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Martínez-Magaña JJ, Hurtado-Soriano J, Rivero-Segura NA, Montalvo-Ortiz JL, Garcia-delaTorre P, Becerril-Rojas K, Gomez-Verjan JC. Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology. Arch Med Res 2024; 55:103033. [PMID: 38955096 DOI: 10.1016/j.arcmed.2024.103033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 05/10/2024] [Accepted: 06/17/2024] [Indexed: 07/04/2024]
Abstract
Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.
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Affiliation(s)
- José Jaime Martínez-Magaña
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; U.S. Department of Veterans Affairs National Center for Post-Traumatic Stress Disorder, Clinical Neuroscience Division, West Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | | | | | - Janitza L Montalvo-Ortiz
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; U.S. Department of Veterans Affairs National Center for Post-Traumatic Stress Disorder, Clinical Neuroscience Division, West Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | - Paola Garcia-delaTorre
- Unidad de Investigación Epidemiológica y en Servicios de Salud, Área de Envejecimiento, Centro Médico Nacional, Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
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Lin F, Chen X, Cai Y, Shi Y, Wang Y, Zeng Y, Ye Q, Chen X, Wu X, Shi Y, Cai G. Accelerated biological aging as potential mediator mediates the relationship between pro-inflammatory diets and the risk of depression and anxiety: A prospective analysis from the UK biobank. J Affect Disord 2024; 355:1-11. [PMID: 38537750 DOI: 10.1016/j.jad.2024.03.135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 03/08/2024] [Accepted: 03/24/2024] [Indexed: 04/22/2024]
Abstract
BACKGROUND The relationship between inflammatory dietary patterns and the risk of depression/anxiety has not been clearly established due to differences in study populations, geographic regions, sex, and methods of calculating the inflammatory index. METHODS We drew upon a prospective cohort in the UK Biobank and calculated the energy-adjusted dietary inflammatory index (E-DII). The follow-up time was defined from the date of completing the last dietary survey questionnaire to the date of diagnosis of depression, anxiety, phobic anxiety, other types of anxiety, death, loss to follow-up, or the respective censoring dates for England (September 30, 2021), Scotland (July 31, 2021), and Wales (February 28, 2018). The final follow-up times end on September 30, 2021, July 31, 2021, and February 28, 2018, for England, Scotland, and Wales, respectively. During the follow-up process, if a participant develops the condition, dies, or is lost to follow-up, the follow-up is terminated. We used Cox regression to evaluate the connection between E-DII and depression/anxiety. We employed restricted cubic spline curves for nonlinear relationships. We also conducted mediation analyses to explore whether biological age mediated the relationship between E-DII and depression. Additionally, we investigated whether genetic susceptibility modified the relationship between E-DII and depression through interaction modeling. RESULTS In the final analysis, we included a total of 151,295, 159,695, 165,649, and 160,097 participants for the analysis of depression, all types of anxiety, specific phobia anxiety, and other types of anxiety, respectively. For every one-unit increase in E-DII, the risk of experiencing depression and anxiety increased by 5 % and 4 %, respectively. We identified a "J"-shaped nonlinear relationship (P for nonlinear = 0.003) for both depression and anxiety. A significant association with an elevated risk of depression was observed when E-DII exceeded 0.440, and an increased risk of anxiety was noted when E-DII was more than -0.196. Mediation analysis demonstrated that PhenoAge age acceleration (AA) (For depression, proportion of mediation = 9.6 %; For anxiety, proportion of mediation = 10.1 %) and Klemera-Doubal method Biological Age (KDM AA) (For depression, proportion of mediation = 2.9 %; For anxiety, proportion of mediation = 5.1 %) acted as mediators between E-DII and the development of depression and anxiety (P < 0.05). CONCLUSIONS Diets with pro-inflammatory characteristics are associated with a heightened risk of depression and anxiety. Furthermore, the association of pro-inflammatory diets and depression is mediated by biological age.
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Affiliation(s)
- Fabin Lin
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, 88 Jiaotong Road, Fuzhou 350001, China; Department of Neurosurgery, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China
| | - Xuanjie Chen
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, 88 Jiaotong Road, Fuzhou 350001, China
| | - Yousheng Cai
- Department of Neurology, Zhangzhou Affiliated Hospital of Fujian Medical University, 59 Shengli Road, Zhangzhou 363000, China
| | - Yisen Shi
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, 88 Jiaotong Road, Fuzhou 350001, China
| | - Yingqing Wang
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, 88 Jiaotong Road, Fuzhou 350001, China
| | - Yuqi Zeng
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, 88 Jiaotong Road, Fuzhou 350001, China
| | - Qinyong Ye
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, 88 Jiaotong Road, Fuzhou 350001, China
| | - Xiaochun Chen
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, 88 Jiaotong Road, Fuzhou 350001, China
| | - Xilin Wu
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, 88 Jiaotong Road, Fuzhou 350001, China
| | - Yanchuan Shi
- Department of Neurology, Zhangzhou Affiliated Hospital of Fujian Medical University, 59 Shengli Road, Zhangzhou 363000, China
| | - Guoen Cai
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, China; Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, 88 Jiaotong Road, Fuzhou 350001, China.
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Zhang S, Tang H, Zhou M, Pan L. Sexual dimorphism association of combined exposure to volatile organic compounds (VOC) with kidney damage. ENVIRONMENTAL RESEARCH 2024; 258:119426. [PMID: 38879106 DOI: 10.1016/j.envres.2024.119426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 06/05/2024] [Accepted: 06/12/2024] [Indexed: 06/21/2024]
Abstract
BACKGROUND Epidemiological evidence emphasizes air pollutants' role in chronic kidney disease (CKD). Volatile organic compounds (VOCs) contribute to air pollution, yet research on VOCs and kidney damage, especially gender disparities, is limited. METHODS This study analyzed NHANES data to explore associations between urinary VOC metabolite mixtures (VOCMs) and key kidney-related parameters: estimated glomerular filtration rate (eGFR), albumin-to-creatinine ratio (ACR), chronic kidney disease (CKD), and albuminuria. Mediation analyses assessed the potential mediating roles of biological aging (BA) and serum albumin in VOCM mixtures' effects on kidney damage. Sensitivity analyses were also conducted. RESULTS The mixture analysis unveiled a noteworthy positive association between VOCM mixtures and the risk of developing CKD, coupled with a significant negative correlation with eGFR within the overall participant cohort. These findings remained consistent when examining the female subgroup. However, among male participants, no significant link emerged between VOCM mixtures and CKD or eGFR. Furthermore, in both the overall and female participant groups, there was an absence of a significant correlation between VOCM mixtures and either ACR or albuminuria. On the other hand, in male participants, while no significant correlation was detected with albuminuria, a significant positive correlation was observed with ACR. Pollutant analysis identified potential links between kidney damage and 1,3-butadiene, toluene, ethylbenzene, styrene, xylene, acrolein, crotonaldehyde and propylene oxide. Mediation analyses suggested that BA might partially mediate the relationship between VOCM mixtures and kidney damage. CONCLUSION The current findings highlight the widespread exposure to VOCs among the general U.S. adult population and indicate a potential correlation between exposure to VOC mixtures and compromised renal function parameters, with notable gender disparities. Females appear to exhibit greater sensitivity to impaired renal function resulting from VOCs exposure. Anti-aging treatments may offer some mitigation against kidney damage due to VOCs exposure.
