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Collinge CW, Razzoli M, Mansk R, McGonigle S, Lamming DW, Pacak CA, van der Pluijm I, Niedernhofer L, Bartolomucci A. The mouse Social Frailty Index (mSFI): a novel behavioral assessment for impaired social functioning in aging mice. GeroScience 2024:10.1007/s11357-024-01263-4. [PMID: 38987495 DOI: 10.1007/s11357-024-01263-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 06/23/2024] [Indexed: 07/12/2024] Open
Abstract
Various approaches exist to quantify the aging process and estimate biological age on an individual level. Frailty indices based on an age-related accumulation of physical deficits have been developed for human use and translated into mouse models. However, declines observed in aging are not limited to physical functioning but also involve social capabilities. The concept of "social frailty" has been recently introduced into human literature, but no index of social frailty exists for laboratory mice yet. To fill this gap, we developed a mouse Social Frailty Index (mSFI) consisting of seven distinct assays designed to quantify social functioning which is relatively simple to execute and is minimally invasive. Application of the mSFI in group-housed male C57BL/6 mice demonstrated a progressively elevated levels of social frailty through the lifespan. Conversely, group-housed females C57BL/6 mice manifested social frailty only at a very old age. Female mice also showed significantly lower mSFI score from 10 months of age onward when compared to males. We also applied the mSFI in male C57BL/6 mice under chronic subordination stress and in chronic isolation, both of which induced larger increases in social frailty compared to age-matched group-housed males. Lastly, we show that the mSFI is enhanced in mouse models that show accelerated biological aging such as progeroid Ercc1-/Δ and Xpg-/- mice of both sexes compared to age matched littermate wild types. In summary, the mSFI represents a novel index to quantify trajectories of biological aging in mice and may help elucidate links between impaired social behavior and the aging process.
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Affiliation(s)
- Charles W Collinge
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Maria Razzoli
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Rachel Mansk
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Seth McGonigle
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Dudley W Lamming
- Department of Medicine, University of Wisconsin, Madison, WI, USA
- William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Christina A Pacak
- Greg Marzolf Jr. Muscular Dystrophy Center & Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Ingrid van der Pluijm
- Department of Molecular Genetics, and Department of Vascular Surgery, Cardiovascular Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Laura Niedernhofer
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
- Institute on the Biology of Aging and Metabolism, University of Minnesota, Minneapolis, MN, USA
| | - Alessandro Bartolomucci
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA.
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Balachandran A, Pei H, Beard J, Caspi A, Cohen A, Domingue BW, Eckstein Indik C, Ferrucci L, Furuya A, Kothari M, Moffitt TE, Ryan C, Skirbekk V, Zhang Y, Belsky DW. Pace of Aging in older adults matters for healthspan and lifespan. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.25.24306359. [PMID: 38712264 PMCID: PMC11071564 DOI: 10.1101/2024.04.25.24306359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
As societies age, policy makers need tools to understand how demographic aging will affect population health and to develop programs to increase healthspan. The current metrics used for policy analysis do not distinguish differences caused by early-life factors, such as prenatal care and nutrition, from those caused by ongoing changes in people's bodies due to aging. Here we introduce an adapted Pace of Aging method designed to quantify differences between individuals and populations in the speed of aging-related health declines. The adapted Pace of Aging method, implemented in data from N=13,626 older adults in the US Health and Retirement Study, integrates longitudinal data on blood biomarkers, physical measurements, and functional tests. It reveals stark differences in rates of aging between population subgroups and demonstrates strong and consistent prospective associations with incident morbidity, disability, and mortality. Pace of Aging can advance the population science of healthy longevity.
