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Mohammadnejad A, Ryg J, Ewertz M, Jylhävä J, Hjelmborg JVB, Galvin A. Association of cancer with functional decline at old age: a longitudinal study in Danish twins. Scand J Public Health 2024:14034948241240823. [PMID: 38570302 DOI: 10.1177/14034948241240823] [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] [Indexed: 04/05/2024]
Abstract
INTRODUCTION There is evidence that older adults with cancer have a higher risk of functional decline than cancer-free older adults. However, few studies are longitudinal, and none are twin studies. Thus, we aimed to investigate the relationship between cancer and functional decline in older adult (aged 70+ years) twins. MATERIALS AND METHODS Cancer cases in the Longitudinal Study of Aging Danish Twins were identified through the Danish Cancer Registry. Functional status was assessed using hand grip strength (6 years follow-up), and self-reported questions on mobility (10 years follow-up), and cut-offs were defined to assess functional decline. Cox regression models were performed for all the individual twins. In addition, we extended the analysis to discordant twin pairs (twin pairs with one having cancer and the other being cancer-free), to control to a certain extent for (unmeasured) shared confounders (genetic and environmental factors). RESULTS The analysis based on individual twins showed that individual twins with cancer are at increased hazard of worsening hand grip strength (hazard ratio (HR) 1.37, 95% confidence interval (CI) 1.04, 1.80) than cancer-free twins. Among the discordant twin pairs, twins with cancer had a higher hazard of worsening hand grip strength (HR 3.50, 95% CI 1.15, 10.63) than cancer-free cotwins. In contrast, there was no evidence of a difference between the hazard of experiencing mobility decline for twins with cancer compared with cancer-free twins, in both individual twins and discordant twin pairs analyses. DISCUSSION Cancer was associated with hand grip strength functional decline in old individual twins and discordant pairs. Our results strengthen the importance of comprehensive geriatric assessment in older adults with cancer, as well as the importance of routine assessment of functional status. Promoting physical activity through exercise training programmes could enable the prevention of functional decline in older adults with cancer.
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Affiliation(s)
- Afsaneh Mohammadnejad
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Denmark
| | - Jesper Ryg
- Academy of Geriatric Cancer Research (AgeCare), Odense University Hospital, Denmark
- Department of Geriatric Medicine, Odense University Hospital, Denmark
- Department of Clinical Research, University of Southern Denmark, Denmark
| | - Marianne Ewertz
- Academy of Geriatric Cancer Research (AgeCare), Odense University Hospital, Denmark
- Department of Clinical Research, University of Southern Denmark, Denmark
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
- Faculty of Social Sciences, Unit of Health Sciences and Gerontology Research Center, University of Tampere, Finland
| | - Jacob vB Hjelmborg
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Denmark
- The Danish Twin Registry, University of Southern Denmark, Denmark
| | - Angéline Galvin
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Denmark
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, Epicene Team, France
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Haapanen MJ, Mikkola TM, Jylhävä J, Wasenius NS, Kajantie E, Eriksson JG, von Bonsdorff MB. Lifestyle-related factors in late midlife as predictors of frailty from late midlife into old age: a longitudinal birth cohort study. Age Ageing 2024; 53:afae066. [PMID: 38557664 PMCID: PMC10982848 DOI: 10.1093/ageing/afae066] [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: 10/05/2023] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Few studies have examined longitudinal changes in lifestyle-related factors and frailty. METHODS We examined the association between individual lifestyle factors (exercise, diet, sleep, alcohol, smoking and body composition), their sum at baseline, their change over the 17-year follow-up and the rate of change in frailty index values using linear mixed models in a cohort of 2,000 participants aged 57-69 years at baseline. RESULTS A higher number of healthy lifestyle-related factors at baseline was associated with lower levels of frailty but not with its rate of change from late midlife into old age. Participants who stopped exercising regularly (adjusted β × Time = 0.19, 95%CI = 0.10, 0.27) and who began experiencing sleeping difficulties (adjusted β × Time = 0.20, 95%CI = 0.10, 0.31) experienced more rapid increases in frailty from late midlife into old age. Conversely, those whose sleep improved (adjusted β × Time = -0.10, 95%CI = -0.23, -0.01) showed a slower increase in frailty from late midlife onwards. Participants letting go of lifestyle-related factors (decline by 3+ factors vs. no change) became more frail faster from late midlife into old age (adjusted β × Time = 0.16, 95% CI = 0.01, 0.30). CONCLUSIONS Lifestyle-related differences in frailty were already evident in late midlife and persisted into old age. Adopting one new healthy lifestyle-related factor had a small impact on a slightly less steeply increasing level of frailty. Maintaining regular exercise and sleeping habits may help prevent more rapid increases in frailty.
