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Ge X, Zhang L, Liu M, Wang X, Xu X, Yan Y, Tian C, Yang J, Ding Y, Yu C, Lu J, Jiang L, Wang Q, Zhang Q, Song C. Association of Mosaic Chromosomal Alterations and Genetic Factors with the Risk of Cirrhosis. J Clin Transl Hepatol 2024; 12:562-570. [PMID: 38974956 PMCID: PMC11224905 DOI: 10.14218/jcth.2023.00575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 04/07/2024] [Accepted: 04/11/2024] [Indexed: 07/09/2024] Open
Abstract
Background and Aims Age-related mosaic chromosomal alterations (mCAs) detected from genotyping of blood-derived DNA are structural somatic variants that indicate clonal hematopoiesis. This study aimed to investigate whether mCAs contribute to the risk of cirrhosis and modify the effect of a polygenic risk score (PRS) on cirrhosis risk prediction. Methods mCA call sets of individuals with European ancestry were obtained from the UK Biobank. The PRS was constructed based on 12 susceptible single-nucleotide polymorphisms for cirrhosis. Cox proportional hazard models were applied to evaluate the associations between mCAs and cirrhosis risk. Results Among 448,645 individuals with a median follow-up of 12.5 years, we identified 2,681 cases of cirrhosis, 1,775 cases of compensated cirrhosis, and 1,706 cases of decompensated cirrhosis. Compared to non-carriers, individuals with copy-neutral loss of heterozygosity mCAs had a significantly increased risk of cirrhosis (hazard ratio (HR) 1.42, 95% confidence interval (CI) 1.12-1.81). This risk was higher in patients with expanded cell fractions of mCAs (cell fractions ≥10% vs. cell fractions <10%), especially for the risk of decompensated cirrhosis (HR 2.03 [95% CI 1.09-3.78] vs. 1.14 [0.80-1.64]). In comparison to non-carriers of mCAs with low genetic risk, individuals with expanded copy-neutral loss of heterozygosity and high genetic risk showed the highest cirrhosis risk (HR 5.39 [95% CI 2.41-12.07]). Conclusions The presence of mCAs is associated with increased susceptibility to cirrhosis risk and could be combined with PRS for personalized cirrhosis risk stratification.
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Affiliation(s)
- Xinyuan Ge
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Lu Zhang
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Maojie Liu
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiao Wang
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- The Dumont-UCLA Transplant Center, Division of Liver and Pancreas Transplantation, Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Xin Xu
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yuqian Yan
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chan Tian
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Juan Yang
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yang Ding
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chengxiao Yu
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Health Promotion Center, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, Jiangsu, China
| | - Jing Lu
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Health Promotion Center, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, Jiangsu, China
| | - Longfeng Jiang
- Department of Infectious Disease, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Qiang Wang
- Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden
| | - Qun Zhang
- Department of Health Promotion Center, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, Jiangsu, China
| | - Ci Song
- Department of Epidemiology, China International Cooperation Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Health Promotion Center, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, Jiangsu, China
- Changzhou Medical Center, Nanjing Medical University, Nanjing, Jiangsu, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
- Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
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Zhang R, Lu Y, Bian Z, Zhou S, Xu L, Jiang F, Yuan S, Tan X, Chen X, Ding Y, Li X. Sleep, physical activity, and sedentary behaviors in relation to overall cancer and site-specific cancer risk: A prospective cohort study. iScience 2024; 27:109931. [PMID: 38974470 PMCID: PMC11225818 DOI: 10.1016/j.isci.2024.109931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 02/20/2024] [Accepted: 05/05/2024] [Indexed: 07/09/2024] Open
Abstract
Large prospective studies are required to better elucidate the associations of physical activity, sedentary behaviors (SBs), and sleep with overall cancer and site-specific cancer risk, accounting for the interactions with genetic predisposition. The study included 360,271 individuals in UK Biobank. After a median follow-up of 12.52 years, we found higher total physical activity (TPA) level and higher sleep scores were related to reduced risk of cancer while higher SB level showed a positive association with cancer. Compared with high TPA-healthy sleep group and low SB-healthy sleep group, low TPA-poor sleep group and high SB-poor sleep group had the highest risk for overall cancer, breast cancer, and lung cancer. Adherence to a more active exercise pattern was associated with a lower risk of cancer irrespective of genetic risk. Our study suggests that improving the quality of sleep and developing physical activity habits might yield benefits in mitigating the cancer risk.
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Affiliation(s)
- Rongqi Zhang
- Department of Big Data in Health Science School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Ying Lu
- Department of Big Data in Health Science School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zilong Bian
- Department of Big Data in Health Science School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Siyun Zhou
- Department of Big Data in Health Science School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Liying Xu
- Department of Big Data in Health Science School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Fangyuan Jiang
- Department of Big Data in Health Science School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Shuai Yuan
- Institute of Environmental Medicine, Karolinska Institutet, Solna, Stockholm, Sweden
| | - Xiao Tan
- Department of Big Data in Health Science, School of Public Health and Department of Psychiatry Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Xiangjun Chen
- Institute of Translational Medicine, Zhejiang University School of Medicine, 268 Kaixuan Road, Hangzhou 310020, China
| | - Yuan Ding
- Department of Hepatobiliary and Pancreatic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xue Li
- Department of Big Data in Health Science School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
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Zhang X, Zhang S, Zhang H, Xiong Z, Li Y, Li L, Pi X, Liu H. Feasibility and Acceptability Evaluation of a Digital Therapeutic Program for Improving Cancer Prevention: A Quasi-experimental Pre-post Interventional Pilot Study. JOURNAL OF CANCER EDUCATION : THE OFFICIAL JOURNAL OF THE AMERICAN ASSOCIATION FOR CANCER EDUCATION 2024:10.1007/s13187-024-02431-y. [PMID: 38898222 DOI: 10.1007/s13187-024-02431-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/23/2024] [Indexed: 06/21/2024]
Abstract
Previous studies have proved that healthy behaviors hinder the onset and progression of tumors. Digital therapeutics (DTx), playing a pivotal role in facilitating behavioral adjustments through educational interventions, lifestyle support, and symptom monitoring, contribute to the goal of tumor prevention. We aim to optimize the evaluation of the feasibility and acceptability of DTx for cancer prevention. This involves assessing AITI's daily activity rates and user feedback, and comparing changes in behavioral habits and differences in SF-36 before and after the intervention. In a 4-week trial with 57 participants engaging actively, we found both the average daily activity rate and 4-week retention rate at 35 (61.4%). The USE Questionnaire scores (validity, ease of use, acquisition, and satisfaction) ranged from 68.06 to 83.10, indicating AITI's user-friendliness and acceptability. Furthermore, positive habit changes were noted among participants in exercise and diet (p < 0.0001), suggesting the effectiveness of the DTx approach in modifying behavioral habits related to physical activity and nutrition. This pilot study underscores the potential of DTx in advancing cancer prevention. However, larger and longer studies are needed to comprehensively assess its impact.
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Affiliation(s)
- Xianwei Zhang
- Key Laboratory of Biorheological Science and Technology of Ministry of Education, College of Bioengineering, Chongqing University, No. 174 Shazheng Road, Shapingba District, Chongqing, 400044, China
| | - Sheng Zhang
- Key Laboratory of Biorheological Science and Technology of Ministry of Education, College of Bioengineering, Chongqing University, No. 174 Shazheng Road, Shapingba District, Chongqing, 400044, China
| | - Haiyan Zhang
- Key Laboratory of Biorheological Science and Technology of Ministry of Education, College of Bioengineering, Chongqing University, No. 174 Shazheng Road, Shapingba District, Chongqing, 400044, China
| | - Ziyou Xiong
- Key Laboratory of Biorheological Science and Technology of Ministry of Education, College of Bioengineering, Chongqing University, No. 174 Shazheng Road, Shapingba District, Chongqing, 400044, China
| | - Yi Li
- Key Laboratory of Biorheological Science and Technology of Ministry of Education, College of Bioengineering, Chongqing University, No. 174 Shazheng Road, Shapingba District, Chongqing, 400044, China
| | - Lufeng Li
- Department of Infectious Diseases, Southwest Hospital, Army Medical University, Gaotan Rock, 30 Main Street, Chongqing, China.
| | - Xitian Pi
- Key Laboratory of Biorheological Science and Technology of Ministry of Education, College of Bioengineering, Chongqing University, No. 174 Shazheng Road, Shapingba District, Chongqing, 400044, China.
| | - Hongying Liu
- Key Laboratory of Biorheological Science and Technology of Ministry of Education, College of Bioengineering, Chongqing University, No. 174 Shazheng Road, Shapingba District, Chongqing, 400044, China.
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Zhang Y, Li Y, Peila R, Wang T, Xue X, Kaplan RC, Dannenberg AJ, Qi Q, Rohan TE. Associations of Lifestyle and Genetic Risks with Obesity and Related Chronic Diseases in the UK Biobank: A Prospective Cohort Study. Am J Clin Nutr 2024; 119:1514-1522. [PMID: 38677521 DOI: 10.1016/j.ajcnut.2024.04.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 04/01/2024] [Accepted: 04/24/2024] [Indexed: 04/29/2024] Open
Abstract
BACKGROUND Interplay between lifestyle risk scores (LRSs) and genetic risk scores (GRSs) on obesity and related chronic diseases are underinvestigated and necessary for understanding obesity causes and developing prevention strategies. OBJECTIVES This study aimed to investigate independent and joint associations and interactions of LRS and GRS with obesity prevalence and risks of diabetes, cardiovascular disease (CVD), and obesity-related cancer. METHODS In this cohort study of 444,957 UK Biobank participants [age: 56.5 ± 8.1 y; BMI (in kg/m2): 27.4 ± 4.7], LRS included physical activity, dietary score, sedentary behavior, sleep duration, and smoking (range: 0-20, each factor had 5 levels). GRS was calculated based on 941 genetic variants related to BMI. Both scores were categorized into quintiles. Obesity (n = 106,301) was defined as baseline BMI ≥30. Incident diabetes (n = 16,311), CVD (n = 18,076), and obesity-related cancer (n = 17,325) were ascertained through linkage to registries over a median of 12-y follow-up. RESULTS The LRS and GRS were independently positively associated with all outcomes. Additive interactions of LRS and GRS were observed for all outcomes (P < 0.021). Comparing the top with bottom LRS quintile, prevalence differences (95% CIs) for obesity were 17.8% (15.9%, 19.7%) in the top GRS quintile and 10.7% (8.3%, 13.1%) in the bottom GRS quintile; for diabetes, CVD, and obesity-related cancer, incidence rate differences associated with per SD increase in LRS were greater in the top than that in the bottom GRS quintile. Participants from top quintiles of both LRS and GRS had 6.16-fold, 3.81-fold, 1.56-fold, and 1.44-fold higher odds/risks of obesity, diabetes, CVD, and obesity-related cancer, respectively, than those from bottom quintiles of both scores. CONCLUSIONS Higher LRS was associated with higher obesity prevalence and risks of related chronic diseases regardless of GRS, highlighting the broad benefits of healthy lifestyles. Additive gene-lifestyle interactions emphasize the public health importance of lifestyle interventions among people with high genetic risks.
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Affiliation(s)
- Yanbo Zhang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Yang Li
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Rita Peila
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Tao Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Xiaonan Xue
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | | | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States.
| | - Thomas E Rohan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States.
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5
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Bian Z, Zhang R, Yuan S, Fan R, Wang L, Larsson SC, Theodoratou E, Zhu Y, Wu S, Ding Y, Li X. Healthy lifestyle and cancer survival: A multinational cohort study. Int J Cancer 2024; 154:1709-1718. [PMID: 38230569 DOI: 10.1002/ijc.34846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 12/11/2023] [Accepted: 12/19/2023] [Indexed: 01/18/2024]
Abstract
Lifestyle factors after a cancer diagnosis could influence the survival of cancer 60 survivors. To examine the independent and joint associations of healthy lifestyle factors with mortality outcomes among cancer survivors, four prospective cohorts (National Health and Nutrition Examination Survey [NHANES], National Health Interview Survey [NHIS], UK Biobank [UKB] and Kailuan study) across three countries. A healthy lifestyle score (HLS) was defined based on five common lifestyle factors (smoking, alcohol drinking, diet, physical activity and body mass index) that related to cancer survival. We used Cox proportional hazards regression to estimate the hazard ratios (HRs) for the associations of individual lifestyle factors and HLS with all-cause and cancer mortality among cancer survivors. During the follow-up period of 37,095 cancer survivors, 8927 all-cause mortality events were accrued in four cohorts and 4449 cancer death events were documented in the UK and US cohorts. Never smoking (adjusted HR = 0.77, 95% CI: 0.69-0.86), light alcohol consumption (adjusted HR = 0.86, 95% CI: 0.82-0.90), adequate physical activity (adjusted HR = 0.90, 95% CI: 0.85-0.94), a healthy diet (adjusted HR = 0.69, 95% CI: 0.61-0.78) and optimal BMI (adjusted HR = 0.89, 95% CI: 0.85-0.93) were significantly associated with a lower risk of all-cause mortality. In the joint analyses of HLS, the HR of all-cause and cancer mortality for cancer survivors with a favorable HLS (4 and 5 healthy lifestyle factors) were 0.55 (95% CI 0.42-0.64) and 0.57 (95% CI 0.44-0.72), respectively. This multicohort study of cancer survivors from the United States, the United Kingdom and China found that greater adherence to a healthy lifestyle might be beneficial in improving cancer prognosis.