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Affiliation(s)
- Shuai Zhang
- Department of Male Reproductive Health, Lianyungang Maternal and Child Health Hospital, Qindongmen Avenue, Haizhou District, Lianyungang, 222000, China; Clinical Center of Reproductive Medicine, Lianyungang Maternal and Child Health Hospital, Qindongmen Avenue, Haizhou District, Lianyungang, 222000, China.
| | - Hanhan Tang
- Graduate School of Xuzhou Medical University, Xuzhou Medical University, No. 209, Tongshan Road, Xuzhou, 221004, China
| | - Minglian Zhou
- Department of Male Reproductive Health, Lianyungang Maternal and Child Health Hospital, Qindongmen Avenue, Haizhou District, Lianyungang, 222000, China; Clinical Center of Reproductive Medicine, Lianyungang Maternal and Child Health Hospital, Qindongmen Avenue, Haizhou District, Lianyungang, 222000, China
| | - Linqing Pan
- Clinical Center of Reproductive Medicine, Lianyungang Maternal and Child Health Hospital, Qindongmen Avenue, Haizhou District, Lianyungang, 222000, China
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Huang Q, Li B, Wang Y, Zi H, Zhang Y, Li F, Fang C, Tang S, Jin Y, Huang J, Zeng X. Clinical biomarker-based biological aging and risk of benign prostatic hyperplasia: A large prospective cohort study. Aging Med (Milton) 2024; 7:393-405. [PMID: 38975310 PMCID: PMC11222739 DOI: 10.1002/agm2.12331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 03/14/2024] [Accepted: 05/30/2024] [Indexed: 07/09/2024] Open
Abstract
Objective Chronological age (CAge), biological age (BAge), and accelerated age (AAge) are all important for aging-related diseases. CAge is a known risk factor for benign prostatic hyperplasia (BPH); However, the evidence of association of BAge and AAge with BPH is limited. This study aimed to evaluate the association of CAge, Bage, and AAge with BPH in a large prospective cohort. Method A total of 135,933 males without BPH at enrolment were extracted from the UK biobank. We calculated three BAge measures (Klemera-Doubal method, KDM; PhenoAge; homeostatic dysregulation, HD) based on 16 biomarkers. Additionally, we calculated KDM-BAge and PhenoAge-BAge measures based on the Levine method. The KDM-AAge and PhenoAge-AAge were assessed by the difference between CAge and BAge and were standardized (mean = 0 and standard deviation [SD] = 1). Cox proportional hazard models were applied to assess the associations of CAge, Bage, and AAge with incident BPH risk. Results During a median follow-up of 13.150 years, 11,811 (8.690%) incident BPH were identified. Advanced CAge and BAge measures were associated with an increased risk of BPH, showing threshold effects at a later age (all P for nonlinearity <0.001). Nonlinear relationships between AAge measures and risk of BPH were also found for KDM-AAge (P = 0.041) and PhenoAge-AAge (P = 0.020). Compared to the balance comparison group (-1 SD < AAge < 1 SD), the accelerated aging group (AAge > 2 SD) had a significantly elevated BPH risk with hazard ratio (HR) of 1.115 (95% CI, 1.000-1.223) for KDM-AAge and 1.180 (95% CI, 1.068-1.303) for PhenoAge-AAge, respectively. For PhenoAge-AAge, subgroup analysis of the accelerated aging group showed an increased HR of 1.904 (95% CI, 1.374-2.639) in males with CAge <50 years and 1.233 (95% CI, 1.088-1.397) in those having testosterone levels <12 nmol/L. Moreover, AAge-associated risk of BPH was independent of and additive to genetic risk. Conclusions Biological aging is an independent and modifiable risk factor for BPH. We suggest performing active health interventions to slow biological aging, which will help mitigate the progression of prostate aging and further reduce the burden of BPH.
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Affiliation(s)
- Qiao Huang
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Evidence‐Based Medicine and Clinical Epidemiology, Second School of Clinical MedicineWuhan UniversityWuhanChina
| | - Bing‐Hui Li
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Evidence‐Based Medicine and Clinical Epidemiology, Second School of Clinical MedicineWuhan UniversityWuhanChina
| | - Yong‐Bo Wang
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Evidence‐Based Medicine and Clinical Epidemiology, Second School of Clinical MedicineWuhan UniversityWuhanChina
| | - Hao Zi
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of UrologyZhongnan Hospital of Wuhan UniversityWuhanChina
| | - Yuan‐Yuan Zhang
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Evidence‐Based Medicine and Clinical Epidemiology, Second School of Clinical MedicineWuhan UniversityWuhanChina
| | - Fei Li
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of UrologyZhongnan Hospital of Wuhan UniversityWuhanChina
| | - Cheng Fang
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Evidence‐Based Medicine and Clinical Epidemiology, Second School of Clinical MedicineWuhan UniversityWuhanChina
| | - Shi‐Di Tang
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Evidence‐Based Medicine and Clinical Epidemiology, Second School of Clinical MedicineWuhan UniversityWuhanChina
| | - Ying‐Hui Jin
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Evidence‐Based Medicine and Clinical Epidemiology, Second School of Clinical MedicineWuhan UniversityWuhanChina
- Department of GeriatricsZhongnan Hospital of Wuhan UniversityWuhanChina
| | - Jiao Huang
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Evidence‐Based Medicine and Clinical Epidemiology, Second School of Clinical MedicineWuhan UniversityWuhanChina
| | - Xian‐Tao Zeng
- Center for Evidence‐Based and Translational MedicineZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Evidence‐Based Medicine and Clinical Epidemiology, Second School of Clinical MedicineWuhan UniversityWuhanChina
- Department of UrologyZhongnan Hospital of Wuhan UniversityWuhanChina
- Department of Epidemiology and Biostatistics, School of Health SciencesWuhan UniversityWuhanChina
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Chen Y, Xue H, Nie Y, Zhou Y, Ai S, Liu Y, Zhang J, Liang YY. Evaluation of Changes in Social Isolation and Loneliness with Incident Cardiovascular Events and Mortality. J Epidemiol Glob Health 2024:10.1007/s44197-024-00243-3. [PMID: 38801491 DOI: 10.1007/s44197-024-00243-3] [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: 01/22/2024] [Accepted: 05/10/2024] [Indexed: 05/29/2024] Open
Abstract
BACKGROUND It remains unknown how the patterns of change of social isolation and loneliness are associated with the onset of cardiovascular disease (CVD) and mortality. We aimed to investigate the longitudinal association of changes in social isolation and loneliness with incident CVD, all-cause mortality, CVD mortality and subsequent cardiac function. METHODS This prospective cohort study included 18,258 participants aged 38-73 years who participated in visit 0 (2006-2010) and visit 1 (2012-2013) using UK Biobank (mean age 57.1, standard deviation [SD] 7.4; 48.7% males). Social isolation or loneliness was categorized into four patterns: never, transient, incident, and persistent. Incident CVD, all-cause and CVD mortality were ascertained through linkage data. Cardiac function was assessed by cardiovascular magnetic resonance imaging in a subsample (N = 5188; visit 2, since 2014). RESULTS Over a median follow-up of 8.3 (interquartile range [IQR] 8.1-8.6) years, compared with never social isolation, persistent social isolation was associated with the higher risk of incident CVD (hazard ratio [HR] 1.17, 95% confidence interval [CI] 1.03-1.33), all-cause (1.42, 1.12-1.81) and CVD (1.53, 1.05-2.23) mortality. Likewise, persistent loneliness was strongly associated with the greater risk of incident CVD (1.13, 1.00-1.27), all-cause (1.28, 1.02-1.61) and CVD mortality (1.52, 1.06-2.18). CONCLUSIONS Persistent social isolation and loneliness posed a substantially higher risk for incident CVD, all-cause and CVD mortality, and cardiac dysfunction than other patterns. Persistent social isolation and loneliness, along with an increasing cumulative score, are associated with lower cardiac function.
