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El Assar M, Rodríguez-Sánchez I, Álvarez-Bustos A, Rodríguez-Mañas L. Biomarkers of frailty. Mol Aspects Med 2024; 97:101271. [PMID: 38631189 DOI: 10.1016/j.mam.2024.101271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 03/19/2024] [Accepted: 03/20/2024] [Indexed: 04/19/2024]
Abstract
Several biomarkers have been proposed to identify frailty, a multisystemic age-related syndrome. However, the complex pathophysiology and the absence of a consensus on a comprehensive and universal definition make it challenging to pinpoint a singular biomarker or set of biomarkers that conclusively characterize frailty. This review delves into the main laboratory biomarkers, placing special emphasis on those associated with various pathways closely tied to the frailty condition, such as inflammation, oxidative stress, mitochondrial dysfunction, metabolic and endocrine alterations and microRNA. Additionally, we provide a summary of different clinical biomarkers encompassing different tools that have been proposed to assess frailty. We further address various imaging biomarkers such as Dual Energy X-ray Absorptiometry, Bioelectrical Impedance analysis, Computed Tomography and Magnetic Resonance Imaging, Ultrasound and D3 Creatine dilution. Intervention to treat frailty, including non-pharmacological ones, especially those involving physical exercise and nutrition, and pharmacological interventions, that include those targeting specific mechanisms such as myostatin inhibitors, insulin sensitizer metformin and with special relevance for hormonal treatments are mentioned. We further address the levels of different biomarkers in monitoring the potential positive effects of some of these interventions. Despite the availability of numerous biomarkers, their performance and usefulness in the clinical arena are far from being satisfactory. Considering the multicausality of frailty, there is an increasing need to assess the role of sets of biomarkers and the combination between laboratory, clinical and image biomarkers, in terms of sensitivity, specificity and predictive values for the diagnosis and prognosis of the different outcomes of frailty to improve detection and monitoring of older people with frailty or at risk of developing it, being this a need in the everyday clinical practice.
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Affiliation(s)
- Mariam El Assar
- Fundación para la Investigación Biomédica del Hospital Universitario de Getafe, Madrid, Spain; Centro de Investigación Biomédica en Red sobre Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | | | - Alejandro Álvarez-Bustos
- Centro de Investigación Biomédica en Red sobre Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Leocadio Rodríguez-Mañas
- Centro de Investigación Biomédica en Red sobre Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain; Servicio de Geriatría, Hospital Universitario de Getafe, Madrid, Spain.
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2
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Dent E, Hanlon P, Sim M, Jylhävä J, Liu Z, Vetrano DL, Stolz E, Pérez-Zepeda MU, Crabtree DR, Nicholson C, Job J, Ambagtsheer RC, Ward PR, Shi SM, Huynh Q, Hoogendijk EO. Recent developments in frailty identification, management, risk factors and prevention: A narrative review of leading journals in geriatrics and gerontology. Ageing Res Rev 2023; 91:102082. [PMID: 37797723 DOI: 10.1016/j.arr.2023.102082] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 09/29/2023] [Accepted: 10/01/2023] [Indexed: 10/07/2023]
Abstract
Frailty is an age-related clinical condition characterised by an increased susceptibility to stressors and an elevated risk of adverse outcomes such as mortality. In the light of global population ageing, the prevalence of frailty is expected to soar in coming decades. This narrative review provides critical insights into recent developments and emerging practices in frailty research regarding identification, management, risk factors, and prevention. We searched journals in the top two quartiles of geriatrics and gerontology (from Clarivate Journal Citation Reports) for articles published between 01 January 2018 and 20 December 2022. Several recent developments were identified, including new biomarkers and biomarker panels for frailty screening and diagnosis, using artificial intelligence to identify frailty, and investigating the altered response to medications by older adults with frailty. Other areas with novel developments included exercise (including technology-based exercise), multidimensional interventions, person-centred and integrated care, assistive technologies, analysis of frailty transitions, risk-factors, clinical guidelines, COVID-19, and potential future treatments. This review identified a strong need for the implementation and evaluation of cost-effective, community-based interventions to manage and prevent frailty. Our findings highlight the need to better identify and support older adults with frailty and involve those with frailty in shared decision-making regarding their care.
