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Pan Y, Li Y, Chhetri JK, Liu P, Li B, Liu Z, Shui G, Ma L. Dysregulation of acyl carnitines, pentose phosphate pathway and arginine and ornithine metabolism are associated with decline in intrinsic capacity in Chinese older adults. Aging Clin Exp Res 2024; 36:36. [PMID: 38345670 PMCID: PMC10861606 DOI: 10.1007/s40520-023-02654-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 11/03/2023] [Indexed: 02/15/2024]
Abstract
BACKGROUND Intrinsic capacity is the combination of individual physical and mental abilities, reflecting the aging degree of the older adults. However, the mechanisms and metabolic characteristics of the decline in intrinsic capacity are still unclear. AIMS To identify metabolic signatures and associated pathways of decline in intrinsic capacity based on the metabolite features. METHODS We recruited 70 participants aged 77.19 ± 8.31 years. The five domains of intrinsic capacity were assessed by Short Physical Performance Battery (for mobility), Montreal cognition assessment (for cognition), 30-Item Geriatric Depression Scale (for psychology), self-reported hearing/visual impairment (for sensory) and Nutritional risk screening (for vitality), respectively. The serum samples of participants were analyzed by liquid chromatography-mass spectrometry-based metabolomics, followed by metabolite set enrichment analysis and metabolic pathway analysis. RESULTS There were 50 participants with a decline in intrinsic capacity in at least one of the domains. A total of 349 metabolites were identified from their serum samples. Overall, 24 differential metabolites, 5 metabolite sets and 13 pathways were associated with the decline in intrinsic capacity. DISCUSSION Our results indicated that decline in intrinsic capacity had unique metabolomic profiles. CONCLUSION The specific change of acyl carnitines was observed to be a feature of decline in intrinsic capacity. Dysregulation of the pentose phosphate pathway and of arginine and ornithine metabolism was strongly associated with the decline in intrinsic capacity.
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Affiliation(s)
- Yiming Pan
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Research Center for Geriatric Medicine, 45 Changchun Street, Beijing, 100053, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Yun Li
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Research Center for Geriatric Medicine, 45 Changchun Street, Beijing, 100053, China.
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China.
| | - Jagadish K Chhetri
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Research Center for Geriatric Medicine, 45 Changchun Street, Beijing, 100053, China
- Department of Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Pan Liu
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Research Center for Geriatric Medicine, 45 Changchun Street, Beijing, 100053, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Bowen Li
- LipidALL Technologies Company Limited, Changzhou, 213022, Jiangsu, China
| | - Zuyun Liu
- Center for Clinical Big Data and Analytics, 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, 310058, Zhejiang, China
| | - Guanghou Shui
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Lina Ma
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Research Center for Geriatric Medicine, 45 Changchun Street, Beijing, 100053, China.
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China.
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Ji S, Kang J, Han C, Xu X, Chen M, Chen J, Chhetri JK, Pan J, Chan P. Potential role of APOE ɛ4 allele as a modifier for the association of BDNF Val66Met polymorphisms and cognitive impairment in community-dwelling older adults. Front Aging Neurosci 2024; 16:1330193. [PMID: 38374884 PMCID: PMC10876185 DOI: 10.3389/fnagi.2024.1330193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 01/16/2024] [Indexed: 02/21/2024] Open
Abstract
Objective To determine whether the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism is associated with cognitive impairment (CI) in community-dwelling Chinese older adults, and to investigate whether this relationship is modified by the Apolipoprotein E (APOE) ɛ4 allele. Methods The study is a secondary analysis of 703 participants aged ≥60 years randomly enrolled from the Beijing Longitudinal Study of Aging II prospective cohort. The education-adjusted Mini-Mental State Examination and the Clinical Dementia Rating Scale were used to measure the cognitive performance of the subjects. The main effects and interactions (additive and multiplicative) of the BDNF Met and the APOE ε4 alleles on CI were estimated by logistic regression models. Results In total, 84 out of 703 older adults aged ≥60 years old had CI. No significant difference was observed in the risk of CI between participants with the BDNF Met allele and that of subjects without the BDNF Met allele (p = 0.213; p = 0.164). Individuals carrying both the BDNF Met and APOE ε4 alleles had an almost 1.5-fold increased odds of CI compared with carriers of the BDNF Met allele but without the APOE ε4 allele. The additive association indicated a positive interaction of both BDNF Met and APOE ε4 alleles with wide CIs (p = 0.021; p = 0.018). Conclusion The results suggest that the APOE ε4 allele may be a potential modifier for the association of the BDNF Val66Met polymorphism with CI in community-dwelling older adults.
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Affiliation(s)
- Shaozhen Ji
- Department of Neurology, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Jia Kang
- Department of Neurology, The Second Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China
| | - Chao Han
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Xitong Xu
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Meijie Chen
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Jie Chen
- Department of Geriatrics, Shenzhen Hospital, Peking University, Shenzhen, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Jing Pan
- Department of Neurology, The Second Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, China
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China
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Yan Wang N, Liu X, Kong X, Sumi Y, Chhetri JK, Hu L, Zhu M, Kang L, Liang Z, Ellis JW, Shi L. Implementation and impact of the World Health Organization integrated care for older people (ICOPE) program in China: a randomised controlled trial. Age Ageing 2024; 53:afad249. [PMID: 38251736 DOI: 10.1093/ageing/afad249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/07/2023] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND Fragmentation of services increases health and social care burden as people live longer with higher prevalence of diseases, frailty and dependency. Local evidence for implementing person-centred integrated care is urgently needed to advance practice and policies to achieve healthy ageing. OBJECTIVE To test the feasibility and impact of World Health Organization's (WHO) Integrated Care for Older People (ICOPE) approach in China. DESIGN A randomised controlled trial examining the feasibility of implementing ICOPE approach, evaluating its impact on health outcomes and health resource utilisation. SETTING Primary care setting in urban and suburban communities of Chaoyang District, Beijing, China. SUBJECTS Community-dwelling older adults screened as at-risk of functional declines and randomised into intervention (537) and control (1611) groups between September 2020 and February 2021. METHODS A 6-month intervention program following WHO's ICOPE care pathways implemented by integrated care managers compared to standard available care. RESULTS After 1 to 1 propensity score matching, participants in intervention and control groups (totally 938) had comparable baseline characteristics, demonstrated feasibility of implementing ICOPE with satisfaction by participants (97-99%) and providers (92-93%). All outcomes showed improvements after a 6-month intervention, while statistically significant least-squares mean differences (control-intervention) in vitality (Mini-Nutritional Assessment Short Form to measure vitality, -0.21, 95% CI, -0.40-0.02), mobility (Short Physical Performance Battery to measure mobility, -0.29, 95% CI, -0.44-0.14) and psychological health (Geriatric Depression Scale five items to measure psychological health, 0.09, 95% CI, 0.03-0.14) were observed (P < 0.05). CONCLUSIONS It is feasible to localise and implement WHO's ICOPE approach in regions with fragmented resources such as China. Preliminary evidence supports its acceptance among key stakeholders and impact on health outcomes.