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Affiliation(s)
- Yilin Chen
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, 510370, Guangzhou, Guangdong, China
- Department of Neurology and National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Huashan Hospital, Fudan University, 200040, Shanghai, China
| | - Huachen Xue
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, 510370, Guangzhou, Guangdong, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, 510260, Guangzhou, Guangdong, China
| | - Yu Nie
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, 510370, Guangzhou, Guangdong, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, 510260, Guangzhou, Guangdong, China
| | - Yujing Zhou
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, 510370, Guangzhou, Guangdong, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, 510260, Guangzhou, Guangdong, China
| | - Sizhi Ai
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, 510370, Guangzhou, Guangdong, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, 510260, Guangzhou, Guangdong, China
- Department of Cardiology, Heart Center, The First Affiliated Hospital of Xinxiang Medical University, 453199, Weihui, Henan, China
| | - Yaping Liu
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, 510370, Guangzhou, Guangdong, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, 510260, Guangzhou, Guangdong, China
| | - Jihui Zhang
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, 510370, Guangzhou, Guangdong, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, 510260, Guangzhou, Guangdong, China
| | - Yannis Yan Liang
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, 510370, Guangzhou, Guangdong, China.
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, 510260, Guangzhou, Guangdong, China.
- Institute of Psycho-neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, 510370, Guangzhou, Guangdong, China.
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Southern Medical University, 510080, Guangzhou, Guangdong, China.
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Ma J, Li P, Jiang Y, Yang X, Luo Y, Tao L, Guo X, Gao B. The Association between Dietary Nutrient Intake and Acceleration of Aging: Evidence from NHANES. Nutrients 2024; 16:1635. [PMID: 38892569 PMCID: PMC11174358 DOI: 10.3390/nu16111635] [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: 04/26/2024] [Revised: 05/23/2024] [Accepted: 05/25/2024] [Indexed: 06/21/2024] Open
Abstract
The acceleration of aging is a risk factor for numerous diseases, and diet has been identified as an especially effective anti-aging method. Currently, research on the relationship between dietary nutrient intake and accelerated aging remains limited, with existing studies focusing on the intake of a small number of individual dietary nutrients. Comprehensive research on the single and mixed anti-aging effects of dietary nutrients has not been conducted. This study aimed to comprehensively explore the effects of numerous dietary nutrient intakes, both singly and in combination, on the acceleration of aging. Data for this study were extracted from the 2015-2018 National Health and Nutrition Examination Surveys (NHANES). The acceleration of aging was measured by phenotypic age acceleration. Linear regression (linear), restricted cubic spline (RCS) (nonlinear), and weighted quantile sum (WQS) (mixed effect) models were used to explore the association between dietary nutrient intake and accelerated aging. A total of 4692 participants aged ≥ 20 were included in this study. In fully adjusted models, intakes of 16 nutrients were negatively associated with accelerated aging (protein, vitamin E, vitamin A, beta-carotene, vitamin B1, vitamin B2, vitamin B6, vitamin K, phosphorus, magnesium, iron, zinc, copper, potassium, dietary fiber, and alcohol). Intakes of total sugars, vitamin C, vitamin K, caffeine, and alcohol showed significant nonlinear associations with accelerated aging. Additionally, mixed dietary nutrient intakes were negatively associated with accelerated aging. Single dietary nutrients as well as mixed nutrient intake may mitigate accelerated aging. Moderately increasing the intake of specific dietary nutrients and maintaining dietary balance may be key strategies to prevent accelerated aging.
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Affiliation(s)
| | | | | | | | | | | | | | - Bo Gao
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Beijing 100069, China
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Liang R, Fan L, Lai X, Shi D, Wang H, Shi W, Liu W, Yu L, Song J, Wang B. Air pollution exposure, accelerated biological aging, and increased thyroid dysfunction risk: Evidence from a nationwide prospective study. ENVIRONMENT INTERNATIONAL 2024; 188:108773. [PMID: 38810493 DOI: 10.1016/j.envint.2024.108773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/30/2024] [Accepted: 05/23/2024] [Indexed: 05/31/2024]
Abstract
BACKGROUND Long-term air pollution exposure is a major health concern, yet its associations with thyroid dysfunction (hyperthyroidism and hypothyroidism) and biological aging remain unclear. We aimed to determine the association of long-term air pollution exposure with thyroid dysfunction and to investigate the potential roles of biological aging. METHODS A prospective cohort study was conducted on 432,340 participants with available data on air pollutants including particulate matter (PM2.5, PM10, and PM2.5-10), nitrogen dioxide (NO2), and nitric oxide (NO) from the UK Biobank. An air pollution score was calculated using principal component analysis to reflect joint exposure to these pollutants. Biological aging was assessed using the Klemera-Doubal method biological age and the phenotypic age algorithms. The associations of individual and joint air pollutants with thyroid dysfunction were estimated using the Cox proportional hazards regression model. The roles of biological aging were explored using interaction and mediation analyses. RESULTS During a median follow-up of 12.41 years, 1,721 (0.40 %) and 9,296 (2.15 %) participants developed hyperthyroidism and hypothyroidism, respectively. All air pollutants were observed to be significantly associated with an increased risk of incident hypothyroidism, while PM2.5, PM10, and NO2 were observed to be significantly associated with an increased risk of incident hyperthyroidism. The hazard ratios (HRs) for hyperthyroidism and hypothyroidism were 1.15 (95 % confidence interval: 1.00-1.32) and 1.15 (1.08-1.22) for individuals in the highest quartile compared with those in the lowest quartile of air pollution score, respectively. Additionally, we noticed that individuals with higher pollutant levels and biologically older generally had a higher risk of incident thyroid dysfunction. Moreover, accelerated biological aging partially mediated 1.9 %-9.4 % of air pollution-associated thyroid dysfunction. CONCLUSIONS Despite the possible underestimation of incident thyroid dysfunction, long-term air pollution exposure may increase the risk of incident thyroid dysfunction, particularly in biologically older participants, with biological aging potentially involved in the mechanisms.
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Affiliation(s)
- Ruyi Liang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Lieyang Fan
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xuefeng Lai
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Da Shi
- Agricultural, Food and Nutritional Science, Faculty of Agricultural, Life and Environmental Sciences, University of Alberta, Edmonton, Alberta T6G 2P5, Canada
| | - Hao Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Wendi Shi
- Lucy Cavendish College, University of Cambridge, Cambridge CB3 0BU, UK
| | - Wei Liu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Linling Yu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Jiahao Song
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Bin Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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Gao X. Environmental aging: through the prism of DNA methylation. Epigenomics 2024:1-4. [PMID: 38869463 DOI: 10.1080/17501911.2024.2345042] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 04/15/2024] [Indexed: 06/14/2024] Open
Affiliation(s)
- Xu Gao
- Department of Occupational & Environmental Health Sciences, School of Public Health,Peking University, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
- Center for Healthy Aging, Peking University Health Science Center, Beijing, 100191, China
- Peking University Institute of Environmental Medicine, Beijing, 100191, China
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Cui F, Tang L, Li D, Ma Y, Wang J, Xie J, Su B, Tian Y, Zheng X. Early-life exposure to tobacco, genetic susceptibility, and accelerated biological aging in adulthood. SCIENCE ADVANCES 2024; 10:eadl3747. [PMID: 38701212 PMCID: PMC11068008 DOI: 10.1126/sciadv.adl3747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 04/03/2024] [Indexed: 05/05/2024]
Abstract
Early-life tobacco exposure serves as a non-negligible risk factor for aging-related diseases. To understand the underlying mechanisms, we explored the associations of early-life tobacco exposure with accelerated biological aging and further assessed the joint effects of tobacco exposure and genetic susceptibility. Compared with those without in utero exposure, participants with in utero tobacco exposure had an increase in Klemera-Doubal biological age (KDM-BA) and PhenoAge acceleration of 0.26 and 0.49 years, respectively, but a decrease in telomere length of 5.34% among 276,259 participants. We also found significant dose-response associations between the age of smoking initiation and accelerated biological aging. Furthermore, the joint effects revealed that high-polygenic risk score participants with in utero exposure and smoking initiation in childhood had the highest accelerated biological aging. There were interactions between early-life tobacco exposure and age, sex, deprivation, and diet on KDM-BA and PhenoAge acceleration. These findings highlight the importance of reducing early-life tobacco exposure to improve healthy aging.