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Affiliation(s)
- Markus J Haapanen
- Public Health Research Program, Folkhälsan Research Center, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tuija M Mikkola
- Public Health Research Program, Folkhälsan Research Center, Helsinki, Finland
- Public Health Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center, Tampere University, Tampere, Finland
| | - Niko S Wasenius
- Public Health Research Program, Folkhälsan Research Center, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
| | - Eero Kajantie
- Public Health Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
- Clinical Medicine Research Unit, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Children’s Hospital, Helsinki University Hospital, Helsinki, Finland
| | - Johan G Eriksson
- Public Health Research Program, Folkhälsan Research Center, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Yong Loo Lin School of Medicine, Department of Obstetrics and Gynecology and Human Potential Translational Research Programme, National University Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Brenner Centre for Molecular Medicine, Singapore
| | - Mikaela B von Bonsdorff
- Public Health Research Program, Folkhälsan Research Center, Helsinki, Finland
- Gerontology Research Center and Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
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Ler P, Ploner A, Finkel D, Reynolds CA, Zhan Y, Jylhävä J, Dahl Aslan AK, Karlsson IK. Interplay of body mass index and metabolic syndrome: association with physiological age from midlife to late-life. GeroScience 2024; 46:2605-2617. [PMID: 38102440 PMCID: PMC10828240 DOI: 10.1007/s11357-023-01032-9] [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: 09/26/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023] Open
Abstract
Obesity and metabolic syndrome (MetS) share common pathophysiological characteristics with aging. To better understand their interplay, we examined how body mass index (BMI) and MetS jointly associate with physiological age, and if the associations changed from midlife to late-life. We used longitudinal data from 1,825 Swedish twins. Physiological age was measured as frailty index (FI) and functional aging index (FAI) and modeled independently in linear mixed-effects models adjusted for chronological age, sex, education, and smoking. We assessed curvilinear associations of BMI and chronological age with physiological age, and interactions between BMI, MetS, and chronological age. We found a significant three-way interaction between BMI, MetS, and chronological age on FI (p-interaction = 0·006), not FAI. Consequently, we stratified FI analyses by age: < 65, 65-85, and ≥ 85 years, and modeled FAI across ages. Except for FI at ages ≥ 85, BMI had U-shaped associations with FI and FAI, where BMI around 26-28 kg/m2 was associated with the lowest physiological age. MetS was associated with higher FI and FAI, except for FI at ages < 65, and modified the BMI-FI association at ages 65-85 (p-interaction = 0·02), whereby the association between higher BMI levels and FI was stronger in individuals with MetS. Age modified the MetS-FI association in ages ≥ 85, such that it was stronger at higher ages (p-interaction = 0·01). Low BMI, high BMI, and metabolic syndrome were associated with higher physiological age, contributing to overall health status among older individuals and potentially accelerating aging.
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Affiliation(s)
- Peggy Ler
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Solna, 171 65, Stockholm, Sweden.