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Affiliation(s)
- Elsa Dent
- Research Centre for Public Health, Equity and Human Flourishing, Torrens University Australia, Adelaide, Australia
| | - Peter Hanlon
- School of Health and Wellbeing, University of Glasgow, Scotland, UK
| | - Marc Sim
- Nutrition and Health Innovation Research Institute, School of Health and Medical Sciences, Edith Cowan University, Perth, Western Australia, Australia; Medical School, The University of Western Australia, Perth, Western Australia, Australia
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Faculty of Social Sciences, Unit of Health Sciences and Gerontology Research Center, University of Tampere, Tampere, Finland
| | - Zuyun Liu
- Second Affiliated Hospital and School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Davide L Vetrano
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center, Stockholm, Sweden
| | - Erwin Stolz
- Institute of Social Medicine and Epidemiology, Medical University of Graz, Graz, Austria
| | - Mario Ulises Pérez-Zepeda
- Instituto Nacional de Geriatría, Dirección de Investigación, ciudad de México, Mexico; Centro de Investigación en Ciencias de la Salud (CICSA), FCS, Universidad Anáhuac México Campus Norte, Huixquilucan Edo. de México
| | | | - Caroline Nicholson
- Centre for Health System Reform & Integration, Mater Research Institute-University of Queensland, Brisbane, Australia
| | - Jenny Job
- Centre for Health System Reform & Integration, Mater Research Institute-University of Queensland, Brisbane, Australia
| | - Rachel C Ambagtsheer
- Research Centre for Public Health, Equity and Human Flourishing, Torrens University Australia, Adelaide, Australia
| | - Paul R Ward
- Research Centre for Public Health, Equity and Human Flourishing, Torrens University Australia, Adelaide, Australia
| | - Sandra M Shi
- Hinda and Arthur Marcus Institute for Aging, Hebrew Senior Life, Boston, Massachusetts, USA; Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Quan Huynh
- Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Emiel O Hoogendijk
- Department of Epidemiology & Data Science and Department of General Practice, Amsterdam UMC, Location VU University Medical Center, Amsterdam, Netherlands; Amsterdam Public Health research institute, Ageing & Later Life Research Program, Amsterdam UMC, Amsterdam, the Netherlands.
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3
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Gonçalves RSDSA, Maciel ÁCC, Rolland Y, Vellas B, de Souto Barreto P. Frailty biomarkers under the perspective of geroscience: A narrative review. Ageing Res Rev 2022; 81:101737. [PMID: 36162706 DOI: 10.1016/j.arr.2022.101737] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 09/20/2022] [Accepted: 09/21/2022] [Indexed: 01/31/2023]
Abstract
Cellular and molecular aging biomarkers might contribute to identify at-risk individuals for frailty before overt clinical manifestations appear. Although studies on the associations of aging biomarkers and frailty exist, no investigation has gathered this information using a structured framework for identifying aging biomarkers; as a result, the evidence on frailty and aging biomarkers is diffuse and incomplete. Therefore, this narrative review aimed to gather information on the associations of the hallmarks of aging and frailty under the perspective of geroscience. The literature on human studies on this topic is sparse and mainly composed of cross-sectional investigations performed in small study samples. The main putative aging biomarkers associated to frailty were: mitochondrial DNA copy number (genomic instability and mitochondrial dysfunction), telomere length (telomere attrition), global DNA methylation (epigenetic alterations), Hsp70 and Hsp72 (loss of proteostasis), IGF-1 and SIRT1 (deregulated nutrient-sensing), GDF-15 (mitochondrial dysfunction, cellular senescence and altered intercellular communication), CD4 + and CD8 + cell percentages (cellular senescence), circulating osteogenic progenitor (COP) cells (stem cell exhaustion), and IL-6, CRP and TNF-alpha (altered intercellular communication). IGF-1, SIRT1, GDF-15, IL-6, CRP and TNF-alpha presented more evidence among these biomarkers, highlighting the importance of inflammation and nutrient sensing on frailty. Further longitudinal studies investigating biomarkers across the hallmarks of aging would provide valuable information on this topic.
