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Zhang W, Zhu J, Wu X, Feng T, Liao W, Li X, Chen J, Zhang L, Xiao C, Cui H, Yang C, Yan P, Wang Y, Tang M, Chen L, Liu Y, Zou Y, Wu X, Zhang L, Yang C, Yao Y, Li J, Liu Z, Jiang X, Zhang B. Phenotypic and genetic effect of carotid intima-media thickness on the risk of stroke. Hum Genet 2024:10.1007/s00439-024-02666-1. [PMID: 38578439 DOI: 10.1007/s00439-024-02666-1] [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: 10/16/2023] [Accepted: 03/05/2024] [Indexed: 04/06/2024]
Abstract
While carotid intima-media thickness (cIMT) as a noninvasive surrogate measure of atherosclerosis is widely considered a risk factor for stroke, the intrinsic link underlying cIMT and stroke has not been fully understood. We aimed to evaluate the clinical value of cIMT in stroke through the investigation of phenotypic and genetic relationships between cIMT and stroke. We evaluated phenotypic associations using observational data from UK Biobank (N = 21,526). We then investigated genetic relationships leveraging genomic data conducted in predominantly European ancestry for cIMT (N = 45,185) and any stroke (AS, Ncase/Ncontrol=40,585/406,111). Observational analyses suggested an increased hazard of stroke per one standard deviation increase in cIMT (cIMTmax-AS: hazard ratio (HR) = 1.39, 95%CI = 1.09-1.79; cIMTmean-AS: HR = 1.39, 95%CI = 1.09-1.78; cIMTmin-AS: HR = 1.32, 95%CI = 1.04-1.68). A positive global genetic correlation was observed (cIMTmax-AS: [Formula: see text]=0.23, P=9.44 × 10-5; cIMTmean-AS: [Formula: see text]=0.21, P=3.00 × 10-4; cIMTmin-AS: [Formula: see text]=0.16, P=6.30 × 10-3). This was further substantiated by five shared independent loci and 15 shared expression-trait associations. Mendelian randomization analyses suggested no causal effect of cIMT on stroke (cIMTmax-AS: odds ratio (OR)=1.12, 95%CI=0.97-1.28; cIMTmean-AS: OR=1.09, 95%CI=0.93-1.26; cIMTmin-AS: OR=1.03, 95%CI = 0.90-1.17). A putative association was observed for genetically predicted stroke on cIMT (AS-cIMTmax: beta=0.07, 95%CI = 0.01-0.13; AS-cIMTmean: beta=0.08, 95%CI = 0.01-0.15; AS-cIMTmin: beta = 0.08, 95%CI = 0.01-0.16) in the reverse direction MR, which attenuated to non-significant in sensitivity analysis. Our work does not find evidence supporting causal associations between cIMT and stroke. The pronounced cIMT-stroke association is intrinsic, and mostly attributed to shared genetic components. The clinical value of cIMT as a surrogate marker for stroke risk in the general population is likely limited.
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Affiliation(s)
- Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Jingwei Zhu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Xuan Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Tianle Feng
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Wei Liao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Xuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Jianci Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Ling Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, West China- PUMC C. C. Chen Institute of Health, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China.
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Department of Clinical Neuroscience, Karolinskaa Institutet, Stockholm, Sweden.
| | - Ben Zhang
- Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
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Tang M, Wu X, Zhang W, Cui H, Zhang L, Yan P, Yang C, Wang Y, Chen L, Xiao C, Liu Y, Zou Y, Yang C, Zhang L, Yao Y, Liu Z, Li J, Jiang X, Zhang B. Epidemiological and Genetic Analyses of Schizophrenia and Breast Cancer. Schizophr Bull 2024; 50:317-326. [PMID: 37467357 PMCID: PMC10919785 DOI: 10.1093/schbul/sbad106] [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] [Indexed: 07/21/2023]
Abstract
BACKGROUND AND HYPOTHESIS While the phenotypic association between schizophrenia and breast cancer has been observed, the underlying intrinsic link is not adequately understood. We aim to conduct a comprehensive interrogation on both phenotypic and genetic relationships between schizophrenia and breast cancer. STUDY DESIGN We first used data from UK Biobank to evaluate a phenotypic association and performed an updated meta-analysis incorporating existing cohort studies. We then leveraged genomic data to explore the shared genetic architecture through a genome-wide cross-trait design. STUDY RESULTS Incorporating results of our observational analysis, meta-analysis of cohort studies suggested a significantly increased incidence of breast cancer among women with schizophrenia (RR = 1.30, 95% CIs = 1.14-1.48). A positive genomic correlation between schizophrenia and overall breast cancer was observed (rg = 0.12, P = 1.80 × 10-10), consistent across ER+ (rg = 0.10, P = 5.74 × 10-7) and ER- subtypes (rg = 0.09, P = .003). This was further corroborated by four local signals. Cross-trait meta-analysis identified 23 pleiotropic loci between schizophrenia and breast cancer, including five novel loci. Gene-based analysis revealed 27 shared genes. Mendelian randomization demonstrated a significantly increased risk of overall breast cancer (OR = 1.07, P = 4.81 × 10-10) for genetically predisposed schizophrenia, which remained robust in subgroup analysis (ER+: OR = 1.10, P = 7.26 × 10-12; ER-: OR = 1.08, P = 3.50 × 10-6). No mediation effect and reverse causality was found. CONCLUSIONS Our study demonstrates an intrinsic link underlying schizophrenia and breast cancer, which may inform tailored screening and management of breast cancer in schizophrenia.
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Affiliation(s)
- Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, College of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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Zhang W, Zhang L, Xiao C, Wu X, Cui H, Yang C, Yan P, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Zhang L, Yang C, Yao Y, Li J, Liu Z, Jiang X, Zhang B. Bidirectional relationship between type 2 diabetes mellitus and coronary artery disease: Prospective cohort study and genetic analyses. Chin Med J (Engl) 2024; 137:577-587. [PMID: 38062574 DOI: 10.1097/cm9.0000000000002894] [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] [Received: 09/18/2023] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND While type 2 diabetes mellitus (T2DM) is considered a putative causal risk factor for coronary artery disease (CAD), the intrinsic link underlying T2DM and CAD is not fully understood. We aimed to highlight the importance of integrated care targeting both diseases by investigating the phenotypic and genetic relationships between T2DM and CAD. METHODS We evaluated phenotypic associations using data from the United Kingdom Biobank ( N = 472,050). We investigated genetic relationships by leveraging genomic data conducted in European ancestry for T2DM, with and without adjustment for body mass index (BMI) (T2DM: Ncase / Ncontrol = 74,124/824,006; T2DM adjusted for BMI [T2DM adj BMI]: Ncase / Ncontrol = 50,409/523,897) and for CAD ( Ncase / Ncontrol = 181,522/984,168). We performed additional analyses using genomic data conducted in multiancestry individuals for T2DM ( Ncase / Ncontrol = 180,834/1,159,055). RESULTS Observational analysis suggested a bidirectional relationship between T2DM and CAD (T2DM→CAD: hazard ratio [HR] = 2.12, 95% confidence interval [CI]: 2.01-2.24; CAD→T2DM: HR = 1.72, 95% CI: 1.63-1.81). A positive overall genetic correlation between T2DM and CAD was observed ( rg = 0.39, P = 1.43 × 10 -75 ), which was largely independent of BMI (T2DM adj BMI-CAD: rg = 0.31, P = 1.20 × 10 -36 ). This was corroborated by six local signals, among which 9p21.3 showed the strongest genetic correlation. Cross-trait meta-analysis replicated 101 previously reported loci and discovered six novel pleiotropic loci. Mendelian randomization analysis supported a bidirectional causal relationship (T2DM→CAD: odds ratio [OR] = 1.13, 95% CI: 1.11-1.16; CAD→T2DM: OR = 1.12, 95% CI: 1.07-1.18), which was confirmed in multiancestry individuals (T2DM→CAD: OR = 1.13, 95% CI: 1.10-1.16; CAD→T2DM: OR = 1.08, 95% CI: 1.04-1.13). This bidirectional relationship was significantly mediated by systolic blood pressure and intake of 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, with mediation proportions of 54.1% (95% CI: 24.9-83.4%) and 90.4% (95% CI: 29.3-151.5%), respectively. CONCLUSION Our observational and genetic analyses demonstrated an intrinsic bidirectional relationship between T2DM and CAD and clarified the biological mechanisms underlying this relationship.
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Affiliation(s)
- Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Ling Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm 17177, Sweden
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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Wang N, Gao YY, Qi BQ, Ruan M, Lyu H, Zhang XY, Zhang RR, Liu TF, Chen YM, Zou Y, Guo Y, Yang WY, Zhang L, Zhu XF, Chen XJ. [Clinical features and prognostic analysis of testicular relapse in pediatric acute lymphoblastic leukemia]. Zhonghua Er Ke Za Zhi 2024; 62:262-267. [PMID: 38378289 DOI: 10.3760/cma.j.cn112140-20230816-00110] [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 the clinical features and prognosis of testicular relapse in pediatric acute lymphoblastic leukemia (ALL). Methods: Clinical data including the age, time from initial diagnosis to recurrence, relapse site, and therapeutic effect of 37 pediatric ALL with testicular relapse and treated in Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences between November 2011 and December 2022 were analyzed retrospectively. Patients were grouped according to different clinical data. Kaplan-Meier analysis was used to evaluate the overall survival (OS) rate and event free survival (EFS) rate for univariate analysis, and Cox proportional-hazards regression model was used to evaluate the influencing factors of OS rate and EFS rate for multivariate analysis. Results: The age at initial diagnosis of 37 pediatric testicular relapse patients was (5±3) years and the time from initial diagnosis to testicular recurrence was (37±15) months. The follow-up time was 43 (22, 56) months. Twenty-three patients (62%) were isolated testis relapse. The 5-year OS rate and EFS rate of the 37 relapsed children were (60±9) % and (50±9) % respectively. Univariate analysis showed that the 2-year EFS rate in the group of patients with time from initial diagnosis to testicular recurrence >28 months was significantly higher than those ≤28 months ((69±10)% vs. (11±11)%, P<0.05), 2-year EFS rate of the isolated testicular relapse group was significantly higher than combined relapse group ((66±11)% vs. (20±13) %, P<0.05), 2-year EFS rate of chimeric antigen receptor T (CAR-T) cell treatment after relapse group was significantly higher than without CAR-T cell treatment after relapse group ((78±10)% vs. (15±10)%, P<0.05). ETV6-RUNX1 was the most common genetic aberration in testicular relapsed ALL (38%, 14/37). The 4-year OS and EFS rate of patients with ETV6-RUNX1 positive were (80±13) % and (64±15) %, respectively. Multivariate analysis identified relapse occurred≤28 months after first diagnosis (HR=3.09, 95%CI 1.10-8.72), combined relapse (HR=4.26, 95%CI 1.34-13.52) and CAR-T cell therapy after relapse (HR=0.15,95%CI 0.05-0.51) were independent prognostic factors for 2-year EFS rate (all P<0.05). Conclusions: The outcome of testicular relapse in pediatric ALL was poor. They mainly occurred 3 years after initial diagnosis. ETV6-RUNX1 is the most common abnormal gene.Patients with ETV6-RUNX1 positive often have a favorable outcome. Early relapse and combined relapse indicate unfavorable prognosis, while CAR-T cell therapy could significantly improve the survival rate of children with testicular recurrence.
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Affiliation(s)
- N Wang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - Y Y Gao
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - B Q Qi
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - M Ruan
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - H Lyu
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - X Y Zhang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - R R Zhang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - T F Liu
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - Y M Chen
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - Y Zou
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - Y Guo
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - W Y Yang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - L Zhang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - X F Zhu
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - X J Chen
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
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5
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Xu Z, Wu X, Xiao C, Zhang W, Yan P, Yang C, Zhang L, Cui H, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Qu Y, Xiao C, Zhang L, Yang C, Li J, Liu Z, Liao J, Yao Y, Zhang B, Jiang X. Observational and genetic analyses of the bidirectional relationship between depression and hypertension. J Affect Disord 2024; 348:62-69. [PMID: 38123074 DOI: 10.1016/j.jad.2023.12.028] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 11/20/2023] [Accepted: 12/09/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND While the association between depression and hypertension has been extensively investigated, the pattern and nature of such association remain inconclusive. We sought to investigate the bidirectional relationship between depression and hypertension and its causal. METHODS We first performed observational analyses using longitudinal data from the UK Biobank. We then performed genetic analyses leveraging summary statistics from large-scale genome-wide association studies (GWASs) conducted in European ancestry for depression and hypertension. RESULTS Observational analysis suggested a significant bidirectional phenotypic association between depression and hypertension (Depression → Hypertension: HR = 1.27, 95 % CI: 1.19, 1.36; Hypertension → Depression: HR = 1.65, 95 % CI: 1.58, 1.72). Linkage disequilibrium score regression demonstrated a positive genetic correlation between the two conditions (rg=0.15, P = 5.75 × 10-10). Bidirectional two-sample Mendelian randomization (MR) suggested that genetic liability to depression was significantly associated with an increased risk of hypertension (OR = 1.27, 95 % CI: 1.12, 1.43), while the genetic liability to hypertension was not associated with the risk of depression (OR = 1.01, 95 % CI: 0.99, 1.03). Multivariate MR, after adjusting for smoking, drinking, and body mass index, further supported an independent causal effect of genetic liability to depression on hypertension risk (OR = 1.10, 95 % CI: 1.02, 1.18). LIMITATIONS (1) interference of confounders, (2) absence of adequate statistical power, and (3) limitation to European populations. CONCLUSION Our study indicates depression is a causal risk factor for hypertension, whereas the reverse maybe not. Findings support that prevention of depression might help in decreasing hypertension incidence.