| | - Alexander Ploner
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Solna, 171 65, Stockholm, Sweden
| | - Deborah Finkel
- Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA
- Institute of Gerontology, Jönköping University, Jönköping, Sweden
| | - Chandra A Reynolds
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Yiqiang Zhan
- School of Public Health, Sun Yat-Sen University, Shenzhen Campus, Shenzhen, Guandong, China
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Solna, 171 65, Stockholm, Sweden
- Faculty of Social Sciences, Unit of Health Sciences and Gerontology Research Center, University of Tampere, Tampere, Finland
| | | | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Solna, 171 65, Stockholm, Sweden
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Lopes De Oliveira T, Tang B, Bai G, Sjölander A, Jylhävä J, Finkel D, Pedersen NL, Hassing LB, Reynolds CA, Karlsson IK, Hägg S. Effects from medications on functional biomarkers of aging in three longitudinal studies of aging in Sweden. Aging Cell 2024:e14132. [PMID: 38426357 DOI: 10.1111/acel.14132] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 02/09/2024] [Accepted: 02/11/2024] [Indexed: 03/02/2024] Open
Abstract
Antihypertensive, lipid-lowering, and blood glucose-lowering drugs have slowed down the aging process in animal models. In humans, studies are limited, have short follow-up times, and show mixed results. Therefore, this study aimed to estimate the effects of commonly used medications on functional aging, cognitive function, and frailty. We included information on individuals from three Swedish longitudinal population-based studies collected between 1986 and 2014. Our exposures were the 21 most used groups of medications among individuals aged 65 years and older in the Swedish population in 2022. Functional aging index (n = 1191), cognitive function (n = 1094), and frailty index (n = 1361) were the outcomes of interest. To estimate the medication effects, we used a self-controlled analysis, where each individual is his/her own control, thereby adjusting for all time-stable confounders. The analysis was additionally adjusted for time-varying confounders (chronological age, Charlson Comorbidity Index, smoking, body mass index, and the number of drugs). The participants were 65.5-82.8 years at the first in-person assessment. Adrenergics/inhalants (effect size = 0.089) and lipid-modifying agents/plain (effect size = 0.082) were associated with higher values of cognitive function (improvement), and selective calcium channel blockers with mainly vascular effects (effect size = -0.129) were associated with lower values of the functional aging index (improvement). No beneficial effects were found on the frailty index. Adrenergics/inhalants, lipid-modifying agents/plain, and selective calcium channel blockers with mainly vascular effects may benefit functional biomarkers of aging. More research is needed to investigate their clinical value in preventing adverse aging outcomes.
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Affiliation(s)
- Thaís Lopes De Oliveira
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Neurobiology, Care Sciences and Society, Aging Research Center, Karolinska Institutet, Stockholm, Sweden
| | - Bowen Tang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ge Bai
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Women's and Children's Health, Uppsala Universitet, Uppsala, Sweden
| | - Arvid Sjölander
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Deborah Finkel
- School of Health and Welfare, Institute of Gerontology, Jönköping University, Jönköping, Sweden
- Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Linda B Hassing
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden
- Centre for Ageing and Health, University of Gothenburg, Gothenburg, Sweden
| | - Chandra A Reynolds
- Department of Psychology, The University of California at Riverside, Riverside, California, USA
- Department of Psychology and Neuroscience, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Mak JKL, Skovgaard AC, Nygaard M, Kananen L, Reynolds CA, Wang Y, Kuja-Halkola R, Karlsson IK, Pedersen NL, Hägg S, Soerensen M, Jylhävä J. Epigenome-wide analysis of frailty: Results from two European twin cohorts. Aging Cell 2024:e14135. [PMID: 38414347 DOI: 10.1111/acel.14135] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/11/2024] [Accepted: 02/17/2024] [Indexed: 02/29/2024] Open
Abstract
Epigenetics plays an important role in the aging process, but it is unclear whether epigenetic factors also influence frailty, an age-related state of physiological decline. In this study, we performed a meta-analysis of epigenome-wide association studies in four samples drawn from the Swedish Adoption/Twin Study of Aging (SATSA) and the Longitudinal Study of Aging Danish Twins (LSADT) to explore the association between DNA methylation and frailty. Frailty was defined using the frailty index (FI), and DNA methylation levels were measured in whole blood using Illumina's Infinium HumanMethylation450K and MethylationEPIC arrays. In the meta-analysis consisting of a total of 829 participants, we identified 589 CpG sites that were statistically significantly associated with either the continuous or categorical FI (false discovery rate <0.05). Many of these CpGs have previously been associated with age and age-related diseases. The identified sites were also largely directionally consistent in a longitudinal analysis using mixed-effects models in SATSA, where the participants were followed up to a maximum of 20 years. Moreover, we identified three differentially methylated regions within the MGRN1, MIR596, and TAPBP genes that have been linked to neuronal aging, tumor growth, and immune functions. Furthermore, our meta-analysis results replicated 34 of the 77 previously reported frailty-associated CpGs at p < 0.05. In conclusion, our findings demonstrate robust associations between frailty and DNA methylation levels in 589 novel CpGs, previously unidentified for frailty, and strengthen the role of neuronal/brain pathways in frailty.