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Affiliation(s)
- Zilong Bian
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Rongqi Zhang
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Rong Fan
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lijuan Wang
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Cancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Yimin Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Shouling Wu
- Department of Cardiology, Kailuan General Hospital, Tangshan, China
| | - Yuan Ding
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xue Li
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
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Bian L, Ma Z, Fu X, Ji C, Wang T, Yan C, Dai J, Ma H, Hu Z, Shen H, Wang L, Zhu M, Jin G. Associations of combined phenotypic aging and genetic risk with incident cancer: A prospective cohort study. eLife 2024; 13:RP91101. [PMID: 38687190 PMCID: PMC11060710 DOI: 10.7554/elife.91101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024] Open
Abstract
Background Age is the most important risk factor for cancer, but aging rates are heterogeneous across individuals. We explored a new measure of aging-Phenotypic Age (PhenoAge)-in the risk prediction of site-specific and overall cancer. Methods Using Cox regression models, we examined the association of Phenotypic Age Acceleration (PhenoAgeAccel) with cancer incidence by genetic risk group among 374,463 participants from the UK Biobank. We generated PhenoAge using chronological age and nine biomarkers, PhenoAgeAccel after subtracting the effect of chronological age by regression residual, and an incidence-weighted overall cancer polygenic risk score (CPRS) based on 20 cancer site-specific polygenic risk scores (PRSs). Results Compared with biologically younger participants, those older had a significantly higher risk of overall cancer, with hazard ratios (HRs) of 1.22 (95% confidence interval, 1.18-1.27) in men, and 1.26 (1.22-1.31) in women, respectively. A joint effect of genetic risk and PhenoAgeAccel was observed on overall cancer risk, with HRs of 2.29 (2.10-2.51) for men and 1.94 (1.78-2.11) for women with high genetic risk and older PhenoAge compared with those with low genetic risk and younger PhenoAge. PhenoAgeAccel was negatively associated with the number of healthy lifestyle factors (Beta = -1.01 in men, p<0.001; Beta = -0.98 in women, p<0.001). Conclusions Within and across genetic risk groups, older PhenoAge was consistently related to an increased risk of incident cancer with adjustment for chronological age and the aging process could be retarded by adherence to a healthy lifestyle. Funding This work was supported by the National Natural Science Foundation of China (82230110, 82125033, 82388102 to GJ; 82273714 to MZ); and the Excellent Youth Foundation of Jiangsu Province (BK20220100 to MZ).
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Affiliation(s)
- Lijun Bian
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjingChina
| | - Zhimin Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
| | - Xiangjin Fu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
| | - Chen Ji
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
| | - Tianpei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
| | - Caiwang Yan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjingChina
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention, Wuxi Medical Center, Nanjing Medical UniversityWuxiChina
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjingChina
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjingChina
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjingChina
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjingChina
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical SciencesBeijingChina
| | - Lu Wang
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention, Wuxi Medical Center, Nanjing Medical UniversityWuxiChina
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjingChina
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention, Wuxi Medical Center, Nanjing Medical UniversityWuxiChina
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical UniversityNanjingChina
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjingChina
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention, Wuxi Medical Center, Nanjing Medical UniversityWuxiChina
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7
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Li J, He C, Ying J, Hua B, Yang Y, Chen W, Liu W, Ye D, Sun X, Mao Y, Chen K. Air pollutants, genetic susceptibility, and the risk of incident gastrointestinal diseases: A large prospective cohort study. ENVIRONMENTAL RESEARCH 2024; 247:118182. [PMID: 38218525 DOI: 10.1016/j.envres.2024.118182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/10/2023] [Accepted: 01/10/2024] [Indexed: 01/15/2024]
Abstract
A comprehensive overview of the associations between air pollution and the risk of gastrointestinal (GI) diseases has been lacking. We aimed to examine the relationships of long-term exposure to ambient particulate matter (PM) with aerodynamic diameter ≤2.5 μm (PM2.5), 2.5-10 μm (PMcoarse), ≤10 μm (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx), with the risk of incident GI diseases, and to explore the interplay between air pollution and genetic susceptibility. A total of 465,703 participants free of GI diseases in the UK Biobank were included at baseline. Land use regression models were employed to calculate the residential air pollutants concentrations. Cox proportional hazard models were used to evaluate the associations of air pollutants with the risk of GI diseases. The dose-response relationships of air pollutants with the risk of GI diseases were evaluated by restricted cubic spline curves. We found that long-term exposure to ambient air pollutants was positively associated with the risk of peptic ulcer (PM2.5 : Q4 vs. Q1: hazard ratio (HR) 1.272, 95% confidence interval (CI) 1.179-1.372, NO2: 1.220, 1.131-1.316, and NOx: 1.277, 1.184-1.376) and chronic gastritis (PM2.5: 1.454, 1.309-1.616, PM10 : 1.232, 1.112-1.366, NO2: 1.456, 1.311-1.617, and NOx: 1.419, 1.280-1.574) after Bonferroni correction. Participants with high genetic risk and high air pollution exposure had the highest risk of peptic ulcer, compared to those with low genetic risk and low air pollution exposure (PM2.5: HR 1.558, 95%CI 1.384-1.754, NO2: 1.762, 1.395-2.227, and NOx: 1.575, 1.403-1.769). However, no significant additive or multiplicative interaction between air pollution and genetic risk was found. In conclusion, long-term exposure to ambient air pollutants was associated with increased risk of peptic ulcer and chronic gastritis.
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Affiliation(s)
- Jiayu Li
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Chunlei He
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jiacheng Ying
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Baojie Hua
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yudan Yang
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Weiwei Chen
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Wei Liu
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Ding Ye
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Xiaohui Sun
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.
| | - Yingying Mao
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.
| | - Kun Chen
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Zhang Y, Lindström S, Kraft P, Liu Y. Genetic Risk, Health-Associated Lifestyle, and Risk of Early-onset Total Cancer and Breast Cancer. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.04.24305361. [PMID: 38633776 PMCID: PMC11023660 DOI: 10.1101/2024.04.04.24305361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Importance Early-onset cancer (diagnosed under 50 years of age) is associated with aggressive disease characteristics and its rising incidence is a global concern. The association between healthy lifestyle and early-onset cancer and whether it varies by common genetic variants is unknown. Objective To examine the associations between genetic risk, lifestyle, and risk of early-onset cancers. Design Setting and Participants We analyzed a prospective cohort of 66,308 white British participants who were under age 50 and free of cancer at baseline in the UK Biobank. Exposures Sex-specific composite total cancer polygenic risk scores (PRSs), a breast cancer-specific PRS, and sex-specific health-associated lifestyle scores (HLSs, which summarize smoking status, body mass index [males only], physical activity, alcohol consumption, and diet). Main Outcomes and Measures Hazard ratios (HRs) and 95% confidence intervals (CIs) for early-onset total and breast cancer. Results A total of 1,247 incident invasive early-onset cancer cases (female: 820, male: 427, breast: 386) were documented. In multivariable-adjusted analyses with 2-year latency, higher genetic risk (highest vs. lowest tertile of PRS) was associated with significantly increased risks of early-onset total cancer in females (HR, 95% CI: 1.85, 1.50-2.29) and males (1.94, 1.45-2.59) as well as early-onset breast cancer in females (3.06, 2.20-4.25). An unfavorable lifestyle (highest vs. lowest category of HLS) was associated with higher risk of total cancer and breast cancer in females across genetic risk categories; the association with total cancer was stronger in the highest genetic risk category than the lowest: HRs in females and men were 1.85 (1.02, 3.36), 3.27 (0.78, 13.72) in the highest genetic risk category and 1.15 (0.44, 2.98), 1.16 (0.39, 3.40) in the lowest. Conclusions and Relevance Both genetic and lifestyle factors were independently associated with early-onset total and breast cancer risk. Compared to those with low genetic risk, individuals with a high genetic risk may benefit more from adopting a healthy lifestyle in preventing early-onset cancer.
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Affiliation(s)
- Yin Zhang
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Sara Lindström
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Peter Kraft
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yuxi Liu
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
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Wu J, Yao L, Liu Y, Zhang S, Wang K. Periodontitis and osteoporosis: a two-sample Mendelian randomization analysis. Braz J Med Biol Res 2024; 57:e12951. [PMID: 38511766 PMCID: PMC10946243 DOI: 10.1590/1414-431x2024e12951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 01/05/2024] [Indexed: 03/22/2024] Open
Abstract
The incidences of periodontitis and osteoporosis are rising worldwide. Observational studies have shown that periodontitis is associated with increased risk of osteoporosis. We performed a Mendelian randomization (MR) study to genetically investigate the causality of periodontitis on osteoporosis. We explored the causal effect of periodontitis on osteoporosis by MR analysis. A total of 9 single nucleotide polymorphisms (SNP) were related to periodontitis. The primary approach in this MR analysis was the inverse variance-weighted (IVW) method. Simple median, weighted median, and penalized weighted median were used to analyze sensitivity. The fixed-effect IVW model and random-effect IVW model showed no significant causal effect of genetically predicted periodontitis on the risk of osteoporosis (OR=1.032; 95%CI: 0.923-1.153; P=0.574; OR=1.032; 95%CI: 0.920-1.158; P=0.588, respectively). Similar results were observed in simple mode (OR=1.031; 95%CI: 0.780-1.361, P=0.835), weighted mode (OR=1.120; 95%CI: 0.944-1.328, P=0.229), simple median (OR=1.003; 95%CI: 0.839-1.197, P=0.977), weighted median (OR=1.078; 95%CI: 0.921-1.262, P=0.346), penalized weight median (OR 1.078; 95%CI: 0.919-1.264, P=0.351), and MR-Egger method (OR=1.360; 95%CI: 0.998-1.853, P=0.092). There was no heterogeneity in the IVW and MR-Egger analyses (Q=7.454, P=0.489 and Q=3.901, P=0.791, respectively). MR-Egger regression revealed no evidence of a pleiotropic influence through genetic variants (intercept: -0.004; P=0.101). The leave-one-out sensitivity analysis indicated no driven influence of any individual SNP on the association between periodontitis and osteoporosis. The Mendelian randomization analysis did not show a significant detrimental effect of periodontitis on the risk of osteoporosis.
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Affiliation(s)
- Jiale Wu
- Department of Oral and Maxillofacial Surgery, Peking University School of Medicine, Hospital of Stomatology, Beijing, China
| | - Lihui Yao
- Department of Stomatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yuchen Liu
- Department of Oral and Maxillofacial Surgery, Peking University School of Medicine, Hospital of Stomatology, Beijing, China
| | - ShuaiShuai Zhang
- Department of Stomatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Kan Wang
- Department of Oral and Maxillofacial Surgery, Peking University School of Medicine, Hospital of Stomatology, Beijing, China
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10
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Yu EYW, Tang QY, Chen YT, Zhang YX, Dai YN, Wu YX, Li WC, Mehrkanoon S, Wang SZ, Zeegers MP, Wesselius A. Genome-wide exploration of genetic interactions for bladder cancer risk. Int J Cancer 2024; 154:81-93. [PMID: 37638657 DOI: 10.1002/ijc.34690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 07/14/2023] [Accepted: 07/31/2023] [Indexed: 08/29/2023]
Abstract
Although GWASs have been conducted to investigate genetic variation of bladder tumorigenesis, little is known about genetic interactions that may influence bladder cancer (BC) risk. By leveraging large-scale participants from UK Biobank, we established a discovery database with 4000 Caucasian participants (2000 cases vs 2000 non-cases), a database with 1648 Caucasian participants (824 cases vs 824 non-cases) and 856 non-Caucasian participants (428 cases vs 428 non-cases) as validation. We then performed a genome-wide SNP-SNP interaction investigation related to BC risk based a machine learning approach (ie, GenEpi). Moreover, we used the selected interactions to build a BC screening model with an integrated interaction-empowered polygenic risk score (iPRS) based on Cox proportional hazard model. With Bonferroni correction, we identified 10 statistically significant pairs of SNPs, which located in 17 chromosomes. Of these, four SNP-SNP interactions were found to be positively associated with BC risk among Caucasian participants (ORs 1.57-2.03), while six SNP-SNP interactions showed negatively associated with BC risk (ORs 0.54-0.65). Only four of the SNP-SNP interactions were consistently identified in non-Caucasian participants located in ST7L-ADSS2, FHIT-CHDH, LARP4B-LHPP and RBFOX3-MPRIP. In addition, the iPRS showed a HR of 1.81 (95% CI: 1.46-2.09) compared the highest tertile to the lowest tertile, with an enhanced AUC (0.91; 95% CI:0.85-0.97) than PRS (AUC: 0.86; 95% CI:0.76-0.95; P-DeLong test = 2.2 × 10-4 ). In summary, this study identified several important SNP-SNP interactions for BC risk, and developed an iPRS model for BC screening, which may help to identify the people at high-risk state of BC before early manifestation.