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Affiliation(s)
- Zhengxing Xu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; School of Public Health, Southwest Medical University, Luzhou, Sichuan, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Changfeng Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yang Qu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ling Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiaqiang Liao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.
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6
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Zou Y, Qin C, Yang Q, Lang Y, Liu K, Yang F, Li X, Zhao Y, Zheng T, Wang M, Shi R, Yang W, Zhou Y, Chen L, Liu F. Clinical characteristics, outcomes and risk factors for mortality in hospitalized diabetes and chronic kidney disease patients after COVID-19 infection following widespread vaccination. J Endocrinol Invest 2024; 47:619-631. [PMID: 37725309 DOI: 10.1007/s40618-023-02180-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 08/17/2023] [Indexed: 09/21/2023]
Abstract
BACKGROUND COVID-19 poses a significant threat to patients with comorbidities, such as diabetes and chronic kidney disease (CKD). China experienced a nationwide COVID-19 endemic from December 2022 to January 2023, which is the first occurrence of such an outbreak following China's widespread administration of COVID-19 vaccinations. METHODS A total of 338 patients with diabetes and CKD combined with COVID-19 infection between December 7, 2022 and January 31, 2023 were included in this study. The end follow-up date was February 10, 2023. Univariate analysis and multivariate Cox analysis were used to analyze risk factors for death. RESULTS During the 50-day median follow-up period, 90 patients in the study cohort died, for a mortality rate of 26.63%. The median age of the study cohort was 74 years, with a male predominance of 74%. During hospitalization, 21% of patients had incident AKI, 17% of patients experienced stroke, and 40% of patients experienced respiratory failure. Cox proportional hazard regression showed that older age, a diagnosis of severe or critically severe COVID-19 infection, incident AKI and respiratory failure, higher level of average values of fasting glucose during hospitalization, UA, and total bilirubin were independent risk factors for death in our multivariate model. CONCLUSIONS These findings highlight the critical importance of identifying and managing comorbid risk factors for COVID-19, especially among the elderly, in order to optimize clinical outcomes, even after COVID-19 vaccination.
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Affiliation(s)
- Y Zou
- Division of Nephrology, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
| | - C Qin
- Division of Nephrology, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
| | - Q Yang
- Division of Nephrology, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
| | - Y Lang
- Division of Nephrology, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
| | - K Liu
- Division of Nephrology, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
| | - F Yang
- Department of Clinical Medicine, Southwest Medical University, Luzhou, China
| | - X Li
- Department of Clinical Research Management, West China Hospital of Sichuan University, Chengdu, China
| | - Y Zhao
- Department of Clinical Research Management, West China Hospital of Sichuan University, Chengdu, China
| | - T Zheng
- Information Center, West China Hospital of Sichuan University, Chengdu, China
- Engineering Research Center of Medical Information Technology, Ministry of Education, Chengdu, China
| | - M Wang
- Information Center, West China Hospital of Sichuan University, Chengdu, China
- Engineering Research Center of Medical Information Technology, Ministry of Education, Chengdu, China
| | - R Shi
- Information Center, West China Hospital of Sichuan University, Chengdu, China
- Engineering Research Center of Medical Information Technology, Ministry of Education, Chengdu, China
| | - W Yang
- Division of Project Design and Statistics, West China Hospital of Sichuan University, Chengdu, China
| | - Y Zhou
- Integrated Care Management Center, West China Hospital of Sichuan University, Chengdu, China
| | - L Chen
- Department of Clinical Research Management, West China Hospital of Sichuan University, Chengdu, China
- Division of Neurology, West China Hospital of Sichuan University, Chengdu, China
| | - Fang Liu
- Division of Nephrology, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
- Department of Clinical Research Management, West China Hospital of Sichuan University, Chengdu, China.
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7
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Cui H, Zhang W, Zhang L, Qu Y, Xu Z, Tan Z, Yan P, Tang M, Yang C, Wang Y, Chen L, Xiao C, Zou Y, Liu Y, Zhang L, Yang Y, Yao Y, Li J, Liu Z, Yang C, Jiang X, Zhang B. Risk factors for prostate cancer: An umbrella review of prospective observational studies and mendelian randomization analyses. PLoS Med 2024; 21:e1004362. [PMID: 38489391 PMCID: PMC10980219 DOI: 10.1371/journal.pmed.1004362] [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: 06/19/2023] [Revised: 03/29/2024] [Accepted: 02/16/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND The incidence of prostate cancer is increasing in older males globally. Age, ethnicity, and family history are identified as the well-known risk factors for prostate cancer, but few modifiable factors have been firmly established. The objective of this study was to identify and evaluate various factors modifying the risk of prostate cancer reported in meta-analyses of prospective observational studies and mendelian randomization (MR) analyses. METHODS AND FINDINGS We searched PubMed, Embase, and Web of Science from the inception to January 10, 2022, updated on September 9, 2023, to identify meta-analyses and MR studies on prostate cancer. Eligibility criteria for meta-analyses were (1) meta-analyses including prospective observational studies or studies that declared outcome-free at baseline; (2) evaluating the factors of any category associated with prostate cancer incidence; and (3) providing effect estimates for further data synthesis. Similar criteria were applied to MR studies. Meta-analysis was repeated using the random-effects inverse-variance model with DerSimonian-Laird method. Quality assessment was then conducted for included meta-analyses using AMSTAR-2 tool and for MR studies using STROBE-MR and assumption evaluation. Subsequent evidence grading criteria for significant associations in meta-analyses contained sample size, P values and 95% confidence intervals, 95% prediction intervals, heterogeneity, and publication bias, assigning 4 evidence grades (convincing, highly suggestive, suggestive, or weak). Significant associations in MR studies were graded as robust, probable, suggestive, or insufficient considering P values and concordance of effect directions. Finally, 92 selected from 411 meta-analyses and 64 selected from 118 MR studies were included after excluding the overlapping and outdated studies which were published earlier and contained fewer participants or fewer instrument variables for the same exposure. In total, 123 observational associations (45 significant and 78 null) and 145 causal associations (55 significant and 90 null) were categorized into lifestyle; diet and nutrition; anthropometric indices; biomarkers; clinical variables, diseases, and treatments; and environmental factors. Concerning evidence grading on significant associations, there were 5 highly suggestive, 36 suggestive, and 4 weak associations in meta-analyses, and 10 robust, 24 probable, 4 suggestive, and 17 insufficient causal associations in MR studies. Twenty-six overlapping factors between meta-analyses and MR studies were identified, with consistent significant effects found for physical activity (PA) (occupational PA in meta: OR = 0.87, 95% CI: 0.80, 0.94; accelerator-measured PA in MR: OR = 0.49, 95% CI: 0.33, 0.72), height (meta: OR = 1.09, 95% CI: 1.06, 1.12; MR: OR = 1.07, 95% CI: 1.01, 1.15, for aggressive prostate cancer), and smoking (current smoking in meta: OR = 0.74, 95% CI: 0.68, 0.80; smoking initiation in MR: OR = 0.91, 95% CI: 0.86, 0.97). Methodological limitation is that the evidence grading criteria could be expanded by considering more indices. CONCLUSIONS In this large-scale study, we summarized the associations of various factors with prostate cancer risk and provided comparisons between observational associations by meta-analysis and genetically estimated causality by MR analyses. In the absence of convincing overlapping evidence based on the existing literature, no robust associations were identified, but some effects were observed for height, physical activity, and smoking.
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Affiliation(s)
- Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yang Qu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhengxing Xu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhixin Tan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Yanfang Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Ben Zhang
- Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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Zou Y, Mao Q, Zhao Z, Zhou X, Pan Y, Zuo Z, Zhang W. Intratumoural and peritumoural CT-based radiomics for diagnosing lepidic-predominant adenocarcinoma in patients with pure ground-glass nodules: a machine learning approach. Clin Radiol 2024; 79:e211-e218. [PMID: 38044199 DOI: 10.1016/j.crad.2023.11.003] [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] [Received: 07/16/2023] [Revised: 10/10/2023] [Accepted: 11/06/2023] [Indexed: 12/05/2023]
Abstract
AIM To develop and validate a diagnostic model utilising machine-learning algorithms that differentiates lepidic predominant adenocarcinoma (LPA) from other pathological subtypes in patients with pure ground-glass nodules (pGGNs). MATERIALS AND METHODS This bicentric study was conducted across two medical centres and included 151 patients diagnosed with lung adenocarcinoma based on histopathological confirmation of pGGNs. The training cohort consisted of 99 patients from Institution 1, while the test cohort included 52 patients from Institution 2. Radiomics features were extracted from both tumours and the 2 mm peritumoural parenchyma. The tumoural and peritumoural radiomics were designated as Modeltumoural and Modelperitumoural, respectively. The diagnostic efficacy of various models was evaluated through the receiver operating characteristic (ROC) curve analysis. Subsequently, a machine-learning-based prediction model that combined Modeltumoural, Modelperitumoural, and Modelclinical-radiological was developed to differentiate LPA from other pathological subtypes in patients with pGGNs. RESULTS Modeltumoural achieved area under the curve (AUC) values of 0.762 and 0.783 in the training and validation sets, respectively. Modelperitumoural attained AUCs of 0.742 and 0.667, and Modelclinical-radiological generated an AUC of 0.727 and 0.739 in the training and validation sets, respectively. Among the machine-learning models evaluated, gradient boosting machines demonstrated the best diagnostic efficacy, with accuracy, AUC, F1 score, and log loss values of 0.885, 0.956, 0.943, and 0.260, respectively. CONCLUSION The combined model based on machine learning that incorporated tumour and peritumoural parenchyma, as well as clinical and imaging characteristics, may offer benefits in assessing the pathological subtype of pGGNs.
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Affiliation(s)
- Y Zou
- Department of Radiology, Liuzhou People's Hospital Affiliated to Guangxi Medical University, Liuzhou, 545006, China; Guangxi Key Clinical Specialties of Medical Imaging, Liuzhou, 545006, China; Liuzhou Key Laboratory of Molecular Imaging, Liuzhou, 545006, China
| | - Q Mao
- Department of Radiology, Liuzhou People's Hospital Affiliated to Guangxi Medical University, Liuzhou, 545006, China; Guangxi Key Clinical Specialties of Medical Imaging, Liuzhou, 545006, China; Liuzhou Key Laboratory of Molecular Imaging, Liuzhou, 545006, China
| | - Z Zhao
- Department of Radiology, Liuzhou People's Hospital Affiliated to Guangxi Medical University, Liuzhou, 545006, China; Guangxi Key Clinical Specialties of Medical Imaging, Liuzhou, 545006, China; Liuzhou Key Laboratory of Molecular Imaging, Liuzhou, 545006, China
| | - X Zhou
- Department of Radiology, Xiangtan Central Hospital, Xiangtan, 411000, China
| | - Y Pan
- Department of Radiology, Liuzhou People's Hospital Affiliated to Guangxi Medical University, Liuzhou, 545006, China; Guangxi Key Clinical Specialties of Medical Imaging, Liuzhou, 545006, China; Liuzhou Key Laboratory of Molecular Imaging, Liuzhou, 545006, China
| | - Z Zuo
- Department of Radiology, Xiangtan Central Hospital, Xiangtan, 411000, China
| | - W Zhang
- Department of Radiology, Liuzhou People's Hospital Affiliated to Guangxi Medical University, Liuzhou, 545006, China; Guangxi Key Clinical Specialties of Medical Imaging, Liuzhou, 545006, China; Liuzhou Key Laboratory of Molecular Imaging, Liuzhou, 545006, China.