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Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Asmus Cosmos Skovgaard
- The Danish Twin Registry and Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense M, Denmark
| | - Marianne Nygaard
- The Danish Twin Registry and Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense M, Denmark
| | - Laura Kananen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Chandra A Reynolds
- Institute for Behavioral Genetics, University of Colorado, Boulder, Colorado, USA
- Department of Psychology, University of California, Riverside, California, USA
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mette Soerensen
- The Danish Twin Registry and Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense M, Denmark
- Department of Clinical Genetics, Odense University Hospital, Odense C, Denmark
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
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Bednorz A, Mak JKL, Jylhävä J, Religa D. Use of Electronic Medical Records (EMR) in Gerontology: Benefits, Considerations and a Promising Future. Clin Interv Aging 2023; 18:2171-2183. [PMID: 38152074 PMCID: PMC10752027 DOI: 10.2147/cia.s400887] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 11/05/2023] [Indexed: 12/29/2023] Open
Abstract
Electronic medical records (EMRs) have many benefits in clinical research in gerontology, enabling data analysis, development of prognostic tools and disease risk prediction. EMRs also offer a range of advantages in clinical practice, such as comprehensive medical records, streamlined communication with healthcare providers, remote data access, and rapid retrieval of test results, ultimately leading to increased efficiency, enhanced patient safety, and improved quality of care in gerontology, which includes benefits like reduced medication use and better patient history taking and physical examination assessments. The use of artificial intelligence (AI) and machine learning (ML) approaches on EMRs can further improve disease diagnosis, symptom classification, and support clinical decision-making. However, there are also challenges related to data quality, data entry errors, as well as the ethics and safety of using AI in healthcare. This article discusses the future of EMRs in gerontology and the application of AI and ML in clinical research. Ethical and legal issues surrounding data sharing and the need for healthcare professionals to critically evaluate and integrate these technologies are also emphasized. The article concludes by discussing the challenges related to the use of EMRs in research as well as in their primary intended use, the daily clinical practice.
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Affiliation(s)
- Adam Bednorz
- John Paul II Geriatric Hospital, Katowice, Poland
- Institute of Psychology, Humanitas Academy, Sosnowiec, Poland
| | - Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Dorota Religa
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
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Li X, Ploner A, Wang Y, Mak JKL, Lu Y, Magnusson PKE, Jylhävä J, Hägg S. Rare functional variants in the CRP and G6PC genes modify the relationship between obesity and serum C-reactive protein in white British population. Mol Genet Genomic Med 2023; 11:e2255. [PMID: 37493001 PMCID: PMC10724514 DOI: 10.1002/mgg3.2255] [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: 01/10/2023] [Revised: 04/03/2023] [Accepted: 07/14/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND C-reactive protein (CRP) is a sensitive biomarker of inflammation with moderate heritability. The role of rare functional genetic variants in relation to serum CRP is understudied. We aimed to examine gene mutation burden of protein-altering (PA) and loss-of-function (LOF) variants in association with serum CRP, and to further explore the clinical relevance. METHODS We included 161,430 unrelated participants of European ancestry from the UK Biobank. Of the rare (minor allele frequency <0.1%) and functional variants, 1,776,249 PA and 266,226 LOF variants were identified. Gene-based burden tests, linear regressions, and logistic regressions were performed to identify the candidate mutations at the gene and variant levels, to estimate the potential interaction effect between the identified PA mutation and obesity, and to evaluate the relative risk of 16 CRP-associated diseases. RESULTS At the gene level, PA mutation burdens of the CRP (β = -0.685, p = 2.87e-28) and G6PC genes (β = 0.203, p = 1.50e-06) were associated with reduced and increased serum CRP concentration, respectively. At the variant level, seven PA alleles in the CRP gene decreased serum CRP, of which the per-allele effects were approximately three to seven times greater than that of a common variant in the same locus. The effects of obesity and central obesity on serum CRP concentration were smaller among the PA mutation carriers in the CRP (pinteraction = 0.008) and G6PC gene (pinteraction = 0.034) compared to the corresponding non-carriers. CONCLUSION PA mutation burdens in the CRP and G6PC genes are strongly associated with decreased serum CRP concentrations. As serum CRP and obesity are important predictors of cardiovascular risks in clinics, our observations suggest taking rare genetic factors into consideration might improve the delivery of precision medicine.