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Affiliation(s)
| | | | - Yves Rolland
- Gerontopole of Toulouse, Institute of Aging, Toulouse University Hospital (CHU Toulouse), Toulouse, France; CERPOP, Inserm 1295, Université de Toulouse, UPS, Toulouse, France.
| | - Bruno Vellas
- Gerontopole of Toulouse, Institute of Aging, Toulouse University Hospital (CHU Toulouse), Toulouse, France; CERPOP, Inserm 1295, Université de Toulouse, UPS, Toulouse, France.
| | - Philipe de Souto Barreto
- Gerontopole of Toulouse, Institute of Aging, Toulouse University Hospital (CHU Toulouse), Toulouse, France; CERPOP, Inserm 1295, Université de Toulouse, UPS, Toulouse, France.
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4
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García-Sánchez J, Mafla-España MA, Torregrosa MD, Cauli O. Androstenedione and Follicle-Stimulating Hormone Concentration Predict the Progression of Frailty Syndrome at One Year Follow-Up in Patients with Localized Breast Cancer Treated with Aromatase Inhibitors. Biomedicines 2022; 10:biomedicines10071634. [PMID: 35884939 PMCID: PMC9312841 DOI: 10.3390/biomedicines10071634] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 07/05/2022] [Accepted: 07/05/2022] [Indexed: 11/16/2022] Open
Abstract
Background: The standard treatment in postmenopausal women with estrogen- and progesterone-positive localized breast cancer consists of aromatase inhibitors (AROi). The ability of AROi to promote or worsen frailty syndrome over time and the relationship with changes in gonadal hormones concentration in blood have not been investigated. Methods: A prospective study to evaluate the relationship between frailty syndrome and gonadal hormones concentrations in blood at baseline (prior to AROi treatment) and after 6 and 12 months under AROi treatment in post-menopausal women with breast cancer. Frailty syndrome was evaluated by the Fried’ criteria. We evaluated whether hormone concentration at baseline could predict frailty syndrome at follow-up. Results: Multinomial regression analysis showed that of the different hormones, those significantly (p < 0.05) associated to the worsening of frailty syndrome were high androstenedione levels and low follicle-stimulating hormone (FSH) levels in blood. Receiver operating characteristic curve analysis showed both androstenedione and FSH significantly (p < 0.05) discriminate patients who developed or presented worsening of frailty syndrome over time, with acceptable sensitivity (approximately 80% in both cases) but low specificity (40%). Conclusion: Hormonal concentrations before AROi treatment constitute possible biomarkers to predict the progression of frailty syndrome.
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Affiliation(s)
- Javier García-Sánchez
- Medical Oncology Department, Doctor Peset University Hospital, 46017 Valencia, Spain; (J.G.-S.); (M.D.T.)
- Medical Oncology Department, Hospital Center of Wallonie Picardy, 7500 Tournai, Belgium
| | - Mayra Alejandra Mafla-España
- Frailty Research Organized Group, University of Valencia, 46010 Valencia, Spain;
- Department of Nursing, University of Valencia, 46010 Valencia, Spain
| | - María Dolores Torregrosa
- Medical Oncology Department, Doctor Peset University Hospital, 46017 Valencia, Spain; (J.G.-S.); (M.D.T.)