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Affiliation(s)
- Feipeng Cui
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, Hubei, PR China
| | - Linxi Tang
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, Hubei, PR China
| | - Dankang Li
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, Hubei, PR China
| | - Yudiyang Ma
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, Hubei, PR China
| | - Jianing Wang
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, Hubei, PR China
| | - Junqing Xie
- Center for Statistics in Medicine, NDORMS, University of Oxford, The Botnar Research Centre, Oxford, UK
| | - Binbin Su
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences/Peking Union Medical College, No. 31, Beijige-3, Dongcheng District, Beijing 100730, PR China
| | - Yaohua Tian
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, Hubei, PR China
| | - Xiaoying Zheng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences/Peking Union Medical College, No. 31, Beijige-3, Dongcheng District, Beijing 100730, PR China
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Zannas AS. Biological Aging and Mental Illness-A Vicious Cycle? JAMA Psychiatry 2024; 81:433-434. [PMID: 38477905 DOI: 10.1001/jamapsychiatry.2024.0084] [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] [Indexed: 03/14/2024]
Abstract
This Viewpoint discusses biological aging and mental illness.
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Affiliation(s)
- Anthony S Zannas
- Department of Psychiatry, University of North Carolina, Chapel Hill
- Department of Genetics, University of North Carolina, Chapel Hill
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Wang W, Liu Y, Yao Z, Chen D, Tang Y, Cui J, Zhang J, Liu H, Hao Z. A microfluidic-based gut-on-a-chip model containing the gut microbiota of patients with depression reveals physiological characteristics similar to depression. LAB ON A CHIP 2024; 24:2537-2550. [PMID: 38623757 DOI: 10.1039/d3lc01052j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
The diverse commensal microbiome of the human intestine has been considered to play a central role in depression. However, no host-microbiota co-culture system has been developed for depression, which hinders the controlled study of the interaction between depression and gut microbiota. We designed and manufactured a microfluidic-based gut-on-a-chip model containing the gut microbiota of patients with depression (depression-on-gut-chip, DoGC), which enables the extended co-culture of viable aerobic human intestinal epithelial cells and anaerobic gut microbiota, and allows the direct study of interactions between human gut microbiota and depression. We introduced representative gut microbiota from individuals with depression into our constructed DoGC model, successfully recapitulating the gut microbiota structure of depressed patients. This further led to the manifestation of physiological characteristics resembling depression, such as reduced gut barrier function, chronic low-grade inflammatory responses and decreased neurotransmitter 5-HT levels. Metabolome analysis of substances in the DoGC revealed a significant increase in lipopolysaccharides and tyrosine, while hyodeoxycholic acid, L-proline and L-threonine were significantly reduced, indicating the occurrence of depression. The proposed DoGC can serve as an effective platform for studying the gut microbiota of patients with depression, providing important cues for their roles in the pathology of this condition and acting as a powerful tool for personalized medicine.
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Affiliation(s)
- Wenxin Wang
- Institute of Environmental Biology and Life Support Technology, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China.
| | - Yiyuan Liu
- Institute of Environmental Biology and Life Support Technology, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China.
| | - Zhikai Yao
- Institute of Environmental Biology and Life Support Technology, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China.
| | - Dengbo Chen
- Institute of Environmental Biology and Life Support Technology, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China.
| | - Yue Tang
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
| | - Jingwei Cui
- Institute of Environmental Biology and Life Support Technology, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China.
| | - Jiangjiang Zhang
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
| | - Hong Liu
- Institute of Environmental Biology and Life Support Technology, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China.
| | - Zikai Hao
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
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Mak JKL, McMurran CE, Hägg S. Clinical biomarker-based biological ageing and future risk of neurological disorders in the UK Biobank. J Neurol Neurosurg Psychiatry 2024; 95:481-484. [PMID: 37926442 DOI: 10.1136/jnnp-2023-331917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/09/2023] [Indexed: 11/07/2023]
Abstract
BACKGROUND Many common neurological disorders are associated with advancing chronological age, but their association with biological age (BA) remains poorly understood. METHODS We studied 325 870 participants in the UK Biobank without a diagnosed neurological condition at baseline and generated three previously-described measures of BA based on 18 routinely measured clinical biomarkers (PhenoAge, Klemera-Doubal method age (KDMAge), homeostatic dysregulation age). Using survival models, we assessed the effect of advanced BA on incident neurological diagnoses, including all-cause and cause-specific dementia, ischaemic stroke, Parkinson's disease and motor neuron disease. RESULTS During a mean follow-up of 9.0 years, there were 1397 incident cases of dementia and 2515 of ischaemic stroke, with smaller case numbers of other diagnoses. The strongest associations with a 1 SD in BA residual were seen for all-cause dementia (KDMAge HR=1.19, 95% CI=1.11 to 1.26), vascular dementia (1.41, 1.25 to 1.60) and ischaemic stroke (1.39, 1.34 to 1.46). Weaker associations were seen for Alzheimer's disease and motor neuron disease, while, in contrast, HRs for Parkinson's disease tended to be <1. Results were largely consistent after adjustment for disease-specific covariates including common cardiometabolic risk factors. CONCLUSIONS Advanced BA calculated from routine clinical biomarker results increases the risk of subsequent neurological diagnoses including all-cause dementia and ischaemic stroke.
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Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Christopher E McMurran
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Gao X, Wang Y, Song Z, Jiang M, Huang T, Baccarelli AA. Early-life risk factors, accelerated biological aging and the late-life risk of mortality and morbidity. QJM 2024; 117:257-268. [PMID: 37930885 DOI: 10.1093/qjmed/hcad247] [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: 07/26/2023] [Revised: 10/18/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND Early-life exposure increases health risks throughout an individual's lifetime. Biological aging is influenced by early-life risks as a key process of disease development, but whether early-life risks could accelerate biological aging and elevate late-life mortality and morbidity risks remains unknown. Knowledge is also limited on the potential moderating role of healthy lifestyle. METHODS We investigate associations of three early-life risks around birth, breastfeeding, maternal smoking and birth weight, with biological aging of 202 580 UK Biobank participants (54.9 ± 8.1 years old). Biological aging was quantified as KDM-BA, PhenoAge and frailty. Moderate alcohol intake, no current smoking, healthy diet, BMI <30 kg/m2 and regular physical activity were considered as healthy lifestyles. Mortality and morbidity data were retrieved from health records. RESULTS Individual early-life risk factors were robustly associated with accelerated biological aging. A one-unit increase in the 'early-life risk score' integrating the three factors was associated with 0.060 (SE=0.0019) and 0.036-unit (SE = 0.0027) increase in z-scored KDM-BA acceleration and PhenoAge acceleration, respectively, and with 22.3% higher odds (95% CI: 1.185-1.262) of frailty. Increased chronological age and healthy lifestyles could mitigate the accelerations of KDM-BA and PhenoAge, respectively. Associations of early-life risk score with late-life mortality and morbidity were mediated by biological aging (proportions: 5.66-43.12%). KDM-BA and PhenoAge accelerations could significantly mediate the impact on most outcomes except anxiety, and frailty could not mediate the impact on T2D. CONCLUSION Biological aging could capture and mediate the late-life health risks stemming from the early-life risks, and could be potentially targeted for healthy longevity promotion.