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9
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Yan P, Zhang L, Yang C, Zhang W, Wang Y, Zhang M, Cui H, Tang M, Chen L, Wu X, Zhao X, Zou Y, Xiao J, Liu Y, Xiao C, Yang Y, Zhang L, Yao Y, Li J, Liu Z, Yang C, Jiang X, Zhang B. Observational and genetic analyses clarify the relationship between type 2 diabetes mellitus and gallstone disease. Front Endocrinol (Lausanne) 2024; 14:1337071. [PMID: 38356679 PMCID: PMC10864641 DOI: 10.3389/fendo.2023.1337071] [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] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 12/26/2023] [Indexed: 02/16/2024] Open
Abstract
Background The relationship between type 2 diabetes mellitus (T2DM) and gallstone disease (GSD) have been incompletely understood. We aimed to investigate their phenotypic and genetic associations and evaluate the biological mechanisms underlying these associations. Methods We first evaluated the phenotypic association between T2DM and GSD using data from the UK Biobank (n>450,000) using a prospective observational design. We then conducted genetic analyses using summary statistics from a meta-analysis of genome-wide association studies of T2DM, with and without adjusting for body mass index (BMI) (Ncase=74,124, Ncontrol=824,006; T2DMadjBMI: Ncase=50,409, Ncontrol=523,897) and GSD (Ncase=43,639, Ncontrol=506,798). Results A unidirectional phenotypic association was observed, where individuals with T2DM exhibited a higher GSD risk (hazard ratio (HR)=1.39, P<0.001), but not in the reverse direction (GSD→T2DM: HR=1.00, P=0.912). The positive T2DM-GSD genetic correlation (rg=0.35, P=7.71×10-23) remained even after adjusting for BMI (T2DMadjBMI: rg=0.22, P=4.48×10-10). Mendelian randomization analyses provided evidence of a unidirectional causal relationship (T2DM→GSD: odds ratio (OR)=1.08, P=4.6×10-8; GSD→T2DM: OR=1.02, P=0.48), even after adjusting for important metabolic confounders (OR=1.02, P=0.02). This association was further corroborated through a comprehensive functional analysis reflected by 23 pleiotropic single nucleotide polymorphisms, as well as multiple neural and motor-enriched tissues. Conclusion Through comprehensive observational and genetic analyses, our study clarified the causal relationship between T2DM and GSD, but not in the reverse direction. These findings might provide new insights into prevention and treatment strategies for T2DM and GSD.
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Affiliation(s)
- Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- School of Public Health, Southwest Medical University, Luzhou, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Min Zhang
- Clinical Research Center, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xunying Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jinyu Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanfang Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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10
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Sun CC, Zhang YC, Wang Y, Chen AL, Xu Z, Zou Y, Xu J, Wang S. Design of a high-power collimating optical system based on Fresnel lenses. LUMINESCENCE 2023. [PMID: 38147880 DOI: 10.1002/bio.4654] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 11/06/2023] [Accepted: 11/21/2023] [Indexed: 12/28/2023]
Abstract
In light-emitting diode (LED) illumination (e.g., LED maritime lighting for ships), creating a uniform light environment for optical systems is an important challenge. In this study, we present a high-power collimating system based on Fresnel lenses, which allows high-brightness LED illumination in the earlier-mentioned remote distance. The work presented in this article focuses on improving the power, compacting the optical structure, and promoting the brightness of the spot. To prove the claims, the system with a total power of 1 kW is designed. The system consists of a 27 W LED array, a freeform surface lens array, and a confocal Fresnel lens array. In comparison with the traditional optical system, the optical structure shortens from 390 to 120 mm, and the divergent angle decreases from 3° to 2° $$ {}^{{}^{\circ}} $$ . Meanwhile, the illuminance of the system is obtained as high as 230 lx at the near field of 200 m and 3.0 lx at the far field of 1.5 nautical miles. This new method provides a practical and effective way to solve the problem of low power, insufficient illuminance, and long optical structure for LED array illumination, which is suitable for remote illumination and guidance of ships.
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Affiliation(s)
- Chang Cheng Sun
- School of Information Science and Engineering, Dalian Polytechnic University, Dalian, China
| | - Yun Cui Zhang
- School of Information Science and Engineering, Dalian Polytechnic University, Dalian, China
| | - Yan Wang
- School of Information Science and Engineering, Dalian Polytechnic University, Dalian, China
| | - Ai Lin Chen
- School of Information Science and Engineering, Dalian Polytechnic University, Dalian, China
| | - Zhe Xu
- School of Information Science and Engineering, Dalian Polytechnic University, Dalian, China
| | - Yanqiu Zou
- Dalian Estar Intelligent Technology Co., Ltd, Dalian, China
| | - Jiyu Xu
- Dalian Estar Intelligent Technology Co., Ltd, Dalian, China
| | - Shuai Wang
- Dalian Estar Intelligent Technology Co., Ltd, Dalian, China
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11
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Zou Y, Yan XL, Flores RM, Zhang LY, Yang SP, Fan LY, Deng T, Deng XJ, Ye DQ. Source apportionment and ozone formation mechanism of VOCs considering photochemical loss in Guangzhou, China. Sci Total Environ 2023; 903:166191. [PMID: 37567293 DOI: 10.1016/j.scitotenv.2023.166191] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 08/13/2023]
Abstract
Understanding the sources and impact of volatile organic compounds (VOCs) on ozone formation is challenging when the traditional method does not account for their photochemical loss. In this study, online monitoring of 56 VOCs was carried out in summer and autumn during high ozone pollution episodes. The photochemical age method was used to evaluate the atmospheric chemical loss of VOCs and to analyze the effects on characteristics, sources, and ozone formation of VOC components. The initial concentrations during daytime were 5.12 ppbv and 4.49 ppbv higher than the observed concentrations in the summer and autumn, respectively. The positive matrix factorization (PMF) model identified 5 major emission sources. However, the omission of the chemical loss of VOCs led to underestimating the contributions of sources associated with highly reactive VOC components, such as those produced by biogenic emissions and solvent usage. Conversely it resulted in overestimating the contributions from VOC components with lower chemical activity such as liquefied petroleum gas (LPG) usage, vehicle emissions, and gasoline evaporation. Furthermore, the estimation of ozone formation may be underestimated when the atmospheric photochemical loss is not taken into account. The ozone formation potential (OFP) method and propylene-equivalent concentration method both underestimated ozone formation by 53.24 ppbv and 47.25 ppbc, respectively, in the summer, and by 40.34 ppbv and 26.37 ppbc, respectively, in the autumn. The determination of the ozone formation regime based on VOC chemical loss was more acceptable. In the summer, the ozone formation regime changed from the VOC-limited regime to the VOC-NOx transition regime, while in the autumn, the ozone formation regime changed from the strong VOC-limited regime to the weak VOC-limited regime. To obtain more thorough and precise conclusions, further monitoring and analysis studies will be conducted in the near future on a wider variety of VOC species such as oxygenated VOCs (OVOCs).
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Affiliation(s)
- Y Zou
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China; Institute of Tropical and Marine Meteorology, China Meteorological Administration (CMA), Guangzhou 510640, China
| | - X L Yan
- State Key Laboratory of Severe Weather & Institute of Tibetan Plateau Meteorology, Chinese Academy of Meteorological Sciences, Beijing, China
| | - R M Flores
- Marmara University, Department of Environmental Engineering, Istanbul, Turkey
| | - L Y Zhang
- Institute of Tropical and Marine Meteorology, China Meteorological Administration (CMA), Guangzhou 510640, China
| | - S P Yang
- Institute of Tropical and Marine Meteorology, China Meteorological Administration (CMA), Guangzhou 510640, China
| | - L Y Fan
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - T Deng
- Institute of Tropical and Marine Meteorology, China Meteorological Administration (CMA), Guangzhou 510640, China
| | - X J Deng
- Institute of Tropical and Marine Meteorology, China Meteorological Administration (CMA), Guangzhou 510640, China
| | - D Q Ye
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
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12
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Zhang W, Zhang L, Zhu J, Xiao C, Cui H, Yang C, Yan P, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Wu X, Zhang L, Yang C, Yao Y, Li J, Liu Z, Jiang X, Zhang B. Additional Evidence for the Relationship Between Type 2 Diabetes and Stroke Through Observational and Genetic Analyses. Diabetes 2023; 72:1671-1681. [PMID: 37552871 DOI: 10.2337/db22-0954] [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] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 08/01/2023] [Indexed: 08/10/2023]
Abstract
While type 2 diabetes mellitus (T2DM) is commonly considered a putative causal risk factor for stroke, the effect of stroke on T2DM remains unclear. The intrinsic link underlying T2DM and stroke has not been thoroughly examined. We aimed to evaluate the phenotypic and genetic relationships underlying T2DM and stroke. We evaluated phenotypic associations using data from the UK Biobank (N = 472,050). We then investigated genetic relationships by leveraging genomic data in European ancestry for T2DM, with and without adjusting (adj) for BMI (T2DM: n = 74,124 case subjects/824,006 control subjects; T2DMadjBMI: n = 50,409 case subjects/523,897 control subjects), and for stroke (n = 73,652 case subjects/1,234,808 control subjects). We performed additional analyses using genomic data in East Asian ancestry for T2DM (n = 77,418 case subjects/356,122 control subjects) and for stroke (n = 27,413 case subjects/237,242 control subjects). Observational analyses suggested a significantly increased hazard of stroke among individuals with T2DM (hazard ratio 2.28 [95% CI 1.97-2.64]), but a slightly increased hazard of T2DM among individuals with stroke (1.22 [1.03-1.45]) which attenuated to 1.14 (0.96-1.36) in sensitivity analysis. A positive global T2DM-stroke genetic correlation was observed (rg = 0.35; P = 1.46 × 10-27), largely independent of BMI (T2DMadjBMI-stroke: rg = 0.27; P = 3.59 × 10-13). This was further corroborated by 38 shared independent loci and 161 shared expression-trait associations. Mendelian randomization analyses suggested a putative causal effect of T2DM on stroke in Europeans (odds ratio 1.07 [95% CI 1.06-1.09]), which remained significant in East Asians (1.03 [1.01-1.06]). Conversely, despite a putative causal effect of stroke on T2DM also observed in Europeans (1.21 [1.07-1.37]), it attenuated to 1.04 (0.91-1.19) in East Asians. Our study provides additional evidence to underscore the significant relationship between T2DM and stroke. ARTICLE HIGHLIGHTS
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Affiliation(s)
- Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Jingwei Zhu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Ling Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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Zhang L, Zhang W, Xiao C, Wu X, Cui H, Yan P, Yang C, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Alfredsson L, Klareskog L, Yang Y, Yao Y, Li J, Liu Z, Yang C, Jiang X, Zhang B. Using human genetics to understand the epidemiological association between obesity, serum urate, and gout. Rheumatology (Oxford) 2023; 62:3280-3290. [PMID: 36734534 DOI: 10.1093/rheumatology/kead054] [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: 08/16/2022] [Revised: 12/31/2022] [Accepted: 01/20/2023] [Indexed: 02/04/2023] Open
Abstract
OBJECTIVES We aimed to clarify the genetic overlaps underlying obesity-related traits, serum urate, and gout. METHODS We conducted a comprehensive genome-wide cross-trait analysis to identify genetic correlation, pleiotropic loci, and causal relationships between obesity (the exposure variable), gout (the primary outcome) and serum urate (the secondary outcome). Summary statistics were collected from the hitherto largest genome-wide association studies conducted for BMI (N = 806 834), waist-to-hip ratio (WHR; N = 697 734), WHR adjusted for BMI (WHRadjBMI; N = 694 649), serum urate (N = 288 649), and gout (Ncases = 13 179 and Ncontrols = 750 634). RESULTS Positive overall genetic correlations were observed for BMI (rg = 0.27, P = 6.62 × 10-7), WHR (rg = 0.22, P = 6.26 × 10-7) and WHRadjBMI (rg = 0.07, P = 6.08 × 10-3) with gout. Partitioning the whole genome into 1703 LD (linkage disequilibrium)-independent regions, a significant local signal at 4q22 was identified for BMI and gout. The global and local shared genetic basis was further strengthened by the multiple pleiotropic loci identified in the cross-phenotype association study, multiple shared gene-tissue pairs observed by Transcriptome-wide association studies, as well as causal relationships demonstrated by Mendelian randomization [BMI-gout: OR (odds ratio) = 1.66, 95% CI = 1.45, 1.88; WHR-gout: OR = 1.57, 95% CI = 1.37, 1.81]. Replacing the binary disease status of gout with its latent pathological measure, serum urate, a similar pattern of correlation, pleiotropy and causality was observed with even more pronounced magnitude and significance. CONCLUSION Our comprehensive genome-wide cross-trait analysis demonstrates a shared genetic basis and pleiotropic loci, as well as a causal relationship between obesity, serum urate, and gout, highlighting an intrinsic link underlying these complex traits.