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Affiliation(s)
- Evan Yi-Wen Yu
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, School of Public Health, Southeast University, Nanjing, China
- Department of Epidemiology & Biostatistics, School of Public Health, Southeast University, Nanjing, China
- Department of Epidemiology, CAPHRI Care and Public Health Research Institute, School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
| | - Qiu-Yi Tang
- Medical School of Southeast University, Nanjing, China
| | - Ya-Ting Chen
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, School of Public Health, Southeast University, Nanjing, China
- Department of Epidemiology & Biostatistics, School of Public Health, Southeast University, Nanjing, China
| | - Yan-Xi Zhang
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, School of Public Health, Southeast University, Nanjing, China
- Department of Epidemiology & Biostatistics, School of Public Health, Southeast University, Nanjing, China
| | - Ya-Nan Dai
- Department of Epidemiology, CAPHRI Care and Public Health Research Institute, School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
| | - Yu-Xuan Wu
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, School of Public Health, Southeast University, Nanjing, China
- Department of Epidemiology & Biostatistics, School of Public Health, Southeast University, Nanjing, China
| | - Wen-Chao Li
- Department of Urology, Affiliated Zhongda Hospital of Southeast University, Nanjing, China
| | - Siamak Mehrkanoon
- Information and Computing Sciences, Utrecht University, Utrecht, Netherlands
| | - Shi-Zhi Wang
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China
| | - Maurice P Zeegers
- Department of Epidemiology, CAPHRI Care and Public Health Research Institute, School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
| | - Anke Wesselius
- Department of Epidemiology, CAPHRI Care and Public Health Research Institute, School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
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11
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Zhu M, Lv J, Huang Y, Ma H, Li N, Wei X, Ji M, Ma Z, Song C, Wang C, Dai J, Tan F, Guo Y, Walters R, Millwood IY, Hung RJ, Christiani DC, Yu C, Jin G, Chen Z, Wei Q, Amos CI, Hu Z, Li L, Shen H. Ethnic differences of genetic risk and smoking in lung cancer: two prospective cohort studies. Int J Epidemiol 2023; 52:1815-1825. [PMID: 37676847 DOI: 10.1093/ije/dyad118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 08/23/2023] [Indexed: 09/09/2023] Open
Abstract
BACKGROUND The role of genetic background underlying the disparity of relative risk of smoking and lung cancer between European populations and East Asians remains unclear. METHODS To assess the role of ethnic differences in genetic factors associated with smoking-related risk of lung cancer, we first constructed ethnic-specific polygenic risk scores (PRSs) to quantify individual genetic risk of lung cancer in Chinese and European populations. Then, we compared genetic risk and smoking as well as their interactions on lung cancer between two cohorts, including the China Kadoorie Biobank (CKB) and the UK Biobank (UKB). We also evaluated the absolute risk reduction over a 5-year period. RESULTS Differences in compositions and association effects were observed between the Chinese-specific PRSs and European-specific PRSs, especially for smoking-related loci. The PRSs were consistently associated with lung cancer risk, but stronger associations were observed in smokers of the UKB [hazard ratio (HR) 1.26 vs 1.15, P = 0.028]. A significant interaction between genetic risk and smoking on lung cancer was observed in the UKB (RERI, 11.39 (95% CI, 7.01-17.94)], but not in the CKB. Obvious higher absolute risk was observed in nonsmokers of the CKB, and a greater absolute risk reduction was found in the UKB (10.95 vs 7.12 per 1000 person-years, P <0.001) by comparing heavy smokers with nonsmokers, especially for those at high genetic risk. CONCLUSIONS Ethnic differences in genetic factors and the high incidence of lung cancer in nonsmokers of East Asian ethnicity were involved in the disparity of smoking-related risk of lung cancer.
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Affiliation(s)
- Meng Zhu
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Yanqian Huang
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaoxia Wei
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Mengmeng Ji
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Zhimin Ma
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Ci Song
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Cheng Wang
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Juncheng Dai
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Fengwei Tan
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yu Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Robin Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada
| | - David C Christiani
- Department of Environmental Health, Harvard School of Public Health, Department of Medicine, Harvard Medical School/Massachusetts General Hospital, Boston, USA
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Guangfu Jin
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Qingyi Wei
- Duke Cancer Institute, Duke University Medical Center, Durham, USA
- Department of Population Health Sciences, Duke University School of Medicine, Durham, USA
| | - Christopher I Amos
- Baylor College of Medicine, Institute for Clinical and Translational Research, Houston, USA
| | - Zhibin Hu
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Hongbing Shen
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
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12
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Zeng L, Wu Z, Yang J, Zhou Y, Chen R. Association of genetic risk and lifestyle with pancreatic cancer and their age dependency: a large prospective cohort study in the UK Biobank. BMC Med 2023; 21:489. [PMID: 38066552 PMCID: PMC10709905 DOI: 10.1186/s12916-023-03202-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 11/29/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Pancreatic cancer (PC) is influenced by both genetic and lifestyle factors. However, further research is still needed to comprehensively clarify the relationships among lifestyle, genetic factors, their combined effect on PC, and how these associations might be age-dependent. METHODS We included 340,631 participants from the UK Biobank. Three polygenic risk score (PRS) models for PC were applied, which were derived from the previous study and were categorized as low, intermediate, and high. Two healthy lifestyle scores (HLSs) were constructed using 9 lifestyle factors based on the World Cancer Research Fund/American Institute of Cancer Research (WCRF/AICR) lifestyle score and the American Cancer Society (ACS) guidelines and were categorized as unfavorable, intermediate, and favorable. Data were analyzed using Cox proportional hazards models. RESULTS There were 1,129 cases of incident PC during a median follow-up of 13.05 years. Higher PRS was significantly associated with an increased risk of PC (hazard ratio [HR], 1.58; 95% confidence intervals [CI], 1.47-1.71). Adhering to a favorable lifestyle was associated with a lower risk (HR, 0.48; 95% CI, 0.41-0.56). Participants with an unfavorable lifestyle and a high PRS had the highest risk of PC (HR, 2.84; 95% CI, 2.22-3.62). Additionally, when stratified by age, a favorable lifestyle was most pronounced associated with a lower risk of PC among participants aged ≤ 60 years (HR, 0.35; 95% CI, 0.23-0.54). However, the absolute risk reduction was more pronounced among those aged > 70 years (ARR, 0.19%, 95% CI, 0.13%-0.26%). A high PRS was more strongly associated with PC among participants aged ≤ 60 years (HR, 1.89; 95% CI, 1.30-2.73). Furthermore, we observed a significant multiplicative interaction and several significant additive interactions. CONCLUSIONS A healthy lifestyle was associated with a lower risk of PC, regardless of the participants' age, sex, or genetic risk. Importantly, our findings indicated the age-dependent association of lifestyle and genetic factors with PC, emphasizing the importance of early adoption for effective prevention and potentially providing invaluable guidance for setting the optimal age to start preventive measures.
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Affiliation(s)
- Liangtang Zeng
- School of Medicine, South China University of Technology, Guangzhou, Guangdong Province, China
- Department of Pancreatic Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China
| | - Zhuo Wu
- School of Medicine, South China University of Technology, Guangzhou, Guangdong Province, China
- Department of Pancreatic Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China
| | - Jiabin Yang
- School of Medicine, South China University of Technology, Guangzhou, Guangdong Province, China
- Department of Pancreatic Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China
| | - Yu Zhou
- Department of Pancreatic Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China.
| | - Rufu Chen
- School of Medicine, South China University of Technology, Guangzhou, Guangdong Province, China.
- Department of Pancreatic Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China.
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Tian R, He Q, Yang Y, Nong X, Wang S. Associations of polysocial risk score, lifestyle and genetic factors with incident psoriasis: a larger-scale prospective cohort study. Public Health 2023; 225:320-326. [PMID: 37972495 DOI: 10.1016/j.puhe.2023.10.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 10/13/2023] [Accepted: 10/17/2023] [Indexed: 11/19/2023]
Abstract
OBJECTIVES The impact of polysocial risk score (PsRS), a composite measure of multiple social risk factors, on the development of psoriasis remains unclear. Moreover, the potential modifying effects of lifestyle and genetic susceptibility on the relationship between PsRS and psoriasis risk require further exploration. STUDY DESIGN This was a prospective cohort study conducted among UK Biobank. METHODS In this study, we analyzed 331,631 participants enrolled in the UK Biobank cohort. To derive the PsRS, we utilized a summative strategy, amalgamating six social determinants of health derived from three domains: socio-economic status, psychosocial factors, and neighborhood and living environment consistently linked to incident psoriasis. Cox proportional hazard models were used to assess the associations between PsRS and psoriasis incidence. Furthermore, we constructed a lifestyle score and a genetic risk score to explore the potential modifying effects of these factors on the relationship between PsRS and psoriasis risk. RESULTS Compared with individuals with a low PsRS (≤1), those with intermediate PsRS (2-4) and high PsRS (≥5) had 1.20 (95% confidence interval [CI], 1.06-1.36) and 1.53 (95% CI, 1.31-1.78) times higher risks of developing psoriasis, respectively. Our findings revealed an additive interaction between PsRS and genetic susceptibility. Moreover, it was found that individuals with high PsRS and unhealthier lifestyles had a 2.60 times higher risk of developing psoriasis than those with lower PsRS and healthier ones. CONCLUSIONS Our study results imply that an elevated PsRS is linked to a heightened risk of psoriasis, which is further influenced by genetic factors. Our results also indicate that greater social vulnerability and unhealthier lifestyle may synergistically contribute to the additional risk of psoriasis.
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Affiliation(s)
- Rongqian Tian
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Qida He
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou City, Jiangsu Province, China
| | - Yi Yang
- Department of Health Statistics, School of Public Health, Weifang Medical University, Weifang, Shandong, China
| | - Xiang Nong
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
| | - Suzhen Wang
- Department of Health Statistics, School of Public Health, Weifang Medical University, Weifang, Shandong, China.
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Long L, He H, Shen Q, Peng H, Zhou X, Wang H, Zhang S, Qin S, Lu Z, Zhu Y, Tian J, Chang J, Miao X, Shen N, Zhong R. Birthweight, genetic risk, and gastrointestinal cancer incidence: a prospective cohort study. Ann Med 2023; 55:62-71. [PMID: 36503347 PMCID: PMC9754019 DOI: 10.1080/07853890.2022.2146743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The epidemiologic studies investigating the association of birthweight and genetic factors with gastrointestinal cancer remain scarce. The study aimed to prospectively assess the interactions and joint effects of birthweight and genetic risk levels on gastrointestinal cancer incidence in adulthood. METHODS A total of 254,997 participants were included in the UK Biobank study. We used multivariate restricted cubic splines and Cox regression models to estimate the hazard ratios (HRs) and 95% confidential intervals (CI) for the association between birthweight and gastrointestinal cancer risk, then constructed a polygenic risk score (PRS) to assess its interaction and joint effect with birthweight on the development of gastrointestinal cancer. RESULTS We documented 2512 incident cases during a median follow-up of 8.88 years. Compare with participants reporting a normal birthweight (2.5-4.5 kg), multivariable-adjusted HR of gastrointestinal cancer incidence for participants with high birthweight (≥4.5 kg) was 1.17 (95%CI: 1.01-1.36). Such association was remarkably observed in pancreatic cancer, with an HR of 1.82 (95%CI: 1.26-2.64). No statistically significant association was observed between low birth weight and gastrointestinal cancers. Participants with high birthweight and high PRS had the highest risk of gastrointestinal cancer (HR: 2.95, 95%CI: 2.19-3.96). CONCLUSION Our findings highlight that high birthweight is associated with a higher incidence of gastrointestinal cancer, especially for pancreatic cancer. Benefits would be obtained from birthweight control, particularly for individuals with a high genetic risk.KEY MESSAGESThe epidemiologic studies investigating the association of birthweight and genetic factors with gastrointestinal cancer remain scarce.This cohort study of 254,997 adults in the United Kingdom found an association of high birthweight with the incidence of gastrointestinal cancer, especially for pancreatic cancer, and also found that participants with high birthweight and high polygenic risk score had the highest risk of gastrointestinal cancer.Our data suggests a possible effect of in utero or early life exposures on adulthood gastrointestinal cancer, especially for those with a high genetic risk.
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Affiliation(s)
- Lu Long
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Heng He
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qian Shen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongxia Peng
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiaorui Zhou
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shifan Qin
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- School of Public Health, Wuhan University, Wuhan, China
| | - Jianbo Tian
- School of Public Health, Wuhan University, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoping Miao
- School of Public Health, Wuhan University, Wuhan, China
| | - Na Shen
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, HUST, Wuhan, China
- Na Shen Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, China
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- CONTACT Rong Zhong Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
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Fallows ESV. Lifestyle medicine: a cultural shift in medicine that can drive integration of care. Future Healthc J 2023; 10:226-231. [PMID: 38162213 PMCID: PMC10753218 DOI: 10.7861/fhj.2023-0094] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
Our traditional medical mindset and healthcare culture are being severely challenged. In the face of novel infectious diseases, such as Coronavirus 2019 (COVID-19), along with rising levels of chronic diseases, such as obesity, type 2 diabetes mellitus, psychiatric illness, cardiovascular disease and cancer, many argue that current healthcare practices are failing to meet our needs. Energy and vision for a new way of practicing medicine are colliding, from both top-down, driven by policy, and bottom-up, driven by clinicians and patients. Policy makers have laid out the need for integration of healthcare delivery to address the complex chronic disease burden; creating integrated care partnerships, health and wellbeing boards and primary care networks to bring together 'at the place level' primary and secondary care, mental and public health services, social care and the voluntary sector. In practice, this is starting to build lasting working relationships between previously siloed services, to address the complex environmental, social, cultural, lifestyle and biopsychosocial drivers of ill health rather than simply providing access to hospitals, doctors and medication. Similarly, out of frustration with our traditional pharmaceutically driven medical model, grass-roots clinicians have built a new vision for their role in this better integrated health system, with the discipline of lifestyle medicine.