| | - Omar Cauli
- Frailty Research Organized Group, University of Valencia, 46010 Valencia, Spain;
- Department of Nursing, University of Valencia, 46010 Valencia, Spain
- Correspondence:
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5
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Perazza LR, Brown-Borg HM, Thompson LV. Physiological Systems in Promoting Frailty. Compr Physiol 2022; 12:3575-3620. [PMID: 35578945 DOI: 10.1002/cphy.c210034] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Frailty is a complex syndrome affecting a growing sector of the global population as medical developments have advanced human mortality rates across the world. Our current understanding of frailty is derived from studies conducted in the laboratory as well as the clinic, which have generated largely phenotypic information. Far fewer studies have uncovered biological underpinnings driving the onset and progression of frailty, but the stage is set to advance the field with preclinical and clinical assessment tools, multiomics approaches together with physiological and biochemical methodologies. In this article, we provide comprehensive coverage of topics regarding frailty assessment, preclinical models, interventions, and challenges as well as clinical frameworks and prevalence. We also identify central biological mechanisms that may be at play including mitochondrial dysfunction, epigenetic alterations, and oxidative stress that in turn, affect metabolism, stress responses, and endocrine and neuromuscular systems. We review the role of metabolic syndrome, insulin resistance and visceral obesity, focusing on glucose homeostasis, adenosine monophosphate-activated protein kinase (AMPK), mammalian target of rapamycin (mTOR), and nicotinamide adenine dinucleotide (NAD+ ) as critical players influencing the age-related loss of health. We further focus on how immunometabolic dysfunction associates with oxidative stress in promoting sarcopenia, a key contributor to slowness, weakness, and fatigue. We explore the biological mechanisms involved in stem cell exhaustion that affect regeneration and may contribute to the frailty-associated decline in resilience and adaptation to stress. Together, an overview of the interplay of aging biology with genetic, lifestyle, and environmental factors that contribute to frailty, as well as potential therapeutic targets to lower risk and slow the progression of ongoing disease is covered. © 2022 American Physiological Society. Compr Physiol 12:1-46, 2022.
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Affiliation(s)
- Laís R Perazza
- Department of Physical Therapy and Athletic Training, Boston University, Boston, Massachusetts, USA
| | - Holly M Brown-Borg
- Department of Biomedical Sciences, University of North Dakota, Grand Forks, North Dakota, USA
| | - LaDora V Thompson
- Department of Physical Therapy and Athletic Training, Boston University, Boston, Massachusetts, USA
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Meng L, Shi H, Wang DG, Shi J, Wu WB, Dang YM, Fan GQ, Shen J, Yu PL, Dong J, Yang RY, Xi H. Specific Metabolites Involved in Antioxidation and Mitochondrial Function Are Correlated With Frailty in Elderly Men. Front Med (Lausanne) 2022; 9:816045. [PMID: 35155500 PMCID: PMC8833032 DOI: 10.3389/fmed.2022.816045] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 01/04/2022] [Indexed: 01/14/2023] Open
Abstract
BackgroundAs an age-related syndrome, frailty may play a central role in poor health among older adults. Sarcopenia overlaps with the physical domain of frailty, and most existing studies have analyzed the associated factors of frailty and sarcopenia as an isolated state. Perturbations in metabolism may play an important role in the presence of frailty or sarcopenia; however, the metabolites associated with frailty, especially overlapping with sarcopenia remain unclear. In this study, we aimed to explore whether amino acids, carnitines, acylcarnitines and lysophosphatidylcholines, as specific panels, are significantly correlated with frailty, especially overlapping with sarcopenia, to gain insight into potential biomarkers and possible biological mechanisms and to facilitate their management.MethodsWe applied a targeted high-performance liquid chromatography-tandem mass spectrometry approach in serum samples from 246 Chinese older men (age 79.2 ± 7.8 years) with frailty (n = 150), non-frailty (n = 96), frailty and sarcopenia (n = 52), non-frail and non-sarcopenic control (n = 85). Frailty was evaluated using Freid phenotype criteria, sarcopenia was defined by diagnostic algorithm of Asian Working Group on Sarcopenia, and the participants were diagnosed as frailty and sarcopenia when they met the evaluation criteria of both frailty and sarcopenia. A panel of 29 metabolomic profiles was assayed and included different classes of amino acids, carnitines, acylcarnitines, and lysophosphatidylcholines (LPCs). Multivariate logistic regression was used to screen the metabolic factors contributing to frailty status, and orthogonal partial least squares discriminant analysis was used to explore important factors and distinguish different groups.ResultsIn older men demonstrating the frail phenotype, amino acid perturbations included lower tryptophan and higher glycine levels. With regard to lipid metabolism, the frailty phenotype was characterized by lower concentrations of isovalerylcarnitine (C5), LPC16:0 and LPC18:2, while higher levels of octanoyl-L-carnitine (C8), decanoyl-L-carnitine (C10), dodecanoyl-L-carnitine (C12) and tetradecanoyl-L-carnitine (C14). After adjusting for several clinical confounders, tryptophan, LPC18:2, LPC 16:0 and C5 were negatively correlated with frailty, and C8 and C12 were positively related to frailty. We preliminarily identified metabolic profiles (LPC16:0, LPC18:2, glycine and tryptophan) that may distinguish older men with frailty from those without frailty. Importantly, a set of serum amino acids and LPCs (LPC16:0, LPC18:2, and tryptophan) was characterized in the metabotype of older adults with an overlap of frailty and sarcopenia. The metabolites that were most discriminating of frailty status implied that the underlying mechanism might be involved in antioxidation and mitochondrial dysfunction.ConclusionsThese present metabolic analyses may provide valuable information on the potential biomarkers and possible biological mechanisms of frailty, and overlapping sarcopenia. The findings obtained may offer insight into their management in older adults.