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Affiliation(s)
- Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Lars Alfredsson
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Lars Klareskog
- Division of Rheumatology, Department of Medicine and Center for Molecular Medicine, Karolinska Institutet at Karolinska University Hospital (Solna), Stockholm, Sweden
| | - Yanfang Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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14
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Wang Y, Zhang L, Zhang W, Tang M, Cui H, Wu X, Zhao X, Chen L, Yan P, Yang C, Xiao C, Zou Y, Liu Y, Zhang L, Yang C, Yao Y, Li J, Liu Z, Jiang X, Zhang B. Understanding the relationship between circulating lipids and risk of chronic kidney disease: a prospective cohort study and large-scale genetic analyses. J Transl Med 2023; 21:671. [PMID: 37759214 PMCID: PMC10537816 DOI: 10.1186/s12967-023-04509-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [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: 05/12/2023] [Accepted: 09/06/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND This study aims to comprehensively investigate the phenotypic and genetic relationships between four common lipids (high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; total cholesterol, TC; and triglycerides, TG), chronic kidney disease (CKD), and estimated glomerular filtration rate (eGFR). METHODS We first investigated the observational association of lipids (exposures) with CKD (primary outcome) and eGFR (secondary outcome) using data from UK Biobank. We then explored the genetic relationship using summary statistics from the largest genome-wide association study of four lipids (N = 1,320,016), CKD (Ncase = 41,395, Ncontrol = 439,303), and eGFR(N = 567,460). RESULTS There were significant phenotypic associations (HDL-C: hazard ratio (HR) = 0.76, 95%CI = 0.60-0.95; TG: HR = 1.08, 95%CI = 1.02-1.13) and global genetic correlations (HDL-C: [Formula: see text] = - 0.132, P = 1.00 × 10-4; TG: [Formula: see text] = 0.176; P = 2.66 × 10-5) between HDL-C, TG, and CKD risk. Partitioning the whole genome into 2353 LD-independent regions, twelve significant regions were observed for four lipids and CKD. The shared genetic basis was largely explained by 29 pleiotropic loci and 36 shared gene-tissue pairs. Mendelian randomization revealed an independent causal relationship of genetically predicted HDL-C (odds ratio = 0.91, 95%CI = 0.85-0.98), but not for LDL-C, TC, or TG, with the risk of CKD. Regarding eGFR, a similar pattern of correlation and pleiotropy was observed. CONCLUSIONS Our work demonstrates a putative causal role of HDL-C in CKD and a significant biological pleiotropy underlying lipids and CKD in populations of European ancestry. Management of low HDL-C levels could potentially benefit in reducing the long-term risk of CKD.
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Affiliation(s)
- Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Xunying Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China.
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China.
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15
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Zhang L, Zhang W, He L, Cui H, Wang Y, Wu X, Zhao X, Yan P, Yang C, Xiao C, Tang M, Chen L, Xiao C, Zou Y, Liu Y, Yang Y, Zhang L, Yao Y, Li J, Liu Z, Yang C, Jiang X, Zhang B. Impact of gallstone disease on the risk of stroke and coronary artery disease: evidence from prospective observational studies and genetic analyses. BMC Med 2023; 21:353. [PMID: 37705021 PMCID: PMC10500913 DOI: 10.1186/s12916-023-03072-6] [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] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 09/06/2023] [Indexed: 09/15/2023] Open
Abstract
BACKGROUND Despite epidemiological evidence associating gallstone disease (GSD) with cardiovascular disease (CVD), a dilemma remains on the role of cholecystectomy in modifying the risk of CVD. We aimed to characterize the phenotypic and genetic relationships between GSD and two CVD events - stroke and coronary artery disease (CAD). METHODS We first performed a meta-analysis of cohort studies to quantify an overall phenotypic association between GSD and CVD. We then investigated the genetic relationship leveraging the largest genome-wide genetic summary statistics. We finally examined the phenotypic association using the comprehensive data from UK Biobank (UKB). RESULTS An overall significant effect of GSD on CVD was found in meta-analysis (relative risk [RR] = 1.26, 95% confidence interval [CI] = 1.19-1.34). Genetically, a positive shared genetic basis was observed for GSD with stroke ([Formula: see text]=0.16, P = 6.00 × 10-4) and CAD ([Formula: see text]=0.27, P = 2.27 × 10-15), corroborated by local signals. The shared genetic architecture was largely explained by the multiple pleiotropic loci identified in cross-phenotype association study and the shared gene-tissue pairs detected by transcriptome-wide association study, but not a causal relationship (GSD to CVD) examined through Mendelian randomization (MR) (GSD-stroke: odds ratio [OR] = 1.00, 95%CI = 0.97-1.03; GSD-CAD: OR = 1.01, 95%CI = 0.98-1.04). After a careful adjustment of confounders or considering lag time using UKB data, no significant phenotypic effect of GSD on CVD was detected (GSD-stroke: hazard ratio [HR] = 0.95, 95%CI = 0.83-1.09; GSD-CAD: HR = 0.98, 95%CI = 0.91-1.06), further supporting MR findings. CONCLUSIONS Our work demonstrates a phenotypic and genetic relationship between GSD and CVD, highlighting a shared biological mechanism rather than a direct causal effect. These findings may provide insight into clinical and public health applications.
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Affiliation(s)
- Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Lin He
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Xunying Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Changfeng Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Yanfang Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China.
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, China.
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
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16
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Zhang W, Zhang L, Yang L, Xiao C, Wu X, Yan P, Cui H, Yang C, Zhu J, Wu X, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Zhang L, Yang C, Yao Y, Li J, Liu Z, Zhang B, Jiang X. Migraine, chronic kidney disease and kidney function: observational and genetic analyses. Hum Genet 2023; 142:1185-1200. [PMID: 37306871 PMCID: PMC10449948 DOI: 10.1007/s00439-023-02575-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 05/23/2023] [Indexed: 06/13/2023]
Abstract
Epidemiological studies demonstrate an association between migraine and chronic kidney disease (CKD), while the genetic basis underlying the phenotypic association has not been investigated. We aimed to help avoid unnecessary interventions in individuals with migraine through the investigation of phenotypic and genetic relationships underlying migraine, CKD, and kidney function. We first evaluated phenotypic associations using observational data from UK Biobank (N = 255,896). We then investigated genetic relationships leveraging genomic data in European ancestry for migraine (Ncase/Ncontrol = 48,975/540,381), CKD (Ncase/Ncontrol = 41,395/439,303), and two traits of kidney function (estimated glomerular filtration rate [eGFR, N = 567,460] and urinary albumin-to-creatinine ratio [UACR, N = 547,361]). Observational analyses suggested no significant association of migraine with the risk of CKD (HR = 1.13, 95% CI = 0.85-1.50). While we did not find any global genetic correlation in general, we identified four specific genomic regions showing significant for migraine with eGFR. Cross-trait meta-analysis identified one candidate causal variant (rs1047891) underlying migraine, CKD, and kidney function. Transcriptome-wide association study detected 28 shared expression-trait associations between migraine and kidney function. Mendelian randomization analysis suggested no causal effect of migraine on CKD (OR = 1.03, 95% CI = 0.98-1.09; P = 0.28). Despite a putative causal effect of migraine on an increased level of UACR (log-scale-beta = 0.02, 95% CI = 0.01-0.04; P = 1.92 × 10-3), it attenuated to null when accounting for both correlated and uncorrelated pleiotropy. Our work does not find evidence supporting a causal association between migraine and CKD. However, our study highlights significant biological pleiotropy between migraine and kidney function. The value of a migraine prophylactic treatment for reducing future CKD in people with migraine is likely limited.
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Affiliation(s)
- Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Luo Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Urology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Jingwei Zhu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Xuan Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Ling Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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17
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Wu X, Yang C, Zou Y, Jones SE, Zhao X, Zhang L, Han Z, Hao Y, Xiao J, Xiao C, Zhang W, Yan P, Cui H, Tang M, Wang Y, Chen L, Zhang L, Yao Y, Liu Z, Li J, Jiang X, Zhang B. Using human genetics to understand the phenotypic association between chronotype and breast cancer. J Sleep Res 2023:e13973. [PMID: 37380357 DOI: 10.1111/jsr.13973] [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: 04/03/2023] [Revised: 05/23/2023] [Accepted: 06/11/2023] [Indexed: 06/30/2023]
Abstract
Little is known regarding the shared genetic influences underlying the observed phenotypic association between chronotype and breast cancer in women. Leveraging summary statistics from the hitherto largest genome-wide association study conducted in each trait, we investigated the genetic correlation, pleiotropic loci, and causal relationship of chronotype with overall breast cancer, and with its subtypes defined by the status of oestrogen receptor. We identified a negative genomic correlation between chronotype and overall breast cancer ( r g $$ {r}_g $$ = -0.06, p = 3.00 × 10-4 ), consistent across oestrogen receptor-positive ( r g $$ {r}_g $$ = -0.05, p = 3.30 × 10-3 ) and oestrogen receptor-negative subtypes ( r g $$ {r}_g $$ = -0.05, p = 1.11 × 10-2 ). Five specific genomic regions were further identified as contributing a significant local genetic correlation. Cross-trait meta-analysis identified 78 loci shared between chronotype and breast cancer, of which 23 were novel. Transcriptome-wide association study revealed 13 shared genes, targeting tissues of the nervous, cardiovascular, digestive, and exocrine/endocrine systems. Mendelian randomisation demonstrated a significantly reduced risk of overall breast cancer (odds ratio 0.89, 95% confidence interval 0.83-0.94; p = 1.30 × 10-4 ) for genetically predicted morning chronotype. No reverse causality was found. Our work demonstrates an intrinsic link underlying chronotype and breast cancer, which may provide clues to inform management of sleep habits to improve female health.
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Affiliation(s)
- Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, Luzhou, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Samuel E Jones
- Institute for Molecular Medicine, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Xunying Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Zhitong Han
- School of Life Sciences, Sichuan University, Chengdu, China
| | - Yu Hao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jinyu Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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18
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Carter-Searjeant S, Fairclough SM, Haigh SJ, Zou Y, Curry RJ, Taylor PN, Huang C, Fleck R, Machado P, Kirkland AI, Green MA. Nanoscale LiZnN - Luminescent Half-Heusler Quantum Dots. ACS Appl Opt Mater 2023; 1:1169-1173. [PMID: 37384133 PMCID: PMC10294247 DOI: 10.1021/acsaom.3c00065] [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: 02/20/2023] [Revised: 06/02/2023] [Accepted: 06/02/2023] [Indexed: 06/30/2023]
Abstract
Colloidal semiconductor quantum dots are a well-established technology, with numerous materials available either commercially or through the vast body of literature. The prevalent materials are cadmium-based and are unlikely to find general acceptance in most applications. While the III-V family of materials is a likely substitute, issues remain about its long-term suitability, and other earth-abundant materials are being explored. In this report, we highlight a nanoscale half-Heusler semiconductor, LiZnN, composed of readily available elements as a potential alternative system to luminescent II-VI and III-V nanoparticle quantum dots.
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Affiliation(s)
| | - S. M. Fairclough
- Department
of Physics, King’s College London, Strand, London WC2R 2LS, U.K.
| | - S. J. Haigh
- Department
of Materials, University of Manchester, Oxford Road, Manchester M19 9PL, U.K.
| | - Y. Zou
- Department
of Materials, University of Manchester, Oxford Road, Manchester M19 9PL, U.K.
| | - R. J. Curry
- Department
of Electrical and Electronic Engineering, Photon Science Institute, University of Manchester, Oxford Road, Manchester M13 9PL, U.K.
| | - P. N. Taylor
- Sharp
Life Science (EU) Ltd., The Hayakawa
Building, Edmund Halley Road, Oxford
Science Park, Oxford OX4 4GB, U.K.
| | - C. Huang
- Electron
Physical Sciences Imaging Centre, Diamond
Light Source, Harwell Science Innovation
Campus, Fermi Ave, Didcot OX110DE, U.K.
- Department
of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, U.K.
| | - R. Fleck
- Centre
for
Ultrastructural Imaging, King’s College
London, New Hunts House, Guys Campus, London SE1 1UL, U.K.
| | - P. Machado
- Centre
for
Ultrastructural Imaging, King’s College
London, New Hunts House, Guys Campus, London SE1 1UL, U.K.
| | - A. I. Kirkland
- Electron
Physical Sciences Imaging Centre, Diamond
Light Source, Harwell Science Innovation
Campus, Fermi Ave, Didcot OX110DE, U.K.
- Department
of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, U.K.
| | - M. A. Green
- Department
of Physics, King’s College London, Strand, London WC2R 2LS, U.K.
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19
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Gao YY, Jia YJ, Qi BQ, Zhang XY, Chen YM, Zou Y, Guo Y, Yang WY, Zhang L, Wang SC, Zhang RR, Liu TF, Song Z, Zhu XF, Chen XJ. [Genomics of next generation sequencing in pediatric B-acute lymphoblastic leukemia and its impact on minimal residual disease]. Zhonghua Er Ke Za Zhi 2023; 61:527-532. [PMID: 37312464 DOI: 10.3760/cma.j.cn112140-20230417-00278] [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] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To describe the gene mutation profile of newly diagnosed pediatric B-acute lymphoblastic leukemia (B-ALL) and analyze its effect on minimal residual disease (MRD). Methods: A total of 506 newly diagnosed B-ALL children treated in Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences from September 2018 to July 2021 were enrolled in this retrospective cohort study. The enrolled children were divided into MRD ≥1.00% group and <1.00% group according to MRD results on the 19th day since chemotherapy, and MRD ≥0.01% group and <0.01% group according to MRD results on the 46th day. Clinical characteristics and gene mutations of two groups were compared. Comparisons between groups were performed with chi-square test or Fisher's exact test. Independent risk factors of MRD results on the 19th day and the 46th day were analyzed by Logistic regression model. Results: Among all 506 patients, there were 318 males and 188 females. On the 19th day, there were 114 patients in the MRD ≥1.00% group and 392 patients in the MRD <1.00% group. On the 46th day, there were 76 patients in the MRD ≥0.01% group and 430 patients in the MRD <0.01% group. A total of 187 gene mutations were detected in 487 (96.2%) of 506 children. The most common gene mutations were signal transduction-related KRAS gene mutations in 111 cases (22.8%) and NRAS gene mutations in 99 cases (20.3%). Multivariate analysis showed that PTPN11 (OR=1.92, 95%CI 1.00-3.63), KMT2A (OR=3.51, 95%CI 1.07-11.50) gene mutations and TEL-AML1 (OR=0.48, 95%CI 0.27-0.87), BCR-ABL1 (OR=0.27, 95%CI 0.08-0.92) fusion genes and age >10 years (OR=1.91, 95%CI 1.12-3.24) were independent influencing factors for MRD ≥1.00% on the 19th day. BCORL1 (OR=2.96, 95%CI 1.18-7.44), JAK2 (OR=2.99, 95%CI 1.07-8.42) and JAK3 (OR=4.83, 95%CI 1.50-15.60) gene mutations and TEL-AML1 (OR=0.43, 95%CI 0.21-0.87) fusion gene were independent influencing factors for MRD ≥0.01% on the 46th day. Conclusions: Children with B-ALL are prone to genetic mutations, with abnormalities in the RAS signaling pathway being the most common. Signal transduction related PTPN11, JAK2 and JAK3 gene mutations, epigenetic related KMT2A gene mutation and transcription factor related BCORL1 gene mutation are independent risk factors for MRD.