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Affiliation(s)
- A Balachandran
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
| | - H Pei
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - J Beard
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Health Policy & Management, Columbia University Mailman School of Public Health, New York, NY, USA
| | - A Caspi
- Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
- Social, Genetic, and Developmental Psychiatry Unit, Institute of Psychiatry, Kings College, University of London, London, UK
| | - A Cohen
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - BW Domingue
- Graduate School of Education, Stanford University, Palo Alto, CA, USA
| | - C Eckstein Indik
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
| | - L Ferrucci
- National Institute on Aging, Bethesda, MD, USA
| | - A Furuya
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - M Kothari
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
| | - TE Moffitt
- Social, Genetic, and Developmental Psychiatry Unit, Institute of Psychiatry, Kings College, University of London, London, UK
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - C Ryan
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
| | - V Skirbekk
- Norwegian Institute for Public Health, Oslo, Norway
| | - Y Zhang
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Sociomedical Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - DW Belsky
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Health Policy & Management, Columbia University Mailman School of Public Health, New York, NY, USA
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3
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Reuter-Lorenz PA, Park DC. Cognitive aging and the life course: A new look at the Scaffolding theory. Curr Opin Psychol 2024; 56:101781. [PMID: 38278087 DOI: 10.1016/j.copsyc.2023.101781] [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: 09/16/2023] [Revised: 11/21/2023] [Accepted: 12/06/2023] [Indexed: 01/28/2024]
Abstract
Our understanding of human neurocognitive aging, its developmental roots, and life course influences has been transformed by brain imaging technologies, increasing availability of longitudinal data sets, and analytic advances. The Scaffolding Theory of Aging and Cognition is a life course model, proposed originally in 2009, featuring adaptivity and compensatory potential as lifelong mechanisms for meeting neurocognitive challenges posed by the environment and by developing or declining brain circuitry. Here, we review the scaffolding theory in relation to new evidence addressing when during the life course potentially enriching and depleting factors exert their effects on brain health and scaffolding, and we consider the implications for separable, and potentially reciprocal, influences on the level of cognitive function and the rate of decline in later life.
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Lua CZB, Gao Y, Li J, Cao X, Lyu X, Tu Y, Jin S, Liu Z. Influencing Factors of Healthy Aging Risk Assessed Using Biomarkers: A Life Course Perspective. China CDC Wkly 2024; 6:219-224. [PMID: 38532748 PMCID: PMC10961214 DOI: 10.46234/ccdcw2024.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 01/23/2024] [Indexed: 03/28/2024] Open
Abstract
Assessing individual risks of healthy aging using biomarkers and identifying associated factors have become important areas of research. In this study, we conducted a literature review of relevant publications between 2018 and 2023 in both Chinese and English databases. Previous studies have predominantly used single biomarkers, such as C-reactive protein, or focused on specific life course stages and factors such as socioeconomic status, mental health, educational levels, and unhealthy lifestyles. By summarizing the progress in this field, our study provides valuable insights and future directions for promoting healthy aging from a life course perspective.
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Affiliation(s)
- Cedric Zhang Bo Lua
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Yajie Gao
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Jinming Li
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Xingqi Cao
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Xinwei Lyu
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Yinuo Tu
- College of Chemical and Biological Engineering, Zhejiang University, Hangzhou City, Zhejiang Province, China
| | - Shuyi Jin
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Zuyun Liu
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
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Li H, Yang Z, You L, Liu S. Exploration of the factors influencing the quality of life among adolescents during the COVID-19 pandemic: the data from a cross-sectional study in Shandong. BMC Public Health 2024; 24:573. [PMID: 38388446 PMCID: PMC10885489 DOI: 10.1186/s12889-024-17981-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 02/04/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND The COVID-19 pandemic has sparked unprecedented transformations in the lives of adolescents, with reshaping their routines, social dynamics, educational experiences, and overall well-being. Our study delves into the influence of various factors on adolescents' quality of life (QOL) among the COVID-19 pandemic in Shandong Province, China. METHODS Employing a cross-sectional research approach combined with multivariable analysis, we scrutinize the association of demographic factors (age, gender, education level, ethnic groups, urban area, and family economic status) and health-related behaviors (sleep duration, and self-reported health status) with QOL in 9953 students. RESULTS During the pandemic, the average QOL for adolescents in Shandong Province was 133. Our analysis revealed that sleep duration and age had statistically significant associations with total QOL, with the OR values of 1.43 (95% confidence interval (CI): 1.03 to 1.83) and 0.44 (95% CI: 0.19 to 0.70), respectively. Notably, we observed that adolescents from economically disadvantaged families, or those with poorer self-reported health status, were more likely to report lower QOL scores. CONCLUSIONS Overall, our study highlights the potential association of sleep duration, age, family economic status, and self-reported health with the QOL of adolescents in Shandong Province during the pandemic. During similar public health crises, policymakers, educators, and healthcare providers can actively work through resource allocation and effective intervention measures towards alleviating financial burdens, improving health conditions, and ultimately enhancing the total QOL for adolescents.
