/320) in Groups A, B, and C, respectively. The incidence of adverse reactions was 8.02% (77/960), with rates of about 7.50% (24/320), 6.88% (22/320), and 9.69% (31/320) in Groups A, B, and C, respectively. No serious adverse events related to the booster were reported. Conclusion: Healthy individuals aged 18-84 years, who had completed primary immunization with the inactivated COVID-19 vaccine 3 to 9 months before, have good immunogenicity and safety profiles following the sequential booster with the recombinant COVID-19 vaccine (CHO cell).
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Affiliation(s)
- D Y Yao
- School of Public Health, Hangzhou Normal University, Hangzhou 311121, China
| | - Y P Chen
- Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - F Ding
- Anhui Zhifei Longcom Biopharmaceutical Company, Hefei 230088, China
| | - X S Hu
- Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Z Z Liang
- Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - B Xing
- Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Y F Cao
- School of Public Health, Hangzhou Normal University, Hangzhou 311121, China
| | - T Q Zhang
- Anhui Zhifei Longcom Biopharmaceutical Company, Hefei 230088, China
| | - X L Wang
- Anhui Zhifei Longcom Biopharmaceutical Company, Hefei 230088, China
| | - Y T Liao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics/National Institute of Diagnostics and Vaccine Development in Infectious Diseases/School of Public Health, Xiamen University, Xiamen 361104, China
| | - J Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics/National Institute of Diagnostics and Vaccine Development in Infectious Diseases/School of Public Health, Xiamen University, Xiamen 361104, China
| | - H K Lyu
- Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
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Tong T, Hao C, Shen J, Liu S, Yan S, Aslam MS, Chen Y, Chen W, Li J, Li Y, Zeng J, Li M, You Z, Gulizhaerkezi T, Wei S, Zhu A, Meng X. Electroacupuncture ameliorates chronic unpredictable mild stress-induced depression-like behavior and cognitive impairment through suppressing oxidative stress and neuroinflammation in rats. Brain Res Bull 2024; 206:110838. [PMID: 38123022 DOI: 10.1016/j.brainresbull.2023.110838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 11/01/2023] [Accepted: 12/05/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Depression is associated with lowered mood, anxiety, anhedonia, cognitive impairments, and even suicidal tendencies in severe cases. Yet few studies have directed acupuncture's mechanism toward enhancing axonal repair correlated with synaptic plasticity and anti-inflammatory effects related to oxidative stress in the hippocampus. METHODS Male Sprague-Dawley (SD) rats were randomly divided into control group (CON), chronic unpredictable mild stress (CUMS) group, CUMS + electroacupuncture group (EA), and CUMS + fluoxetine group (FLX) (n = 10/group). Rats were given a 28-day treatment at the Shangxing (GV23) and Fengfu (GV16) acupoints with electroacupuncture or fluoxetine (2.1 mg/kg). RESULTS Rats exposed to CUMS induced depression-like behaviors and spatial learning-memory impairment, changed the ionized calcium binding adaptor molecule 1 (IBA-1), Vglut1, myelin basic protein (MBP), and postsynaptic density protein 95 (PSD95) level of hippocampal, increased the Nod-like receptor protein 3 (NLRP3), atypical squamous cell (ASC), Caspase level and hippocampal reactive oxygen species (ROS), and prompted the activation of Epha4-mediated signaling and an inflammatory response. Conversely, electroacupuncture administration reduced these changes and prevented depression-like behaviors and cognitive impairment. Electroacupuncture also promoted hippocampal expression of Sirtuin1(SIRT1), Nuclear factor erythroid 2-like (Nrf2), Heme oxygenase-1 (HO-1); reduced the expression of interleukin-1β (IL-1β), interleukin-18 (IL-18), and tumor necrosis factor-alpha (TNF-α); and prevented neural damage, particularly the synaptic myelin sheath, and neuroinflammation by regulating Eph receptor A4 (EphA4) in the hippocampal. CONCLUSION These results indicate that electroacupuncture prevents depression-like behaviors with cognitive impairment and synaptic and neuronal damage, probably by reducing EphA4, which mediates ROS hyperfunction and the inflammatory response.