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Affiliation(s)
- Y Y Gao
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - Y J Jia
- Next Generation Sequencing Preparatory Group, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - B Q Qi
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - X Y Zhang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - Y M Chen
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - Y Zou
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - Y Guo
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - W Y Yang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - L Zhang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - S C Wang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - R R Zhang
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - T F Liu
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - Z Song
- Information and Resource Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - X F Zhu
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
| | - X J Chen
- Pediatric Blood Diseases Center, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Institutes of Health Science, Tianjin 300020, China
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20
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Xiao J, Hao Y, Wu X, Zhao X, Xu B, Xiao C, Zhang W, Zhang L, Cui H, Yang C, Yan P, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Yang C, Yao Y, Li J, Jiang X, Zhang B. Nuclear magnetic resonance-determined lipoprotein profile and risk of breast cancer: a Mendelian randomization study. Breast Cancer Res Treat 2023; 200:115-126. [PMID: 37162625 DOI: 10.1007/s10549-023-06930-2] [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] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 03/30/2023] [Indexed: 05/11/2023]
Abstract
PURPOSE While crudely quantified lipoproteins have been reported to affect the risk of breast cancer, the effects of subclass lipoproteins characterized by particle size, particle number, and lipidomes remain unknown. METHODS Utilizing nuclear magnetic resonance-based GWAS of 85 lipoprotein traits, we performed two-sample univariable Mendelian randomization (MR) to evaluate the causal relationship between each trait with breast cancer (Ncase/control = 133,384/113,789) and with its estrogen receptor (ER) subtypes. Then, we applied multivariable MR to investigate the independent effects considering both general and central obesity. RESULTS In univariable MR, a heterogeneous effect of subclass high-density lipoproteins (HDL) was observed, in which small HDL traits (ORs ranged from 0.89 to 0.94) were associated with a decreased risk of breast cancer while non-small HDLs traits (OR ranged from 1.04 to 1.08) were associated with an increased risk of breast cancer. Very-low-density lipoproteins (VLDL) traits and serum total triglycerides (TG) were associated with a decreased risk of breast cancer (ORs ranged from 0.88 to 0.94). Similar association patterns were found for ER + subtype. In multivariable MR, only the protective effects of small HDL, VLDL and TG on ER + subtype remained significant. CONCLUSION We identified a heterogeneous effect of subclass HDLs and a consistent protective effect of VLDL on breast cancer. Only the effects of small HDL and VLDL on ER + subtype remained robust after controlling for obesity. These findings provide new insight into the causal pathway underlying lipoproteins and breast cancer.
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Affiliation(s)
- Jinyu Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yu Hao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xunying Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Bin Xu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Department of Epidemiology and Biostatistics, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
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Cui H, Qu Y, Zhang L, Zhang W, Yan P, Yang C, Zhang M, Bai Y, Tang M, Wang Y, Chen L, Xiao C, Zou Y, Liu Y, Zhang L, Yang Y, Yao Y, Li J, Liu Z, Yang C, Jiang X, Zhang B. Epidemiological and genetic evidence for the relationship between ABO blood group and human cancer. Int J Cancer 2023; 153:320-330. [PMID: 37074298 DOI: 10.1002/ijc.34533] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/28/2023] [Accepted: 03/14/2023] [Indexed: 04/20/2023]
Abstract
To comprehensively evaluate the etiological role of ABO blood group in human cancer, we conducted a large-scale meta-analysis of 127 publications totaling 20 million participants including 231 737 patients of 20 cancers, supplemented by genetic evidence. Effects of A, AB and B groups on cancer risk were investigated by respectively comparing with O group and their combined counterparts, and subgroup analysis by ethnicity was conducted for O-referent models. For cancer categories, A group increased risk of cancers of oral cavity and nasopharynx, digestive and female genital organs, while both AB and B groups showed associations with only digestive cancers. For individual cancers, A group significantly increased the risk of nine cancers including oral cavity (OR = 1.17, P = .013), stomach (OR = 1.19, P = 3.90 × 10-15 ), pancreas (OR = 1.33, P = 9.89 × 10-33 ), colorectum (OR = 1.09, P = .001), liver (OR = 1.23, P = .011), ovary (OR = 1.13, P = .001), cervix (OR = 1.17, P = .025), bladder (OR = 1.12, P = .025) and breast (OR = 1.06, P = .043). AB group showed associations with only three cancers: stomach (OR = 1.10, P = .007), pancreas (OR = 1.21, P = .001) and ovary (OR = 1.28, P = .006). B group, except for shared associations with A group on pancreas (OR = 1.20, P = 2.27 × 10-5 ) and cervix cancers (OR = 1.13, P = .011), had two distinct associations with esophagus (OR = 1.17, P = .002) and nonmelanoma skin cancers (OR = 0.96, P = .017). Ethnicity-specific analyses revealed the notable effects of non-O groups on pancreatic cancer both in Caucasians and Asians. In genetic analysis, four SNPs were associated with the risk of pancreatic cancer, with rs505922 corresponding to O group showing the strongest protective effect (P = 1.16 × 10-23 ). Our study provides comprehensive evidence of ABO blood group associated with cancers and highlighted its carcinogenic role.
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Affiliation(s)
- Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yang Qu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Min Zhang
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Ye Bai
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Yanfang Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
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Zou Y, Laothamatas K, Sonett J, Lemaitre P, Stanifer B, Magda G, Grewal H, Shah L, Robbins H, Patel S, Miller A, Anderson M, Costa J, D'Ovidio F, Arcasoy S, Benvenuto L. Effect of Age and Transplant Type on Survival and Hospital-Free Days in COPD Patients. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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23
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Lou W, Zhang H, Luo H, Chen Z, Shi R, Guo X, Zou Y, Liu L, Brito LF, Guo G, Wang Y. Corrigendum to “Genetic analyses of blood β-hydroxybutyrate predicted from milk infrared spectra and its association with longevity and female reproductive traits in Holstein cattle” (J. Dairy Sci. 105:3269–3281). J Dairy Sci 2023; 106:3051. [PMID: 37003636 DOI: 10.3168/jds.2023-106-4-3051] [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: 04/01/2023]
Affiliation(s)
- W Lou
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - H Zhang
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - H Luo
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Z Chen
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - R Shi
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; Animal Breeding and Genomics Group, Wageningen University & Research, PO Box 338, 6700 AH Wageningen, the Netherlands
| | - X Guo
- Center of Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark
| | - Y Zou
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - L Liu
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - L F Brito
- Department of Animal Science, Purdue University, West Lafayette, IN 47907
| | - G Guo
- Beijing Sunlon Livestock Development Company Limited, Beijing, 10029, China
| | - Y Wang
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
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Zhang L, Zhang W, Wu X, Cui H, Yan P, Yang C, Zhao X, Xiao J, Xiao C, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Zhang L, Yang Y, Yao Y, Li J, Liu Z, Yang C, Zhang B, Jiang X. A sex- and site-specific relationship between body mass index and osteoarthritis: evidence from observational and genetic analyses. Osteoarthritis Cartilage 2023; 31:819-828. [PMID: 36889626 DOI: 10.1016/j.joca.2023.02.073] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 02/18/2023] [Accepted: 02/22/2023] [Indexed: 03/10/2023]
Abstract
OBJECTIVE We primarily aimed to investigate whether there are phenotypic and genetic links underlying body mass index (BMI) and overall osteoarthritis (OA). We then intended to explore whether the relationships differ across sexes and sites. METHOD We first evaluated the phenotypic association between BMI and overall OA using data from the UK Biobank. We then investigated the genetic relationship leveraging summary statistics of the hitherto largest genome-wide association studies performed for BMI and overall OA. Finally, we repeated all analyses in a sex- (female, male) and site- (knee, hip, spine) specific manner. RESULTS Observational analysis suggested an increased hazard of diagnosed OA per 5 kg/m2 increment in BMI (hazard ratio = 1.38, 95% confidence interval (CI) = 1.37-1.39). A positive overall genetic correlation was observed for BMI and OA (rg = 0.43, P = 4.72 × 10-133), corroborated by 11 significant local signals. Cross-trait meta-analysis identified 34 pleiotropic loci shared between BMI and OA, of which seven were novel. Transcriptome-wide association study revealed 29 shared gene-tissue pairs, targeting nervous, digestive, and exo/endocrine systems. Mendelian randomization demonstrated a robust BMI-OA causal relationship (odds ratio = 1.47, 95% CI = 1.42-1.52). A similar pattern of effects was observed in sex- and site-specific analyses, with BMI affecting OA comparably in both sexes and most strongly in the knee. CONCLUSION Our work demonstrates an intrinsic relationship underlying BMI and overall OA, reflected by a pronounced phenotypic association, significant biological pleiotropy, and a putative causal link. Stratified analysis further reveals that the effects are distinct across sites and comparable across sexes.
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Affiliation(s)
- L Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - W Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - X Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - H Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - P Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - C Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - X Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - J Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - C Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - M Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - L Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - L Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Y Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - J Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Z Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - C Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - B Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - X Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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Chen B, Li M, Zhao H, Liao R, Lu J, Tu J, Zou Y, Teng X, Huang Y, Liu J, Huang P, Wu J. Effect of Multicomponent Intervention on Functional Decline in Chinese Older Adults: A Multicenter Randomized Clinical Trial. J Nutr Health Aging 2023; 27:1063-1075. [PMID: 37997729 DOI: 10.1007/s12603-023-2031-9] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 11/04/2023] [Indexed: 11/25/2023]
Abstract
OBJECTIVES To confirm whether multicomponent exercise following vivifrail recommendations was an effective method for improving physical ability, cognitive function, gait, balance, and muscle strength in Chinese older adults. METHODS This was a multicenter and randomized clinical trial conducted in Jiangsu, China, from April 2021 to April 2022. Intervention lasted for 12 weeks and 104 older adults with functional declines were enrolled. All participants were randomly assigned to a control (usual care plus health education) or exercise group (usual care plus health education plus exercise). Primary outcomes were the change score of Short Physical Performance Battery (SPPB) and activities of daily living (ADL). The secondary outcomes included instrumental activities of daily living, Tinetti scores, Frailty score, short-form Mini Nutritional Assessment, Mini-Mental State Examination, Geriatric Depression Scale-15, the 12-item Short Form Survey, 4-meter gait speed test, 6-min walking distance, grip strength, and body composition analysis. RESULTS Among the participants, the average age was 85 (82, 88) years. After 12 weeks of follow-up, the exercise group showed a significant improvement in SPPB, with a change of 2 points (95% confidence interval [0, 3.5], P<0.001) compared to control. In contrast, SPPB remained stable in the control group. Compared to the control group, ADL improved in the exercise group, as did instrumental activities of daily living, Tinetti, Frailty, Short Form Survey, 4-meter gait speed test, and 6-min walking distance. Although there was no significant difference between groups in body composition analysis after post-intervention, the exercise group still improved in soft lean mass (P=0.002), fat-free mass (P=0.002), skeletal muscle mass index (P<0.001), fat-free mass index (P=0.004), appendicular skeletal muscle mass (P<0.001), and leg muscle mass (P<0.001), while the control group had no significant increase. No difference was observed in adverse events during trial period. CONCLUSIONS The multicomponent exercise intervention following vivifrail recommendations is an effective method for older adults with functional decline and can reverse the functional decline and improve gait, balance, and muscle strength. Additionally, the 12-week multicomponent exercise method provides guidance for Chinese medical professionals working in the field of geriatrics and is a promising method to improve physical function in the general population.