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Affiliation(s)
- Ninie Yan Wang
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Xiaohong Liu
- Department of Geriatrics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiangrong Kong
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yuka Sumi
- Ageing and Health (AAH), Department of Maternal, Newborn, Child & Adolescent Health & Ageing (MCA), World Health Organization, Geneva, Switzerland
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Linlin Hu
- School of Health Policy and Management, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Minglei Zhu
- Department of Geriatrics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Lin Kang
- Department of Geriatrics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhen Liang
- Shenzhen People's Hospital, Shenzhen, China
| | - John W Ellis
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Leiyu Shi
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
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Li KF, Li J, Liao YP, Zhu SH, Chhetri JK, Chen HZ, Yang WM. Elderly-onset severe parkinsonism in Wilson disease: A case report. Parkinsonism Relat Disord 2023:105924. [PMID: 37945393 DOI: 10.1016/j.parkreldis.2023.105924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 10/17/2023] [Accepted: 10/31/2023] [Indexed: 11/12/2023]
Affiliation(s)
- Ke-Fan Li
- Department of Neurology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, China
| | - Jun Li
- Department of Neurology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, China; Anhui Branch Center of National Clinical Research Center for Geriatric Disorders, Hefei, China.
| | - Ya-Ping Liao
- School of Life Science, Bengbu Medical College, Bengbu, China
| | - Si-Huan Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, China
| | | | - Huai-Zhen Chen
- Department of Neurology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, China; Anhui Branch Center of National Clinical Research Center for Geriatric Disorders, Hefei, China
| | - Wen-Ming Yang
- Department of Neurology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, China; Anhui Branch Center of National Clinical Research Center for Geriatric Disorders, Hefei, China
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Chhetri JK, Mei S, Wang C, Chan P. New horizons in Parkinson's disease in older populations. Age Ageing 2023; 52:afad186. [PMID: 37847793 DOI: 10.1093/ageing/afad186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 07/07/2023] [Indexed: 10/19/2023] Open
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease. Ageing is considered to be the greatest risk factor for PD, with a complex interplay between genetics and the environment. With population ageing, the prevalence of PD is expected to escalate worldwide; thus, it is of utmost importance to reduce the burden of PD. To date, there are no therapies to cure the disease, and current treatment strategies focus on the management of symptoms. Older adults often have multiple chronic diseases and geriatric syndromes, which further complicates the management of PD. Healthcare systems and care models necessary to address the broad needs of older PD patients are largely unavailable. In this New Horizon article, we discuss various aspects of PD from an ageing perspective, including disease management. We highlight recent advancements in PD therapies and discuss new care models with the potential to improve patient's quality of life.
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Affiliation(s)
- Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Shanshan Mei
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Chaodong Wang
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
- Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China
- Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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6
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Chhetri JK, Ma L, Kang L, Chan P. Optimizing intrinsic capacity to prevent frailty and sarcopenia in old age. J Frailty Sarcopenia Falls 2023; 8:136-138. [PMID: 37663158 PMCID: PMC10472034 DOI: 10.22540/jfsf-08-136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2023] [Indexed: 09/05/2023] Open
Affiliation(s)
- Jagadish K. Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lina Ma
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lin Kang
- Geriatric Department of Peking Union Medical College Hospital, Beijing, China
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
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7
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. Sci China Life Sci 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Citation(s) in RCA: 42] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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Su D, Su Y, Xu B, Chhetri JK, Chan P. Age as a risk factor for orthostatic hypotension induced by the levodopa challenge test in patients with Parkinson's disease: Results from a single-center trial. Medicine (Baltimore) 2023; 102:e33161. [PMID: 36862872 PMCID: PMC9981374 DOI: 10.1097/md.0000000000033161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/04/2023] Open
Abstract
BACKGROUND Hypotension can occur in patients receiving levodopa (L-dopa) treatment for parkinsonism. However, only few studies have focused on the characteristics of orthostatic hypotension (OH) induced by the L-dopa challenge test (LCT). This study aimed to investigate the characteristics and influencing factors of LCT-induced OH in a relatively large sample of patients with Parkinson's disease (PD). METHODS Seventy-eight patients with PD without a previous diagnosis of OH underwent the LCT. Blood pressure (BP) in the supine and standing positions was measured before and 2 hours after the LCT. If diagnosed with OH, the patients' BP was monitored again 3 hours after the LCT. The clinical features and demographics of the patients were analyzed. RESULTS Eight patients were diagnosed with OH 2 hours after the LCT (median dose of 375 mg L-dopa/benserazide; incidence = 10.3%). One patient without symptoms had OH 3 hours after the LCT. Compared with patients without OH, patients with OH had lower 1- and 3-minutes standing systolic BP and 1-minute standing diastolic BP at baseline and 2 hours after the LCT. Patients in the OH group were of older age (65.31 ± 4.17 years vs 59.74 ± 5.55years) and had lower Montreal Cognitive Assessment scores (17.5 vs 24) and higher L-dopa/benserazide levels (375 [250, 500] mg vs 250 [125, 500] mg). Older age markedly increased the odds of having LCT-induced OH (odds ratio, 1.451; 95% confidence interval, 1.055-1.995; P = .022). CONCLUSIONS LCT increased the odds of OH in non-OH PD, causing symptomatic OH in 10.3% of patients in our study, thereby raising safety concerns. Increase in age was observed to be a risk factor for LCT-induced OH in PD patients. A study with a larger sample size is warranted to confirm our results. TRIAL REGISTRATION NUMBER Clinical Trials Registry under ChiCTR2200055707. DATE OF REGISTRATION January 16, 2022.
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Affiliation(s)
- Dan Su
- Department of Geriatrics, Liangxiang Hospital of Beijing Fangshan District, Beijing, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Yanling Su
- Department of Geriatrics, Liangxiang Hospital of Beijing Fangshan District, Beijing, China
| | - Baolei Xu
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Jagadish K. Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, China
- *Correspondence: Jagadish K. Chhetri, National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing 100053, China (e-mail: )
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, China
- Department of Neurology, Neurobiology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
- Clinical Center for Parkinson’s Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China
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9
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Chhetri JK, Harwood RH, Ma L, Michel JP, Chan P. Intrinsic capacity and healthy ageing. Age Ageing 2022; 51:6806171. [PMID: 36346737 DOI: 10.1093/ageing/afac239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 07/25/2022] [Indexed: 01/27/2023] Open
Affiliation(s)
- Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Department of Geriatrics, Neurology, and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Rowan H Harwood
- Faculty of Medicine and Health Sciences, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Lina Ma
- National Clinical Research Center for Geriatric Diseases, Department of Geriatrics, Neurology, and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | | | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Department of Geriatrics, Neurology, and Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China.,Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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10
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Li J, Chhetri JK, Ma L. Physical resilience in older adults: Potential use in promoting healthy aging. Ageing Res Rev 2022; 81:101701. [PMID: 35905815 DOI: 10.1016/j.arr.2022.101701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 07/06/2022] [Accepted: 07/25/2022] [Indexed: 01/31/2023]
Abstract
Physical resilience is a dynamic concept referring to the physiological response when the body is exposed to stressors. The level of physical resilience is the sum of underlying physiological reserves. Moreover, it may not only be determined by age, genetics, or exposure to a variety of diseases, but is also closely related to the psychological, social, and environmental factors of an individual. This paper summarizes our present understanding of the relationship between physical resilience and other concepts closely related to it. Furthermore, we illustrate the current research progress on physical resilience models and clinical resilience assessment. Besides, this paper intends to present a better understanding of physical resilience and its use in treatment decision-making, personalized diagnosis and disease management, and prevention and rehabilitation strategies.
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Affiliation(s)
- Jiatong Li
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Jagadish K Chhetri
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China.
| | - Lina Ma
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China.
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11
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Abstract
Population aging is evident globally. The traditional model of care based on disease management is not sufficient to develop a generation of functional older adult population. The construct of Physical Resilience (PR) holds great potential to make the agenda of healthy aging a reality if we were to properly understand it and develop intervention strategies to maintain PR through life. There are several difficulties and challenges with this novel construct that need to be resolved through research, so as to foster its vast possibilities to maintain functional ability in old age.