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Affiliation(s)
- Hongjin Li
- Institute for Infectious Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, 350012, Fuzhou, Fujian, China
| | - Zhiping Yang
- Department of Clinical Nutrition, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, 361003, Xiamen, China
| | - Libin You
- Institute for Infectious Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, 350012, Fuzhou, Fujian, China
- Key Laboratory of Fujian Province for Zoonotic Disease Research, Fujian Provincial Center for Disease Control and Prevention, 350012, Fuzhou, China
| | - Shaojie Liu
- Department of Clinical Nutrition, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, 361003, Xiamen, China.
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Yang G, Cao X, Yu J, Li X, Zhang L, Zhang J, Ma C, Zhang N, Lu Q, Wu C, Chen X, Hoogendijk EO, Gill TM, Liu Z. Association of Childhood Adversity With Frailty and the Mediating Role of Unhealthy Lifestyle: A Lifespan Analysis. Am J Geriatr Psychiatry 2024; 32:71-82. [PMID: 37770350 PMCID: PMC11078585 DOI: 10.1016/j.jagp.2023.08.015] [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: 04/20/2023] [Revised: 08/10/2023] [Accepted: 08/23/2023] [Indexed: 09/30/2023]
Abstract
OBJECTIVES Childhood adversity and lifestyle have been associated with frailty in later life, but not much is known about factors that may explain these associations. Therefore, this study aims to investigate the association of childhood adversity with frailty, and the mediating role of unhealthy lifestyle in the association. METHODS This lifespan analysis included 152,914 adults aged 40-69 years old from the UK Biobank. We measured childhood adversity with five items: physical neglect, emotional neglect, sexual abuse, physical abuse, and emotional abuse through online mental health survey. Frailty was measured by the frailty index; an unhealthy lifestyle score (range: 0-5) was calculated based on unhealthy body mass index, smoking, alcohol consumption, physical inactivity, and unhealthy diet at the baseline survey. Multiple logistic regression and mediation analysis were performed. RESULTS A total of 10,078 participants (6.6%) were defined as having frailty. Participants with any childhood adversity had higher odds of frailty. For example, in the fully adjusted model, with a one-point increase in cumulative score of childhood adversity, the odds of frailty increased by 38% (odds ratio: 1.38; 95% Confidence Interval: 1.36, 1.40). Unhealthy lifestyle partially mediated the associations of childhood adversity with frailty (mediation proportion: 4.4%-7.0%). The mediation proportions were largest for physical (8.2%) and sexual (8.1%) abuse. CONCLUSIONS Childhood adversity was positively associated with frailty, and unhealthy lifestyle partially mediated the association. This newly identified pathway highlights the potential of lifestyle intervention strategies among those who experienced childhood adversity (in particular, physical, and sexual abuse) to promote healthy aging.