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Affiliation(s)
- B Chen
- Jianqing Wu, Jiangsu Provincial Key Laboratory of Geriatrics, Department of Geriatrics, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu 210029, P.R. China, Fax: 011-86-25-83780170, Telephone number: 011-86-25-68305103, Email address:
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Liang Y, Wu M, Zou Y, Wan X, Liu Y, Liu X. Prevalence of suicide ideation, self-harm, and suicide among Chinese patients with schizophrenia: a systematic review and meta-analysis. Front Public Health 2023; 11:1097098. [PMID: 37200989 PMCID: PMC10186199 DOI: 10.3389/fpubh.2023.1097098] [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] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 04/04/2023] [Indexed: 05/20/2023] Open
Abstract
Aims Suicide ideation, self-harm, and suicide are common in patients with schizophrenia, but the reported prevalence vary largely across studies. Improved prevalence estimates and identification of moderators of the above self-directed violence are needed to enhance recognition and care, and to guide future management and research. This systematic review aims to estimate the pooled prevalence and identify moderators of suicide ideation, self-harm, and suicide among patients diagnosed with schizophrenia in China. Methods Relevant articles published until September 23, 2021, were searched using PubMed, EBSCO, Web of Science, Embase, Science Direct, CNKI, CBM, VIP, and Wanfang databases. Eligible studies published in English or Chinese which reported the prevalence of suicide ideation, self-harm, or suicide among Chinese patients with schizophrenia were collected. All studies passed a quality evaluation. This systematic review was registered with PROSPERO (registration number CRD42020222338). PRISMA guidelines were used in extracting and reporting data. Random-effects meta-analyses were generated using the meta package in R. Results A total of 40 studies were identified, 20 of which were evaluated as high-quality studies. Based on these studies, the prevalence of lifetime suicide ideation was 19.22% (95% CI: 7.57-34.50%), prevalence of suicide ideation at the time of investigation was 18.06% (95% CI: 6.49-33.67%), prevalence of lifetime self-harm was 15.77% (95% CI: 12.51-19.33%), and prevalence of suicide was 1.49% (95% CI: 0.00-7.95%). Multivariate meta-regression analysis revealed that age (β = - 0.1517, p = 0.0006) and dependency ratio (β = 0.0113, p < 0.0001) were associated with the lifetime prevalence of self-harm. Study assessment score (β = 0.2668, p < 0.0001) and dependency ratio (β = 0.0050, p = 0.0145) were associated with the lifetime prevalence of suicide ideation. Results of the spatial analysis showed that the prevalence of self-directed violence varied greatly across different provinces. Conclusion This systematic review provides estimates of the prevalence of self-directed violence among Chinese patients with schizophrenia and explores its moderators and spatial patterns. Findings also have important implications for allocating prevention and intervention resources to targeted high-risk populations in high prevalence areas.
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Affiliation(s)
- Yiying Liang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Manqi Wu
- Department of Social Medicine and Health Management, School of Public Health, Peking University, Beijing, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiaoyan Wan
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yuanyuan Liu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiang Liu
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- *Correspondence: Xiang Liu,
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Ghaderpour A, Jeong J, Kim Y, Zou Y, Park K, Hong E, Koh Y, Seong S. 335 HY209, a GPCR19 agonist, ameliorates atopic dermatitis in mice. J Invest Dermatol 2022. [DOI: 10.1016/j.jid.2022.09.348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Huang Y, Li JH, Wang X, Zou Y, Huang WF, Liu C, Zhang H. [Susceptibility study on the germline rare variants of bromodomain and extraterminal domain protein family-encoding genes and patients with cancer living in some regions of China]. Zhonghua Yi Xue Za Zhi 2022; 102:3374-3381. [PMID: 36372767 DOI: 10.3760/cma.j.cn112137-20220620-01352] [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] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To explore the relationship between germline rare variants of bromodomain and extraterminal domain (BET) protein family-encoding genes and susceptibility to cancer in some regions of China. Methods: Capturing probes were designed for bromodomain-containing protein 2 (BRD2), BRD3 and BRD4 genes, and Illumina high-throughput sequencing platform was used to conduct targeted sequencing of genomic DNA of peripheral blood leukocytes from 1 673 patients with cancer and 1 661 individuals without cancer recruited between October 2015 and July 2018 from Chinese PLA General Hospital, the Second Affiliated Hospital of Guangxi Medical University, People's Hospital of Macheng City, Hubei Province and Geneplus-Beijing Co. Ltd. Mutation detection and analysis were carried out according to the genome analysis toolkit (GATK) best practice guidelines, ANNOVAR and VEP software were used for annotation, and germline rare variants in BET family were screened. To determine potential pathogenic germline rare variants, clinical and experimental evidence was obtained from the ClinVar database and SIFT and Polyphen-2 softwares were used to predict pathogenicity. Fisher's exact test was used to compare the difference of the carrying rate of variants in the case group and the control group, and multivariate regression analysis was performed with the SKAT software with sex and age used as covariates. Results: Among the 1 673 cancer patients, 911 were males and 762 were females, with the mean age was (57.9±11.7) years. There were 1, 111 cases (66.4%) of lung cancer, 266 cases (15.9%) of colorectal cancer, 186 cases of breast cancer (11.1%), and 110 cases (6.6%) of esophagus or gastric cancer. In the same period 1, 661 non-tumor control individuals were recruited, including 821 males and 840 females, with the mean age was (44.5±13.9) years. It was observed that there were 4 potential pathogenic germline rare variants in BRD2 gene carried by 17 patients with cancer, 5 potential pathogenic germline rare variants in BRD3 gene and 8 potential pathogenic germline rare variants in BRD4 gene. The carrying rate of potential pathogenic germline rare variants in BRD2 gene in cancer patients was 1.02% (17/1 673), significantly higher than that in controls without cancer [0 (0/1 661); OR=+∞, 95%CI: 4.81-+∞, P<0.001]. The carrying rate of potential pathogenic germline rare variants in BRD3 gene in cancer patients was 0.24% (4/1 673), and the difference was not statistically significant compared with controls without cancer [0.12% (2/1 661); OR=1.99, 95%CI: 0.46-10.47, P=0.690]. The carrying rate of potential pathogenic germline rare variants in BRD4 gene in cancer patients was 0.18% (3/1 673), and the difference was not statistically significant compared with controls without cancer [0.36% (6/1 661); OR=0.50, 95%CI: 0.14-2.08, P=0.340]. Furthermore, the dataset of whole exome sequencing of Chinese individuals in "Huabiao Project" was used as an additional control, and the rate of carrying BRD2 rare variants in cancer patients was 17/3 346 (0.51%), significantly higher than that in controls without cancer [0.07% (3/4 154); OR=7.07, 95%CI: 2.32-22.83, P<0.001]. Among the 17 patients carrying 4 potentially pathogenic germline rare variants of BRD2 gene, 9 were patients with lung cancer, 6 were patients with colorectal cancer, 1 was patient with breast cancer, and 1 was patients with esophagus or gastric cancer. The carrying rate of potential pathogenic germline rare variants in BRD2 gene in lung cancer patients was 0.81 (9/1 111), significantly higher than that in controls without cancer [0(0/1 661); OR=+∞, 95%CI: 3.95-+∞,P<0.001]. The carrying rate of potential pathogenic germline rare variants in BRD2 gene in patients with colorectal cancer was 2.26% (6/266), significantly higher than that in controls without cancer [0(0/1 661); OR=+∞, 95%CI: 9.03-+∞, P<0.001]. Wilcoxon rank-sum test results showed that patients with colorectal cancer carrying BRD2 rare variants had an earlier age at diagnosis [(47.0±7.4) vs (57.2±12.1) years old, P=0.017]. Conclusions: BRD2 gene may be served as a candidate genetic susceptibility gene for lung cancer and colorectal cancer. Carrying BRD2 potential pathogenic germline rare variants is associated with higher risk of lung cancer and colorectal cancer, and with earlier age of colorectal cancer.
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Affiliation(s)
- Y Huang
- School of Basic Medicine, Anhui Medical University, Hefei 230032, China
| | - J H Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing 102206, China
| | - X Wang
- Department of Stomatology, the Third Medical Centre, Chinese PLA General Hospital, Beijng 100039, China
| | - Y Zou
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing 102206, China
| | - W F Huang
- Department of Oncology, the Second Affiliated Hospital of Guangxi Medical University, Nanning 530007, China
| | - C Liu
- Department of Orthopedics, People's Hospital of Macheng City, Hubei Province, Macheng 438300, China
| | - Hongxing Zhang
- School of Basic Medicine, Anhui Medical University, Hefei 230032, China
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Ng J, Chen L, Omelchenko Y, Zou Y, Lavraud B. Hybrid Simulations of the Cusp and Dayside Magnetosheath Dynamics Under Quasi-Radial Interplanetary Magnetic Fields. J Geophys Res Space Phys 2022; 127:e2022JA030359. [PMID: 36591323 PMCID: PMC9787681 DOI: 10.1029/2022ja030359] [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] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 09/28/2022] [Accepted: 10/03/2022] [Indexed: 06/17/2023]
Abstract
Under quasi-radial interplanetary magnetic fields (IMF), foreshock turbulence can have an impact on the magnetosheath and cusps depending on the location of the quasi-parallel shock. We perform three-dimensional simulations of Earth's dayside magnetosphere using the hybrid code HYPERS, and compare northward and southward quasi-radial IMF configurations. We study the magnetic field configuration, fluctuations in the magnetosheath and the plasma in the regions around the northern cusp. Under northward IMF with Earthward B x , there is a time-varying plasma depletion layer immediately outside the northern cusp. In the southward IMF case, the impact of foreshock turbulence and high-speed jets, together with magnetopause reconnection, can lead to strong density enhancements in the cusp.
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Affiliation(s)
- J. Ng
- Department of AstronomyUniversity of MarylandCollege ParkMDUSA
- NASA Goddard Space Flight CenterGreenbeltMDUSA
| | - L.‐J. Chen
- NASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Y. Omelchenko
- Trinum Research IncSan DiegoCAUSA
- Space Science InstituteBoulderCOUSA
| | - Y. Zou
- Department of Space ScienceUniversity of Alabama in HuntsvilleHuntsvilleALUSA
| | - B. Lavraud
- Laboratoire d'astrophysique de BordeauxCNRSUniversity BordeauxPessacFrance
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Wang L, Zou Y, Li S. [Analysis of the stressors and mental status of civil aviation pilots under the background of the major infectious disease]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2022; 40:688-693. [PMID: 36229216 DOI: 10.3760/cma.j.cn121094-20210802-00381] [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] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To study the stressors and mental status of civil aviation pilots under the background of major infectious disease. Methods: From January to March 2021, a cluster sampling method was used to select 143 airline pilots in service as the research objects. The self-made emotion and stress source questionnaire, Chinese version of stress perception scale (CPSS) , self rating Anxiety Scale (SAS) and self rating Depression Scale (SDS) were used to investigate the airline pilot population. 136 valid questionnaires were collected, with an effective recovery rate of 95.1%. The measurement data conform to the normal distribution and are expressed by (x±s) . T-test and analysis of variance are used for comparison between groups, and Pearson correlation is used for correlation analysis. The data that do not conform to the normal distribution are expressed by the median and quartile [M (Q(1), Q(3)) ], and the non parametric test is used for the comparison between groups. Multiple linear stepwise regression was used to analyze the influencing factors of pressure perception. In addition, Amos 23.0 software was used to construct structural equation models of stress perception and negative emotions. Results: Under the background of the epidemic, the main sources of stress for civil aviation pilots are: the risk of possible reduction in income, the risk of contracting COVID-19, the pressure at work, and the risk of possible slow progress of upgrading. Among them, the first co pilot was more worried about the possible reduction of income than the instructor (P=0.009) ; The first co pilot and the captain of the airline were more worried about the possible slowdown of the upgrade progress than the instructor (P<0.001, P=0.014) . The mean pressure perception of pilots was higher than that of Chinese norm (t=3.11, P=0.002) . The standard scores of anxiety and depression were slightly higher than the standard scores of the Chinese norm under the non epidemic situation (t=7.00, 4.07, all P<0.001) . The results of multiple linear stepwise regression analysis showed that stress perception was negatively correlated with good family relations (t=-8.50, P=0.000) , and positively correlated with worries about slow progress of upgrading, COVID-19 infection, lack of interpersonal communication and income reduction (t=3.31、3.86、2.88、2.06, P<0.05) . Pressure perception was positively correlated with negative emotion (all P<0.001) . The results of structural equation model show that stress perception affects pilots' negative emotions directly or indirectly, and its standardized total effects on anxiety, depression, hypochondriac, fear, compulsion and irritability are 0.719, 0.811, 0.403, 0.355, 0.295 and 0.244 respectively. Conclusion: Public health emergencies have an impact on the mental status of pilots. Should pay attention to the stressors and psychological conditions of pilots in time, and consider formulating measures to relieve the stress of pilots.