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He Q, Wu S, Zhou Y, Liu Y, Xia B, Li W, Zhao J, Mi N, Xie P, Qin X, Yuan J, Pan Y. Genetic factors, adherence to healthy lifestyle behaviors, and risk of bladder cancer. BMC Cancer 2023; 23:965. [PMID: 37828430 PMCID: PMC10568887 DOI: 10.1186/s12885-023-11455-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 09/27/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Genetic and lifestyle factors both contribute to the pathogenesis of bladder cancer, but the extent to which the increased genetic risk can be mitigated by adhering to a healthy lifestyle remains unclear. We aimed to investigate the association of combined lifestyle factors with bladder cancer risk within genetic risk groups. METHODS We conducted a prospective study of 375 998 unrelated participants of European ancestry with genotype and lifestyle data and free of cancer from the UK biobank. We generated a polygenic risk score (PRS) using 16 single nucleotide polymorphisms and a healthy lifestyle score based on body weight, smoking status, physical activity, and diet. Cox models were fitted to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of genetic and lifestyle factors on bladder cancer. RESULTS During a median follow-up of 11.8 years, 880 participants developed bladder cancer. Compared with those with low PRS, participants with intermediate and high PRS had a higher risk of bladder cancer (HR 1.29, 95% CI 1.07-1.56; HR 1.63, 95% CI 1.32-2.02, respectively). An optimal lifestyle was associated with an approximately 50% lower risk of bladder cancer than a poor lifestyle across all genetic strata. Participants with a high genetic risk and a poor lifestyle had 3.6-fold elevated risk of bladder cancer compared with those with a low genetic risk and an optimal lifestyle (HR 3.63, 95% CI 2.23 -5.91). CONCLUSIONS Adhering to a healthy lifestyle could substantially reduce the bladder cancer risk across all genetic strata, even for high-genetic risk individuals. For all populations, adopting an intermediate lifestyle is more beneficial than a poor one, and adhering to an optimal lifestyle is the ideal effective strategy for bladder cancer prevention.
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Affiliation(s)
- Qiangsheng He
- Scientific Research Center, Big Data Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
- Clinical Research Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
- Guangdong Provincial Key Laboratory of Gastroenterology, Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
| | - Siqing Wu
- School of Medicine, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
| | - Ying Zhou
- Primary Care Office, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
| | - Yuchen Liu
- Scientific Research Center, Big Data Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
| | - Bin Xia
- Scientific Research Center, Big Data Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
- Clinical Research Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
- Guangdong Provincial Key Laboratory of Gastroenterology, Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
| | - Wenjing Li
- Scientific Research Center, Big Data Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
| | - Jinyu Zhao
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Ningning Mi
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Peng Xie
- Guangdong Provincial Key Laboratory of Gastroenterology, Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China
| | - Xiwen Qin
- Department of Pharmacology and Pharmacy, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
- School of Population and Global Health, Faculty of Medicine, Density and Health Sciences, University of Western Australia, Perth, AU-WA, Australia
| | - Jinqiu Yuan
- Scientific Research Center, Big Data Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China.
- Clinical Research Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China.
- Guangdong Provincial Key Laboratory of Gastroenterology, Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China.
| | - Yihang Pan
- Scientific Research Center, Big Data Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China.
- Guangdong Provincial Key Laboratory of Gastroenterology, Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, Guangdong, China.
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Wang J, Chen C, Zhou J, Ye L, Li Y, Xu L, Xu Z, Li X, Wei Y, Liu J, Lv Y, Shi X. Healthy lifestyle in late-life, longevity genes, and life expectancy among older adults: a 20-year, population-based, prospective cohort study. THE LANCET. HEALTHY LONGEVITY 2023; 4:e535-e543. [PMID: 37804845 DOI: 10.1016/s2666-7568(23)00140-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/17/2023] [Accepted: 07/17/2023] [Indexed: 10/09/2023] Open
Abstract
BACKGROUND Lifestyle and longevity genes have different and important roles in the human lifespan; however, the association between a healthy lifestyle in late-life and life expectancy mediated by genetic risk is yet to be elucidated. We aimed to investigate the associations of healthy lifestyle in late-life and genetic risk with life expectancy among older adults. METHODS A weighted healthy lifestyle score was constructed from the following variables: current non-smoking, non-harmful alcohol consumption, regular physical activity, and a healthy diet. Participants were recruited from the Chinese Longitudinal Healthy Longevity Survey, a prospective community-based cohort study that took place between 1998 and 2018. Eligible participants were aged 65 years and older with available information on lifestyle factors at baseline, and then were categorised into unhealthy (bottom tertile of the weighted healthy lifestyle score), intermediate (middle tertile), and healthy (top tertile) lifestyle groups. A genetic risk score was constructed based on 11 lifespan loci among 9633 participants, divided by the median and classified into low and high genetic risk groups. Stratified Cox proportional hazard regression was used to estimate the interaction between genetic and lifestyle factors on all-cause mortality risk. FINDINGS Between Jan 13, 1998, and Dec 31, 2018, 36 164 adults aged 65 years and older were recruited, among whom a total of 27 462 deaths were documented during a median follow-up of 3·12 years (IQR 1·62-5·94) and included in the lifestyle association analysis. Compared with the unhealthy lifestyle category, participants in the healthy lifestyle group had a lower all-cause mortality risk (hazard ratio [HR] 0·56 [95% CI 0·54-0·57]; p<0·0001). The highest mortality risk was observed in individuals in the high genetic risk and unhealthy lifestyle group (HR 1·80 [95% CI 1·63-1·98]; p<0·0001). The absolute risk reduction was greater for participants in the high genetic risk group. A healthy lifestyle was associated with a gain of 3·84 years (95% CI 3·05-4·64) at the age of 65 years in the low genetic risk group, and 4·35 years (3·70-5·06) in the high genetic risk group. INTERPRETATION A healthy lifestyle, even in late-life, was associated with lower mortality risk and longer life expectancy among Chinese older adults, highlighting the importance of a healthy lifestyle in extending the lifespan, especially for individuals with high genetic risk. FUNDING National Natural Science Foundation of China. TRANSLATION For the Mandarin translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Jun Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chen Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jinhui Zhou
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lihong Ye
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yang Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Lanjing Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Zinan Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xinwei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Yuan Wei
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Hygienic Inspection, School of Public Health, Jilin University, Changchun, China
| | - Junxin Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuebin Lv
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
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He H, Shen Q, He MM, Qiu W, Wang H, Zhang S, Qin S, Lu Z, Zhu Y, Tian J, Chang J, Wang K, Zhang X, Miao X, Song M, Zhong R. In Utero and Childhood/Adolescence Exposure to Tobacco Smoke, Genetic Risk, and Cancer Incidence in Adulthood: A Prospective Cohort Study. Mayo Clin Proc 2023; 98:1164-1176. [PMID: 37422733 DOI: 10.1016/j.mayocp.2023.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 03/11/2023] [Accepted: 03/28/2023] [Indexed: 07/10/2023]
Abstract
OBJECTIVE To evaluate the association of early-life tobacco smoke exposure, especially interacting with cancer genetic variants, with adult cancer. PARTICIPANTS AND METHODS We examined the associations of in utero tobacco smoke exposure, age of smoking initiation, and their interaction with genetic risk levels with cancer incidence in 393,081 participants from the UK Biobank. Information on tobacco exposure was obtained by self-reported questionnaires. A cancer polygenic risk score was constructed by weighting and integrating 702 genome-wide association studies-identified risk variants. Cox proportional hazards regression models were used to calculate hazard ratios (HRs) for overall cancer and organ-specific cancer incidence. RESULTS During 11.8 years of follow-up, 23,450 (5.97%) and 23,413 (6.03%) incident cancers were included in the analyses of in utero exposure and age of smoking initiation, respectively. The HR (95% CI) for incident cancer in participants with in utero exposure to tobacco smoke was 1.04 (1.01-1.07) for overall cancer, 1.59 (1.44-1.75) for respiratory cancer, and 1.09 (1.03-1.17) for gastrointestinal cancer. The relative risk of incident cancer increased with earlier smoking initiation (Ptrend<.001), with the HR (95% CI) of 1.44 (1.36-1.51) for overall cancer, 13.28 (11.39-15.48) for respiratory cancer, and 1.72 (1.54-1.91) for gastrointestinal cancer in smokers with initiation in childhood compared with never smokers. Importantly, a positive additive interaction between age of smoking initiation and genetic risk was observed for overall cancer (Padditive=.04) and respiratory cancer (Padditive=.003) incidence. CONCLUSION In utero exposure and earlier smoking initiation are associated with overall and organ-specific cancer, and age of smoking initiation interaction with genetic risk is associated with respiratory cancer.
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Affiliation(s)
- Heng He
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qian Shen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming-Ming He
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Weihong Qiu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shifan Qin
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kai Wang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Mingyang Song
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA; Clinical and Translational Epidemiology Unit, Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Ma Y, Chu M, Fu Z, Liu Q, Liang J, Xu J, Weng Z, Chen X, Xu C, Gu A. The Association of Metabolomic Profiles of a Healthy Lifestyle with Heart Failure Risk in a Prospective Study. Nutrients 2023; 15:2934. [PMID: 37447260 PMCID: PMC10346862 DOI: 10.3390/nu15132934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/26/2023] [Accepted: 06/27/2023] [Indexed: 07/15/2023] Open
Abstract
Lifestyle has been linked to the incidence of heart failure, but the underlying biological mechanisms remain unclear. Using the metabolomic, lifestyle, and heart failure data of the UK Biobank, we identified and validated healthy lifestyle-related metabolites in a matched case-control and cohort study, respectively. We then evaluated the association of healthy lifestyle-related metabolites with heart failure (HF) risk and the added predictivity of these healthy lifestyle-associated metabolites for HF. Of 161 metabolites, 8 were identified to be significantly related to healthy lifestyle. Notably, omega-3 fatty acids and docosahexaenoic acid (DHA) positively associated with a healthy lifestyle score (HLS) and exhibited a negative association with heart failure risk. Conversely, creatinine negatively associated with a HLS, but was positively correlated with the risk of HF. Adding these three metabolites to the classical risk factor prediction model, the prediction accuracy of heart failure incidence can be improved as assessed by the C-statistic (increasing from 0.806 [95% CI, 0.796-0.816] to 0.844 [95% CI, 0.834-0.854], p-value < 0.001). A healthy lifestyle is associated with significant metabolic alterations, among which metabolites related to healthy lifestyle may be critical for the relationship between healthy lifestyle and HF. Healthy lifestyle-related metabolites might enhance HF prediction, but additional validation studies are necessary.
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Affiliation(s)
- Yuanyuan Ma
- State Key Laboratory of Reproductive Medicine and Offspring Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211166, China
- Department of Toxicology, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Maomao Chu
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China
| | - Zuqiang Fu
- State Key Laboratory of Reproductive Medicine and Offspring Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211166, China
- School of Public Health, Southeast University, Nanjing 211189, China
| | - Qian Liu
- State Key Laboratory of Reproductive Medicine and Offspring Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211166, China
- Department of Toxicology, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Jingjia Liang
- State Key Laboratory of Reproductive Medicine and Offspring Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211166, China
- Department of Toxicology, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Jin Xu
- State Key Laboratory of Reproductive Medicine and Offspring Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211166, China
- Department of Maternal, Child, and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zhenkun Weng
- State Key Laboratory of Reproductive Medicine and Offspring Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211166, China
- Department of Toxicology, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Xiu Chen
- State Key Laboratory of Reproductive Medicine and Offspring Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211166, China
- Department of Toxicology, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Cheng Xu
- State Key Laboratory of Reproductive Medicine and Offspring Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211166, China
- Department of Toxicology, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Aihua Gu
- State Key Laboratory of Reproductive Medicine and Offspring Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211166, China
- Department of Toxicology, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
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20
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Liu J, Wang L, Cui X, Shen Q, Wu D, Yang M, Dong Y, Liu Y, Chen H, Yang Z, Liu Y, Zhu M, Ma H, Jin G, Qian Y. Polygenic Risk Score, Lifestyles, and Type 2 Diabetes Risk: A Prospective Chinese Cohort Study. Nutrients 2023; 15:2144. [PMID: 37432247 DOI: 10.3390/nu15092144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 04/28/2023] [Accepted: 04/28/2023] [Indexed: 07/12/2023] Open
Abstract
The aim of this study was to generate a polygenic risk score (PRS) for type 2 diabetes (T2D) and test whether it could be used in identifying high-risk individuals for lifestyle intervention in a Chinese cohort. We genotyped 80 genetic variants among 5024 participants without non-communicable diseases at baseline in the Wuxi Non-Communicable Diseases cohort (Wuxi NCDs cohort). During the follow-up period of 14 years, 440 cases of T2D were newly diagnosed. Using Cox regression, we found that the PRS of 46 SNPs identified by the East Asians was relevant to the future T2D. Participants with a high PRS (top quintile) had a two-fold higher risk of T2D than the bottom quintile (hazard ratio: 2.06, 95% confidence interval: 1.42-2.97). Lifestyle factors were considered, including cigarette smoking, alcohol consumption, physical exercise, diet, body mass index (BMI), and waist circumference (WC). Among high-PRS individuals, the 10-year incidence of T2D slumped from 6.77% to 3.28% for participants having ideal lifestyles (4-6 healthy lifestyle factors) compared with poor lifestyles (0-2 healthy lifestyle factors). When integrating the high PRS, the 10-year T2D risk of low-clinical-risk individuals exceeded that of high-clinical-risk individuals with a low PRS (3.34% vs. 2.91%). These findings suggest that the PRS of 46 SNPs could be used in identifying high-risk individuals and improve the risk stratification defined by traditional clinical risk factors for T2D. Healthy lifestyles can reduce the risk of a high PRS, which indicates the potential utility in early screening and precise prevention.