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Affiliation(s)
- Gan Yang
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xingqi Cao
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jie Yu
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xueqin Li
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Liming Zhang
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jingyun Zhang
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Chao Ma
- School of Economics and Management (CM), Southeast University, Nanjing, Jiangsu, China
| | - Ning Zhang
- Department of Social Medicine School of Public Health and Center for Clinical Big Data and Analytics Second Affiliated Hospital (NZ), Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qingyun Lu
- School of Public Health (QL), Nantong University, Nantong, JiangSu, China
| | - Chenkai Wu
- Global Health Research Center (CW), Duke Kunshan University, Kunshan, Jiangsu, China
| | - Xi Chen
- Department of Health Policy and Management (XC), Yale School of Public Health, New Haven, CT, USA; Department of Economics (XC), Yale University, New Haven, CT, USA
| | - Emiel O Hoogendijk
- Department of Epidemiology & Data Science (EOH), Amsterdam Public Health research institute, Amsterdam UMC-Location VU University Medical Center, Amsterdam, The Netherlands
| | - Thomas M Gill
- Department of Internal Medicine (TMG), Yale School of Medicine, New Haven, CT, USA
| | - Zuyun Liu
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
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Hoang CT, Kohler IV, Amin V, Behrman JR, Kohler HP. Resilience, Accelerated Aging and Persistently Poor Health: Diverse Trajectories of Health in Malawi. POPULATION AND DEVELOPMENT REVIEW 2023; 49:771-800. [PMID: 38605849 PMCID: PMC11005366 DOI: 10.1111/padr.12590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
Individuals age at vastly different rates resulting in significant within-population heterogeneity in health and aging outcomes. This diversity in health and aging trajectories has rarely been investigated among low-income aging populations that have experienced substantial hardships throughout their lifecourses. Utilizing 2006-2018 data from the Malawi Longitudinal Study of Families and Health (MLSFH) and estimating group-based trajectory models (GBTM), our analyses identified three distinct lifecourse health trajectories: (1) comparatively good initial mental and physical health that persisted throughout the lifecourse ("resilient aging"); (2) relatively good initial mental and physical health that started to deteriorate during mid-adulthood ("accelerated aging"); and (3) poor initial mental and physical health that further declined over the lifecourse ("aging with persistently poor health"). For both physical and mental health, men were more likely to enjoy resilient aging than women. Predictors other than gender of trajectory membership sometimes confirmed, and sometimes contradicted, hypotheses derived from high-income country studies. Our analyses highlight the long arm of early life conditions and gender in determining aging trajectories and show that a non-trivial sub-population is characterized by aging with persistently poor health. The study uncovers widening gaps in health outcomes between those who age with resilience and those who experience accelerated aging.
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Dai Z, Xu W, Ding R, Peng X, Shen X, Song J, Du P, Wang Z, Liu Y. Two-sample Mendelian randomization analysis evaluates causal associations between inflammatory bowel disease and osteoporosis. Front Public Health 2023; 11:1151837. [PMID: 37304119 PMCID: PMC10250718 DOI: 10.3389/fpubh.2023.1151837] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/15/2023] [Indexed: 06/13/2023] Open
Abstract
Introduction Over the past few years, multiple observational studies have speculated a potential association between inflammatory bowel disease (IBD), which includes ulcerative colitis (UC) and Crohn's disease (CD), and osteoporosis. However, no consensus has been reached regarding their interdependence and pathogenesis. Herein, we sought to further explore the causal associations between them. Methods We validated the association between IBD and reduced bone mineral density in humans based on genome-wide association studies (GWAS) data. To investigate the causal relationship between IBD and osteoporosis, we performed a two-sample Mendelian randomization study using training and validation sets. Genetic variation data for IBD, CD, UC, and osteoporosis were derived from published genome-wide association studies in individuals of European ancestry. After a series of robust quality control steps, we included eligible instrumental variables (SNPs) significantly associated with exposure (IBD/CD/UC). We adopted five algorithms, including MR Egger, Weighted median, Inverse variance weighted, Simple mode, and Weighted mode, to infer the causal association between IBD and osteoporosis. In addition, we evaluated the robustness of Mendelian randomization analysis by heterogeneity test, pleiotropy test, leave-one-out sensitivity test, and multivariate Mendelian randomization. Results Genetically predicted CD was positively associated with osteoporosis risk, with ORs of 1.060 (95% CIs 1.016, 1.106; p = 0.007) and 1.044 (95% CIs 1.002, 1.088; p = 0.039) for CD in the training and validation sets, respectively. However, Mendelian randomization analysis did not reveal a significant causal relationship between UC and osteoporosis (p > 0.05). Furthermore, we found that overall IBD was associated with osteoporosis prediction, with ORs of 1.050 (95% CIs 0.999, 1.103; p = 0.055) and 1.063 (95% CIs 1.019, 1.109; p = 0.005) in the training and validation sets, respectively. Conclusion We demonstrated the causal association between CD and osteoporosis, complementing the framework for genetic variants that predispose to autoimmune disease.