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Affiliation(s)
- Jagadish K. Chhetri
- Department of Geriatrics, Neurology, and Neurobiology, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, China
- Corresponding author:Dr. Jagadish K Chhetri, MD, PhD, Department of Geriatrics, Neurology and Neurobiology, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing 100053, China E-mail:
| | - Lina Ma
- Department of Geriatrics, Neurology, and Neurobiology, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, China
| | - Piu Chan
- Department of Geriatrics, Neurology, and Neurobiology, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, China
- Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson’s Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China
- Clinical Center for Parkinson’s Disease, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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12
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Zhao J, Chhetri JK, Chang Y, Zheng Z, Ma L, Chan P. Intrinsic Capacity vs. Multimorbidity: A Function-Centered Construct Predicts Disability Better Than a Disease-Based Approach in a Community-Dwelling Older Population Cohort. Front Med (Lausanne) 2021; 8:753295. [PMID: 34651003 PMCID: PMC8505775 DOI: 10.3389/fmed.2021.753295] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 08/30/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: This study aimed to assess the status of intrinsic capacity (IC)—a novel function-centered construct proposed by the WHO and examine whether impairment in IC predicts subsequent 1-year activities of daily living (ADL) disability better than a disease-based approach, i. e., multimorbidity status. Methods: This study included data of community-dwelling older adults from the Beijing Longitudinal Study on Aging II aged 65 years or older who were followed up at 1 year. Multivariate logistic regressions were performed to estimate the odds of ADL disability at baseline and 1-year follow-up. Results: A total of 7,298 older participants aged 65 years or older were included in the current study. About 4,742 older adults were followed up at 1 year. At baseline, subjects with a higher impairment in IC domains showed higher odds of ADL disability [adj. odds ratio (OR) = 9.51 for impairment in ≥3 domains, area under the curve (AUC) = 0.751] compared to much lower odds of ADL disability in subjects with a higher number (≥3) of chronic diseases (adj. OR 3.92, AUC = 0.712). At 1-year follow-up, the overall incidence of ADL disability increased with the impairment in IC domains higher than the increase in multimorbidity status. A higher impairment in IC domains showed higher odds of incidence ADL disability for impairment in 2 or ≥3 IC domains (adj. OR 2.32 for impairment in ≥3 domains, adj. OR 1.43 for impairment in two domains, AUC = 0.685). Only subjects who had ≥3 chronic diseases had higher odds of 1-year incident ADL disability (adj. OR 1.73, AUC = 0.681) that was statistically significant. Conclusion: Our results imply that a function-centered construct could have higher predictability of disability compared to the multimorbidity status in community older people. Our results need to be confirmed by studies with longer follow-up.
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Affiliation(s)
- Jing Zhao
- Department of Geriatrics, Neurology and Neurobiology, National Clinical Research Center for Geriatric Disease, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Jagadish K Chhetri
- Department of Geriatrics, Neurology and Neurobiology, National Clinical Research Center for Geriatric Disease, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Yi Chang
- Department of Respiration, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Zheng Zheng
- Department of Geriatrics, Neurology and Neurobiology, National Clinical Research Center for Geriatric Disease, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Lina Ma
- Department of Geriatrics, Neurology and Neurobiology, National Clinical Research Center for Geriatric Disease, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Piu Chan
- Department of Geriatrics, Neurology and Neurobiology, National Clinical Research Center for Geriatric Disease, Xuanwu Hospital of Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China.,Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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Affiliation(s)
- Jagadish K Chhetri
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
- National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Beijing, China
| | - Lina Ma
- National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Beijing, China
| | - Jean Woo
- Jockey Club Institute of Ageing, The Chinese University of Hong Kong, Hong Kong, SAR, China
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Piu Chan
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
- National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Beijing, China
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Ma L, Chhetri JK, Zhang L, Sun F, Li Y, Tang Z. Cross-sectional study examining the status of intrinsic capacity decline in community-dwelling older adults in China: prevalence, associated factors and implications for clinical care. BMJ Open 2021; 11:e043062. [PMID: 33402410 PMCID: PMC7786809 DOI: 10.1136/bmjopen-2020-043062] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 12/07/2020] [Accepted: 12/16/2020] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVES Intrinsic capacity (IC) was proposed by the WHO as a new concept for capturing an individual's functional capacities across their lifetime. We aimed to investigate the prevalence and factors associated with IC decline and examine associations between IC and adverse outcomes among community-dwelling older adults in China. DESIGN A cross-sectional study. SETTING Community, China. PARTICIPANTS Data were derived from the China Comprehensive Geriatric Assessment Study, a population-based nationally representative sample. IC comprises of five domains: locomotion, cognition, vitality, sensory and psychology. Participants were deemed to have IC decline if they showed a decline in any of the five domains. Sociodemographic characteristics, chronic diseases, geriatric syndromes and adverse outcomes were also examined. RESULTS Of the 5823 community-dwelling participants aged 60-98 years, 2506 had IC decline (weighted 39.9%): 57.7% in western, 38.3% in northern, 33.7% in northwest, 36.1% in middle, 16.9% in eastern and 19.8% in northeast China. The number of participants with decline in the locomotion, cognition, vitality, sensory and psychological domains were 1039 (17.8%), 646 (11.1%), 735 (12.6%), 824 (14.2%) and 713 (12.2%), respectively. Age, northern residence, low education, being unmarried, low income, less exercise, less meat intake, insomnia, memory loss, urinary incontinence, constipation, slowness, chronic obstructive pulmonary disease and osteoarthritis were related to IC decline. After adjusting for age, sex, area, district, marriage, education, waist-hip ratio, smoking, alcohol consumption, exercise, income and chronic diseases, IC decline was independently associated with risk of frailty, disability, falls, fractures and immobility. CONCLUSION The prevalence of IC decline in China is high. IC decline was significantly associated with adverse outcomes, after adjustment for related variables. Efforts promoting IC to delay functional dependence should focus on modifiable factors, including negative social factors, poor lifestyle, chronic diseases and geriatric syndromes.
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Affiliation(s)
- Lina Ma
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, China National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Jagadish K Chhetri
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, China National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Li Zhang
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, China National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Fei Sun
- Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yun Li
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, China National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Zhe Tang
- Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China
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Chhetri JK, Ma L, Zheng Z, Liu FY, Zhao J, Gu ZQ, Chan P. Apolipoprotein E Polymorphism and Frailty: Apolipoprotein ε4 Allele Is Associated with Fatigue but Not Frailty Syndrome in a Community-Dwelling Older Population Cohort. J Nutr Health Aging 2021; 25:410-415. [PMID: 33786555 DOI: 10.1007/s12603-020-1522-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
OBJECTIVE Frailty is known to be influenced by genetics, however, little evidence on the association of Apolipoprotein E (ApoE) genotype and frailty exists which we aim to investigate. DESIGN This study is a cross-sectional analysis from a prospective longitudinal study cohort. SETTING AND PARTICIPANTS Community-dwelling individuals aged 55 years and older from Beijing region in China. MEASUREMENTS A total of 3,569 older adults with a mean age of 75.06(±6.79) years were included. We investigated the association between ApoE polymorphism and frailty syndrome using the frailty index (FI) and frailty phenotype (including association with individual components of the frailty phenotype). Logistic regressions were performed to investigate the relation between ApoE variants and frailty. RESULTS There was no significant association between ApoE variants and frailty as assessed by the FI. In the age and sex-adjusted model, compared to the ApoE e3/e3 carriers ApoE e4 carriers had almost 1.5 times higher odds of being frail as assessed by the frailty phenotype. However, the significance was lost on the model with adjustment for cognitive impairment. Compared to the ApoE e3/e3 carriers ApoE e4 carriers had almost two times higher odds of fatigue. ApoE e4 heterozygotes had higher odds of fatigue compared to ApoE e4 non-carriers. No significant association was found between ApoE variants and other components of frailty phenotype. CONCLUSIONS Our findings do not support an association between ApoE genotype and frailty irrespective of the frailty assessment tools. Fatigue in older adults is the only component of frailty phenotype influenced by ApoE genotype.