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Affiliation(s)
- Jia Liu
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Lu Wang
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Xuan Cui
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Qian Shen
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Dun Wu
- College of Arts and Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Man Yang
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Yunqiu Dong
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Yongchao Liu
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Hai Chen
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Zhijie Yang
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Yaqi Liu
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Meng Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Hongxia Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Guangfu Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yun Qian
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
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21
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Kim ES, Scharpf RB, Garcia-Closas M, Visvanathan K, Velculescu VE, Chatterjee N. Potential utility of risk stratification for multicancer screening with liquid biopsy tests. NPJ Precis Oncol 2023; 7:39. [PMID: 37087533 PMCID: PMC10122653 DOI: 10.1038/s41698-023-00377-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/30/2023] [Indexed: 04/24/2023] Open
Abstract
Our proof-of-concept study reveals the potential of risk stratification by the combined effects of age, polygenic risk scores (PRS), and non-genetic risk factors in increasing the risk-benefit balance of rapidly emerging non-invasive multicancer early detection (MCED) liquid biopsy tests. We develop and validate sex-specific pan-cancer risk scores (PCRSs), defined by the combination of body mass index, smoking, family history of cancers, and cancer-specific polygenic risk scores (PRSs), to predict the absolute risk of developing at least one of the many common cancer types. We demonstrate the added value of PRSs in improving the predictive performance of the risk factors only model and project the positive and negative predictive values for two promising multicancer screening tests across risk strata defined by age and PCRS.
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Affiliation(s)
- Elle S Kim
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Robert B Scharpf
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Montserrat Garcia-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute of Health, 9609 Medical Center Drive 7E-342, Rockville, MD, 20850, USA
| | - Kala Visvanathan
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Victor E Velculescu
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
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22
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Yu EYW, Liu YX, Chen YT, Tang QY, Mehrkanoon S, Wang SZ, Li WC, Zeegers MP, Wesselius A. The effects of the interaction of genetic predisposition with lifestyle factors on bladder cancer risk. BJU Int 2023; 131:443-451. [PMID: 36053730 DOI: 10.1111/bju.15880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVES To investigate the association of polygenic risk score (PRS) and bladder cancer (BC) risk and whether this PRS can be offset by a healthy lifestyle. METHODS Individuals with BC (n = 563) and non-BC controls (n = 483 957) were identified in the UK Biobank, and adjusted Cox regression models were used. A PRS was constructed based on 34 genetic variants associated with BC development, while a healthy lifestyle score (HLS) was constructed based on three lifestyle factors (i.e., smoking, physical activity, and diet). RESULTS Overall, a negative interaction was observed between the PRS and the HLS (P = 0.02). A 7% higher and 28% lower BC risk per 1-standard deviation (SD) increment in PRS and HLS were observed, respectively. A simultaneous increment of 1 SD in both HLS and PRS was associated with a 6% lower BC risk. In addition, individuals with a high genetic risk and an unfavourable lifestyle showed an increased BC risk compared to individuals with low genetic risk and a favourable lifestyle (hazard ratio 1.55, 95% confidence interval 1.16-1.91; P for trend <0.001). Furthermore, population-attributable fraction (PAF) analysis showed that 12%-15% of the BC cases might have been prevented if individuals had adhered to a healthy lifestyle. CONCLUSION This large-scale cohort study shows that a genetic predisposition combined with unhealthy behaviours have a joint negative effect on the risk of developing BC. Behavioural lifestyle changes should be encouraged for people through comprehensive, multifactorial approaches, although high-risk individuals may be selected based on genetic risk.
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Affiliation(s)
- Evan Yi-Wen Yu
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology & Biostatistics, School of Public Health, Southeast University, Nanjing, China
- Department of Epidemiology, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands
| | - Yu-Xiang Liu
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology & Biostatistics, School of Public Health, Southeast University, Nanjing, China
| | - Ya-Ting Chen
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology & Biostatistics, School of Public Health, Southeast University, Nanjing, China
| | - Qiu-Yi Tang
- Medical School of Southeast University, Nanjing, China
| | - Siamak Mehrkanoon
- Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, The Netherlands
| | - Shi-Zhi Wang
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China
| | - Wen-Chao Li
- Department of Urology, Affiliated Zhongda Hospital of Southeast University, Nanjing, China
| | - Maurice P Zeegers
- Department of Epidemiology, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands
| | - Anke Wesselius
- Department of Epidemiology, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands
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23
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Healthy Diet, Polygenic Risk Score, and Upper Gastrointestinal Cancer Risk: A Prospective Study from UK Biobank. Nutrients 2023; 15:nu15061344. [PMID: 36986074 PMCID: PMC10054787 DOI: 10.3390/nu15061344] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 03/04/2023] [Accepted: 03/07/2023] [Indexed: 03/12/2023] Open
Abstract
Dietary and genetic factors are considered to be associated with UGI cancer risk. However, examinations of the effect of healthy diet on UGI cancer risk and the extent to which healthy diet modifies the impact of genetic susceptibility on UGI cancer remains limited. Associations were analyzed through Cox regression of the UK Biobank data (n = 415,589). Healthy diet, based on “healthy diet score,” was determined according to fruit, vegetables, grains, fish, and meat consumption. We compared adherence to healthy diet and the risk of UGI cancer. We also constructed a UGI polygenic risk score (UGI-PRS) to assess the combined effect of genetic risk and healthy diet. For the results high adherence to healthy diet reduced 24% UGI cancer risk (HR high-quality diet: 0.76 (0.62–0.93), p = 0.009). A combined effect of high genetic risk and unhealthy diet on UGI cancer risk was observed, with HR reaching 1.60 (1.20–2.13, p = 0.001). Among participants with high genetic risk, the absolute five-year incidence risk of UGI cancer was significantly reduced, from 0.16% to 0.10%, by having a healthy diet. In summary, healthy diet decreased UGI cancer risk, and individuals with high genetic risk can attenuate UGI cancer risk by adopting a healthy diet.
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24
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Xin J, Jiang X, Li H, Chen S, Zhang Z, Wang M, Gu D, Du M, Christiani DC. Prognostic evaluation of polygenic risk score underlying pan-cancer analysis: evidence from two large-scale cohorts. EBioMedicine 2023; 89:104454. [PMID: 36739632 PMCID: PMC9931923 DOI: 10.1016/j.ebiom.2023.104454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 12/07/2022] [Accepted: 01/12/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Polygenic risk score (PRS) has been demonstrated to be effective in identifying individuals at high risk of developing cancer, but its prognostic value remains unclear. METHODS We constructed site-specific PRSs by aggregating the risk effect of independent variants derived from previous genome-wide association studies (GWASs) across 17 cancer types. The Cox proportional hazards model was used to evaluate the association of each PRS with cancer survival, leveraging data from two prospective European cohorts, namely the UK Biobank involving 19,628 incident cases and The Cancer Genome Atlas involving 7079 prevalent cases. The combined PRS (CPRS), determined by merging site-specific PRSs, was further used to assess the prognostic effect of PRS on overall cancer in a sex-specific manner. FINDINGS We discovered that the cancer risk-related PRS was associated with neither overall survival (OS) nor cancer-specific survival (CSS) of each site-specific cancer with an underlying false discovery rate (FDR) P > 0.05, as evidenced by consistent findings from the two cohorts. Furthermore, the fixed-effect meta-analysis of the two cohorts provided no evidence to support for an association between CPRS and overall cancer survival in both males [OS: hazard ratio (HR)meta = 1.00, Pmeta = 0.760; CSS: HRmeta = 1.01, Pmeta = 0.447] and females (OS: HRmeta = 0.97, Pmeta = 0.067; CSS: HRmeta = 0.96, Pmeta = 0.054). Similar results were observed across multiple sensitivity analyses. INTERPRETATION Our findings indicate that the risk-specific PRS might not be a clinically useful tool in cancer prognosis prediction and further studies focusing on the development of polygenic prognostic score are warranted. FUNDING This project was funded by the National Natural Science Foundation of China (82173601 and 82073631), and Priority Academic Program Development of Jiangsu Higher Education Institutions (Public Health and Preventive Medicine).
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Affiliation(s)
- Junyi Xin
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Xia Jiang
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Huiqin Li
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Silu Chen
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Zhengdong Zhang
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meilin Wang
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Dongying Gu
- Department of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
| | - Mulong Du
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Departments of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA, USA.
| | - David C Christiani
- Departments of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA, USA; Department of Medicine, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, USA
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25
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Ye X, Wang Y, Zou Y, Tu J, Tang W, Yu R, Yang S, Huang P. Associations of socioeconomic status with infectious diseases mediated by lifestyle, environmental pollution and chronic comorbidities: a comprehensive evaluation based on UK Biobank. Infect Dis Poverty 2023; 12:5. [PMID: 36717939 PMCID: PMC9885698 DOI: 10.1186/s40249-023-01056-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 01/16/2023] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Socioeconomic status (SES) inequity was recognized as a driver of some certain infectious diseases. However, few studies evaluated the association between SES and the burden of overall infections, and even fewer identified preventable mediators. This study aimed to assess the association between SES and overall infectious diseases burden, and the potential roles of factors including lifestyle, environmental pollution, chronic disease history. METHODS We included 401,009 participants from the UK Biobank (UKB) and defined the infection status for each participant according to their diagnosis records. Latent class analysis (LCA) was used to define SES for each participant. We further defined healthy lifestyle score, environment pollution score (EPS) and four types of chronic comorbidities. We used multivariate logistic regression to test the associations between the four above covariates and infectious diseases. Then, we performed the mediation and interaction analysis to explain the relationships between SES and other variables on infectious diseases. Finally, we employed seven types of sensitivity analyses, including considering the Townsend deprivation index as an area level SES variable, repeating our main analysis for some individual or composite factors and in some subgroups, as well as in an external data from the US National Health and Nutrition Examination Survey, to verify the main results. RESULTS In UKB, 60,771 (15.2%) participants were diagnosed with infectious diseases during follow-up. Lower SES [odds ratio (OR) = 1.5570] were associated with higher risk of overall infections. Lifestyle score mediated 2.9% of effects from SES, which ranged from 2.9 to 4.0% in different infection subtypes, while cardiovascular disease (CVD) mediated a proportion of 6.2% with a range from 2.1 to 6.8%. In addition, SES showed significant negative interaction with lifestyle score (OR = 0.8650) and a history of cancer (OR = 0.9096), while a significant synergy interaction was observed between SES and EPS (OR = 1.0024). In subgroup analysis, we found that males and African (AFR) with lower SES showed much higher infection risk. Results from sensitivity and validation analyses showed relative consistent with the main analysis. CONCLUSIONS Low SES is shown to be an important risk factor for infectious disease, part of which may be mediated by poor lifestyle and chronic comorbidities. Efforts to enhance health education and improve the quality of living environment may help reduce burden of infectious disease, especially for people with low SES.
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Affiliation(s)
- Xiangyu Ye
- grid.89957.3a0000 0000 9255 8984Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yidi Wang
- grid.89957.3a0000 0000 9255 8984Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yixin Zou
- grid.89957.3a0000 0000 9255 8984Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Junlan Tu
- grid.89957.3a0000 0000 9255 8984Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Weiming Tang
- grid.89957.3a0000 0000 9255 8984Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China ,grid.410711.20000 0001 1034 1720Institute of Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, CA USA
| | - Rongbin Yu
- grid.89957.3a0000 0000 9255 8984Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Sheng Yang
- grid.89957.3a0000 0000 9255 8984Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Peng Huang
- grid.89957.3a0000 0000 9255 8984Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
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26
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Ling Z, Zhang C, He J, Ouyang F, Qiu D, Li L, Li Y, Li X, Duan Y, Luo D, Xiao S, Shen M. Association of Healthy Lifestyles with Non-Alcoholic Fatty Liver Disease: A Prospective Cohort Study in Chinese Government Employees. Nutrients 2023; 15:nu15030604. [PMID: 36771311 PMCID: PMC9921275 DOI: 10.3390/nu15030604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/19/2023] [Accepted: 01/19/2023] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Evidence indicates that certain healthy lifestyle factors are associated with non-alcoholic fatty liver disease (NAFLD). However, little is known about the effect of combined healthy lifestyle factors. OBJECTIVE To assess the association of combined healthy lifestyle factors with the incidence of NAFLD. METHODS This cohort study was conducted in Changsha, Hunan Province, China. The healthy lifestyles factors studied were not being a current smoker, having a healthy diet, engaging in physical activity, having a normal body mass index (BMI) and engaging in non-sedentary behavior. NAFLD was diagnosed based on abdominal ultrasonography. Logistic regression models were conducted to investigate the associations being studied. RESULTS Of the 5411 participants, 1280 participants had NAFLD, with a prevalence of 23.7% at baseline. The incidence of NAFLD among participants without NAFLD at baseline was found to be 7.2% over a mean follow-up of 1.1 years. Compared with participants with 0-1 low-risk factors, the OR of NAFLD was 0.50 (95% CI: 0.29-0.82, p = 0.008) for those with at least 4 low-risk factors. Similar associations were observed in subgroup analyses and sensitivity analyses. CONCLUSION This study suggests that a combined healthy lifestyle pattern may considerably decrease the risk of NAFLD in Chinese government employees.