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Affiliation(s)
- Tao Tong
- Department of Traditional Chinese Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Second Clinical College, Shanxi University of Traditional Chinese Medicine, Taiyuan, Shanxi, PR China.
| | - Chongyao Hao
- Second Clinical College, Shanxi University of Traditional Chinese Medicine, Taiyuan, Shanxi, PR China.
| | - Junliang Shen
- Department of Traditional Chinese Medicine, School of Medicine, Xiamen University, Xiamen, Fujian, PR China.
| | - Siyu Liu
- Longyan Hospital of Traditional Chinese Medicine of Xiamen University, Longyan, Fujian, PR China.
| | - Simin Yan
- Department of Traditional Chinese Medicine, School of Medicine, Xiamen University, Xiamen, Fujian, PR China.
| | | | - Yiping Chen
- Second Clinical College, Shanxi University of Traditional Chinese Medicine, Taiyuan, Shanxi, PR China.
| | - Wenjie Chen
- Department of Traditional Chinese Medicine, School of Medicine, Xiamen University, Xiamen, Fujian, PR China.
| | - Jianguo Li
- Second Clinical College, Shanxi University of Traditional Chinese Medicine, Taiyuan, Shanxi, PR China.
| | - Yuhan Li
- The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, PR China.
| | - Jingyu Zeng
- Department of Traditional Chinese Medicine, School of Medicine, Xiamen University, Xiamen, Fujian, PR China.
| | - Meng Li
- Second Clinical College, Shanxi University of Traditional Chinese Medicine, Taiyuan, Shanxi, PR China.
| | - Zhuoran You
- Second Clinical College, Shanxi University of Traditional Chinese Medicine, Taiyuan, Shanxi, PR China.
| | - Tuergong Gulizhaerkezi
- Department of Traditional Chinese Medicine, School of Medicine, Xiamen University, Xiamen, Fujian, PR China.
| | - Simiao Wei
- Department of Traditional Chinese Medicine, School of Medicine, Xiamen University, Xiamen, Fujian, PR China.
| | - Anning Zhu
- Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
| | - Xianjun Meng
- Department of Traditional Chinese Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Department of Traditional Chinese Medicine, School of Medicine, Xiamen University, Xiamen, Fujian, PR China.
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Xiao M, Li A, Wang Y, Yu C, Pang Y, Pei P, Yang L, Chen Y, Du H, Schmidt D, Avery D, Sun Q, Chen J, Chen Z, Li L, Lv J, Sun D. A wide landscape of morbidity and mortality risk associated with marital status in 0.5 million Chinese men and women: a prospective cohort study. Lancet Reg Health West Pac 2024; 42:100948. [PMID: 38357394 PMCID: PMC10865043 DOI: 10.1016/j.lanwpc.2023.100948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 09/26/2023] [Accepted: 10/16/2023] [Indexed: 02/16/2024]
Abstract
Background A comprehensive depiction of long-term health impacts of marital status is lacking. Methods Sex-stratified phenome-wide association analyses (PheWAS) of marital status (living with vs. without a spouse) were performed using baseline (2004-2008) and follow-up information (ICD10-coded events till Dec 31, 2017) from the China Kadoorie Biobank (CKB). We estimated adjusted hazard ratios (aHRs) to evaluate the associations of marital status with morbidity risks of phenome-wide significant diseases or sex-specific top-10 death causes in China documented in 2017. Additionally, the association between marital status and mortality risks among participants with major chronic diseases at baseline was assessed. Findings During up to 11.1 years of the median follow-up period, 1,946,380 incident health events were recorded among 210,202 men and 302,521 women aged 30-79. Marital status was found to have phenome-wide significant associations with thirteen diseases among men (p < 9.92 × 10-5) and nine diseases among women (p < 9.33 × 10-5), respectively. After adjusting for all disease-specific covariates in the final model, participants living without a spouse showed increased risks of schizophrenia, schizotypal and delusional disorders (aHR [95% CI]: 2.55, [1.83-3.56] for men; 1.49, [1.13-1.97] for women) compared with their counterparts. Additional higher risks in overall mental and behavioural disorder (1.31, 1.13-1.53), cardiovascular disease (1.07, 1.04-1.10) and cancer (1.06, 1.00-1.12) were only observed among men without a spouse, whereas women living without a spouse were at lower risks of developing genitourinary diseases (0.89, 0.85-0.93) and injury & poisoning (0.93, 0.88-0.97). Among 282,810 participants with major chronic diseases at baseline, 39,166 deaths were recorded. Increased mortality risks for those without a spouse were observed in 12 of 21 diseases among male patients and one of 23 among female patients. For patients with any self-reported disease at baseline, compared with those living with a spouse, the aHRs (95% CIs) of mortality risk were 1.29 (1.24-1.34) and 1.04 (1.00-1.07) among men and women without a spouse (pinteraction<0.0001), respectively. Interpretation Long-term associations of marital status with morbidity and mortality risks are diverse among middle-aged Chinese adults, and the adverse impacts due to living without a spouse are more profound among men. Marital status may be an influential factor for health needs. Funding The National Natural Science Foundation of China, the Kadoorie Charitable Foundation, the National Key R&D Program of China, the Chinese Ministry of Science and Technology, and the UK Wellcome Trust.