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Affiliation(s)
- J K Chhetri
- Piu Chan, MD, PhD, Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing 100053, China, E-mail: , Tel: +86-10-83198677
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Fu W, Zhang A, Ma L, Jia L, Chhetri JK, Chan P. Severity of frailty as a significant predictor of mortality for hemodialysis patients: a prospective study in China. Int J Med Sci 2021; 18:3309-3317. [PMID: 34400900 PMCID: PMC8364462 DOI: 10.7150/ijms.51569] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 07/13/2021] [Indexed: 01/23/2023] Open
Abstract
Background: Frailty is known to be highly prevalent in older hemodialysis (HD) patients. We studied the prevalence of frailty and its associated factors in Chinese HD patients. We further studied if frailty could predict survival in HD patients. Methods: This is a prospective study involving patients receiving maintenance HD in the dialysis center of Xuanwu Hospital, Beijing. Study subjects were enrolled from October to December, 2017 and followed up for two years. Demographic data, comorbidities and biological parameters were collected. Frailty was assessed using the Fried frailty phenotype at baseline. Cox regression analysis was performed to identify the relationship between frailty and mortality in HD patients. Kaplan-Meier was plotted using the cutoff value obtained by ROC curve to evaluate survival rates in different frailty status. Results: Total of 208 HD patients were enrolled with a mean age of 60.5±12.7 years. According to the frailty criteria, at baseline the prevalence of robust, pre-frail and frail in HD patients was 28.7%, 45.9%, and 25.4%, respectively. The two-year all-cause mortality was 18.8% (39/207) and underlying causes of death included coronary artery disease (CAD), cerebrovascular disease (CVD), hyperkalemia, severe infection, malignant tumor and others. Survival curve showed the patients with frailty score ≥4 to have significantly shorter survival time as compared to patients with frailty score ≤ 3. Frailty predicted two-year mortality when frailty score ≥4 with a sensitivity of 70% and a specificity of 83.67% with an AUC of 0.819. Frailty score was positively associated with age and ratio of ultrafiltration volume to dry weight, while negatively associated with levels of serum albumin, uric acid and diastolic blood pressure after HD. Conclusions: Our results confirm frailty to be very common among HD patients and severity of frailty was a significant predictor of mortality for HD patients. Factors such as age, malnutrition and low blood pressure are the factors to be associated with frailty. Interdialytic weight gain inducing excessive ultrafiltration volume is an important risk factor.
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Affiliation(s)
- Wenjing Fu
- Department of Nephrology, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China.,Department of Geriatrics, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Aihua Zhang
- Department of Nephrology, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Lina Ma
- Department of Geriatrics, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Linpei Jia
- Department of Nephrology, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Jagadish K Chhetri
- Department of Neurobiology, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China.,Department of Geriatrics, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Piu Chan
- Department of Neurobiology, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China.,Department of Geriatrics, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
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Ma L, Zhang Y, Liu P, Li S, Li Y, Ji T, Zhang L, Chhetri JK, Li Y. Plasma N-Terminal Pro-B-Type Natriuretic Peptide Is Associated with Intrinsic Capacity Decline in an Older Population. J Nutr Health Aging 2021; 25:271-277. [PMID: 33491044 DOI: 10.1007/s12603-020-1468-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
OBJECTIVES To determine the association between plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) and intrinsic capacity in an older population. METHOD We recruited 283 participants aged 60-97 years (mean 77.42±4.08 years). Intrinsic capacity was assessed with the World Health Organization Integrated Care for Older People (ICOPE) screening tool including six domains: cognition, locomotion, vitality, hearing, vision, and psychology. Multimorbidity, polypharmacy, gait speed, physical activity, lifestyles, and chronic inflammation were assessed. We used multivariate logistic regression and the Spearman's correlation to assess the association between plasma NT-proBNP and intrinsic capacity. RESULTS The average intrinsic capacity score was 4.53±1.34. The percentage of decreased intrinsic capacity was 75.3%. Participants with decreased intrinsic capacity were older, with more cardiovascular and cerebrovascular diseases and polypharmacy, and had lower gait speed and higher C-reactive protein. Plasma NT-proBNP was significantly higher in the decreased intrinsic capacity group (128.0[56.8-280.8] pg/mL vs. 72.6[39.7-120.0] pg/mL, p<0.001). Multivariate logistic regression analysis revealed that NT-proBNP was the only independent risk factor for decreased intrinsic capacity among multiple covariates (odds ratio=1.005, p=0.038). Elevated NT-proBNP levels were associated with abnormal locomotion, hearing, vision, and psychology domains. Additionally, NT-proBNP levels were inversely correlated with the intrinsic capacity score adjusted for both age and coronary artery disease (r=-0.371, p< 0.001). CONCLUSION Elevated NT-proBNP levels were associated with decreased intrinsic capacity in older persons, independent of age, multimorbidity, polypharmacy, and chronic inflammation. Further longitudinal studies are required to explore the predictive role of NT-proBNP on declines in intrinsic capacity.
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Affiliation(s)
- L Ma
- Lina Ma, M.D., Ph.D., Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Research Center for Geriatric Medicine, E-mail address:
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Chhetri JK, Xue QL, Ma L, Chan P, Varadhan R. Intrinsic Capacity as a Determinant of Physical Resilience in Older Adults. J Nutr Health Aging 2021; 25:1006-1011. [PMID: 34545921 PMCID: PMC8035602 DOI: 10.1007/s12603-021-1629-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 12/28/2020] [Indexed: 12/02/2022]
Abstract
The traditional disease-oriented model of healthcare is inadequate to address the needs of the older population. Greater attention should be given to strategies that promote healthy aging. Recently proposed constructs of intrinsic capacity (IC) and physical resilience (PR) hold great potential to reshape geriatric medicine and aging research. These constructs accentuate the positive health attributes of older people in contrast to the popular frailty construct that is centered on functional deficits. IC was introduced by the World Health Organization (WHO) as a composite of all the physical and mental capacities. WHO has emphasized enhancement of IC throughout the life course so as to maintain functional ability in old age. PR, recently highlighted by the National Institute on Aging, is the ability to successfully cope with stressors. High levels of resilience can result in desirable clinical and functional outcomes after stressors. Therefore, it is important to understand the underlying physiology of PR and the risk factors contributing to diminished PR. The main goal of this article is to explore the potential relationship between IC and PR. Based on a classical theory of aging, we postulate that IC is a determinant of PR and is also a high-level integrative measure of physiologic reserve which is the fundamental factor underlying one's ability to withstand stressors. A major implication of our postulates is that even though IC is only one of the many determinants of PR, it could serve as an important intervenable target for enhancing resilience in older adults.