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Affiliation(s)
- Zhen Ling
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
| | - Chengcheng Zhang
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
| | - Jun He
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
| | - Feiyun Ouyang
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
| | - Dan Qiu
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
| | - Ling Li
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
| | - Yilu Li
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
| | - Xuping Li
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
| | - Yanying Duan
- Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Dan Luo
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
| | - Shuiyuan Xiao
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410008, China
- Correspondence: (S.X.); (M.S.)
| | - Minxue Shen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha 430013, China
- Furong Laboratory, Changsha 410008, China
- Correspondence: (S.X.); (M.S.)
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27
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Byrne S, Boyle T, Ahmed M, Lee SH, Benyamin B, Hyppönen E. Lifestyle, genetic risk and incidence of cancer: a prospective cohort study of 13 cancer types. Int J Epidemiol 2023:6990971. [PMID: 36651198 DOI: 10.1093/ije/dyac238] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 12/20/2022] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Genetic and lifestyle factors are associated with cancer risk. We investigated the benefits of adhering to lifestyle advice by the World Cancer Research Fund (WCRF) with the risk of 13 types of cancer and whether these associations differ according to genetic risk using data from the UK Biobank. METHODS In 2006-2010, participants aged 37-73 years had their lifestyle assessed and were followed up for incident cancers until 2015-2019. Analyses were restricted to those of White European ancestry with no prior history of malignant cancer (n = 195 822). Polygenic risk scores (PRSs) were computed for 13 cancer types and these cancers combined ('overall cancer'), and a lifestyle index was calculated from WCRF recommendations. Associations with cancer incidence were estimated using Cox regression, adjusting for relevant confounders. Additive and multiplicative interactions between lifestyle index and PRSs were assessed. RESULTS There were 15 240 incident cancers during the 1 926 987 person-years of follow-up (median follow-up = 10.2 years). After adjusting for confounders, the lifestyle index was associated with a lower risk of overall cancer [hazard ratio per standard deviation increase (95% CI) = 0.89 (0.87, 0.90)] and of eight specific cancer types. There was no evidence of interactions on the multiplicative scale. There was evidence of additive interactions in risks for colorectal, breast, pancreatic, lung and bladder cancers, such that the recommended lifestyle was associated with greater change in absolute risk for persons at higher genetic risk (P < 0.0003 for all). CONCLUSIONS The recommended lifestyle has beneficial associations with most cancers. In terms of absolute risk, the protective association is greater for higher genetic risk groups for some cancers. These findings have important implications for persons most genetically predisposed to those cancers and for targeted strategies for cancer prevention.
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Affiliation(s)
- Stephanie Byrne
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, Australia
- UniSA Allied Health & Human Performance, University of South Australia, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Terry Boyle
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, Australia
- UniSA Allied Health & Human Performance, University of South Australia, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Muktar Ahmed
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
- UniSA Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia
- Department of Epidemiology, Faculty of Public Health, Jimma University Institute of Health, Jimma, Ethiopia
| | - Sang Hong Lee
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, Australia
- UniSA Allied Health & Human Performance, University of South Australia, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Beben Benyamin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, Australia
- UniSA Allied Health & Human Performance, University of South Australia, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Elina Hyppönen
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
- UniSA Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia
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28
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Xin J, Gu D, Chen S, Ben S, Li H, Zhang Z, Du M, Wang M. SUMMER: a Mendelian randomization interactive server to systematically evaluate the causal effects of risk factors and circulating biomarkers on pan-cancer survival. Nucleic Acids Res 2023; 51:D1160-D1167. [PMID: 35947748 PMCID: PMC9825440 DOI: 10.1093/nar/gkac677] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/18/2022] [Accepted: 07/26/2022] [Indexed: 01/30/2023] Open
Abstract
Genome-wide association studies (GWASs) underlying case-control design have uncovered hundreds of genetic loci involved in tumorigenesis and provided rich resources for identifying risk factors and biomarkers associated with cancer susceptibility. However, the application of GWAS in determining the genetic architecture of cancer survival remains unestablished. Here, we systematically evaluated genetic effects at the genome-wide level on cancer survival that included overall survival (OS) and cancer-specific survival (CSS), leveraging data deposited in the UK Biobank cohort of a total of 19 628 incident patients across 17 cancer types. Furthermore, we assessed the causal effects of risk factors and circulating biomarkers on cancer prognosis via a Mendelian randomization (MR) analytic framework, which integrated cancer survival GWAS dataset, along with phenome-wide association study (PheWAS) and blood genome-wide gene expression/DNA methylation quantitative trait loci (eQTL/meQTL) datasets. On average, more than 10 traits, 700 genes, and 4,500 CpG sites were prone to cancer prognosis. Finally, we developed a user-friendly online database, SUrvival related cancer Multi-omics database via MEndelian Randomization (SUMMER; http://njmu-edu.cn:3838/SUMMER/), to help users query, browse, and download cancer survival results. In conclusion, SUMMER provides an important resource to assist the research community in understanding the genetic mechanisms of cancer survival.
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Affiliation(s)
- Junyi Xin
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Dongying Gu
- Department of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Silu Chen
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Shuai Ben
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Huiqin Li
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Zhengdong Zhang
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Mulong Du
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meilin Wang
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
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29
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Liu Y, Yan C, Yin S, Wang T, Zhu M, Liu L, Jin G. Genetic risk, metabolic syndrome, and gastrointestinal cancer risk: A prospective cohort study. Cancer Med 2023; 12:597-605. [PMID: 35730595 PMCID: PMC9844643 DOI: 10.1002/cam4.4923] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/07/2022] [Accepted: 05/28/2022] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Gastrointestinal (GI) cancer risk has been associated with metabolic syndrome (MetS), a surrogate indicator for unhealthy lifestyles, and a number of genetic loci, but the combined effect of MetS and genetic variants on GI cancer risk is uncertain. METHODS We included 430,036 participants with available MetS and genotype data from UK Biobank. During the follow-up time, 5494 incident GI cancer cases, including esophageal cancer, gastric cancer, and colorectal cancer, were identified. We created a GI polygenic risk score (GI-PRS) for overall GI cancer derived from three site-specific cancer PRSs. Cox proportional hazards regression was used to estimate the associations of MetS and GI-PRS with the risk of GI cancer. RESULTS MetS was significantly associated with 28% increment in GI cancer risk (hazard ratio [HR]MetS vs. non-MetS : 1.28, 95% confidence interval [CI]: 1.21-1.35, p < 0.0001), whereas a high GI-PRS (top quintile) was associated with 2.28-fold increase in risk (HRhigh vs. low : 2.28, 95% CI: 2.09-2.49, p < 0.0001). Compared with participants without MetS and at low genetic risk (bottom quintile of GI-PRS), those with MetS and at high genetic risk had 2.75-fold increase in GI cancer risk (HR: 2.75, 95% CI: 2.43-3.12, p < 0.0001). Additionally, MetS in comparison with no MetS had 1.49‰, 2.75‰, and 3.37‰ absolute risk increases in 5 years among participants at low, intermediate (quintiles 2-4 of GI-PRS) and high genetic risk, respectively, representing the number of subjects diagnosed as MetS causing a new GI cancer case in 5 years were 669, 364, and 296, respectively. CONCLUSIONS Metabolic and genetic factors may jointly contribute to GI cancer risk and may serve as predictors by quantitative measurements to identify high-risk populations of GI cancer for precise prevention.
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Affiliation(s)
- Yaqian Liu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
| | - Caiwang Yan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Shuangshuang Yin
- Digestive Endoscopy Department and General Surgery Department, The First Affiliated Hospital with Nanjing Medical University and Jiangsu Province Hospital, Nanjing, China
| | - Tianpei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Li Liu
- Digestive Endoscopy Department and General Surgery Department, The First Affiliated Hospital with Nanjing Medical University and Jiangsu Province Hospital, Nanjing, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
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Abdollahi S, Hasanpour Ardekanizadeh N, Poorhosseini SM, Gholamalizadeh M, Roumi Z, Goodarzi MO, Doaei S. Unraveling the Complex Interactions between the Fat Mass and Obesity-Associated (FTO) Gene, Lifestyle, and Cancer. Adv Nutr 2022; 13:2406-2419. [PMID: 36104156 PMCID: PMC9776650 DOI: 10.1093/advances/nmac101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 06/28/2022] [Accepted: 09/12/2022] [Indexed: 01/29/2023] Open
Abstract
Carcinogenesis is a complicated process and originates from genetic, epigenetic, and environmental factors. Recent studies have reported a potential critical role for the fat mass and obesity-associated (FTO) gene in carcinogenesis through different signaling pathways such as mRNA N6-methyladenosine (m6A) demethylation. The most common internal modification in mammalian mRNA is the m6A RNA methylation that has significant biological functioning through regulation of cancer-related cellular processes. Some environmental factors, like physical activity and dietary intake, may influence signaling pathways engaged in carcinogenesis, through regulating FTO gene expression. In addition, people with FTO gene polymorphisms may be differently influenced by cancer risk factors, for example, FTO risk allele carriers may need a higher intake of nutrients to prevent cancer than others. In order to obtain a deeper viewpoint of the FTO, lifestyle, and cancer-related pathway interactions, this review aims to discuss upstream and downstream pathways associated with the FTO gene and cancer. The present study discusses the possible mechanisms of interaction of the FTO gene with various cancers and provides a comprehensive picture of the lifestyle factors affecting the FTO gene as well as the possible downstream pathways that lead to the effect of the FTO gene on cancer.
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Affiliation(s)
- Sepideh Abdollahi
- Department of Medical Genetics, School of Medicine, Tehran University of
Medical Sciences, Tehran, Iran
| | - Naeemeh Hasanpour Ardekanizadeh
- Department of Clinical Nutrition, School of Nutrition and Food Sciences,
Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Maryam Gholamalizadeh
- Cancer Research Center, Shahid Beheshti University of Medical
Sciences, Tehran, Iran
| | - Zahra Roumi
- Department of Nutrition, Science and Research Branch, Islamic Azad
University, Tehran, Iran
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine,
Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Saeid Doaei
- Department of Community Nutrition, School of Nutrition and Food Sciences,
Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Feng X, Wang F, Yang W, Zheng Y, Liu C, Huang L, Li L, Cheng H, Cai H, Li X, Chen X, Yang X. Association Between Genetic Risk, Adherence to Healthy Lifestyle Behavior, and Thyroid Cancer Risk. JAMA Netw Open 2022; 5:e2246311. [PMID: 36508215 PMCID: PMC9856466 DOI: 10.1001/jamanetworkopen.2022.46311] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 10/21/2022] [Indexed: 12/14/2022] Open
Abstract
Importance Genetic and lifestyle factors are related to thyroid cancer (TC). Whether a healthy lifestyle is associated with TC and could attenuate the influence of genetic variants in TC remains equivocal. Objectives To examine the associations between genetics and healthy lifestyle with incident TC and whether adherence to a healthy lifestyle modifies the association between genetic variants and TC. Design, Setting, and Participants A prospective cohort study using UK Biobank data recruited 502 505 participants aged 40 to 69 years between March 13, 2006, and October 1, 2010. A total of 307 803 participants of European descent were recruited at baseline, and 264 956 participants were available for the present study. Data analysis was conducted from November 1, 2021, to April 22, 2022. Exposures Lifestyle behaviors were determined by diet index, physical activity, weight, smoking, and alcohol consumption. Lifestyle was categorized as unfavorable (scores 0-1), intermediate (score 2), and favorable (scores 3-5). The polygenic risk score (PRS) was derived from a meta-genome-wide association study using 3 cohorts and categorized as low, intermediate, and high. Main Outcomes and Measures Thyroid cancer was defined using the International Classification of Diseases, Ninth Revision (code 193), International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (code C73), and self-report (code 1065). Results Of 264 956 participants, 137 665 were women (52%). The median age was 57 (IQR, 49-62) years. During a median follow-up of 11.1 (IQR, 10.33-11.75) years (2 885 046 person-years), 423 incident TCs were ascertained (14.66 per 100 000 person-years). Higher PRSs were associated with TC (hazard ratio [HR], 2.25; 95% CI, 1.91-2.64; P = 8.65 × 10-23). An unfavorable lifestyle was also associated with a higher risk of TC (HR, 1.93; 95% CI, 1.50-2.49; P < .001). When stratified by PRS, unfavorable lifestyle was associated with TC in the higher PRS group (favorable vs unfavorable HR, 0.52; 95% CI, 0.37-0.73; P < .001). Furthermore, participants with both a high PRS and unfavorable lifestyle had the highest risk of TC (HR, 4.89; 95% CI, 3.03-7.91; P < .001). Conclusions and Relevance In this prospective cohort study, genetic and lifestyle factors were independently associated with incident TC, which suggests that a healthier lifestyle may attenuate the deleterious influence of genetics on the risk of TC in individuals of European descent.