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Affiliation(s)
- Li Meng
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Beijing Hospital/National Center of Gerontology of National Health Commission, Chinese Academy of Medical Sciences, Beijing, China
| | - Hong Shi
- Department of Geriatrics, National Clinical Research Center for Geriatrics, National Center of Gerontology, Institute of Geriatric Medicine, Beijing Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Da-guang Wang
- Department of Laboratory Medicine, National Center of Gerontology, Institute of Geriatric Medicine, Beijing Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Jing Shi
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Beijing Hospital/National Center of Gerontology of National Health Commission, Chinese Academy of Medical Sciences, Beijing, China
| | - Wen-bin Wu
- Department of Geriatrics, National Clinical Research Center for Geriatrics, National Center of Gerontology, Institute of Geriatric Medicine, Beijing Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Ya-min Dang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Beijing Hospital/National Center of Gerontology of National Health Commission, Chinese Academy of Medical Sciences, Beijing, China
| | - Guo-qing Fan
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Beijing Hospital/National Center of Gerontology of National Health Commission, Chinese Academy of Medical Sciences, Beijing, China
| | - Ji Shen
- Department of Geriatrics, National Clinical Research Center for Geriatrics, National Center of Gerontology, Institute of Geriatric Medicine, Beijing Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Pu-lin Yu
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Beijing Hospital/National Center of Gerontology of National Health Commission, Chinese Academy of Medical Sciences, Beijing, China
| | - Jun Dong
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Beijing Hospital/National Center of Gerontology of National Health Commission, Chinese Academy of Medical Sciences, Beijing, China
| | - Rui-yue Yang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Beijing Hospital/National Center of Gerontology of National Health Commission, Chinese Academy of Medical Sciences, Beijing, China
- *Correspondence: Rui-yue Yang
| | - Huan Xi
- Department of Geriatrics, National Clinical Research Center for Geriatrics, National Center of Gerontology, Institute of Geriatric Medicine, Beijing Hospital, Chinese Academy of Medical Sciences, Beijing, China
- Huan Xi
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Mak JKL, Reynolds CA, Hägg S, Li X, Ericsson M, Pedersen NL, Jylhävä J, Kuja-Halkola R. Sex differences in genetic and environmental influences on frailty and its relation to body mass index and education. Aging (Albany NY) 2021; 13:16990-17023. [PMID: 34230219 PMCID: PMC8312411 DOI: 10.18632/aging.203262] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 06/22/2021] [Indexed: 11/25/2022]
Abstract
Frailty is influenced by numerous genetic and environmental factors. However, sex differences in how these factors affect frailty, and the gene-environment interplay among frailty and two of its well-established risk factors, unhealthy body mass index (BMI) and low education, are less clear. In a large sample of 42,994 Swedish twins, we used structural equation models to estimate the genetic (heritability) and environmental sources of variance in frailty, defined as the frailty index (FI), separately in men and women. Genetic and individual-specific environmental factors contributed approximately equally to the FI variance. The heritability of FI was slightly, but significantly, higher in women (52%) than in men (45%), yet we found only weak-to-no indication of different sources of genetic variance influencing frailty across sexes. We observed a small-to-moderate genetic overlap between FI and BMI, and that the correlation between FI and education was largely explained by environmental factors common to twins in a pair. Additionally, genetic factors accounted for more of FI variation at both low and high BMI levels, with similar patterns in both sexes. In conclusion, the twin-based heritability of frailty is higher in women than in men, and different mechanisms may underlie the associations of frailty with BMI and education.