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Affiliation(s)
- X Gao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
- Center for Healthy Aging, Peking University Health Science Center, Beijing 100191, China
| | - Y Wang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Z Song
- Department of Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing 100191, China
| | - M Jiang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - T Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - A A Baccarelli
- Laboratory of Environmental Precision Health, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
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Dan YL, Yang YQ, Zhu DC, Bo L, Lei SF. Accelerated biological aging as a potential risk factor for rheumatoid arthritis. Int J Rheum Dis 2024; 27:e15156. [PMID: 38665050 DOI: 10.1111/1756-185x.15156] [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: 02/08/2024] [Revised: 03/15/2024] [Accepted: 04/05/2024] [Indexed: 05/31/2024]
Abstract
OBJECTS Previous studies have suggested a potential correlation between rheumatoid arthritis (RA) and biological aging, but the intricate connections and mechanisms remain elusive. METHODS In our study, we focused on two specific measures of biological age (PhenoAge and BioAge), which are derived from clinical biomarkers. The residuals of these measures, when compared to chronological age, are defined as biological age accelerations (BAAs). Utilizing the extensive UK Biobank dataset along with various genetic datasets, we conducted a thorough assessment of the relationship between BAAs and RA at both the individual and aggregate levels. RESULTS Our observational studies revealed positive correlations between the two BAAs and the risk of developing both RA and seropositive RA. Furthermore, the genetic risk score (GRS) for PhenoAgeAccel was associated with an increased risk of RA and seropositive RA. Linkage disequilibrium score regression (LDSC) analysis further supported these findings, revealing a positive genetic correlation between PhenoAgeAccel and RA. PLACO analysis identified 38 lead pleiotropic single nucleotide polymorphisms linked to 301 genes, providing valuable insights into the potential mechanisms connecting PhenoAgeAccel and RA. CONCLUSION In summary, our study has successfully revealed a positive correlation between accelerated biological aging, as measured by BAAs, and the susceptibility to RA.
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Affiliation(s)
- Yi-Lin Dan
- Collaborative Innovation Center for Bone and Immunology between Sihong Hospital and Soochow University, Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Soochow University, Suzhou, Jiangsu, China
| | - Yi-Qun Yang
- Collaborative Innovation Center for Bone and Immunology between Sihong Hospital and Soochow University, Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Soochow University, Suzhou, Jiangsu, China
| | - Dong-Cheng Zhu
- Department of Orthopedics, Collaborative Innovation Center for Bone and Immunology between Sihong Hospital and Soochow University, Suqian, Jiangsu, China
| | - Lin Bo
- Department of Rheumatology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Shu-Feng Lei
- Collaborative Innovation Center for Bone and Immunology between Sihong Hospital and Soochow University, Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Soochow University, Suzhou, Jiangsu, China
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Cortez BN, Pan H, Hinthorn S, Sun H, Neretti N, Gloyn AL, Aguayo-Mazzucato C. Heterogeneity of increased biological age in type 2 diabetes correlates with differential tissue DNA methylation, biological variables, and pharmacological treatments. GeroScience 2024; 46:2441-2461. [PMID: 37987887 PMCID: PMC10828255 DOI: 10.1007/s11357-023-01009-8] [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: 07/17/2023] [Accepted: 11/02/2023] [Indexed: 11/22/2023] Open
Abstract
Biological age (BA) closely depicts age-related changes at a cellular level. Type 2 diabetes mellitus (T2D) accelerates BA when calculated using clinical biomarkers, but there is a large spread in the magnitude of individuals' age acceleration in T2D suggesting additional factors contributing to BA. Additionally, it is unknown whether BA can be changed with treatment. We hypothesized that potential determinants of the heterogeneous BA distribution in T2D could be due to differential tissue aging as reflected at the DNA methylation (DNAm) level, or biological variables and their respective therapeutic treatments. Publicly available DNAm samples were obtained to calculate BA using the DNAm phenotypic age (DNAmPhenoAge) algorithm. DNAmPhenoAge showed age acceleration in T2D samples of whole blood, pancreatic islets, and liver, but not in adipose tissue or skeletal muscle. Analysis of genes associated with differentially methylated CpG sites found a significant correlation between eight individual CpG methylation sites and gene expression. Clinical biomarkers from participants in the NHANES 2017-2018 and ACCORD cohorts were used to calculate BA using the Klemera and Doubal (KDM) method. Cardiovascular and glycemic biomarkers associated with increased BA while intensive blood pressure and glycemic management reduced BA to CA levels, demonstrating that accelerated BA can be restored in the setting of T2D.
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Affiliation(s)
- Briana N Cortez
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
- University of Texas Rio Grande Valley School of Medicine, Edinburg, TX, USA
| | - Hui Pan
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - Samuel Hinthorn
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, 02912, USA
| | - Han Sun
- Division of Endocrinology, Department of Pediatrics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Nicola Neretti
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, 02912, USA
| | - Anna L Gloyn
- Division of Endocrinology, Department of Pediatrics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
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Wu D, Qu C, Huang P, Geng X, Zhang J, Shen Y, Rao Z, Zhao J. Better Life's Essential 8 contributes to slowing the biological aging process: a cross-sectional study based on NHANES 2007-2010 data. Front Public Health 2024; 12:1295477. [PMID: 38544722 PMCID: PMC10965682 DOI: 10.3389/fpubh.2024.1295477] [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] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 02/07/2024] [Indexed: 05/03/2024] Open
Abstract
Objective To investigate the relationship between Life's Essential 8 (LE8) and Phenotypic Age Acceleration (PhenoAgeAccel) in United States adults and to explore the impact of LE8 on phenotypic biological aging, thereby providing references for public health policies and health education. Methods Utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2010, this cross-sectional study analyzed 7,339 adults aged 20 and above. Comprehensive assessments of LE8, PhenoAgeAccel, and research covariates were achieved through the integration of Demographics Data, Dietary Data, Laboratory Data, and Questionnaire Data derived from NHANES. Weighted generalized linear regression models and restricted cubic spline plots were employed to analyze the linear and non-linear associations between LE8 and PhenoAgeAccel, along with gender subgroup analysis and interaction effect testing. Results (1) Dividing the 2007-2010 NHANES cohort into quartiles based on LE8 unveiled significant disparities in age, gender, race, body mass index, education level, marital status, poverty-income ratio, smoking and drinking statuses, diabetes, hypertension, hyperlipidemia, phenotypic age, PhenoAgeAccel, and various biological markers (p < 0.05). Mean cell volume demonstrated no intergroup differences (p > 0.05). (2) The generalized linear regression weighted models revealed a more pronounced negative correlation between higher quartiles of LE8 (Q2, Q3, and Q4) and PhenoAgeAccel compared to the lowest LE8 quartile in both crude and fully adjusted models (p < 0.05). This trend was statistically significant (p < 0.001) in the full adjustment model. Gender subgroup analysis within the fully adjusted models exhibited a significant negative relationship between LE8 and PhenoAgeAccel in both male and female participants, with trend tests demonstrating significant results (p < 0.001 for males and p = 0.001 for females). (3) Restricted cubic spline (RCS) plots elucidated no significant non-linear trends between LE8 and PhenoAgeAccel overall and in gender subgroups (p for non-linear > 0.05). (4) Interaction effect tests denoted no interaction effects between the studied stratified variables such as age, gender, race, education level, and marital status on the relationship between LE8 and PhenoAgeAccel (p for interaction > 0.05). However, body mass index and diabetes manifested interaction effects (p for interaction < 0.05), suggesting that the influence of LE8 on PhenoAgeAccel might vary depending on an individual's BMI and diabetes status. Conclusion This study, based on NHANES data from 2007-2010, has revealed a significant negative correlation between LE8 and PhenoAgeAccel, emphasizing the importance of maintaining a healthy lifestyle in slowing down the biological aging process. Despite the limitations posed by the study's design and geographical constraints, these findings provide a scientific basis for the development of public health policies focused on healthy lifestyle practices. Future research should further investigate the causal mechanisms underlying the relationship between LE8 and PhenoAgeAccel and consider cross-cultural comparisons to enhance our understanding of healthy aging.