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Affiliation(s)
- Meng Xiao
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Aolin Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yueqing Wang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Yuanjie Pang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Dan Schmidt
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Qiang Sun
- NCDs Prevention and Control Department, Pengzhou CDC, Pengzhou, Sichuan, 611930, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, 100022, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
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Bennett DA, Parish S, Millwood IY, Guo Y, Chen Y, Turnbull I, Yang L, Lv J, Yu C, Davey Smith G, Wang Y, Wang Y, Peto R, Collins R, Walters RG, Li L, Chen Z, Clarke R. MTHFR and risk of stroke and heart disease in a low-folate population: a prospective study of 156 000 Chinese adults. Int J Epidemiol 2023; 52:1862-1869. [PMID: 37898918 PMCID: PMC10749746 DOI: 10.1093/ije/dyad147] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 10/12/2023] [Indexed: 10/31/2023] Open
Abstract
BACKGROUND The relevance of folic acid for stroke prevention in low-folate populations such as in China is uncertain. Genetic studies of the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism, which increases plasma homocysteine (tHcy) levels, could clarify the causal relevance of elevated tHcy levels for stroke, ischaemic heart disease (IHD) and other diseases in populations without folic acid fortification. METHODS In the prospective China Kadoorie Biobank, 156 253 participants were genotyped for MTHFR and 12 240 developed a stroke during the 12-year follow-up. Logistic regression was used to estimate region-specific odds ratios (ORs) for total stroke and stroke types, IHD and other diseases comparing TT genotype for MTHFR C677T (two thymine alleles at position 677 of MTHFR C677T polymorphism) vs CC (two cytosine alleles) after adjustment for age and sex, and these were combined using inverse-variance weighting. RESULTS Overall, 21% of participants had TT genotypes, but this varied from 5% to 41% across the 10 study regions. Individuals with TT genotypes had 13% (adjusted OR 1.13, 95% CI 1.09-1.17) higher risks of any stroke [with a 2-fold stronger association with intracerebral haemorrhage (1.24, 1.17-1.32) than for ischaemic stroke (1.11, 1.07-1.15)] than the reference CC genotype. In contrast, MTHFR C677T was unrelated to risk of IHD or any other non-vascular diseases, including cancer, diabetes and chronic obstructive lung disease. CONCLUSIONS In Chinese adults, the MTHFR C677T polymorphism was associated with higher risks of stroke. The findings warrant corroboration by further trials of folic acid and implementation of mandatory folic acid fortification programmes for stroke prevention in low-folate populations.
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Affiliation(s)
- Derrick A Bennett
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Sarah Parish
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing, China
| | - Yiping Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iain Turnbull
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | | | - Yongjun Wang
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yilong Wang
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Richard Peto
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robert Clarke
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
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Xu Y, Wang L, Qian R, Zhao M, Chen X, Sun D, Wang Y, Cheng W, Chen Y, He Q, Dai Y, Yao Y. Increased m6A-RNA methylation and demethylase FTO suppression is associated with silica-induced pulmonary inflammation and fibrosis. Toxicology 2023; 500:153673. [PMID: 37979906 DOI: 10.1016/j.tox.2023.153673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 11/06/2023] [Accepted: 11/14/2023] [Indexed: 11/20/2023]
Abstract
Silicosis is a severe worldwide occupational hazard, characterized with lung tissue inflammation and irreversible fibrosis caused by crystalline silicon dioxide. As the most common and abundant internal modification of messenger RNAs or noncoding RNAs, N6-methyladenosine (m6A) methylation is dysregulated in the chromic period of silicosis. However, whether m6A modification is involved in the early phase of silica-induced pulmonary inflammation and fibrosis and its specific effector cells remains unknown. In this study, we established a pulmonary inflammation and fibrosis mouse model by silica particles on day 7 and day 28. Then, we examined the global m6A modification level by m6A dot blot and m6A RNA methylation quantification kits. The key m6A regulatory factors were analyzed by RTqPCR, Western blot, and immunohistochemistry (IHC) in normal and silicosis mice. The results showed that the global m6A modification level was upregulated in silicosis lung tissues with the demethylase FTO suppression after silica exposure for 7 days and 28 days. METTL3, METTL14, ALKBH5, and other m6A readers had no obvious differences between the control and silicosis groups. Then, single-cell sequencing analysis revealed that thirteen kinds of cells were recognized in silicosis lung tissues, and the mRNA expression of FTO was downregulated in epithelial cells, endothelial cells, fibroblasts, and monocytes. These results were further confirmed in mouse lung epithelial cells (MLE-12) exposed to silica and in the peripheral blood mononuclear cells of silicosis patients. In conclusion, the high level of global m6A modification in the early stage of silicosis is induced by the downregulation of the demethylase FTO, which may provide a novel target for the diagnosis and treatment of silicosis.