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Affiliation(s)
- Jonathan K. L. Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, CA 92521, USA
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Xia Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Malin Ericsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Melbourne School of Psychological Sciences, MDHS, The University of Melbourne, Melbourne, Australia
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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8
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Rabaneda-Bueno R, Torres-Carrillo N, Ávila-Funes JA, Gutiérrez-Robledo LM, Pérez-Suárez TG, Acosta JL, Torres-Castro S, Fletes-Rayas AL, Gutierrez-Hurtado I, Sandoval-Pinto E, Cremades R, Torres-Carrillo NM. PTPN22 gene functional polymorphism (rs2476601) in older adults with frailty syndrome. Mol Biol Rep 2021; 48:1193-1204. [PMID: 33611779 DOI: 10.1007/s11033-021-06212-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 02/02/2021] [Indexed: 10/22/2022]
Abstract
The frailty syndrome is a common clinical marker of vulnerability in older adults conducive to an overall decline in inflammatory stress responsiveness; yet little is known about the genetic risk factors for frailty in elderly. Our aim was to investigate the association between the rs2476601 polymorphism in PTPN22 gene and susceptibility to frailty in Mexican older adults. Data included 630 subjects 70 and older from The Coyoacán cohort, classified as frail, pre-frail, and non-frail following Fried's criteria. Sociodemographic and clinical characteristics were compared between groups at baseline and after a multivariate analysis. The rs2476601 polymorphism was genotyped by TaqMan genotyping assay using real-time PCR and genotype frequencies were determined for each frailty phenotype in all participants and subsets by age range. Genetic association was examined using stratified and interaction analyses adjusting for age, sex and variables selected in the multivariate analysis. Disability for day-life activities, depression and cognitive impairment were associated with the risk of pre-frailty and frailty at baseline and after adjustment. Carrying the T allele increased significantly the risk of frailty in patients 76 and older (OR 5.64, 95% CI 4.112-7.165) and decreased the risk of pre-frailty under no clinical signs of depression (OR 0.53; 95% CI 0.17-1.71). The PTPN22 polymorphism, rs2476601, could be a genetic risk factor for frailty as subject to quality of life. This is the first study analyzing such relationship in Mexican older adults. Confirming these findings requires additional association studies on wider age ranges in populations of older adults with frailty syndrome.
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Affiliation(s)
- Rubén Rabaneda-Bueno
- Biology Centre of the Czech Academy of Sciences, Institute of Hydrobiology, 370 05, České Budějovice, Czech Republic.,Departamento de Microbiología y Patología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - Norma Torres-Carrillo
- Departamento de Microbiología y Patología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - José Alberto Ávila-Funes
- Departamento de Geriatría, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, México
| | | | - Thalía Gabriela Pérez-Suárez
- Departamento de Microbiología y Patología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - José Luis Acosta
- Departamento de Biotecnología Agrícola, Instituto Politécnico Nacional-Centro Interdisciplinario de Investigación Para el Desarrollo Integral Regional (CIIDIR), Unidad Sinaloa, Guasave, Sinaloa, México
| | | | - Ana Lilia Fletes-Rayas
- Departamento de Enfermería Clínica Integrada, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - Itzae Gutierrez-Hurtado
- Departamento de Biología Molecular, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - Elena Sandoval-Pinto
- Departamento de Biología Celular y Molecular, Centro Universitario de Ciencias Biológicas y Agropecuarias, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - Rosa Cremades
- Departamento de Microbiología y Patología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - Nora Magdalena Torres-Carrillo
- Departamento de Microbiología y Patología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, México.