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Affiliation(s)
- Jagadish K. Chhetri
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, No. 45 Changchun Street, Xicheng District, Beijing, 100053 China
- National Clinical Research Center for Geriatric Disorders, Beijing, China
- Department of Medicine, Division of Geriatric Medicine and Gerontology, School of Medicine, Johns Hopkins University, Baltimore, MD USA
| | - Q.-L. Xue
- Department of Medicine, Division of Geriatric Medicine and Gerontology, School of Medicine, Johns Hopkins University, Baltimore, MD USA
- Center on Aging and Health, Johns Hopkins Medical Institutions, Baltimore, USA
| | - L. Ma
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, No. 45 Changchun Street, Xicheng District, Beijing, 100053 China
- National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - P. Chan
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, No. 45 Changchun Street, Xicheng District, Beijing, 100053 China
- National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Ravi Varadhan
- Center on Aging and Health, Johns Hopkins Medical Institutions, Baltimore, USA
- Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, 550 N. Broadway, Suite 1103-A, Baltimore, MD 21205 USA
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Abstract
Although geriatric research in general has increased in recent years, there is no effective treatment for frailty. Among older adults, those with frailty have an increased risk of falls, disability, and death. The population of older adults has increased rapidly in China, and resulting in an increased demand for medical care services for older adults, including those with frailty. However, much of the research on frailty has been conducted in Europe and the United States, and European and American standards for frailty are not always applicable to Chinese individuals. Clinicians and researchers in China have shown increasing interest in frailty in recent years. Here, we reviewed the current state of frailty research in China.
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Affiliation(s)
- L Ma
- Dr. Lina Ma, Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China, E-mail:
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Abstract
BACKGROUND Gait disturbance is an important risk factor for falls in Parkinson's disease (PD). Using wearable sensors, we can obtain the spatiotemporal parameters of gait and calculate the gait variability. This prospective study aims to objectively evaluate the gait characteristics of PD fallers, and further explore the relationship between spatiotemporal parameters of gait, gait variability and falls in PD patients followed for six months. METHODS Fifty-one PD patients were enrolled in this study. A seven-meter timed up and go test was performed. Gait characteristics were determined by a gait analysis system. Patients were followed monthly by telephone until the occurrence of falls or till the end of six months. The patients were categorized into fallers and non-fallers based on whether fell during the follow-up period. Gait parameters were compared between two groups, and binary logistic regression was used to establish the falls prediction model. In the receiver-operating characteristic curve, area under the curve (AUC) was utilized to evaluate the prediction accuracy of each indicator. RESULTS All subjects completed the follow-up, and 14 (27.5%) patients reported falls. PD fallers had greater gait variability. The range of motion of the trunk in sagittal plane variability was an independent risk factor for falls and achieved moderate prediction accuracy (AUC = 0.751), and the logistic regression model achieved a good accuracy of falls prediction (AUC = 0.838). CONCLUSIONS Increased gait variability is a significant feature of PD fallers and is more sensitive to detect PD patients at high risk of falls than spatiotemporal parameters.
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Affiliation(s)
- Lin Ma
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
| | - Tao-Mian Mi
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Qian Jia
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
| | - Chao Han
- National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Jagadish K Chhetri
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Piu Chan
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China.,Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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Ma L, Chhetri JK, Zhang Y, Liu P, Chen Y, Li Y, Chan P. Integrated Care for Older People Screening Tool for Measuring Intrinsic Capacity: Preliminary Findings From ICOPE Pilot in China. Front Med (Lausanne) 2020; 7:576079. [PMID: 33330532 PMCID: PMC7734133 DOI: 10.3389/fmed.2020.576079] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 10/30/2020] [Indexed: 01/03/2023] Open
Abstract
Objectives: The World Health Organization (WHO) proposed the Integrated Care for Older People (ICOPE) screening tool to identify older people with priority conditions associated with declines in intrinsic capacity (IC). We aimed to determine the clinical utility of the WHO ICOPE screening tool in a Chinese population. Method: A total of 376 adults aged 68.65 ± 11.41 years participated in the study. IC was assessed with the WHO ICOPE screening tool, covering five domains: cognitive, locomotor, sensory, vision, and psychological capacity. We assessed the activities of daily living (ADL); instrumental activities of daily living (IADL); the Fried frailty phenotype; FRAIL scale; Strength, Assistance With Walking, Rising From chair, Climbing Stairs, and Falls (SARC-F) scale; Mini-mental State Examination (MMSE); Geriatric Depression Scale (GDS); social frailty; and quality of life. Results: There were 260 (69.1%) participants who showed declines in one or more IC dimensions. The percentages of decline in mobility, cognition, vitality, hearing, vision, and psychological capacity were 25.3, 46.8, 16.2, 15.4, 11.7, and 12.0%, respectively. IC decreased with increasing age. After adjusting for age, sex, and multimorbidity, participants with declines in IC were more likely to be older, frail, and disabled. They also had worse physical, mental, and overall health. There was a higher prevalence of declines in IC in participants with frailty. After adjusting for age, IC was positively correlated with walking speed, resilience score, and MMSE score and negatively correlated with frailty, SARC-F score, IADL score, GDS score, and physical and mental fatigue. The IC score was not associated with body composition variables such as fat-free mass, body fat percentage, or visceral fat area. Higher IC was associated with better quality of life. The area under the curve of the receiver operating characteristic (AUC-ROC) for the ICOPE screening tool vs. Fried phenotype, FRAIL, ADL disability, IADL disability, and SARC-F were 0.817, 0.843, 0.954, 0.912, and 0.909, respectively. Conclusion: Our research affirms that the ICOPE screening tool is useful to identify adults with poor physical and mental function in a Chinese sample. This tool may assist in identifying declines in IC in an integrative care model and help slow down function decline and onset of care dependence.
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Affiliation(s)
- Lina Ma
- Department of Geriatrics, National Research Center for Geriatric Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jagadish K. Chhetri
- Department of Neurology and Neurobiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yaxin Zhang
- Department of Geriatrics, National Research Center for Geriatric Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Pan Liu
- Department of Geriatrics, National Research Center for Geriatric Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yumeng Chen
- Department of Geriatrics, National Research Center for Geriatric Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yun Li
- Department of Geriatrics, National Research Center for Geriatric Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Piu Chan
- Department of Geriatrics, National Research Center for Geriatric Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Department of Neurology and Neurobiology, Xuanwu Hospital, Capital Medical University, Beijing, China
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Chhetri JK, Chan P, Vellas B, Touchon J, Gauthier S. Report from the First Clinical Trials on Alzheimer's Disease (CTAD) Asia-China 2018 : Bringing together Global Leaders. J Prev Alzheimers Dis 2020; 6:144-147. [PMID: 30756122 DOI: 10.14283/jpad.2019.2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Population of older adults in Asia, and particularly in China is increasing rapidly. Older population are at increased risk of Alzheimer's disease (AD) and other dementias. Soon, the Chinese population with AD will represent almost half of the world's AD population. There is a desperate need of disease modifying therapies to delay or slow the progression of AD, to tackle this emerging healthcare emergency. In this context, the first CTAD Asia-China conference was held in China to bring together Western and Asian leaders in AD. This meeting focused largely on how to develop successful trials in China, utilizing past experiences from the West.