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Affiliation(s)
- L Wang
- Civil Aviation University Of China, Graduate School, Tianjin 300300, China
| | - Y Zou
- Civil Aviation University Of China, School of Safety Science and Engineering, Tianjin 300300, China
| | - S Li
- Civil Aviation University Of China, Flight Academy, Tianjin 300300, China
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Liu H, Zhao F, Chen J, Zou Y, Yu Y, Wang Y, Liu S, Tan H, Sa R, Xie J. Comparison of amino acid digestibility and its additivity determined with slaughter or cecectomy method for yellow-feather chicken. Poult Sci 2022; 101:102196. [PMID: 36272234 PMCID: PMC9579792 DOI: 10.1016/j.psj.2022.102196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 09/06/2022] [Accepted: 09/16/2022] [Indexed: 11/26/2022] Open
Abstract
The objective of this experiment was to compare the slaughter and cecectomy methods to determine amino acid (AA) digestibility of corn and soybean meal and their additivity in a corn-soybean meal diet. A completely randomized design was adopted to determine endogenous AA losses (EAAL) and AA digestibility in each of corn, soybean meal, and a corn-soybean meal diet using either slaughter or cecectomy methods. Each treatment contained 6 replicates with 3 chickens per replicate. The endogenous loss (EL) of histidine and glycine was lower and the EL of methionine and phenylalanine was greater when determined by slaughter vs. cecectomy (P < 0.05). The EL of arginine, isoleucine, leucine, lysine, methionine, phenylalanine, valine, alanine, aspartic acid, glutamic acid, and serine determined by slaughter were 1.2 to 3.2 times of those from cecectomy. The standard error (SE) of EL of 14 AA (excluding histidine and glycine) obtained by slaughter method was 2.1 to 9.6 times of those by cecectomy method. The apparent and standardized digestibility was not affected by methods for most AA except apparent digestibility of methionine, phenylalanine and glycine, and standardized digestibility of glycine in corn. The apparent and standardized digestibility of most AA except apparent digestibility of glycine and standardized digestibility of lysine, cysteine and glycine were less for slaughter versus cecectomy methods in soybean meal (P < 0.05). Using slaughter method resulted in reduced apparent digestibility of 15 AA (except glycine) and reduced standardized digestibility of 7 AA (arginine, isoleucine, leucine, valine, aspartic acid, glutamic acid, and proline) relative to cecectomy method (P < 0.05), but the standardized digestibility of glycine was greater when determined by slaughter vs. cecectomy methods in corn-soybean meal diet (P < 0.05). The mean value of SE of 16 AA digestibility in slaughter method was 2.9 times of that by cecectomy method. The apparent digestibility of 2 and 9 of 16 AA and the standardized digestibility of 15 and 7 of 16 AA were additive when using slaughter and cecectomy determinations, respectively. In conclusion, compared to the slaughter method, cecectomy method had less SE and EAAL but greater apparent digestibility of methionine and phenylalanine in corn, and the apparent digestibility of 15 AA (except glycine) in soybean meal and corn-soybean meal diet. Additivity in apparent and standardized AA digestibility was more inconsistent when determined with slaughter vs. cecectomy methods. These findings suggest that the cecectomy method is more suitable than the slaughter method to determine the digestibility of AA.
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Zou Y, Wu H, Zong SM, Xiao HJ. [Allergy in the pathogenesis of otitis media with effusion]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2022; 57:1016-1022. [PMID: 36058674 DOI: 10.3760/cma.j.cn115330-20210611-00346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Affiliation(s)
- Y Zou
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - H Wu
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - S M Zong
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - H J Xiao
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
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Li B, Tian S, Kolbe L, Zou Y, Wang S. 503 Skin multi-omics data analysis reveals in the impact of life stress on skin. J Invest Dermatol 2022. [DOI: 10.1016/j.jid.2022.05.512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Cheng K, Wang Y, Chen Y, Zhu J, Qi X, Wang Y, Zou Y, Lu Q, Li Z. Multisite Radiotherapy Combined With Tislelizumab for Metastatic Castration-Resistant Prostate Cancer With Second-Line and Above Therapy Failure: Study Protocol for an Open-Label, Single-Arm, Phase Ib/II Study. Front Oncol 2022; 12:888707. [PMID: 35875078 PMCID: PMC9300836 DOI: 10.3389/fonc.2022.888707] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/10/2022] [Indexed: 11/24/2022] Open
Abstract
Background Tislelizumab combined with radiotherapy as a salvage treatment for patients with end-stage metastatic castration-resistant prostate cancer (mCRPC) is not reported. This study aimed to describe a protocol to evaluate the safety and efficacy of multisite radiotherapy combined with tislelizumab as a salvage therapy for mCRPC in patients who had at least one second-line treatment failure. Methods The study included patients with mCRPC who had at least one lesion suitable for radiotherapy and failed androgen deprivation therapy (ADT), followed by at least one novel second-line endocrine therapy. All patients received tislelizumab monotherapy induction therapy for two cycles, then combined with multisite radiotherapy for one cycle, followed by tislelizumab maintenance therapy, until either disease progressed or the patient developed unacceptable toxicity. Radiation methods and lesions were individually selected according to the specified protocol. Primary endpoints included safety and objective response rate. Secondary endpoints included prostate-specific antigen (PSA) response rate, disease control rate, overall survival, radiographic progression-free survival (rPFS), and biochemical progression-free survival (bPFS). Furthermore, the exploratory endpoints included the identification of the predictive biomarkers and exploration of the correlation between biomarkers and the tumor response to the combined regimen. Discussion This study included three treatment stages to evaluate the efficacy of immunotherapy and the combination of immunotherapy and radiotherapy for patients with mCRPC who have had at least second-line treatment failure. Additionally, radiation-related and immune-related early and late toxicities were determined, respectively. Furthermore, the study also aimed to identify the predictive biomarkers associated with immunotherapy for treating mCRPC. Trial Registration https://www.chictr.org.cn/showproj.aspx?proj=126359, identifier ChiCTR2100046212.
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Affiliation(s)
- Ke Cheng
- Department of Abdominal Oncology, West China Hospital, Sichuan University, Chengdu, China
| | - Yuqing Wang
- State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Ye Chen
- Department of Abdominal Oncology, West China Hospital, Sichuan University, Chengdu, China
| | - Jingjie Zhu
- West China School of Public Health, Sichuan University, Chengdu, China
| | - Xiaohui Qi
- Laboratory of Clinical Pharmacy and Adverse Drug Reaction, West China Hospital, Sichuan University, Chengdu, China
| | - Yachen Wang
- West China School of Public Health, Sichuan University, Chengdu, China
| | - Yanqiu Zou
- West China School of Public Health, Sichuan University, Chengdu, China
| | - Qiuhan Lu
- West China School of Public Health, Sichuan University, Chengdu, China
| | - Zhiping Li
- Department of Radiotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Zhiping Li,
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Wu H, Zou Y, Zong SM, Xiao HJ. [Research advances in cochlear blood-labyrinth barrier in stria vascularis]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2022; 57:769-773. [PMID: 35725327 DOI: 10.3760/cma.j.cn115330-20210710-00448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Affiliation(s)
- H Wu
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Y Zou
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - S M Zong
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - H J Xiao
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
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Ruan WC, Li J, Zhang YJ, Zheng SS, Wang D, Yu H, Chen JP, Bao YY, Shao L, Fu LL, Zou Y, Hua J, Li HF. [Investigate developmental coordination disorder of kindergarten children in Zhejiang Province]. Zhonghua Yu Fang Yi Xue Za Zhi 2022; 56:838-842. [PMID: 35785866 DOI: 10.3760/cma.j.cn112150-20210719-00691] [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] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In order to investigate developmental coordination disorder (DCD) of kindergarten children in Zhejiang province, 200 ordinary kindergartens were randomly selected by stratified random sampling in 11 prefecture-level cities of Zhejiang Province, and 38 900 children from 1 000 classes in each grade were then randomly selected into the study from June 2019 to December 2019. The Little DCD Questionnaire and a self-designed questionnaire were used to screen the DCD of those children. There were 36 807 valid questionnaires, and 6.50% (2 391/36 807) of them were positive results. The results showed that boy, age ≤5 years, overweight or obesity, left handedness, comorbidity with motor or developmental disorders and premature infants were risk factors of DCD in children. As for parents and families, maternal gestational age<20 years, maternal overweight or obesity before pregnancy, low-middle level education of parents, direct family and low income of family were also associated with DCD in children. Therefore, it is necessary to conduct early prevention and intervention strategies targeting on identified risk factors among relevant population.
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Affiliation(s)
- W C Ruan
- Department of Rehabilitation, the Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - J Li
- Jiaxing Maternity and Child Health Care Hospital, Jiaxing 314050, China
| | - Y J Zhang
- The Second People's Hospital of Haining, Haining 314419, China
| | - S S Zheng
- Wenling Women's and Children's Hospital, Wenling 317599, China
| | - D Wang
- Yiwu Maternity and Children Hospital, Yiwu 322099, China
| | - H Yu
- Shaoxing Maternity and Child Health Care Hospital, Shaoxing 312099, China
| | - J P Chen
- The Women and Children Hospital of Dongyang, Dongyang 322199, China
| | - Y Y Bao
- Kindergarten of Hangzhou Normal University, Hangzhou 310012, China
| | - L Shao
- Jinhua Maternal and Child Health Care Hospital, Jinhua 321099, China
| | - L L Fu
- Pujiang Maternity and Child Health Care Hospital, Pujiang 322299, China
| | - Y Zou
- Zhejiang Center for Disease Control and Prevention, Hangzhou 310057, China
| | - J Hua
- Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai 200040, China
| | - H F Li
- Department of Rehabilitation, the Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
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Chang L, zhang L, An W, wan Y, cai Y, Lan Y, Ruan M, liu X, Zou Y, Zhu X. P814: CLINICAL CHARACTERISTICS AND GENE MUTATION ANALYSIS OF 148 CHILDREN WITH FANCONI ANEMIA IN CHINA. Hemasphere 2022. [PMCID: PMC9431339 DOI: 10.1097/01.hs9.0000846140.75399.5d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Zou Y. M015 Establishing and verifying a very rapid inductively coupled plasma-mass spectrometry method to determine iodine concentrations in amniotic fluid, breast milk and cerebrospinal fluid. Clin Chim Acta 2022. [DOI: 10.1016/j.cca.2022.04.306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Zou Y, Weishaupt L, Enger S. SP-0014 McMedHacks: Deep learning for medical image analysis workshops and Hackathon in radiation oncology. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)03869-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Cao J, Xu W, Liu Y, Zhang B, Zhang Y, Yu T, Huang T, Zou Y, Zhang B. Trends in maternal age and the relationship between advanced age and adverse pregnancy outcomes: a population-based register study in Wuhan, China, 2010–2017. Public Health 2022; 206:8-14. [DOI: 10.1016/j.puhe.2022.02.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 01/24/2022] [Accepted: 02/09/2022] [Indexed: 10/18/2022]
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41
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Zou Y. W160 Evaluation of the urine and serum iodine status in Tibet, China: A multicenter study. Clin Chim Acta 2022. [DOI: 10.1016/j.cca.2022.04.918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Honglei L, Wang D, Zou Y, Qiu L. M135 Source of variation evaluation of specific proteins in apparently healthy Tibetan Chinese adults: A multicenter cross-sectional study. Clin Chim Acta 2022. [DOI: 10.1016/j.cca.2022.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Deng Y, Wang W, Zheng Q, Feng Y, Zou Y, Dong H, Tan Z, Zeng X, Zhao Y, Peng D, Yang X, Sun A. Menopausal hormone therapy: what are the problems in the perception of Chinese physicians? Climacteric 2022; 25:413-420. [PMID: 35438051 DOI: 10.1080/13697137.2022.2058391] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
OBJECTIVE This study aimed to investigate Chinese physicians' perception and attitudes toward menopausal hormone therapy (MHT). METHODS This nationwide online survey was conducted in China. Physicians registered in the WeChat groups of the Gynecological Endocrinology Committee of China's Maternal and Child Health Care Association received a message invitation to complete this anonymous online survey from April 2020 to July 2020. Physicians' knowledge of and attitudes toward MHT were surveyed. RESULTS In total, 4672 questionnaires were submitted; only completed questionnaires could be submitted. The message was sent to 6021 doctors, so the response rate was 77.6%. Overall, 77.9-92.9% of physicians knew the common indications and contraindications to MHT. Additionally, 90.6%, 85.4%, 80.7% and 37.5% of physicians thought that MHT would increase the risk of venous thrombosis, breast cancer, endometrial cancer and weight gain, respectively. In total, 58.1% of the physicians mistakenly believed that a sex hormone test was one of the necessary examinations to reassess MHT prescription during follow-up visits. We found that 68.5% of physicians would consider using MHT themselves or recommend MHT to their partners in the future, and 11.4% were currently using MHT. CONCLUSIONS Most Chinese physicians have basic knowledge of MHT. Their misunderstandings about MHT mainly centered on the risks of endometrial cancer, weight gain and the necessary examinations during follow-up visits. These misunderstandings need to be clarified in future professional training programs.