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Affiliation(s)
- Xiuming Feng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Fei Wang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
- Guangxi Key Laboratory on Precise Prevention and Treatment for Thyroid Tumor, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
| | - Wenjun Yang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Yuan Zheng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Chaoqun Liu
- Department of Nutrition and Food Hygiene, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Lulu Huang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
- Department of Radiotherapy, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Longman Li
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
- Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Hong Cheng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Haiqing Cai
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Xiangzhi Li
- Guangxi Key Laboratory on Precise Prevention and Treatment for Thyroid Tumor, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
- Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
| | - Xing Chen
- Department of Sanitary Chemistry, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Xiaobo Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
- Guangxi Key Laboratory on Precise Prevention and Treatment for Thyroid Tumor, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
- Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
- Guangxi Key Laboratory of Environment and Health Research, Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
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Qin N, Wang C, Chen C, Yang L, Liu S, Xiang J, Xie Y, Liang S, Zhou J, Xu X, Zhao X, Zhu M, Jin G, Ma H, Dai J, Hu Z, Shen H. Association of the interaction between mosaic chromosomal alterations and polygenic risk score with the risk of lung cancer: an array-based case-control association and prospective cohort study. Lancet Oncol 2022; 23:1465-1474. [PMID: 36265503 DOI: 10.1016/s1470-2045(22)00600-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/13/2022] [Accepted: 09/15/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Mosaic chromosomal alterations (mCAs) detected from blood-derived DNA are large structural alterations of clonal haematopoietic origin and are associated with various diseases, such as haematological malignancies, infections, and solid cancers. We aimed to investigate whether mCAs contribute to the risk of lung cancer and modify the effect of polygenic risk score (PRS) on lung cancer risk prediction. METHODS The blood-derived DNA of patients with lung cancer and cancer-free controls with Chinese ancestry from the Nanjing Lung Cancer Cohort (NJLCC) study were genotyped with a Global Screening Array, and mCAs were detected with the Mosaic Chromosomal Alterations (MoChA) pipeline. mCA call sets of individuals with European ancestry were obtained from the prospective cohort UK Biobank (UKB) study, including documented incident lung cancer. All patients with lung cancer from the NJLCC study (aged 15 years or older at diagnosis) were histopathologically confirmed as new lung cancer cases by at least two pathologists and were free of chemotherapy or radiotherapy before diagnosis. Participants with incident lung cancer (aged 37-73 years at assessment) diagnosed after recruitment to the UKB were identified through linkage to national cancer registries. Logistic regression and Cox proportional hazard models were applied to evaluate associations between mCAs and risk of lung cancer in the NJLCC (logistic regression) and UKB (Cox proportional hazard model) studies. FINDINGS The NJLCC study included 10 248 individuals (6445 [62·89%] men and 3803 [37·11%] women; median age 60·0 years [IQR 53·0-66·0]) with lung cancer and 9298 individuals (5871 [63·14%] men and 3427 [36·86%] women; median age 60·0 years [52·0-65·0]) without lung cancer recruited from three sub-regions (north, central, and south) across China between April 15, 2003, and Aug 18, 2017. The UKB included 450 821 individuals recruited from 22 centres across the UK between March 13, 2006, and Nov 1, 2010, including 2088 individuals with lung cancer (1075 [51·48%] men and 1013 [48·52%] women; median age 63·0 years [IQR 59·0-66·0]), and 448 733 participants were free of lung cancer (204 713 [45·62%] men and 244 020 [54·38%] women; median age 58·0 years [IQR 50·0-63·0]). Compared with non-carriers of mosaic losses, carriers had a significantly increased risk of lung cancer in the NJLCC (odds ratio [OR] 1·81, 95% CI 1·43-2·28; p=6·69 × 10-7) and UKB (hazard ratio [HR] 1·40, 95% CI 1·00-1·95; p=0·048) studies. This increased risk was even higher in patients with expanded cell fractions of mCAs (ie, cell fractions ≥10% vs cell fractions <10%) in the NJLCC (OR 1·61 [95% CI 1·26-2·08] vs 1·03 [0·83-1·26]; p for heterogeneity test=6·41 × 10-3). A significant multiplicative interaction was observed between PRS and mosaic losses on the risk of lung cancer in both the NJLCC (interaction p value=0·030) and UKB (p=0·043). Compared with non-carriers of mosaic loss abnormalities with low genetic risk, participants with expanded mosaic losses (cell fractions ≥10%) and high genetic risk had around a six-times increased risk of lung cancer in the NJLCC study (OR 6·40 [95% CI 3·22-12·69]), and an almost four-times increased risk of lung cancer (HR 3·75 [95% CI 1·86-7·55]) in the UKB study. The additive interaction also contributed a 3·67 (95% CI 0·49-6·85) relative excess risk of developing lung cancer in the NJLCC study, and a 2·15 (0·12-4·19) relative excess risk in the UKB study. INTERPRETATION mCAs act as a new endogenous indicator for the risk of lung cancer and might be jointly used with PRS to optimise personalised risk stratification for lung cancer. FUNDING National Natural Science Foundation of China, Outstanding Youth Foundation of Jiangsu Province, Natural Science Foundation of Jiangsu Province, and Postdoctoral Science Foundation of China. TRANSLATION For the Chinese translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Na Qin
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Cheng Wang
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Congcong Chen
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Liu Yang
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Su Liu
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jun Xiang
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yuan Xie
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Shuang Liang
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jun Zhou
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xianfeng Xu
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xiaoyu Zhao
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Guangfu Jin
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Nanjing, China; Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| | - Juncheng Dai
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Nanjing, China.
| | - Hongbing Shen
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China.
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Diez de los Rios de la Serna C, Fernández-Ortega P, Lluch-Canut T. Lifestyle Behavior Interventions for Preventing Cancer in Adults with Inherited Cancer Syndromes: Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:14098. [PMID: 36360977 PMCID: PMC9655661 DOI: 10.3390/ijerph192114098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 10/24/2022] [Accepted: 10/25/2022] [Indexed: 06/16/2023]
Abstract
(1) Background: The link between lifestyle behaviors and cancer risk is well established, which is important for people with personal/family history or genetic susceptibility. Genetic testing is not sufficient motivation to prompt healthier lifestyle behaviors. This systematic review aims to describe and assess interventions for promoting healthy behaviors in people at high risk of cancer. (2) Methods: The review was performed according to PRISMA guidelines using search terms related to hereditary cancer and health education to identify studies indexed in: CINAHL, MEDLINE, PubMed, Cochrane Library, Scopus, and Joanna Briggs, and published from January 2010 to July 2022. (3) Results: The search yielded 1558 initial records; four randomized controlled trials were eligible. Three included patients with and without a personal history of cancer who were at increased risk of cancer due to inherited cancer syndromes, and one included people undergoing genetic testing due to family history. Interventions targeted diet, physical activity, and alcohol. (4) Conclusions: There is a paucity of research on interventions for promoting healthy lifestyle behaviors in people with a high risk of cancer. Interventions produced positive short-term results, but there was no evidence that behavioral modifications were sustained over time. All healthcare professionals can actively promote healthy behaviors that may prevent cancer.
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Affiliation(s)
| | - Paz Fernández-Ortega
- School of Nursing, Faculty of Medicine and Health Sciences, Bellvitge Campus, University of Barcelona (UB), 08907 Barcelona, Spain
- Institut Català d’Oncologia (ICO) Barcelona, Bellvitge, 08908 Barcelona, Spain
| | - Teresa Lluch-Canut
- School of Nursing, Faculty of Medicine and Health Sciences, Bellvitge Campus, University of Barcelona (UB), 08907 Barcelona, Spain
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Zhu M, Ma Z, Zhang X, Hang D, Yin R, Feng J, Xu L, Shen H. C-reactive protein and cancer risk: a pan-cancer study of prospective cohort and Mendelian randomization analysis. BMC Med 2022; 20:301. [PMID: 36117174 PMCID: PMC9484145 DOI: 10.1186/s12916-022-02506-x] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 08/01/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Although observational studies have reported associations between serum C-reactive protein (CRP) concentration and risks of lung, breast, and colorectal cancer, inconsistent or absent evidences were showed for other cancers. We conducted a pan-cancer analysis to comprehensively assess the role of CRP, including linearity and non-linearity associations. METHODS We analyzed 420,964 cancer-free participants from UK Biobank cohort. Multivariable-adjusted Cox proportional hazards model was conducted to evaluate the observed correlation of CRP with overall cancer and 21 site-specific cancer risks. Furthermore, we performed linear and non-linear Mendelian randomization analyses to explore the potential causal relation between them. RESULTS During a median follow-up period of 7.1 years (interquartile range: 6.3, 7.7), 34,979 incident cancer cases were observed. Observational analyses showed higher CRP concentration was associated with increased risk of overall cancer (hazard ratio (HR) = 1.02, 95% CI: 1.01, 1.02 per 1mg/L increase, P < 0.001). There was a non-linear association between CRP and overall cancer risk with inflection point at 3mg/L (false-discovery rate adjust (FDR-adjusted) Poverall < 0.001 and FDR-adjusted Pnon-linear < 0.001). For site-specific cancer, we observed positive linear associations for cancers of esophagus and stomach (FDR-adjusted Poverall < 0.050 and FDR-adjusted Pnon-linear > 0.050). In addition, we also observed three different patterns of non-linear associations, including "fast-to-low increase" (head and neck, colorectal, liver, lung, kidney cancer, and non-Hodgkin lymphoma), "increase-to-decrease" (breast cancer), and "decrease-to-platform" (chronic lymphocytic leukemia). Furthermore, the inflection points of non-linear association patterns were consistently at around 3mg/L. By contrast, there was no evidence for linear or non-linear associations between genetically predicted CRP and risks of overall cancer or site-specific cancers. CONCLUSIONS Our results indicated that CRP was a potential biomarker to assess risks of overall cancer and 12 site-specific cancers, while no association were observed for genetically-predicted CRP and cancer risks.
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Affiliation(s)
- Meng Zhu
- Department of Thoracic Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China
| | - Zhimin Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China.,Department of Epidemiology, School of Public Health, Southeast University, Nanjing, China
| | - Xu Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China
| | - Dong Hang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China
| | - Rong Yin
- Department of Thoracic Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, China
| | - Jifeng Feng
- Department of Medical Oncology, Jiangsu Cancer Hospital &Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, China.
| | - Lin Xu
- Department of Thoracic Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, China.
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Rd, Nanjing, 211166, China.
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Zhu Z, Li FR, Jia Y, Li Y, Guo D, Chen J, Tian H, Yang J, Yang HH, Chen LH, Zhang K, Yang P, Sun L, Shi M, Zhang Y, Qin LQ, Chen GC. Association of Lifestyle With Incidence of Heart Failure According to Metabolic and Genetic Risk Status: A Population-Based Prospective Study. Circ Heart Fail 2022; 15:e009592. [PMID: 35975661 DOI: 10.1161/circheartfailure.122.009592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Whether lifestyle factors are similarly associated with risk of heart failure (HF) for individuals with different metabolic or genetic risk status remains unclear. METHODS We included 464 483 participants from UK Biobank who were free of major cardiovascular disease or HF during baseline recruitment. Healthy lifestyle factors included avoidance of smoking, no obesity, regular physical activity, and healthy diet. Lifestyle was categorized as favorable (3 or 4 healthy lifestyle factors), intermediate (2 healthy lifestyle factors), and unfavorable (0 or 1 healthy lifestyle factor) lifestyles. Metabolic status was defined by the presence of hypertension, high total cholesterol, or diabetes at baseline. A weighted genetic risk score was created based on 12 single-nucleotide polymorphisms associated with HF. RESULTS Compared with favorable lifestyle, the multivariable-adjusted hazard ratios of HF were 1.79 (95% CI, 1.68-1.90) and 2.90 (95% CI, 2.70-3.11) for intermediate lifestyle and unfavorable lifestyle, respectively (Ptrend <0.0001). This association was largely consistent regardless of the presence of any single metabolic risk factor or the number of metabolic risk factors (Pinteraction ≥0.21). The association was also similar across different genetic risk categories (Pinteraction=0.92). In a joint analysis, the hazard ratio of HF was 4.05 (95% CI, 3.43-4.77) comparing participants who had both higher genetic risk and an unfavorable lifestyle with those having lower genetic risk and a favorable lifestyle. CONCLUSIONS Combined lifestyle was associated with incident HF regardless of metabolic or genetic risk status, supporting the recommendation of healthy lifestyles for HF prevention across the entire population.