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Affiliation(s)
- J K Chhetri
- J.K Chhetri, Department of Neurobiology, Geriatrics and Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China,
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Chen M, Chen J, Xu X, Qiao F, Wang X, Ji S, Gu Z, Chhetri JK, Chan P. Education Moderates the Association of Probable REM Sleep Behavior Disorder With Cognitive and Motor Impairments in Community-Dwelling Older People. Front Neurol 2020; 11:109. [PMID: 32184754 PMCID: PMC7059092 DOI: 10.3389/fneur.2020.00109] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 01/30/2020] [Indexed: 01/12/2023] Open
Abstract
Objectives: To investigate the relationship between probable rapid eye movement (REM) sleep behavior disorder (pRBD) and cognitive/motor impairments in a community-dwelling population and explore the moderating effects of education. Methods: In this cross-sectional study of the Beijing Longitudinal Study of Aging II (BLSA II), 4,477 subjects (≥55 years) fulfilled the inclusion criteria. pRBD was determined by the RBD Questionnaire-Hong Kong (RBDQ-HK). Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to test the global cognitive performance. Walking speed was used to measure motor function. Logistic regression was performed to assess the relationship between pRBD and cognitive/motor impairments and the moderating effects of education. Results: There were 147 participants (3.3%) with pRBD. Participants with pRBD showed increased risks for cognitive impairment [odds ratio (OR) = 1.88, 95% CI 1.24-2.85, p = 0.003], decreased gait speed (OR = 1.43, 95% CI 1.02-2.01, p = 0.03), but not for mild cognitive impairment (MCI) (measured by MoCA: OR = 1.01, 95% CI 0.68-1.50, p = 0.95; measured by MMSE: OR = 0.90, 95% CI 0.59-1.37, p = 0.62). Education modified the effect of pRBD on MCI (measured by MoCA: p < 0.001; measured by MMSE: p = 0.061) and gait speed (p = 0.008). Conclusions: Our findings suggest that pRBD increases the risk of cognitive/motor impairments for a community-dwelling older population, and education could alleviate the negative effects. These findings implicate that education may have beneficial effects on delaying the onset of cognitive/motor decline in pRBD subjects.
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Affiliation(s)
- Meijie Chen
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
| | - Jie Chen
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
| | - Xitong Xu
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
| | - Fangwei Qiao
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
| | - Xue Wang
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
| | - Shaozhen Ji
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,Clinical Center for Parkinson's Disease, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Zhuqin Gu
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,Clinical Center for Parkinson's Disease, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China
| | - Jagadish K Chhetri
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Piu Chan
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,Clinical Center for Parkinson's Disease, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
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Zhang W, Mao W, Xu E, Chhetri JK, Chan P. Progressive supranuclear palsy presenting with hyperkinetic movement disorder and hemiplegic dystonia: a case report. Int J Neurosci 2020; 130:1278-1281. [PMID: 32075473 DOI: 10.1080/00207454.2020.1732965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Background: Progressive supranuclear palsy (PSP) is a progressive neurodegenerative brain disease which has been rarely described in association with hyperkinetic symptoms. Here, we report a case of PSP that was presented with hyperkinetic movement disorder, hemiplegic dystonia, and other clinical features that overlap with behavioral variant frontotemporal dementia (bvFTD) and corticobasal syndrome (CBS).Case presentation: A 63-year-old female presented to our hospital with a history of frontal lobe symptoms, impaired cognition, hyperkinetic movement disorders, dystonia, and frequent falls. Her magnetic resonance imaging (MRI) scan showed atrophy of midbrain and right temporal lobe. [18F]FDG PET result revealed reduced 18F-FDG uptake with obvious laterality (right > left). [18F]THK5317 PET scan showed evident increased uptake in the brain stem and basal ganglia. Treatment with Tiapride significantly improved hyperkinetic symptoms, but other motor symptoms were not alleviated. Three years later, the patient could hardly walk even with assistance.Conclusion: PSP can present hyperkinetic movement disorders and asymmetry in image that widen the existing phenotypic spectrum.
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Affiliation(s)
- Wei Zhang
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,Department of Neurology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Wei Mao
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Erhe Xu
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Jagadish K Chhetri
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Piu Chan
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China.,Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
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Liu H, Shang N, Chhetri JK, Liu L, Guo W, Li P, Guo S, Ma L. A Frailty Screening Questionnaire (FSQ) to Rapidly Predict Negative Health Outcomes of Older Adults in Emergency Care Settings. J Nutr Health Aging 2020; 24:627-633. [PMID: 32510116 DOI: 10.1007/s12603-020-1374-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
BACKGROUND Frailty, at the core of geriatric medicine, is an important concept underpinning health problems but the rapid and valid measurement of frailty for older adults in the Emergency Department (ED) is lacking in China. The Frailty Screening Questionnaire (FSQ), has been shown to be a simple, rapid and practical tool to identify frailty in both community and inpatients settings, yet its utility in acute care settings is not well understood. OBJECTIVE To determine whether FSQ is useful to identify frailty and predict adverse outcomes in an emergency care setting. DESIGN AND PARTICIPANTS This prospective study included 350 adults aged 60 and over and admitted to the ED. MEASUREMENTS The FSQ questionnaire which assessed self-reported slowness, weakness, inactivity, exhaustion, and weight loss was used to rapidly recognize frailty. FRAIL, Clinical frailty score (CFS), activities of daily living (ADL) and nutrition risk screening 2002 were also assessed. Outcome measures included all-cause 28-day mortality, ADL dependency, mechanical ventilation, length of hospital stay, and ICU readmissions 30 and 90 days after discharge. Cox proportional hazard model was used for survival comparison. RESULTS The prevalence of FSQ frailty and prefrailty in older adults were 44.6% and 30.9% respectively in the emergency setting. FSQ frailty was associated with increasing age, chronic diseases, malnutrition risk, poor physical function and worse outcomes indicated by higher 28-d mortality, ADL dependency, mechanical ventilation, length of hospital stay, and ICU readmissions after discharge. The Kappa coefficient between the FSQ and FRAIL was 0.552. FSQ score was negatively correlated with grip strength and positively correlated with Barthel index, length of hospital stay and CFS score. Cox regression adjusted by epidemiological variables and chronic diseases showed FSQ and all components predicted mortality except weight loss. CONCLUSION The FSQ is a rapid and useful tool to screen frailty and an effective tool to predict mortality in busy emergency settings.
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Affiliation(s)
- H Liu
- Dr. Lina Ma, Department of Geriatrics, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China, E-mail: ; Dr. Shubin Guo, Department of Emergency Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Beijing 100020, China, E-mail:
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Chhetri JK, Chan P, Arai H, Chul Park S, Sriyani Gunaratne P, Setiati S, Assantachai P. Prevention of COVID-19 in Older Adults: A Brief Guidance from the International Association for Gerontology and Geriatrics (IAGG) Asia/Oceania region. J Nutr Health Aging 2020; 24:471-472. [PMID: 32346683 PMCID: PMC7156899 DOI: 10.1007/s12603-020-1359-7] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 04/08/2020] [Indexed: 12/28/2022]
Affiliation(s)
- J K Chhetri
- Dr. Jagadish K Chhetri M.D, Xuanwu Hospital of Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing 100053, China, E-mail:, Tel: +86-10-83198677
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Ma L, Mao W, Xu E, Cai Y, Wang C, Chhetri JK, Chan P. Novel POLG mutation in a patient with early-onset parkinsonism, progressive external ophthalmoplegia and optic atrophy. Int J Neurosci 2019; 130:319-321. [PMID: 31613174 DOI: 10.1080/00207454.2019.1681422] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Introduction: Mitochondrial DNA polymerase gamma (pol γ) encoded by POLG plays an indispensable role in the process of mitochondrial DNA replication and repair. The mutation of POLG can result in mitochondrial dysfunction leading to a broad spectrum of disease.Methods: We report a 29-year-old Chinese female presented with levodopa-responsive parkinsonism, external ophthalmoplegia and optic atrophy. We conducted clinical, molecular iconographic, histological and genetic analyses on this patient.Results: Sequencing of the POLG gene revealed compound heterozygote mutations of a novel c.2693T > C (p.I898T) mutation in exon17 and c.2993C > T (p.S998L) in exon19. The mutation c.2693T > C (p.I898T) has never been reported. Also our patient's cardinal symptoms are rare and different from other cases which have been reported.Conclusion: This finding of ours has broadened the spectrum of phenotype caused by the mutation of POLG.