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Affiliation(s)
- Y Deng
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - W Wang
- Department of Reproductive Medicine, The Second Hospital of Hebei Medical University, Hebei, China
| | - Q Zheng
- Department of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Shandong, China
| | - Y Feng
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Nanchang University, JiangXi, China
| | - Y Zou
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Hunan, China
| | - H Dong
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Jinzhou, Liaoning, China
| | - Z Tan
- Department of Obstetrics and Gynecology, Xinhui Maternity and Children's Hospital, Guangxi, China
| | - X Zeng
- Department of Gynecology, Guangzhou Women and Children's Medical Centre, Guangdong, China
| | - Y Zhao
- Department of Obstetrics and Gynecology, Xinhui Maternity and Children's Hospital, Guangxi, China
| | - D Peng
- Department of Obstetrics and Gynecology, Zhongda Hospital Southeast Univeisity, Jiangsu, China
| | - X Yang
- Department of Obstetrics and Gynecology, Liuzhou Maternity and Child Healthcare Hospital, GuangXi, China
| | - A Sun
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
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Hu X, Zou Y, Chen HJ, He X, Zhang HY. [Spindle cell hemangioma: a clinicopathological and molecular analysis of eight cases]. Zhonghua Bing Li Xue Za Zhi 2022; 51:196-201. [PMID: 35249281 DOI: 10.3760/cma.j.cn112151-20211102-00794] [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] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To investigate the clinicopathological and genetic characteristics of spindle cell hemangioma (SCH). Methods: The clinical, morphological and immunohistochemical features of 8 SCHs diagnosed from January 2013 to September 2021 in West China Hospital, Sichuan University, Chengdu, China were retrospectively analyzed. Hotspot mutations for IDH1 codon 132 and IDH2 codon 172 were tested in 4 SCHs and 29 other non-SCH lesions using Sanger sequencing. Results: The 8 cases occurred in patients with a wide age range, from neonate to 46 years (mean 28 years, median 32 years). Both genders were equally affected. The course of the disease spanned from half a year to 31 years. Two SCHs were recurrent tumors. All tumors involved the distal extremities (4 of foot, 2 of ankle and 2 of hand). Six cases were presented as a single lesion and 2 cases as multiple lesions. The tumor diameters were 1-5 cm. All the 8 SCHs were typically composed of cavernous vascular space and solid components consisting of slit-like vessels, spindle cells and epithelioid endothelial cells which often exhibited cytoplasmic vacuolation. These two alternating components and the vacuolated epithelioid endothelial cells were the distinctive diagnostic clues for SCH. Vascular endothelial cells including epithelioid cells in the solid areas expressed CD31 (8/8), ERG (4/4), CD34 (5/8) and D2-40 (2/3). The spindle cells expressed SMA (8/8). Neither endothelial cells nor spindle cells expressed HHV8 (0/7), Desmin (0/5) or S-100 (0/3). Mutations were revealed in 2 SCHs, with IDH1 mutation (p.R132C) and IDH2 mutation (p.R172G), respectively. The IDH1/2 gene hotspot mutations were not found in the remaining 2 SCHs or the other 29 non-SCH lesions. Simple excisions were performed for 7 cases, and partial resection for 1 case. Follow-up information was obtained in 6 cases, with follow-up time ranging from 5 to 90 months (average, 46 months). No metastasis occurred in the 6 cases. No recurrence occurred in cases treated with simple excision. The residual lesions of the patient who received partial resection were stable. Conclusions: SCH is rare and should be differentiated from a variety of benign and malignant vascular lesions. An accurate diagnosis of SCH is clinically important and can be achieved by combining clinical information and typical pathological presentation. IDH1/2 gene hotspot mutations are specific to SCH in vascular lesions. Genetic detection is helpful in the diagnosis of challenging cases.
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Affiliation(s)
- X Hu
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Y Zou
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - H J Chen
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - X He
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - H Y Zhang
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
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ZHAN Y, He X, Pu L, Zou Y, He Q, Hong D, Li G. POS-197 INVESTIGATION ON THE ACHIEVEMENT OF CKD-MBD SERUM INDICATORS OF HEMODIALYSIS PATIENTS IN SICHUAN PROVINCE. Kidney Int Rep 2022. [DOI: 10.1016/j.ekir.2022.01.215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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46
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Song Y, Chen J, Yang X, Zhang D, Zou Y, Ni D, Ye J, Yu Z, Chen Q, Jin S, Liang P. Fabrication of Fe3O4@Ag magnetic nanoparticles for highly active SERS enhancement and paraquat detection. Microchem J 2022. [DOI: 10.1016/j.microc.2021.107019] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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47
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Wang S, Zhou C, Cai C, Zhu H, Wang N, Zou Y. Experimental research on convective heat transfer characteristics of molten salt in a pebble bed channel with internal heat source. Nuclear Engineering and Design 2022. [DOI: 10.1016/j.nucengdes.2021.111619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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48
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Lou W, Zhang H, Luo H, Chen Z, Shi R, Guo X, Zou Y, Liu L, Brito LF, Guo G, Wang Y. Genetic analyses of blood β-hydroxybutyrate predicted from milk infrared spectra and its association with longevity and female reproductive traits in Holstein cattle. J Dairy Sci 2022; 105:3269-3281. [PMID: 35094854 DOI: 10.3168/jds.2021-20389] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 11/16/2021] [Indexed: 11/19/2022]
Abstract
Ketosis is one of the most prevalent and complex metabolic disorders in high-producing dairy cows and usually detected through analyses of β-hydroxybutyrate (BHB) concentration in blood. Our main objectives were to evaluate genetic parameters for blood BHB predicted based on Fourier-transform mid-infrared spectra from 5 to 305 d in milk, and estimate the genetic relationships of blood BHB with 7 reproduction traits and 6 longevity traits in Holstein cattle. Predicted blood BHB records of 11,609 Holstein cows (after quality control) were collected from 2016 to 2019 and used to derive 4 traits based on parity number, including predicted blood BHB in all parities (BHBp), parity 1 (BHB1), parity 2 (BHB2), and parity 3+ (BHB3). Single- and multitrait repeatability models were used for estimating genetic parameters for the 4 BHB traits. Random regression test-day models implemented via Bayesian inference were used to evaluate the daily genetic feature of BHB variability. In addition, genetic correlations were calculated for the 4 BHB traits with reproduction and longevity traits. The heritability estimates of BHBp, BHB1, BHB2, and BHB3 ranged from 0.100 ± 0.026 (± standard error) to 0.131 ± 0.023. The BHB in parities 1 to 3+ were highly genetically correlated and ranged from 0.788 (BHB1 and BHB2) to 0.911 (BHB1 and BHB3). The daily heritability of BHBp ranged from 0.069 to 0.195, higher for the early and lower for the later lactation periods. A similar trend was observed for BHB1, BHB2, and BHB3. There are low direct genetic correlations between BHBp and selected reproductive performance and longevity traits, which ranged from -0.168 ± 0.019 (BHBp and production life) to 0.157 ± 0.019 (BHBp and age at first calving) for the early lactation stage (5 to 65 d). These direct genetic correlations indicate that cows with higher BHBp (greater likelihood of having ketosis) in blood usually have shorter production life (-0.168 ± 0.019). Cows with higher fertility and postpartum recovery, such as younger age at first calving (0.157 ± 0.019) and shorter interval from calving to first insemination in heifer (0.111 ± 0.006), usually have lower BHB concentration in the blood. Furthermore, the direct genetic correlations change across parity and lactation stage. In general, our results suggest that selection for lower predicted BHB in early lactation could be an efficient strategy for reducing the incidence of ketosis as well as indirectly improving reproductive and longevity performance in Holstein cattle.
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Affiliation(s)
- W Lou
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - H Zhang
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - H Luo
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Z Chen
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - R Shi
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; Animal Breeding and Genomics Group, Wageningen University & Research, PO Box 338, 6700 AH Wageningen, the Netherlands
| | - X Guo
- Center of Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark
| | - Y Zou
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - L Liu
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - L F Brito
- Department of Animal Science, Purdue University, West Lafayette, IN 47907
| | - G Guo
- Beijing Sunlon Livestock Development Company Limited, Beijing, 10029, China
| | - Y Wang
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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Hu J, Zou Y, Sun B, Yu X, Shang Z, Huang J, Jin S, Liang P. Raman spectrum classification based on transfer learning by a convolutional neural network: Application to pesticide detection. Spectrochim Acta A Mol Biomol Spectrosc 2022; 265:120366. [PMID: 34509888 DOI: 10.1016/j.saa.2021.120366] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [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: 08/02/2021] [Revised: 08/28/2021] [Accepted: 09/02/2021] [Indexed: 06/13/2023]
Abstract
Pesticide detection is of tremendous importance in agriculture, and Raman spectroscopy/Surface-Enhanced Raman Scattering (SERS) has proven extremely effective as a stand-alone method to detect pesticide residues. Machine learning may be able to automate such detection, but conventional algorithms require a complete database of Raman spectra, which is not feasible. To bypass this problem, the present study describes a transfer learning method that improves the algorithm's accuracy and speed to extract features and classify Raman spectra. The transfer learning model described here was developed through the following steps: (1) the classification model was pre-trained using an open-source Raman spectroscopy database; (2) the feature extraction layer was saved after training; and (3) the training model for the Raman spectroscopy database was re-established while using self-tested pesticides and keeping the feature extraction layer unchanged. Three models were evaluated with or without transfer learning: CNN-1D, Resnet-1D, and Inception-1D, and they have improved the accuracy of spectrum classification by 6%, 2%, and 3%, with reduced training time and increased curve smoothness. These results suggest that transfer learning can improve the feature extraction capability and therefore accuracy of Raman spectroscopy models, expanding the range of Raman-based applications where transfer learning model can be used to identify the spectra of different substances.
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Affiliation(s)
- Jiaqi Hu
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018 China; Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yanqiu Zou
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018 China
| | - Biao Sun
- School of Electrical and Information Engineering, Tianjin University, 300000 Tianjin, China
| | - Xinyao Yu
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018 China
| | - Ziyang Shang
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018 China
| | - Jie Huang
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018 China
| | - Shangzhong Jin
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018 China
| | - Pei Liang
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018 China.
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50
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Zhao L, Zhang Y, Liu F, Yang H, Zhong Y, Wang Y, Li S, Su Q, Tang L, Bai L, Ren H, Zou Y, Wang S, Zheng S, Xu H, Li L, Zhang J, Chai Z, Cooper ME, Tong N. Urinary complement proteins and risk of end-stage renal disease: quantitative urinary proteomics in patients with type 2 diabetes and biopsy-proven diabetic nephropathy. J Endocrinol Invest 2021; 44:2709-2723. [PMID: 34043214 PMCID: PMC8572220 DOI: 10.1007/s40618-021-01596-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 05/18/2021] [Indexed: 02/05/2023]
Abstract
PURPOSE To investigate the association between urinary complement proteins and renal outcome in biopsy-proven diabetic nephropathy (DN). METHODS Untargeted proteomic and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses and targeted proteomic analysis using parallel reaction-monitoring (PRM)-mass spectrometry was performed to determine the abundance of urinary complement proteins in healthy controls, type 2 diabetes mellitus (T2DM) patients, and patients with T2DM and biopsy-proven DN. The abundance of each urinary complement protein was individually included in Cox proportional hazards models for predicting progression to end-stage renal disease (ESRD). RESULTS Untargeted proteomic and functional analysis using the KEGG showed that differentially expressed urinary proteins were primarily associated with the complement and coagulation cascades. Subsequent urinary complement proteins quantification using PRM showed that urinary abundances of C3, C9, and complement factor H (CFAH) correlated negatively with annual estimated glomerular filtration rate (eGFR) decline, while urinary abundances of C5, decay-accelerating factor (DAF), and CD59 correlated positively with annual rate of eGFR decline. Furthermore, higher urinary abundance of CFAH and lower urinary abundance of DAF were independently associated with greater risk of progression to ESRD. Urinary abundance of CFAH and DAF had a larger area under the curve (AUC) than that of eGFR, proteinuria, or any pathological parameter. Moreover, the model that included CFAH or DAF had a larger AUC than that with only clinical or pathological parameters. CONCLUSION Urinary abundance of complement proteins was significantly associated with ESRD in patients with T2DM and biopsy-proven DN, indicating that therapeutically targeting the complement pathway may alleviate progression of DN.
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Affiliation(s)
- L Zhao
- Division of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- Division of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Y Zhang
- Key Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- West China-Washington Mitochondria and Metabolism Research Center, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- Frontiers Science Center for Disease-Related Molecular Network, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
| | - F Liu
- Division of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
- Division of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
- Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
| | - H Yang
- Key Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
- West China-Washington Mitochondria and Metabolism Research Center, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
- Frontiers Science Center for Disease-Related Molecular Network, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
| | - Y Zhong
- Key Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- West China-Washington Mitochondria and Metabolism Research Center, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- Frontiers Science Center for Disease-Related Molecular Network, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
| | - Y Wang
- Division of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- Division of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - S Li
- Division of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Q Su
- Division of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - L Tang
- Histology and Imaging Platform, Core Facility of West China Hospital, Chengdu, Sichuan, China
| | - L Bai
- Histology and Imaging Platform, Core Facility of West China Hospital, Chengdu, Sichuan, China
| | - H Ren
- Division of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- Division of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Y Zou
- Division of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- Division of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - S Wang
- Key Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- West China-Washington Mitochondria and Metabolism Research Center, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- Frontiers Science Center for Disease-Related Molecular Network, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
| | - S Zheng
- Key Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- West China-Washington Mitochondria and Metabolism Research Center, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
- Frontiers Science Center for Disease-Related Molecular Network, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China
| | - H Xu
- Division of Pathology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - L Li
- Division of Pathology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - J Zhang
- Histology and Imaging Platform, Core Facility of West China Hospital, Chengdu, Sichuan, China
| | - Z Chai
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, Australia
| | - M E Cooper
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, Australia
| | - N Tong
- Division of Endocrinology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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