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Affiliation(s)
- Dongzhe Wu
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
| | - Chaoyi Qu
- Physical Education College, Hebei Normal University, Shijiazhuang, China
| | - Peng Huang
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
| | - Xue Geng
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
| | | | - Yulin Shen
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
| | - Zhijian Rao
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
- College of Physical Education, Shanghai Normal University, Shanghai, China
| | - Jiexiu Zhao
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
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Wang J, Liu M, Tian C, Gu J, Chen S, Huang Q, Lv P, Zhang Y, Li W. Elaboration and validation of a novelty nomogram for the prognostication of anxiety susceptibility in individuals suffering from low back pain. J Clin Neurosci 2024; 122:35-43. [PMID: 38461740 DOI: 10.1016/j.jocn.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/22/2024] [Accepted: 03/06/2024] [Indexed: 03/12/2024]
Abstract
Low back pain (LBP) constitutes a distressing emotional ordeal and serves as a potent catalyst for adverse emotional states, notably anxiety. We dedicated to discerning methodologies for identifying patients who are predisposed to heightened levels of anxiety and pain. A self-assessment questionnaire was administered to patients afflicted with LBP. The pain scores were subjected to analysis in conjunction with anxiety scores, and a clustering procedure was executed using the scientific k-means methodology. Subsequently, six machine learning algorithms, including Logistics Regression (LR), K-Nearest Neighbor (KNN), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGB), were employed. Next, five pertinent variables were identified, namely Age, Course, Body Mass Index (BMI), Education, and Marital status. Furthermore, a LR model was utilized to construct a nomogram, which was subsequently subjected to assessment for discrimination, calibration, and evaluation of its clinical utility. As a result, 599 questionnaires were valid (effective rate: 99 %). The correlation analysis revealed a significant association between anxiety and pain scores (r = 0.31, P < 0.001). LBP patients could be divided into two clusters, Cluster1 had higher pain scores (P < 0.05) and SAS scores (P < 0.001). The proposed nomogram demonstrated an area under the receiver operating characteristics curve (ROC) of 0.841 (95 %CI: 0.804-0.878) and 0.800 (95 %CI: 0.733-0.867) in the training and test groups, respectively. Briefly, the established nomogram has demonstrated remarkable proficiency in discerning individuals afflicted with LBP who are at a heightened risk of experiencing anxiety.
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Affiliation(s)
- Jian Wang
- Department of Neurosurgery, Tangdu Hospital, Affiliated Hospital of the Air Force Medical University, Xi'an, China
| | - Miaomiao Liu
- Department of Respiratory and Critical Care Medicine, Tangdu Hospital, Affiliated Hospital of the Air Force Medical University, Xi'an, China
| | - Chao Tian
- Department of Rehabilitation, Southeast Hospital, Affiliated Hospital of Xiamen University, Xiamen, China
| | - Junxiang Gu
- Department of Neurosurgery, the Second Affiliated Hospital of the Xi'an Jiaotong University, Xi'an, China
| | - Sihai Chen
- Department of Psychiatry, Xiaogan Mental Health Center, Xiaogan, China
| | - Qiujuan Huang
- Department of Rehabilitation, Southeast Hospital, Affiliated Hospital of Xiamen University, Xiamen, China
| | - Peiyuan Lv
- Department of Neurosurgery, Tangdu Hospital, Affiliated Hospital of the Air Force Medical University, Xi'an, China
| | - Yuhai Zhang
- Department of Health Statistics and Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational, China.
| | - Weixin Li
- Department of Neurosurgery, Tangdu Hospital, Affiliated Hospital of the Air Force Medical University, Xi'an, China.
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Zou X, Zhao J, Feng A, Chan KHK, Wu WC, Manson JE, Liu S, Li J. Adversities in childhood and young adulthood and incident cardiovascular diseases: a prospective cohort study. EClinicalMedicine 2024; 69:102458. [PMID: 38333371 PMCID: PMC10850111 DOI: 10.1016/j.eclinm.2024.102458] [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: 10/14/2023] [Revised: 01/15/2024] [Accepted: 01/16/2024] [Indexed: 02/10/2024] Open
Abstract
Background Much remains unknown regarding the associations of adversities in childhood and adulthood with incident cardiovascular diseases (CVD). We aimed to examine the independent and cumulative relations of adversities in childhood and adulthood with incident CVD and whether these associations can be mitigated by adopting a healthy lifestyle later in life. Methods We included 136,073 men and women [38-72 years at baseline] free of diagnosed CVD at baseline who responded to surveys on adversities in childhood and adulthood in the United Kingdom Biobank prospective cohort. They were recruited between 2006 and 2010 and were followed-up until 28 January 2021. Adversities included physical abuse, emotional abuse, sexual abuse, emotional neglect, and physical neglect. Participants were categorised into four groups according to the exposure periods, which were no adversity, childhood adversity only, adulthood adversity only, and cumulative adversity (both childhood and adulthood). The primary outcomes included incident fatal and non-fatal CVD events. The modifiable lifestyle factors were smoking, physical activity, diet, sleeping, social or leisure activities, and friend or family visits. Findings We identified 16,415 (10.71/1000 person-year) incident CVD during a median follow-up of 11.8 years. Compared with participants with no adversity, CVD incidence increased by 11% in those with childhood adversity only (adjusted hazard ratio [HR]: 1.11 [95% CI 1.06-1.17], p < 0.001), 4% in those with adulthood adversity only (1.04 [1.00-1.09], p = 0.05), and 21% in those with cumulative adversity (1.21 [1.16-1.26], p < 0.001). Analysis of interactions showed that adulthood adversity amplified the childhood adversity-CVD association (p for interaction = 0.03). Compared with the participants with one or fewer ideal lifestyle factors, those with more than four ideal factors had a 25%-36% lower risk of CVD across the three adversity groups. Interpretation Our findings suggested that childhood adversities were associated with an increased risk of CVD which can be magnified by adulthood adversities and substantially mitigated by adopting a healthy lifestyle later in life. Funding The National Natural Science Foundation of China and Guangzhou Foundation for Basic and Applied Basic Research.
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Affiliation(s)
- Xia Zou
- Global Health Research Centre, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Junfei Zhao
- Department of Cardiovascular Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Anping Feng
- Global Health Research Centre, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Kei Hang Katie Chan
- Department of Epidemiology and Centre for Global Cardiometabolic Health, School of Public Health, Brown University, Providence, RI, USA
- Departments of Biomedical Sciences and Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China
| | - Wen-Chih Wu
- Department of Epidemiology and Centre for Global Cardiometabolic Health, School of Public Health, Brown University, Providence, RI, USA
- Division of Cardiology, Department of Medicine, Providence VA Medical Centre & Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Simin Liu
- Global Health Research Centre, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
- Department of Epidemiology and Centre for Global Cardiometabolic Health, School of Public Health, Brown University, Providence, RI, USA
- Departments of Medicine and Surgery, The Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Jie Li
- Global Health Research Centre, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
- School of Medicine, South China University of Technology, Guangzhou, China
- Department of Epidemiology and Centre for Global Cardiometabolic Health, School of Public Health, Brown University, Providence, RI, USA
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Zhi Z, Yan S, Yijuan H, Jiahuan Z, Xiaohan J, Dandan C. Trends in the disease burden of anxiety disorders in middle-aged and older adults in China. BMC Psychol 2024; 12:83. [PMID: 38373999 PMCID: PMC10877872 DOI: 10.1186/s40359-024-01575-2] [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: 01/01/2024] [Accepted: 02/05/2024] [Indexed: 02/21/2024] Open
Abstract
BACKGROUND Anxiety disorders in middle-aged and older adults are an important public health concern in China. Based on the data in the global disease burden (GDB) research database, this study evaluated and analyzed the trend of the disease burden of middle-aged and older patients living with anxiety in China in the past 30 years. METHODS The incidence and disability-adjusted life years (DALYs) data of anxiety disorders in China for individuals aged 45-89 years were collected from the Global Burden of Disease Study 2019, and the effects of age, period, and cohort on the incidence of and DALY rate for anxiety disorders were analysed using an age-period-cohort model. Because of the COVID-19 pandemic, the global disease burden research database has not been updated since 2019. However, this did not affect the analysis of future trends in this study, which combined data in the past three decades from 1990 to 2019. RESULTS (1) The overall age-standardised incidence rate (ASIR) and age-standardised DALY rate (ASDR) for anxiety disorders in middle-aged and older adults in China decreased by 4.0 and 7.7% from 1990 to 2019, respectively, and the ASIR and ASDR were always higher in women than in men. (2)Age-period-cohort analysis showed that the net drifts for incidence and DALY rate were - 0.27% and - 0.55% per year, respectively. For both genders, the local drifts for incidence were lower than zero in those aged 45-79 years and higher than zero in those aged 80-89 years; the local drifts for the DALY rate were lower than zero in all groups. (3) From the 1990-1994 to 2015-2019, the relative risks of anxiety disorder incidence and DALY decreased by 5.6 and 7.3% in men and 4.3 and 11.7% in women, respectively. CONCLUSION The disease burden of anxiety disorders in middle-aged and older adults in China has been relieved over the past 30 years; however, recent ASDR, ASDR, period, and cohort effects have shown adverse trends. The incidence and DALY rate decreased with age in women, while men showed a trend of increasing first and decreasing afterwards.