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Affiliation(s)
- Lin Ma
- Department of Neurology, Neurobiology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China
| | - Wei Mao
- Department of Neurology, Neurobiology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China
| | - Erhe Xu
- Department of Neurology, Neurobiology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China
| | - Yanning Cai
- Department of Neurology, Neurobiology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China
| | - Chaodong Wang
- Department of Neurology, Neurobiology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China
| | - Jagadish K Chhetri
- Department of Neurology, Neurobiology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China
| | - Piu Chan
- Department of Neurology, Neurobiology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China.,Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China.,Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing, China.,National Clinical Research Center for Geriatrics, Beijing, China
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Abstract
As aging is becoming a global phenomenon, the burden of population aging is increasing rapidly, and is soon expected to be the highest in low-and middle-income countries. China represents the world's largest population, and will face the largest number of older individuals, while the economy still remains developing. There is an urgent need to address the negative consequences of aging such as disability, that creates a myriad of challenges, including financial burden to the economy. In order to achieve successful aging-i.e., aging without being frail or disabled, the traditional healthcare model based on a disease-centered approach is not enough, but require a more holistic course. Here, we briefly outline the current scenario of aging and disability in the Chinese older population, its impact and challenges. We strongly believe that public health initiatives centered on frailty, a clinically distinguishable state of extreme vulnerability in older adults, could be the most relevant approach to meet the current needs of the aging population. Such initiatives are immediately needed to reshape the existing model of geriatric healthcare, to promote healthy aging and to reduce the burden of disability in the Chinese population.
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Affiliation(s)
- J K Chhetri
- Jagadish K Chhetri M.D, Department of Neurobiology and Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
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Chhetri JK, de Souto Barreto P, Cantet C, Pothier K, Cesari M, Andrieu S, Coley N, Vellas B. Effects of a 3-Year Multi-Domain Intervention with or without Omega-3 Supplementation on Cognitive Functions in Older Subjects with Increased CAIDE Dementia Scores. J Alzheimers Dis 2019; 64:71-78. [PMID: 29865075 DOI: 10.3233/jad-180209] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Findings from recent Alzheimer's disease prevention trials have shown subjects with increased dementia score based upon mid-life cardiovascular risk factors, to benefit from multi-domain intervention strategies to some extent. The effects of such interventions on cognitive functions remains yet to be well-established. This study is a secondary analysis of the MAPT study, 1,293 older subjects (mean age 75 years) with high CAIDE score (i.e., ≥6) were classified according to the four intervention groups: 1) multi-domain intervention plus placebo, 2) isolated supplementation with Omega-3 polyunsaturated fatty acid (n-3 PUFA), 3) combination of the two interventions, and 4) placebo alone. Linear mixed-model repeated-measures analyses were used to assess the cognitive changes according to various neuropsychological test scores between intervention groups compared to the placebo at 36 months from baseline. Compared to the placebo, group with multi-domain intervention in combination withn-3PUFA was found to show significant improvement in the delayed total recall test of the free and cued selective reminding test (FCSRT) (mean±standard error(SE) = 0.20±0.10) and MMSE orientation test (mean±SE = 0.15±0.06) at 36 months. Isolated multi-domain intervention group showed significant less decline in the MMSE orientation test (mean±SE = 0.12±0.06) compared to the placebo. There was significant less improvement (mean±SE = - 1.01±0.46) in the FCSRT free recall test in the n-3 PUFA intervention group compared to the placebo at 36 months. Our findings show high-risk subjects for dementia screened with CAIDE dementia score might benefit from multi-domain intervention strategies as in the MAPT study, particularly in the orientation and delayed recall domain.
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Affiliation(s)
- Jagadish K Chhetri
- Department of Geriatrics, Gérontopôle, CHU Toulouse, Purpan University Hospital, Toulouse, France.,Department of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China.,NSGG, Kathmandu, Nepal
| | - Philipe de Souto Barreto
- Department of Geriatrics, Gérontopôle, CHU Toulouse, Purpan University Hospital, Toulouse, France
| | - Christelle Cantet
- Department of Geriatrics, Gérontopôle, CHU Toulouse, Purpan University Hospital, Toulouse, France.,Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France
| | - Kristell Pothier
- Department of Geriatrics, Gérontopôle, CHU Toulouse, Purpan University Hospital, Toulouse, France
| | - Matteo Cesari
- Department of Geriatrics, Gérontopôle, CHU Toulouse, Purpan University Hospital, Toulouse, France.,Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France.,INSERM, UMR1027, Université de Toulouse, UPS, Toulouse, France.,Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, Università di Milano, Milan, Italy
| | - Sandrine Andrieu
- Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France.,INSERM, UMR1027, Université de Toulouse, UPS, Toulouse, France
| | - Nicola Coley
- Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France.,INSERM, UMR1027, Université de Toulouse, UPS, Toulouse, France
| | - Bruno Vellas
- Department of Geriatrics, Gérontopôle, CHU Toulouse, Purpan University Hospital, Toulouse, France.,Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France.,INSERM, UMR1027, Université de Toulouse, UPS, Toulouse, France
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Xiu S, Chhetri JK, Sun L, Mu Z, Wang L. Association of serum prealbumin with risk of osteoporosis in older adults with type 2 diabetes mellitus: a cross-sectional study. Ther Adv Chronic Dis 2019; 10:2040622319857361. [PMID: 31223465 PMCID: PMC6566483 DOI: 10.1177/2040622319857361] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2018] [Accepted: 05/24/2019] [Indexed: 01/08/2023] Open
Abstract
Background: Poor nutritional status is associated with osteoporosis. Prealbumin is a more sensitive marker than albumin to assess nutritional status. Therefore, the relationship between serum levels of prealbumin and osteoporosis in older adults with type 2 diabetes mellitus (T2DM) was investigated. Methods: A total of 370 older adults with T2DM were divided into two groups: older adults with osteoporosis (n = 249) and older adults without osteoporosis (n = 121). Bone mineral density (BMD) and appendicular skeletal muscle (ASM) were measured by dual-energy X-ray absorptiometry (DEXA). Serum levels of prealbumin, highly sensitive C-reactive protein (hs-CRP), interleukin-6 (IL-6), 25-hydroxyvitamin D3 [25(OH) D3] were also tested. Logistic regression analysis was performed to assess the association between prealbumin and osteoporosis. Results: The adults with osteoporosis had lower prealbumin levels than those without osteoporosis (235.40 ± 60.66 versus 261.34 ± 55.28 mg/l, p < 0.001). The proportion of adults with prealbumin levels below the normal range was significantly higher in individuals with osteoporosis compared with those without osteoporosis (16.53% versus 4.42%, respectively). After adjusting for age, sex, body mass index (BMI), anemia, handgrip strength and skeletal muscle index (SMI), logistic regression showed that participants with lower levels of prealbumin had a higher risk of osteoporosis [odds ratio (OR): 3.85; 95% confidence interval (CI): 1.54–6.34; p = 0.004]. Conclusion: Our findings suggested that low levels of prealbumin were associated with an increased risk of osteoporosis in older adults with T2DM. Further longitudinal studies should be conducted to determine if there is a causative association between prealbumin and osteoporosis.