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Mladenovic Djordjevic AN, Kapetanou M, Loncarevic-Vasiljkovic N, Todorovic S, Athanasopoulou S, Jovic M, Prvulovic M, Taoufik E, Matsas R, Kanazir S, Gonos ES. Pharmacological intervention in a transgenic mouse model improves Alzheimer's-associated pathological phenotype: Involvement of proteasome activation. Free Radic Biol Med 2021; 162:88-103. [PMID: 33279620 PMCID: PMC7889698 DOI: 10.1016/j.freeradbiomed.2020.11.038] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/23/2020] [Accepted: 11/28/2020] [Indexed: 12/16/2022]
Abstract
Alzheimer's disease (AD) is the most common form of dementia worldwide, characterized by a progressive decline in a variety of cognitive and non-cognitive functions. The amyloid beta protein cascade hypothesis places the formation of amyloid beta protein aggregates on the first position in the complex pathological cascade leading to neurodegeneration, and therefore AD might be considered to be a protein-misfolding disease. The Ubiquitin Proteasome System (UPS), being the primary protein degradation mechanism with a fundamental role in the maintenance of proteostasis, has been identified as a putative therapeutic target to delay and/or to decelerate the progression of neurodegenerative disorders that are characterized by accumulated/aggregated proteins. The purpose of this study was to test if the activation of proteasome in vivo can alleviate AD pathology. Specifically by using two compounds with complementary modes of proteasome activation and documented antioxidant and redox regulating properties in the 5xFAD transgenic mice model of AD, we ameliorated a number of AD related deficits. Shortly after proteasome activation we detected significantly reduced amyloid-beta load correlated with improved motor functions, reduced anxiety and frailty level. Essentially, to our knowledge this is the first report to demonstrate a dual activation of the proteasome and its downstream effects. In conclusion, these findings open up new directions for future therapeutic potential of proteasome-mediated proteolysis enhancement.
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Affiliation(s)
- Aleksandra N Mladenovic Djordjevic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia.
| | - Marianna Kapetanou
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Ave., 11635, Athens, Greece
| | - Natasa Loncarevic-Vasiljkovic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia; Molecular Nutrition and Health Lab, CEDOC - Centro de Estudos de Doenças Crónicas, NOVA Medical School / Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Edifício CEDOC II, Rua Câmara Pestana 6, 1150-082, Lisboa, Portugal
| | - Smilja Todorovic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia
| | - Sofia Athanasopoulou
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Ave., 11635, Athens, Greece; Department of Biology, Faculty of Medicine, University of Thessaly, Biopolis, 41500, Larissa, Greece
| | - Milena Jovic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia
| | - Milica Prvulovic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia
| | - Era Taoufik
- Laboratory of Cellular and Molecular Neurobiology-Stem Cells, Department of Neurobiology, Hellenic Pasteur Institute, 127 Vasilissis Sofias Avenue, 11521, Athens, Greece
| | - Rebecca Matsas
- Laboratory of Cellular and Molecular Neurobiology-Stem Cells, Department of Neurobiology, Hellenic Pasteur Institute, 127 Vasilissis Sofias Avenue, 11521, Athens, Greece
| | - Selma Kanazir
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia
| | - Efstathios S Gonos
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Ave., 11635, Athens, Greece.
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10
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Omics biomarkers for frailty in older adults. Clin Chim Acta 2020; 510:363-372. [PMID: 32745578 DOI: 10.1016/j.cca.2020.07.057] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 07/29/2020] [Accepted: 07/29/2020] [Indexed: 12/14/2022]
Abstract
Frailty is a clinical state characterized by an age-related unsteady state of the body, a decline in physiological function, and an increased vulnerability to adverse outcomes. Early diagnosis of frailty is important for improving the quality of life in older adults and promoting healthy aging. The biological mechanisms underlying frailty have been extensively studied in recent years. Combining assessment tools and biomarkers can facilitate the early diagnosis of frailty. However, there is a lack of stable and reliable frailty-related biomarkers for use in clinical practice. Advances in the multi-omics platforms have provided new information on the molecular mechanisms underlying frailty. Thus, identifying biomarkers using omics-based approaches helps explore the physiological mechanisms underlying frailty, and aids the evaluation of the risk of frailty development and progression. This article reviews the current status of frailty biomarkers from the genomics, transcriptomics, proteomics, and metabolomics perspectives.