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Affiliation(s)
- Zhujiang Dai
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai Colorectal Cancer Research Center, Shanghai, China
| | - Weimin Xu
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai Colorectal Cancer Research Center, Shanghai, China
| | - Rui Ding
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai Colorectal Cancer Research Center, Shanghai, China
| | - Xiang Peng
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai Colorectal Cancer Research Center, Shanghai, China
| | - Xia Shen
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai Colorectal Cancer Research Center, Shanghai, China
| | - Jinglue Song
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai Colorectal Cancer Research Center, Shanghai, China
| | - Peng Du
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai Colorectal Cancer Research Center, Shanghai, China
| | - Zhongchuan Wang
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai Colorectal Cancer Research Center, Shanghai, China
| | - Yun Liu
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Shanghai Colorectal Cancer Research Center, Shanghai, China
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Schrempft S, Stringhini S. Socioeconomic inequalities in the Pace of Aging. Aging (Albany NY) 2023; 15:1706-1707. [PMID: 36917095 PMCID: PMC10085604 DOI: 10.18632/aging.204595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 02/14/2023] [Indexed: 03/16/2023]
Affiliation(s)
- Stephanie Schrempft
- Division of Primary Care, Unit of Population Epidemiology, Geneva University Hospitals, Switzerland
| | - Silvia Stringhini
- Division of Primary Care, Unit of Population Epidemiology, Geneva University Hospitals, Switzerland
- Department of Health and Community Medicine, Faculty of Medicine, University of Geneva, Switzerland
- University Centre for General Medicine and Public Health, University of Lausanne, Switzerland
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Yang G, Cao X, Yu J, Li X, Zhang L, Zhang J, Ma C, Zhang N, Lu Q, Wu C, Chen X, Hoogendijk EO, Gill TM, Liu Z. Association of childhood adversity with frailty and the mediating role of unhealthy lifestyle: Findings from the UK biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.08.23285634. [PMID: 36798168 PMCID: PMC9934802 DOI: 10.1101/2023.02.08.23285634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Background Childhood adversity and lifestyle have been associated with frailty in later life, but not much is known about factors that may explain these associations. An unhealthy lifestyle may play an important role in the pathway from childhood adversity to frailty. Therefore, this study aims to investigate the association of childhood adversity with frailty, and the mediating role of unhealthy lifestyle in the association. Methods This lifespan analysis included 152914 adults aged 40-69 years old from the UK Biobank. We measured childhood adversity with five items: physical neglect, emotional neglect, sexual abuse, physical abuse, and emotional abuse through online mental health survey. Frailty was measured by the frailty index; an unhealthy lifestyle score (range: 0-5) was calculated based on unhealthy body mass index, smoking, drinking, physical inactivity, and unhealthy diet at the baseline survey. Multiple logistic regression and mediation analysis were performed. Results A total of 10078 participants (6.6%) were defined as having frailty. Participants with any childhood adversity had higher odds of frailty. For example, in the fully adjusted model, with a one-point increase in cumulative score of childhood adversity, the odds of frailty increased by 41% (Odds Ratio: 1.41; 95% Confidence Interval: 1.39, 1.44). Unhealthy lifestyle partially mediated the associations of childhood adversity with frailty (mediation proportion: 4.4%-7.0%). The mediation proportions were largest for physical (8.2%) and sexual (8.1%) abuse. Conclusions Among this large sample, childhood adversity was positively associated with frailty, and unhealthy lifestyle partially mediated the association. This newly identified pathway highlights the potential of lifestyle intervention strategies among those who experienced childhood adversity (in particular, physical and sexual abuse) to promote healthy aging.