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Affiliation(s)
- Zeng Zhi
- School of Health and Economics Management, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
- School of Nursing, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
| | - Shi Yan
- Pukou Hospital of Traditional Chinese Medicine in Nanjing, Nanjing, 211899, China.
| | - He Yijuan
- School of Health and Economics Management, Nanjing University of Chinese Medicine, Nanjing, 210023, China
- Science and Education Department, Taicang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou, 215400, Jiangsu Province, China
| | - Zheng Jiahuan
- School of Health and Economics Management, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Jiang Xiaohan
- School of Health and Economics Management, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Chen Dandan
- School of Health and Economics Management, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
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20
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Chen X, Wei D, Fang F, Song H, Yin L, Kaijser M, Gurholt TP, Andreassen OA, Valdimarsdóttir U, Hu K, Duan M. Peripheral vertigo and subsequent risk of depression and anxiety disorders: a prospective cohort study using the UK Biobank. BMC Med 2024; 22:63. [PMID: 38336700 PMCID: PMC10858592 DOI: 10.1186/s12916-023-03179-w] [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] [Received: 07/03/2023] [Accepted: 11/15/2023] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND Peripheral vertigo is often comorbid with psychiatric disorders. However, no longitudinal study has quantified the association between peripheral vertigo and risk of psychiatric disorders. Furthermore, it remains unknown how the white matter integrity of frontal-limbic network relates to the putative peripheral vertigo-psychiatric disorder link. METHODS We conducted a cohort study including 452,053 participants of the UK Biobank with a follow-up from 2006 through 2021. We assessed the risks of depression and anxiety disorders in relation to a hospitalization episode involving peripheral vertigo using Cox proportional hazards models. We also examined the associations of peripheral vertigo, depression, and anxiety with MRI fractional anisotropy (FA) in a subsample with brain MRI data (N = 36,087), using multivariable linear regression. RESULTS Individuals with an inpatient diagnosis of peripheral vertigo had elevated risks of incident depression (hazard ratio (HR) 2.18; 95% confidence interval (CI) 1.79-2.67) and anxiety (HR 2.11; 95% CI 1.71-2.61), compared to others, particularly within 2 years after hospitalization (HR for depression 2.91; 95% CI 2.04-4.15; HR for anxiety 4.92; 95% CI 3.62-6.69). Depression was associated with lower FA in most studied white matter regions, whereas anxiety and peripheral vertigo did not show statistically significant associations with FA. CONCLUSIONS Individuals with an inpatient diagnosis of peripheral vertigo have increased subsequent risks of depression and anxiety disorders, especially within 2 years after hospitalization. Our findings further indicate a link between depression and lower microstructural connectivity as well as integrity beyond the frontal-limbic network.
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Affiliation(s)
- Xiaowan Chen
- Department of Otolaryngology Head and Neck Surgery, the First Hospital of Lanzhou University, Lanzhou, Gansu Province, China
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
- Department of Otolaryngology Head and Neck Surgery & Audiology and Neurotology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Dang Wei
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Fang Fang
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Huan Song
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
- Centre of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Li Yin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Magnus Kaijser
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Tiril Pedersen Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital &, University of Oslo, Oslo, Norway
| | - Ole Andreas Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital &, University of Oslo, Oslo, Norway
| | - Unnur Valdimarsdóttir
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
- Centre of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Epidemiology, Harvard TH Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Kejia Hu
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden.
| | - Maoli Duan
- Department of Otolaryngology Head and Neck Surgery & Audiology and Neurotology, Karolinska University Hospital, Stockholm, Sweden.
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 171 77, Stockholm, Sweden.
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21
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Wang T, Duan W, Jia X, Huang X, Liu Y, Meng F, Ni C. Associations of combined phenotypic ageing and genetic risk with incidence of chronic respiratory diseases in the UK Biobank: a prospective cohort study. Eur Respir J 2024; 63:2301720. [PMID: 38061785 PMCID: PMC10882326 DOI: 10.1183/13993003.01720-2023] [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: 02/09/2023] [Accepted: 11/29/2023] [Indexed: 02/24/2024]
Abstract
BACKGROUND Accelerated biological ageing has been associated with an increased risk of several chronic respiratory diseases. However, the associations between phenotypic age, a new biological age indicator based on clinical chemistry biomarkers, and common chronic respiratory diseases have not been evaluated. METHODS We analysed data from 308 592 participants at baseline in the UK Biobank. The phenotypic age was calculated from chronological age and nine clinical chemistry biomarkers, including albumin, alkaline phosphatase, creatinine, glucose, C-reactive protein, lymphocyte percent, mean cell volume, red cell distribution width and white blood cell count. Furthermore, phenotypic age acceleration (PhenoAgeAccel) was calculated by regressing phenotypic age on chronological age. The associations of PhenoAgeAccel with incident common chronic respiratory diseases and cross-sectional lung function were investigated. Moreover, we constructed polygenic risk scores and evaluated whether PhenoAgeAccel modified the effect of genetic susceptibility on chronic respiratory diseases and lung function. RESULTS The results showed significant associations of PhenoAgeAccel with increased risk of idiopathic pulmonary fibrosis (IPF) (hazard ratio (HR) 1.52, 95% CI 1.45-1.59), COPD (HR 1.54, 95% CI 1.51-1.57) and asthma (HR 1.18, 95% CI 1.15-1.20) per 5-year increase and decreased lung function. There was an additive interaction between PhenoAgeAccel and the genetic risk for IPF and COPD. Participants with high genetic risk and who were biologically older had the highest risk of incident IPF (HR 5.24, 95% CI 3.91-7.02), COPD (HR 2.99, 95% CI 2.66-3.36) and asthma (HR 2.07, 95% CI 1.86-2.31). Mediation analysis indicated that PhenoAgeAccel could mediate 10∼20% of the associations between smoking and chronic respiratory diseases, while ∼10% of the associations between particulate matter with aerodynamic diameter <2.5 µm and the disorders were mediated by PhenoAgeAccel. CONCLUSION PhenoAgeAccel was significantly associated with incident risk of common chronic respiratory diseases and decreased lung function and could serve as a novel clinical biomarker.