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Affiliation(s)
- Yunyi Xu
- Molecular Toxicology Key Laboratory of Sichuan Provincial Education Office, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China; Department of Toxicology and Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Liqun Wang
- Department of Toxicology and Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Rui Qian
- Department of Toxicology and Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Manyu Zhao
- Department of Toxicology and Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xuxi Chen
- Department of Toxicology and Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Donglei Sun
- Molecular Toxicology Key Laboratory of Sichuan Provincial Education Office, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China; Department of Toxicology and Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Ye Wang
- Molecular Toxicology Key Laboratory of Sichuan Provincial Education Office, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China; Department of Toxicology and Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Weibo Cheng
- Molecular Toxicology Key Laboratory of Sichuan Provincial Education Office, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China; Department of Toxicology and Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yiping Chen
- Department of Clinical Lab, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Qiurong He
- Department of Clinical Lab, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yi Dai
- Department of Urology and Pelvic surgery and Andrology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Yuqin Yao
- Molecular Toxicology Key Laboratory of Sichuan Provincial Education Office, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China; Department of Toxicology and Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
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Millwood IY, Im PK, Bennett D, Hariri P, Yang L, Du H, Kartsonaki C, Lin K, Yu C, Chen Y, Sun D, Zhang N, Avery D, Schmidt D, Pei P, Chen J, Clarke R, Lv J, Peto R, Walters RG, Li L, Chen Z. Alcohol intake and cause-specific mortality: conventional and genetic evidence in a prospective cohort study of 512 000 adults in China. Lancet Public Health 2023; 8:e956-e967. [PMID: 38000378 PMCID: PMC7615754 DOI: 10.1016/s2468-2667(23)00217-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 09/10/2023] [Accepted: 09/12/2023] [Indexed: 11/26/2023]
Abstract
BACKGROUND Genetic variants that affect alcohol use in East Asian populations could help assess the causal effects of alcohol consumption on cause-specific mortality. We aimed to investigate the associations between alcohol intake and cause-specific mortality using conventional and genetic epidemiological methods among more than 512 000 adults in China. METHODS The prospective China Kadoorie Biobank cohort study enrolled 512 724 adults (210 205 men and 302 519 women) aged 30-79 years, during 2004-08. Residents with no major disabilities from ten diverse urban and rural areas of China were invited to participate, and alcohol use was self-reported. During 12 years of follow-up, 56 550 deaths were recorded through linkage to death registries, including 23 457 deaths among 168 050 participants genotyped for ALDH2-rs671 and ADH1B-rs1229984. Adjusted hazard ratios (HRs) for cause-specific mortality by self-reported and genotype-predicted alcohol intake were estimated using Cox regression. FINDINGS 33% of men drank alcohol most weeks. In conventional observational analyses, ex-drinkers, non-drinkers, and heavy drinkers had higher risks of death from most major causes than moderate drinkers. Among current drinkers, each 100 g/week higher alcohol intake was associated with higher mortality risks from cancers (HR 1·18 [95% CI 1·14-1·22]), cardiovascular disease (CVD; HR 1·19 [1·15-1·24]), liver diseases (HR 1·51 [1·27-1·78]), non-medical causes (HR 1·15 [1·08-1·23]), and all causes (HR 1·18 [1·15-1·20]). In men, ALDH2-rs671 and ADH1B-rs1229984 genotypes predicted 60-fold differences in mean alcohol intake (4 g/week in the lowest group vs 255 g/week in the highest). Genotype-predicted alcohol intake was uniformly and positively associated with risks of death from all causes (n=12 939; HR 1·07 [95% CI 1·05-1·10]) and from pre-defined alcohol-related cancers (n=1274; 1·12 [1·04-1·21]), liver diseases (n=110; 1·31 [1·02-1·69]), and CVD (n=6109; 1·15 [1·10-1·19]), chiefly due to stroke (n=3285; 1·18 [1·12-1·24]) rather than ischaemic heart disease (n=2363; 1·06 [0·99-1·14]). Results were largely consistent using a polygenic score to predict alcohol intake, with higher intakes associated with higher risks of death from alcohol-related cancers, CVD, and all causes. Approximately 2% of women were current drinkers, and although power was low to assess observational associations of alcohol with mortality, the genetic evidence suggested that the excess risks in men were due to alcohol, not pleiotropy. INTERPRETATION Higher alcohol intake increased the risks of death overall and from major diseases for men in China. There was no genetic evidence of protection from moderate drinking for all-cause and cause-specific mortality, including CVD. FUNDING Kadoorie Charitable Foundation, National Natural Science Foundation of China, British Heart Foundation, Cancer Research UK, GlaxoSmithKline, Wellcome Trust, Medical Research Council, and Chinese Ministry of Science and Technology.
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Affiliation(s)
- Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
| | - Pek Kei Im
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Derrick Bennett
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Parisa Hariri
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Christiana Kartsonaki
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Ningmei Zhang
- NCD Prevention and Control Department, Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Dan Schmidt
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Richard Peto
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
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Hamilton EM, Yang L, Wright N, Turnbull I, Mentzer AJ, Matthews PC, Chen Y, Du H, Kartsonaki C, Pang Y, Pei P, Tian H, Yang X, Avery D, Yu C, Lv J, Clarke R, Li L, Millwood IY, Chen Z. Chronic Hepatitis B Virus Infection and Risk of Stroke Types: A Prospective Cohort Study of 500 000 Chinese Adults. Stroke 2023; 54:3046-3053. [PMID: 37942646 PMCID: PMC10664797 DOI: 10.1161/strokeaha.123.043327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 10/12/2023] [Accepted: 10/17/2023] [Indexed: 11/10/2023]
Abstract
BACKGROUND Stroke is a leading cause of mortality and permanent disability in China, with large and unexplained geographic variations in rates of different stroke types. Chronic hepatitis B virus infection is prevalent among Chinese adults and may play a role in stroke cause. METHODS The prospective China Kadoorie Biobank included >500 000 adults aged 30 to 79 years who were recruited from 10 (5 urban and 5 rural) geographically diverse areas of China from 2004 to 2008, with determination of hepatitis B surface antigen (HBsAg) positivity at baseline. During 11 years of follow-up, a total of 59 117 incident stroke cases occurred, including 11 318 intracerebral hemorrhage (ICH), 49 971 ischemic stroke, 995 subarachnoid hemorrhage, and 3036 other/unspecified stroke. Cox regression models were used to estimate adjusted hazard ratios (HRs) for risk of stroke types associated with HBsAg positivity. In a subset of 17 833 participants, liver enzymes and lipids levels were measured and compared by HBsAg status. RESULTS Overall, 3.0% of participants were positive for HBsAg. HBsAg positivity was associated with an increased risk of ICH (adjusted HR, 1.29 [95% CI, 1.16-1.44]), similarly for fatal (n=5982; adjusted HR, 1.36 [95% CI, 1.16-1.59]) and nonfatal (n=5336; adjusted HR, 1.23 [95% CI, 1.06-1.44]) ICH. There were no significant associations of HBsAg positivity with risks of ischemic stroke (adjusted HR, 0.97 [95% CI, 0.92-1.03]), subarachnoid hemorrhage (adjusted HR, 0.87 [95% CI, 0.57-1.33]), or other/unspecified stroke (adjusted HR, 1.12 [95% CI, 0.89-1.42]). Compared with HBsAg-negative counterparts, HBsAg-positive individuals had lower lipid and albumin levels and higher liver enzyme levels. After adjustment for liver enzymes and albumin, the association with ICH from HBsAg positivity attenuated to 1.15 (0.90-1.48), suggesting possible mediation by abnormal liver function. CONCLUSIONS Among Chinese adults, chronic hepatitis B virus infection is associated with an increased risk of ICH but not other stroke types, which may be mediated through liver dysfunction and altered lipid metabolism.