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Affiliation(s)
- Shuangling Xiu
- Department of Endocrinology, Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, No.45 ChangChun Street, XiCheng District, Beijing, 100053, China
| | - Jagadish K Chhetri
- Department of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lina Sun
- Department of Endocrinology, Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zhijing Mu
- Department of Endocrinology, Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Li Wang
- Department of Endocrinology, Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China
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Chhetri JK, de Souto Barreto P, Fougère B, Rolland Y, Vellas B, Cesari M. Chronic inflammation and sarcopenia: A regenerative cell therapy perspective. Exp Gerontol 2018; 103:115-123. [DOI: 10.1016/j.exger.2017.12.023] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 12/20/2017] [Accepted: 12/27/2017] [Indexed: 01/06/2023]
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Chhetri JK, de Souto Barreto P, Cantet C, Cesari M, Coley N, Andrieu S, Vellas B. Trajectory of the MAPT-PACC-Preclinical Alzheimer Cognitive Composite in the Placebo Group of a Randomized Control Trial: Results from the MAPT Study: Lessons for Further Trials. J Prev Alzheimers Dis 2018; 5:31-35. [PMID: 29405230 DOI: 10.14283/jpad.2017.21] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Defining the primary cognitive endpoint is a major decision for Alzheimer's disease preventive trials. As an example for further trials we present in detail the three-year cognitive decline in the placebo group of MAPT trial, a randomized controlled trial (RCT) using a cognitive composite score (MAPT-PACC). Participants were dementia-free adults 70 years or older, with subjective memory complaints. Our findings as expected showed subjects with older age (>75), higher beta amyloid brain deposition, APOE-ε4 allele carriers, with low RBC DHA+EPA levels and higher CDR level are at higher risk of cognitive decline. The data presented in this paper can be useful for future preventive trials to choose the primary cognitive end point, assess the clinical relevance of cognitive changes and perform sample size calculation for several targeted population eg. ApoE4, amyloid +, oldest old, lower n3-PUFA. We believe that the trial group with CDR 0.5, without being selected by a memory test endpoint is a good target population for AD preventive trials.
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Affiliation(s)
- J K Chhetri
- Prof. Bruno Vellas, Gérontopôle, Department of Geriatrics, CHU Toulouse, Purpan University Hospital, Toulouse, France,
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Chhetri JK, Chan P, Vellas B, Cesari M. Motoric Cognitive Risk Syndrome: Predictor of Dementia and Age-Related Negative Outcomes. Front Med (Lausanne) 2017; 4:166. [PMID: 29119100 PMCID: PMC5660976 DOI: 10.3389/fmed.2017.00166] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 09/20/2017] [Indexed: 01/09/2023] Open
Abstract
Cognitive disorders represent a leading cause of disability in the aging population, of which dementia has the highest global burden. Early signs of dementia such as slow gait and memory complaints are known to present well before the overt manifestation of the disease. Motoric cognitive risk (MCR) syndrome characterized by the simultaneous presence of gait disturbances and memory complaints in older subjects has been proposed to study the close interactions between the physical and cognitive domains as well as a possible approach to identify individuals at increased risk of dementia. In addition, studies have shown MCR as a predictor of other negative outcomes in older adults, including disability, falls and death. However, the concept of MCR is still in its early stage and approach to the syndrome is still not well established. This review aims to put together the various aspects of MCR syndrome including its pathophysiology, diagnosis, epidemiology, and relationship with other geriatric conditions.
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Affiliation(s)
- Jagadish K Chhetri
- Gérontopôle, Department of Geriatrics, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Piu Chan
- Department of Neurobiology, Geriatrics, and Neurology, Beijing Institute of Geriatrics, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Bruno Vellas
- Gérontopôle, Department of Geriatrics, Centre Hospitalier Universitaire de Toulouse, Toulouse, France.,INSERM UMR 1027, University of Toulouse III Paul Sabatier, Toulouse, France
| | - Matteo Cesari
- Gérontopôle, Department of Geriatrics, Centre Hospitalier Universitaire de Toulouse, Toulouse, France.,INSERM UMR 1027, University of Toulouse III Paul Sabatier, Toulouse, France
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Chhetri JK. Immunisation of older adults: where are the frail? The Lancet Public Health 2017; 2:e449. [DOI: 10.1016/s2468-2667(17)30155-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Accepted: 07/24/2017] [Indexed: 10/18/2022] Open
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Zhang M, Zhao QC, Liu YP, Yang L, Zhu HM, Chhetri JK. Prognostic analysis and comparison of colon cancer in Han and Hui patients. World J Gastroenterol 2014; 20:5082-5086. [PMID: 24803822 PMCID: PMC4009544 DOI: 10.3748/wjg.v20.i17.5082] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2014] [Revised: 02/27/2014] [Accepted: 03/13/2014] [Indexed: 02/06/2023] Open
Abstract
AIM: To investigate the relevant prognostic factors and their differences between colorectal cancer (CRC) patients of Chinese Han and Hui ethnicities in the Beijing region.
METHODS: A retrospective analysis of 880 patients diagnosed with CRC at Xuanwu Hospital, Capital Medical University between September 2001 and September 2011 was performed. Among the 880 patients, 398 and 482 were Hui and Han, respectively. Characteristics including sex, age, diet, tumor size, primary tumor site, Dukes’ stage and degree of differentiation were analyzed for their influence on prognosis. Data on dietary structures were recorded through a questionnaire survey conducted during the patient’s first visit, return visit or follow-up checkups.
RESULTS: Among patients with colon cancer, the 5-year survival rate for patients of Hui ethnicity was lower than that for Han patients (P = 0.025). Six risk factors (age of onset, dietary structure, tumor size, Dukes’ stage, location of cancer and degree of differentiation) in both Han and Hui patients were identified as prognostic factors (P < 0.05). Multivariate analysis showed that age of onset (P = 0.002), diet (P = 0.000), Dukes’ stage (P = 0.000) and degree of differentiation (P = 0.000) are prognostic factors affecting both ethnic groups. Comparison of prognostic factors between Han and Hui patients with CRC showed that dietary structure was a statistically significant factor, and diet varied significantly between the two ethnic groups.
CONCLUSION: Dietary structure has a significant influence on colon cancer prognosis among Han and Hui patients with colon cancer in Beijing, which may cause a difference in their survival rates.
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Zhang M, Zhou YZ, Li XY, Tang Z, Zhu HM, Yang Y, Chhetri JK. Seroepidemiology of Helicobacter pylori infection in elderly people in the Beijing region, China. World J Gastroenterol 2014; 20:3635-3639. [PMID: 24707148 PMCID: PMC3974532 DOI: 10.3748/wjg.v20.i13.3635] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2014] [Revised: 02/25/2014] [Accepted: 03/05/2014] [Indexed: 02/06/2023] Open
Abstract
AIM: To investigate seroepidemiology of cagA+ and vacA+ strains of Helicobacter pylori (H. pylori) in an elderly population in Beijing and to determine risk factors for seropositivity.
METHODS: A total of 2006 elderly persons (> 60 years) were selected using a random cluster sampling method in different parts of the Beijing area (urban, suburban and mountainous districts). Structured questionnaires were completed during home visits, including history of H. pylori infection, history of gastrointestinal diseases, diet types, hygiene habits, occupation and economic status. Blood samples (2 mL) were collected from each participant, and serum IgG antibodies to cagA, vacA and H. pylori urease antigens were measured by immunodetection.
RESULTS: The prevalence of H. pylori infection in elderly subjects was 83.4% and the type I H. pylori strain infection rate was 56%. The seroprevalence for type I H. pylori strain infection in urban and suburban districts was higher than that in the mountainous areas (P < 0.001). Elderly subjects who had previously performed manual labor or were in the young-old age group (age < 75 years) had a higher seroprevalence of H. pylori infection than those who had previously performed mental labor or were in the oldest-old age group (age ≥ 75 year) (P < 0.05). The type I H. pylori strain infection rate in the elderly with vegetarian diets was higher than in those eating high-protein foods (P < 0.001). There was no significant difference in the prevalence of H. pylori strains between male and female elderly participants (P > 0.05).
CONCLUSION: Type I H. pylori seroprevalence is higher in elderly people. The distribution of strains of H. pylori is significantly affected by age, area and dietary habits.
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