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Affiliation(s)
- Ting Wang
- Department of Pathology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- Department of Occupational Medical and Environmental Health, Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Public Health, Kangda College of Nanjing Medical University, Lianyungang, China
| | - Weiwei Duan
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
- Joint first authors
- Joint first authors
| | - Xinying Jia
- Department of Occupational Medical and Environmental Health, Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xinmei Huang
- Department of Respiratory Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Yi Liu
- Department of Occupational Medical and Environmental Health, Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China
- Contributed equally to this article as lead authors and supervised the work
| | - Fanqing Meng
- Department of Pathology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- Contributed equally to this article as lead authors and supervised the work
| | - Chunhui Ni
- Department of Occupational Medical and Environmental Health, Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Public Health, Kangda College of Nanjing Medical University, Lianyungang, China
- Contributed equally to this article as lead authors and supervised the work
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22
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Diniz BS, Seitz-Holland J, Sehgal R, Kasamoto J, Higgins-Chen AT, Lenze E. Geroscience-Centric Perspective for Geriatric Psychiatry: Integrating Aging Biology With Geriatric Mental Health Research. Am J Geriatr Psychiatry 2024; 32:1-16. [PMID: 37845116 PMCID: PMC10841054 DOI: 10.1016/j.jagp.2023.09.014] [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] [Received: 07/20/2023] [Revised: 08/30/2023] [Accepted: 09/14/2023] [Indexed: 10/18/2023]
Abstract
The geroscience hypothesis asserts that physiological aging is caused by a small number of biological pathways. Despite the explosion of geroscience research over the past couple of decades, the research on how serious mental illnesses (SMI) affects the biological aging processes is still in its infancy. In this review, we aim to provide a critical appraisal of the emerging literature focusing on how we measure biological aging systematically, and in the brain and how SMIs affect biological aging measures in older adults. We will also review recent developments in the field of cellular senescence and potential targets for interventions for SMIs in older adults, based on the geroscience hypothesis.
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Affiliation(s)
- Breno S Diniz
- UConn Center on Aging & Department of Psychiatry (BSD), School of Medicine, University of Connecticut Health Center, Farmington, CT.
| | - Johanna Seitz-Holland
- Department of Psychiatry (JSH), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry (JSH), Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Raghav Sehgal
- Program in Computational Biology and Bioinformatics (RS, JK), Yale University, New Haven, CT
| | - Jessica Kasamoto
- Program in Computational Biology and Bioinformatics (RS, JK), Yale University, New Haven, CT
| | - Albert T Higgins-Chen
- Department of Psychiatry (ATHC), Yale University School of Medicine, New Haven, CT; Department of Pathology (ATHC), Yale University School of Medicine, New Haven, CT
| | - Eric Lenze
- Department of Psychiatry (EL), School of Medicine, Washington University at St. Louis, St. Louis, MO
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23
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Liu W, You J, Ge Y, Wu B, Zhang Y, Chen S, Zhang Y, Huang S, Ma L, Feng J, Cheng W, Yu J. Association of biological age with health outcomes and its modifiable factors. Aging Cell 2023; 22:e13995. [PMID: 37723992 PMCID: PMC10726867 DOI: 10.1111/acel.13995] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 09/04/2023] [Accepted: 09/07/2023] [Indexed: 09/20/2023] Open
Abstract
Identifying the clinical implications and modifiable and unmodifiable factors of aging requires the measurement of biological age (BA) and age gap. Leveraging the biomedical traits involved with physical measures, biochemical assays, genomic data, and cognitive functions from the healthy participants in the UK Biobank, we establish an integrative BA model consisting of multi-dimensional indicators. Accelerated aging (age gap >3.2 years) at baseline is associated incident circulatory diseases, related chronic disorders, all-cause, and cause-specific mortality. We identify 35 modifiable factors for age gap (p < 4.81 × 10-4 ), where pulmonary functions, body mass, hand grip strength, basal metabolic rate, estimated glomerular filtration rate, and C-reactive protein show the most significant associations. Genetic analyses replicate the possible associations between age gap and health-related outcomes and further identify CST3 as an essential gene for biological aging, which is highly expressed in the brain and is associated with immune and metabolic traits. Our study profiles the landscape of biological aging and provides insights into the preventive strategies and therapeutic targets for aging.
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Affiliation(s)
- Wei‐Shi Liu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical College, Fudan UniversityShanghaiChina
| | - Jia You
- Institute of Science and Technology for Brain‐Inspired Intelligence, Fudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University), Ministry of EducationShanghaiChina
| | - Yi‐Jun Ge
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical College, Fudan UniversityShanghaiChina
| | - Bang‐Sheng Wu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical College, Fudan UniversityShanghaiChina
| | - Yi Zhang
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical College, Fudan UniversityShanghaiChina
| | - Shi‐Dong Chen
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical College, Fudan UniversityShanghaiChina
| | - Ya‐Ru Zhang
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical College, Fudan UniversityShanghaiChina
| | - Shu‐Yi Huang
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical College, Fudan UniversityShanghaiChina
| | - Ling‐Zhi Ma
- Department of Neurology, Qingdao Municipal HospitalQingdao UniversityQingdaoChina
| | - Jian‐Feng Feng
- Institute of Science and Technology for Brain‐Inspired Intelligence, Fudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University), Ministry of EducationShanghaiChina
- Department of Computer ScienceUniversity of WarwickCoventryUK
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical College, Fudan UniversityShanghaiChina
- Institute of Science and Technology for Brain‐Inspired Intelligence, Fudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University), Ministry of EducationShanghaiChina
- Fudan ISTBI—ZJNU Algorithm Centre for Brain‐Inspired IntelligenceZhejiang Normal UniversityJinhuaChina
- Shanghai Medical College and Zhongshan Hosptital Immunotherapy Technology Transfer CenterShanghaiChina
| | - Jin‐Tai Yu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical College, Fudan UniversityShanghaiChina
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24
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Zhang Z, Zeng C, Chen Z, Liu P, Gao J, Guo Q, Wu M, He W, Gao Q, Guo D, Liang X, Huang Z, Wang J, Zhang H, Chen Y. Age at job initiation and risk of coronary heart disease: findings from the UK biobank cohort study. BMC Public Health 2023; 23:2123. [PMID: 37899473 PMCID: PMC10614325 DOI: 10.1186/s12889-023-17034-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 10/20/2023] [Indexed: 10/31/2023] Open
Abstract
BACKGROUND Commencing work at an early age has been linked to various risk factors for coronary heart disease (CHD), such as shift work and intensive job strain. However, the relationship between starting work too early and CHD risk remains largely unclear. We examined the association between age at job initiation and the risk of CHD. METHODS UK Biobank participants aged 38 to 70 years without cardiovascular disease who provided data on their age at job initiation were included. The primary outcome was CHD, which was ascertained using hospital and death records. The hazard ratios (HRs) and 95% confidence interval (CIs) for the association between age at job initiation and CHD were calculated using multivariable Cox regression. RESULTS Of the 501,971 participants, 114,418 eligible participants were included in the final analysis. The median age at job initiation was 19.0 years. During the mean follow-up of 12.6 years, 6,130 (5.4%) first CHD events occurred. We observed that age at job initiation was inversely associated with CHD (HR 0.98, 95% CI 0.97-0.99), and the association was potentially J-shaped. The HRs for the < 17-year, 17-18-year, and 19-21-year age groups were 1.29 (95%CI 1.18-1.41), 1.12 (95% CI 1.03-1.22) and 1.05 (95% CI 0.97-1.14), respectively, compared with those of the ≥ 22-year group. CONCLUSIONS Age at job initiation was associated with incident CHD, which was independent of socioeconomic status. Participants who commenced employment before the age of 19 years exhibited a higher risk of developing CHD later in adulthood.
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Affiliation(s)
- Zenghui Zhang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Chuanrui Zeng
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhiteng Chen
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Pinming Liu
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jingwei Gao
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qi Guo
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Maoxiong Wu
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Wanbing He
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qingyuan Gao
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Dachuan Guo
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaotian Liang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zegui Huang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jingfeng Wang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
| | - Haifeng Zhang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
| | - Yangxin Chen
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
- Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
- Guangzhou Key Laboratory of Molecular Mechanism and Translation in Major Cardiovascular Disease, Sun Yat- sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
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25
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Radford-Smith DE, Anthony DC. Leveraging Health Linkage Data From the UK Biobank-With Great Power Comes Great Responsibility. JAMA Psychiatry 2023; 80:1077. [PMID: 37610725 DOI: 10.1001/jamapsychiatry.2023.2966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Affiliation(s)
| | - Daniel C Anthony
- Department of Pharmacology, University of Oxford, Oxford, United Kingdom
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