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Affiliation(s)
- Gan Yang
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Xingqi Cao
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Jie Yu
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Xueqin Li
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Liming Zhang
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Jingyun Zhang
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Chao Ma
- School of Economics and Management, Southeast University, Nanjing 211189, Jiangsu, China
| | - Ning Zhang
- Department of Social Medicine School of Public Health and Center for Clinical Big Data and Analytics Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Qingyun Lu
- School of Public Health, Nantong University, Nantong 226007, JiangSu, China
| | - Chenkai Wu
- Duke Global Health Institute, Duke University, Durham, NC, USA
| | - Xi Chen
- Department of Health Policy and Management, Yale School of Public Health, New Haven, CT 06520, United States of America
- Department of Economics, Yale University, New Haven, CT 06520, United States of America
| | - Emiel O. Hoogendijk
- Department of Epidemiology & Data Science, Amsterdam Public Health research institute, Amsterdam UMC – location VU University medical center, Amsterdam, the Netherlands
| | - Thomas M. Gill
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520, United States of America
| | - Zuyun Liu
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
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11
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Hillmann AR, Dhingra R, Reed RG. Positive social factors prospectively predict younger epigenetic age: Findings from the Health and Retirement Study. Psychoneuroendocrinology 2023; 148:105988. [PMID: 36446244 PMCID: PMC9898135 DOI: 10.1016/j.psyneuen.2022.105988] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 11/18/2022] [Accepted: 11/21/2022] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Positive social factors may slow biological aging, but this has yet to be rigorously tested. This study investigated whether baseline levels or changes over time in social support and contact frequency prospectively predicted epigenetic age. METHOD Health and Retirement Study participants (N = 1912, 46.3 % male, aged 42-87 at baseline) reported longitudinal social support and contact frequency data up to 3 times between 2006 and 2016 and provided blood in 2016. Baseline levels (intercepts) and changes over time (slopes) in social support from and contact frequency with spouses, children, friends, and other family were outputted from multilevel models and used to predict epigenetic age, estimated from Horvath, Hannum, GrimAge, PhenoAge, and Dunedin Pace of Aging. RESULTS In models adjusted for demographic and health characteristics, higher baseline levels of support from and contact frequency with friends were prospectively associated with a slower Pace of Aging (support: p = .002; contact: p = 0.009) and a lower GrimAge (contact: p = .001). In addition, higher contact frequency with children at baseline was prospectively associated with a lower GrimAge (p < .001), and higher contact frequency with family at baseline and an increase in family contact over time was associated with a lower Hannum age (baseline: p = .005; slope: p = .015). CONCLUSIONS Perceived support from and contact with close others, particularly friends, may have implications for healthy biological aging. Notably, the effect sizes for friends were comparable to the effect of body mass index on epigenetic age. Positive social factors were generally associated with second- and third-generation clocks, which may be more sensitive to psychosocial factors than first-generation clocks.