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Affiliation(s)
- Zhengbao Zhu
- Department of Epidemiology (Z.Z., Y.J., D.G., K.Z., P.Y., L.S., M.S., Y.Z.), Suzhou Medical College of Soochow University, China
| | - Fu-Rong Li
- Shenzhen Key Laboratory of Cardiovascular Health and Precision Medicine (F.-R.L.), Southern University of Science and Technology, China
- School of Public Health and Emergency Management (F.-R.L.), Southern University of Science and Technology, China
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China (F.-R.L.)
| | - Yiming Jia
- Department of Epidemiology (Z.Z., Y.J., D.G., K.Z., P.Y., L.S., M.S., Y.Z.), Suzhou Medical College of Soochow University, China
| | - Yang Li
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY (Y.L.)
| | - Daoxia Guo
- Department of Epidemiology (Z.Z., Y.J., D.G., K.Z., P.Y., L.S., M.S., Y.Z.), Suzhou Medical College of Soochow University, China
- School of Public Health and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases and School of Nursing (D.G.), Suzhou Medical College of Soochow University, China
| | - Jingsi Chen
- Department of Nutrition and Food Hygiene (J.C., J.Y., L.-Q.Q., G.-C.C.), Suzhou Medical College of Soochow University, China
| | - Haili Tian
- School of Kinesiology, Shanghai University of Sport, China (H.T.)
| | - Jing Yang
- Department of Nutrition and Food Hygiene (J.C., J.Y., L.-Q.Q., G.-C.C.), Suzhou Medical College of Soochow University, China
- Department of Clinical Nutrition, First Affiliated Hospital of Soochow University, Suzhou, China (J.Y.)
| | - Huan-Huan Yang
- Vanke School of Public Health, Tsinghua University, Beijing, China (H.-H.Y.)
| | - Li-Hua Chen
- Department of Nutrition and Food Hygiene, School of Public Health, Nantong University, China (L.-H.C.)
| | - Kaixin Zhang
- Department of Epidemiology (Z.Z., Y.J., D.G., K.Z., P.Y., L.S., M.S., Y.Z.), Suzhou Medical College of Soochow University, China
| | - Pinni Yang
- Department of Epidemiology (Z.Z., Y.J., D.G., K.Z., P.Y., L.S., M.S., Y.Z.), Suzhou Medical College of Soochow University, China
| | - Lulu Sun
- Department of Epidemiology (Z.Z., Y.J., D.G., K.Z., P.Y., L.S., M.S., Y.Z.), Suzhou Medical College of Soochow University, China
| | - Mengyao Shi
- Department of Epidemiology (Z.Z., Y.J., D.G., K.Z., P.Y., L.S., M.S., Y.Z.), Suzhou Medical College of Soochow University, China
| | - Yonghong Zhang
- Department of Epidemiology (Z.Z., Y.J., D.G., K.Z., P.Y., L.S., M.S., Y.Z.), Suzhou Medical College of Soochow University, China
| | - Li-Qiang Qin
- Department of Nutrition and Food Hygiene (J.C., J.Y., L.-Q.Q., G.-C.C.), Suzhou Medical College of Soochow University, China
| | - Guo-Chong Chen
- Department of Nutrition and Food Hygiene (J.C., J.Y., L.-Q.Q., G.-C.C.), Suzhou Medical College of Soochow University, China
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Abbott L, Graven L, Schluck G, Lemacks J. A Structural Equation Modeling Analysis to Explore Diabetes Self-Care Factors in a Rural Sample. Healthcare (Basel) 2022; 10:1536. [PMID: 36011193 PMCID: PMC9407851 DOI: 10.3390/healthcare10081536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/07/2022] [Accepted: 08/09/2022] [Indexed: 11/16/2022] Open
Abstract
Diabetes is a public health problem that requires management to avoid health sequelae. Little is known about the determinants that influence diabetes self-care activities among rural populations. The purpose of this analysis was to explore the relationships among diabetes self-care activities, diabetes knowledge, perceived diabetes self-management, diabetes fatalism, and social support among an underserved rural group in the southern United States. A diabetes health promotion program was tested during a cluster randomized trial that tested a disease risk reduction program among adults living with prediabetes and diabetes. A structural equation model was fit to test psychosocial factors that influence diabetes self-care activities using the Information-Motivation-Behavioral Skills Model of Diabetes Self-Care (IMB-DSC) to guide the study. Perceived diabetes self-management significantly predicted self-care behaviors, and there was also a correlation between perceived diabetes self-management and diabetes fatalism. Perceived diabetes self-management influenced diabetes self-care activities in this rural sample and had an association with diabetes fatalism. The findings of this study can facilitate clinical care and community programs targeting diabetes and advance health equity among underserved rural groups.
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Affiliation(s)
- Laurie Abbott
- College of Nursing, Florida State University, Tallahassee, FL 32306, USA
| | - Lucinda Graven
- College of Nursing, Florida State University, Tallahassee, FL 32306, USA
| | - Glenna Schluck
- College of Nursing, Florida State University, Tallahassee, FL 32306, USA
| | - Jennifer Lemacks
- College of Nursing and Health Professions, University of Southern Mississippi, Hattiesburg, MS 39406, USA
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Xu C, Weng Z, Liang J, Liu Q, Zhang X, Xu J, Li Q, Zhou Y, Gu A. Shift Work, Genetic Factors, and the Risk of Heart Failure: A Prospective Study of the UK Biobank. Mayo Clin Proc 2022; 97:1134-1144. [PMID: 35662426 DOI: 10.1016/j.mayocp.2021.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 11/08/2021] [Accepted: 12/07/2021] [Indexed: 11/22/2022]
Abstract
OBJECTIVE To quantify the association of combined shift work and genetic factors with the incidence of heart failure (HF). PARTICIPANTS AND METHODS This study included 242,754 participants with complete shift work information in the UK Biobank. Participants were followed from baseline (2006 to 2010) through January 31, 2018. The association between shift work and HF incidence was investigated separately in males and females using a Cox proportional hazards model adjusted for covariates. In addition, we established a polygenic risk score and assessed whether shift work alters genetic susceptibility to HF. RESULTS The results showed a significant association of permanent night shift work with incident HF among females (hazard ratio, 2.25; 95% CI, 1.34 to 3.76; P=.002) after adjusting for age, and the association was attenuated in the fully adjusted model. Among men, we did not detect an association between shift work and HF. In addition, we observed that the association between the risk of HF and shift work was strengthened by high genetic risk. Permanent night shift work paired with high genetic risk, compared with low genetic risk, was suggested to be associated with the risk of HF in females (hazard ratio, 2.89; 95% CI, 1.05 to 7.94) but not in males. CONCLUSION Shift work, particularly permanent night shift work, may increase the risk of HF in females, especially in those with high genetic risk.
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Affiliation(s)
- Cheng Xu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Zhenkun Weng
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Jingjia Liang
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Qian Liu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Xin Zhang
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Jin Xu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Qingguo Li
- Department of Cardiothoracic Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China; Cardiovascular Surgery Department, The Affiliated Hospital of Qinghai University, Xining, Qinghai, China.
| | - Yong Zhou
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Aihua Gu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China.
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Arena R, Lavie CJ, Faghy MA. What Comes First, the Behavior or the Condition? In the COVID-19 Era, It May Go Both Ways. Curr Probl Cardiol 2022; 47:100963. [PMID: 34391763 PMCID: PMC8358102 DOI: 10.1016/j.cpcardiol.2021.100963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 08/08/2021] [Indexed: 01/12/2023]
Abstract
Which came first, the chicken or the egg? This causality dilemma was first proposed by the Greek biographer Plutarch in the 1st century CE. While the cause-effect relationship between lifestyle behaviors and chronic disease is not always a certainty, and genetic predisposition can independently lead to premature chronic disease, the likelihood of developing one or more chronic conditions is significantly higher in those who: (1) lead sedentary lifestyles; (2) consume unhealthy diets; (3) smoke; or (4) have excess body mass. Recently, the Royal College of General Practitioners issued an apology for the title of an online event that suggested the coronavirus disease 2019 (COVID-19) is a lifestyle disease. We feel that this was the correct course of action as leading an unhealthy lifestyle is certainly not the cause for an individual contracting COVID-19 (ie, effect). However, a body of evidence has demonstrated that unhealthy lifestyle behaviors and characteristics as well as being diagnosed with one or more chronic diseases does significantly increase the risk for a complicated medical course in individuals infected with COVID-19. Moreover, the cause-effect relationship between lifestyle behaviors and characteristics and COVID-19 may eventually prove to go both ways, as the pandemic may lead to a higher prevalence of unhealthy lifestyle behaviors and characteristics over the long term that eventually leads to a higher prevalence of chronic disease. As such, health living medicine must be widely practiced and prescribed to all individuals globally.
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Affiliation(s)
- Ross Arena
- Department of Physical Therapy, College of Applied Sciences, University of Illinois at Chicago, Chicago, IL; Healthy Living for Pandemic Event Protection (HL-PIVOT) Network, Chicago, IL.
| | - Carl J Lavie
- Healthy Living for Pandemic Event Protection (HL-PIVOT) Network, Chicago, IL; Department of Cardiovascular Diseases, John Ochsner Heart and Vascular Institute, Ochsner Clinical School-University of Queensland School of Medicine, New Orleans, LA
| | - Mark A Faghy
- Department of Physical Therapy, College of Applied Sciences, University of Illinois at Chicago, Chicago, IL; Healthy Living for Pandemic Event Protection (HL-PIVOT) Network, Chicago, IL; Human Sciences Research Centre, University of Derby, Derby, United Kingdom
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Yu XH, Bo L, Cao RR, Yang YQ, He P, Lei SF, Deng FY. Systematic Evaluation of Rheumatoid Arthritis Risk by Integrating Lifestyle Factors and Genetic Risk Scores. Front Immunol 2022; 13:901223. [PMID: 35874719 PMCID: PMC9299428 DOI: 10.3389/fimmu.2022.901223] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 06/07/2022] [Indexed: 11/13/2022] Open
Abstract
Background Effective identification of high-risk rheumatoid arthritis (RA) individuals is still a challenge. Whether the combined effects of multiple previously reported genetic loci together with lifestyle factors can improve the prediction of RA risk remains unclear. Methods Based on previously reported results and a large-scale Biobank dataset, we constructed a polygenic risk score (PRS) for RA to evaluate the combined effects of the previously identified genetic loci in both case-control and prospective cohorts. We then evaluated the relationships between several lifestyles and RA risk and determined healthy lifestyles. Then, the joint effects of healthy lifestyles and genetic risk on RA risk were evaluated. Results We found a positive association between PRS and RA risk (OR = 1.407, 95% confidence interval (CI) = 1.354~1.463; HR = 1.316, 95% CI = 1.257~1.377). Compared with the low genetic risk group, the group with intermediate or high genetic risk had a higher risk (OR = 1.347, 95% CI = 1.213~1.496; HR = 1.246, 95% CI = 1.108~1.400) (OR = 2.169, 95% CI = 1.946~2.417; HR = 1.762, 95% CI = 1.557~1.995). After adjusting for covariates, we found protective effects of three lifestyles (no current smoking, regular physical activity, and moderate body mass index) on RA risk and defined them as healthy lifestyles. Compared with the individuals with low genetic risks and favorable lifestyles, those with high genetic risks and unfavorable lifestyles had as high as OR of 4.637 (95%CI = 3.767~5.708) and HR of 3.532 (95%CI = 2.799~4.458). Conclusions In conclusion, the integration of PRS and lifestyles can improve the prediction of RA risk. High RA risk can be alleviated by adopting healthy lifestyles but aggravated by adopting unfavorable lifestyles.
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Affiliation(s)
- Xing-Hao Yu
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
| | - Lin Bo
- Department of Rheumatology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Rong-Rong Cao
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
| | - Yi-Qun Yang
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
| | - Pei He
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
| | - Shu-Feng Lei
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
| | - Fei-Yan Deng
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
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Genetic and epigenetic processes linked to cancer. Cancer 2022. [DOI: 10.1016/b978-0-323-91904-3.00013-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Psychological intervention to treat distress: An emerging frontier in cancer prevention and therapy. Biochim Biophys Acta Rev Cancer 2021; 1877:188665. [PMID: 34896258 DOI: 10.1016/j.bbcan.2021.188665] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 11/27/2021] [Accepted: 12/01/2021] [Indexed: 02/05/2023]
Abstract
Psychological distress, such as chronic depression and anxiety, is a topical problem. In the context of cancer patients, prevalence rates of psychological distress are four-times higher than in the general population and often confer worse outcomes. In addition to evidence from epidemiological studies confirming the links between psychological distress and cancer progression, a growing body of cellular and molecular studies have also revealed the complex signaling networks which are modulated by psychological distress-derived chronic stress during cancer progression. In this review, aiming to uncover the intertwined networks of chronic stress-driven oncogenesis and progression, we summarize physiological stress response pathways, like the HPA, SNS, and MGB axes, that modulate the release of stress hormones with potential carcinogenic properties. Furthermore, we discuss in detail the mechanisms behind these chronic stimulations contributing to the initiation and progression of cancer through direct regulation of cancer hallmarks-related signaling or indirect promotion of cancer risk factors (including obesity, disordered circadian rhythms, and premature senescence), suggesting a novel research direction into cancer prevention and therapy on the basis of psychological interventions.
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