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11
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Borras C, Ingles M, Mas-Bargues C, Dromant M, Sanz-Ros J, Román-Domínguez A, Gimeno-Mallench L, Gambini J, Viña J. Centenarians: An excellent example of resilience for successful ageing. Mech Ageing Dev 2019; 186:111199. [PMID: 31899226 DOI: 10.1016/j.mad.2019.111199] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 12/17/2019] [Accepted: 12/19/2019] [Indexed: 12/13/2022]
Abstract
Centenarians are remarkable not only because of their prolonged life, but also because they compress morbidity until the very last moments of their lives, thus being proposed as a model of successful, extraordinary ageing. From the medical viewpoint, centenarians do not escape the physiological decline or the age-related diseases or syndromes (i.e. frailty), but the rate of such processes is slow enough to be counterbalanced by their increased intrinsic capacity to respond to minor stresses of daily life (i.e. resilience). These new concepts are reviewed in this paper. Allostatic stresses lead to a chronic low-grade inflammation that has led to the proposal of the "inflammaging" theory of ageing and frailty. The biology of centenarians, described in this review, provides us with clues for intervention to promote healthy ageing in the general population. One of the major reasons for this healthy ageing has to do with the genetic signature that is specific for centenarians and certainly different from octogenarians who do not enjoy the extraordinary qualities of centenarians.
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Affiliation(s)
- C Borras
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia, CIBERFES-ISCIII, INCLIVA, Valencia, Spain.
| | - M Ingles
- Freshage Research Group, Department of Physiotherapy, Faculty of Physiotherapy, University of Valencia, CIBERFES-ISCIII, INCLIVA, Valencia, Spain
| | - C Mas-Bargues
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia, CIBERFES-ISCIII, INCLIVA, Valencia, Spain
| | - M Dromant
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia, CIBERFES-ISCIII, INCLIVA, Valencia, Spain
| | - J Sanz-Ros
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia, CIBERFES-ISCIII, INCLIVA, Valencia, Spain
| | - A Román-Domínguez
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia, CIBERFES-ISCIII, INCLIVA, Valencia, Spain
| | - L Gimeno-Mallench
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia, CIBERFES-ISCIII, INCLIVA, Valencia, Spain
| | - J Gambini
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia, CIBERFES-ISCIII, INCLIVA, Valencia, Spain
| | - J Viña
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia, CIBERFES-ISCIII, INCLIVA, Valencia, Spain
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12
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Abstract
Using neXtProt release 2019-01-11, we manually curated a list of 1837 functionally uncharacterized human proteins. Using OrthoList 2, we found that 270 of them have homologues in Caenorhabditis elegans, including 60 with a one-to-one orthology relationship. According to annotations extracted from WormBase, the vast majority of these 60 worm genes have RNAi experimental data or mutant alleles, but manual inspection shows that only 15% have phenotypes that could be interpreted in terms of a specific function. One third of the worm orthologs have protein-protein interaction data, and two of these interactions are conserved in humans. The combination of phenotypic, protein-protein interaction, and gene expression data provides functional hypotheses for 8 uncharacterized human proteins. Experimental validation in human or orthologs is necessary before they can be considered for annotation.
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Affiliation(s)
- Paula Duek
- CALIPHO Group , SIB-Swiss Institute of Bioinformatics, CMU , Michel-Servet 1 , 1211 Geneva 4 , Switzerland
| | - Lydie Lane
- CALIPHO Group , SIB-Swiss Institute of Bioinformatics, CMU , Michel-Servet 1 , 1211 Geneva 4 , Switzerland.,Department of Microbiology and Molecular Medicine, Faculty of Medicine , University of Geneva, CMU , Michel-Servet 1 , 1211 Geneva 4 , Switzerland
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