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Affiliation(s)
- Elizabeth M. Hamilton
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
- Medical Research Council Population Health Research Unit (L.Y., C.K., I.Y.M., Z.C), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Neil Wright
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Iain Turnbull
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Alexander J. Mentzer
- Wellcome Centre for Human Genetics (A.J.M.), University of Oxford, United Kingdom
| | - Philippa C. Matthews
- Division of Infection and Immunity, University College London, United Kingdom (P.C.M.)
- Matthews lab HBV Elimination Laboratory, The Francis Crick Institute, London, United Kingdom (P.C.M.)
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (Y.P., P.P., C.Y., J.L., L.L.)
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Christiana Kartsonaki
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
- Medical Research Council Population Health Research Unit (L.Y., C.K., I.Y.M., Z.C), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China (Y.P., C.Y., J.L., L.L.)
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (Y.P., P.P., C.Y., J.L., L.L.)
| | - Huizi Tian
- Non-Communicable Diseases Prevention and Control Department, Henan, China (H.T.)
| | - Xiaoming Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China (Y.P., C.Y., J.L., L.L.)
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (Y.P., P.P., C.Y., J.L., L.L.)
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China (Y.P., C.Y., J.L., L.L.)
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (Y.P., P.P., C.Y., J.L., L.L.)
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China (Y.P., C.Y., J.L., L.L.)
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (Y.P., P.P., C.Y., J.L., L.L.)
| | - Iona Y. Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
- Medical Research Council Population Health Research Unit (L.Y., C.K., I.Y.M., Z.C), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (E.M.H., L.Y., N.W., I.T., Y.C., H.D., C.K., X.Y., D.A., R.C., I.Y.M., Z.C.), Nuffield Department of Population Health, University of Oxford, United Kingdom
- Medical Research Council Population Health Research Unit (L.Y., C.K., I.Y.M., Z.C), Nuffield Department of Population Health, University of Oxford, United Kingdom
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50
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Wang X, Wu Z, Lv J, Yu C, Sun D, Pei P, Yang L, Millwood IY, Walters R, Chen Y, Du H, Yuan M, Schmidt D, Barnard M, Chen J, Chen Z, Li L, Pang Y. Life-course adiposity and severe liver disease: a Mendelian randomization analysis. Obesity (Silver Spring) 2023; 31:3077-3085. [PMID: 37869961 DOI: 10.1002/oby.23913] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 07/21/2023] [Accepted: 08/04/2023] [Indexed: 10/24/2023]
Abstract
OBJECTIVE There is little evidence on the genetic associations between life-course adiposity (including birth weight, childhood BMI, and adulthood BMI) and severe liver disease (SLD; including cirrhosis and liver cancer). The current study aimed to examine and contrast these associations. METHODS Genetic variants were obtained from genome-wide association studies. Two-sample Mendelian randomization (MR) analyses were performed to assess the genetic associations of life-course adiposity with SLD and liver biomarkers. Cox regression was used to estimate adjusted hazard ratios for SLD associated with genetic risk scores of life-course adiposity and adulthood weight change in the China Kadoorie Biobank. RESULTS In observational analyses, genetic predispositions to childhood adiposity and adulthood adiposity were each associated with SLD. There was a U-shaped association between adulthood weight change and risk of SLD. In meta-analyses of MR results, genetically predicted 1-standard deviation increase in birth weight was inversely associated with SLD at a marginal significance (odds ratio: 0.81 [95% CI: 0.65-1.00]), whereas genetically predicted 1-standard deviation higher childhood BMI and adulthood BMI were positively associated with SLD (odds ratio: 1.27 [95% CI: 1.05-1.55] and 1.79 [95% CI: 1.59-2.01], respectively). The results of liver biomarkers mirrored those of SLD. CONCLUSIONS The current study provided genetic evidence on the associations between life-course adiposity and SLD.
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Affiliation(s)
- Xinyu Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zhiyu Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Mingqiang Yuan
- Pengzhou Center for Disease Control and Prevention, Pengzhou, China
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Maxim Barnard
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing, China
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