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Affiliation(s)
- Abby R Hillmann
- Department of Psychology, Dietrich School of Arts and Sciences, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Roma Dhingra
- Department of Biology, Georgetown College, Georgetown University, Washington, DC, USA
| | - Rebecca G Reed
- Department of Psychology, Dietrich School of Arts and Sciences, University of Pittsburgh, Pittsburgh, PA, USA
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12
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Petrovic D, Carmeli C, Sandoval JL, Bodinier B, Chadeau-Hyam M, Schrempft S, Ehret G, Dhayat NA, Ponte B, Pruijm M, Vineis P, Gonseth-Nusslé S, Guessous I, McCrory C, Bochud M, Stringhini S. Life-course socioeconomic factors are associated with markers of epigenetic aging in a population-based study. Psychoneuroendocrinology 2023; 147:105976. [PMID: 36417838 DOI: 10.1016/j.psyneuen.2022.105976] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 11/14/2022] [Accepted: 11/14/2022] [Indexed: 11/18/2022]
Abstract
Adverse socioeconomic circumstances negatively affect the functioning of biological systems, but the underlying mechanisms remain only partially understood. Here, we explore the associations between life-course socioeconomic factors and four markers of epigenetic aging in a population-based setting. We included 684 participants (52 % women, mean age 52.6 ± 15.5 years) from a population and family-based Swiss study. We used nine life-course socioeconomic indicators as the main exposure variables, and four blood-derived, second generation markers of epigenetic aging as the outcome variables (Levine's DNAmPhenoAge, DunedinPoAm38, GrimAge epigenetic age acceleration (EAA), and the mortality risk score (MS)). First, we investigated the associations between socioeconomic indicators and markers of epigenetic aging via mixed-effect linear regression models, adjusting for age, sex, participant's recruitment center, familial structure (random-effect covariate), seasonality of blood sampling, and technical covariates. Second, we implemented counterfactual mediation analysis to investigate life-course and intermediate mechanisms underlying the socioeconomic gradient in epigenetic aging. Effect-size estimates were assessed using regression coefficients and counterfactual mediation parameters, along with their respective 95 % confidence intervals. Individuals reporting a low father's occupation, adverse financial conditions in childhood, a low income, having financial difficulties, or experiencing unfavorable socioeconomic trajectories were epigenetically older and had a higher mortality risk score than their more advantaged counterparts. Specifically, this corresponded to an average increase of 1.1-1.5 years for Levine's epigenetic age (β and 95 %CI range, β (minimum and maximum): 1.1-1.5 95 %CI[0.0-0.2; 2.3-3.0]), 1.1-1.5 additional years for GrimAge (β: 1.1-1.5 95 %CI[0.2-0.6; 1.9-3.0]), a 1-3 % higher DunedinPoAm38 age acceleration (β: 0.01-0.03 95 %CI[0.00; 0.03-0.04]), and a 10-50 % higher MS score (β: 0.1-0.4 95 %CI[0.0-0.2; 0.3-0.4]) for the aforementioned socioeconomic indicators. By exploring the life-course mechanisms underlying the socioeconomic gradient in epigenetic aging, we found that both childhood and adulthood socioeconomic factors contributed to epigenetic aging, and that detrimental lifestyle factors mediated the relation between socioeconomic circumstances in adulthood and EAA (31-89 % mediated proportion). This study provides emerging evidence for an association between disadvantaged life-course socioeconomic circumstances and detrimental epigenetic aging patterns, supporting the "sensitive-period" life-course model. Counterfactual mediation analyses further indicated that the effect of socioeconomic factors in adulthood operates through detrimental lifestyle factors, whereas associations involving early-life socioeconomic factors were less clear.
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Affiliation(s)
- Dusan Petrovic
- Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (UNISANTE), Lausanne, Switzerland; Centre for Environment and Health, School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
| | - Cristian Carmeli
- Population Health Laboratory, University of Fribourg, Fribourg, Switzerland
| | - José Luis Sandoval
- Department of Oncology, Geneva University Hospitals, Geneva, Switzerland
| | - Barbara Bodinier
- Centre for Environment and Health, School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Marc Chadeau-Hyam
- Centre for Environment and Health, School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Stephanie Schrempft
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Georg Ehret
- Department of Cardiology, Geneva University Hospitals, Geneva, Switzerland
| | - Nasser Abdalla Dhayat
- Nephrology & Renal Care Center, B. Braun Medical Care AG, Hochfelden, Zurich, Switzerland
| | - Belén Ponte
- Department of Nephrology and Hypertension, Geneva University Hospitals, Geneva, Switzerland
| | - Menno Pruijm
- Department of Nephrology and Hypertension, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Paolo Vineis
- Department of Medical Gerontology, Trinity College Dublin, Dublin, Ireland
| | - Sémira Gonseth-Nusslé
- Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (UNISANTE), Lausanne, Switzerland
| | - Idris Guessous
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Cathal McCrory
- Department of Medical Gerontology, Trinity College Dublin, Dublin, Ireland
| | - Murielle Bochud
- Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (UNISANTE), Lausanne, Switzerland
| | - Silvia Stringhini
- Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (UNISANTE), Lausanne, Switzerland; Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
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