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Affiliation(s)
- Xia Li
- School of Public Health and Emergency ManagementSouthern University of Science and TechnologyShenzhenChina
- Shenzhen Key Laboratory of Cardiovascular Health and Precision MedicineSouthern University of Science and TechnologyShenzhenChina
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Alexander Ploner
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Jonathan K. L. Mak
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Yi Lu
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Social Sciences (Health Sciences) and Gerontology Research Center (GEREC)University of TampereTampereFinland
| | - Sara Hägg
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
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Kananen L, Molnár C, Ansker F, Kozlowska DJ, Hägg S, Jylhävä J, Religa D, Raaschou P. Anticoagulant treatment and COVID-19 mortality among older adults living in nursing homes in Sweden. Health Sci Rep 2023; 6:e1692. [PMID: 38028709 PMCID: PMC10644256 DOI: 10.1002/hsr2.1692] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/23/2023] [Indexed: 12/01/2023] Open
Abstract
Background Anticoagulants (AC) were introduced in March 2020 as standard of care in nursing home (NH) residents affected with COVID-19 in the Stockholm region, Sweden. ACs are proven to reduce the risk of complications and mortality from COVID-19 among patients of other ages and settings, but there is limited scientific evidence underpinning this practice in the NH setting. Methods This matched cohort study included 182 NH residents in the Stockholm Region diagnosed with COVID-19 in March-May 2020. The main exposure was any AC treatment. Exposed (n = 91), 49% prevalent (pre-COVID-19 diagnosis) AC and 51% incident AC were compared with unexposed controls (n = 91). The outcome was 28-days all-cause mortality after COVID-19 infection. The mortality odds ratios (OR) were assessed using logistic regression, adjusted for age, sex, multimorbidity, and mobility, also stratified by incident or prevalent AC-type, age group, and sex. Results Of the 182 individuals diagnosed with COVID-19 (median age 88 years, 68% women), 39% died within 28 days after diagnosis. Use of either incident or prevalent AC was associated with a reduced, adjusted 28-day mortality (OR[95% CI]: 0.31[0.16-0.62]). In stratified analyses, the association was significant in both age groups: 70-89 (OR: 0.37 [0.15-0.89]) and 90-99 years of age (OR: 0.22 [0.07-0.65]. In sex-stratified analysis, the AC-lowering effect was significant in women only (OR: 0.28[0.11-0.67]). In the analyses stratified by AC type, the mortality-lowering effect was observed for both prevalent AC (OR: 0.35[0.12-0.99]) and incident AC (OR: 0.29[0.11-0.76]). Conclusions Both prevalent and incident use of ACs in prophylactic dosing was associated with reduced 28-day mortality among older individuals with COVID-19 in a NH setting. The effect was seen across age-strata and in women. The findings present new insight in best practice for individuals diagnosed with COVID-19 in the NH setting.
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Affiliation(s)
- Laura Kananen
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetSolnaStockholmSweden
- Faculty of Social Sciences (Health Sciences), and Gerontology Research CenterTampere UniversityTampereFinland
- Faculty of Medicine and Health Technology, and Gerontology Research CenterTampere UniversityTampereFinland
| | - Christian Molnár
- Department of Neurobiology, Care Sciences and Society (NVS)Karolinska InstitutetStockholmSweden
- Familjeläkarna SÄBOFamiljeläkarna i SaltsjöbadenStockholmSweden
| | - Fredrik Ansker
- Familjeläkarna SÄBOFamiljeläkarna i SaltsjöbadenStockholmSweden
| | | | - Sara Hägg
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetSolnaStockholmSweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetSolnaStockholmSweden
- Faculty of Social Sciences (Health Sciences), and Gerontology Research CenterTampere UniversityTampereFinland
| | - Dorota Religa
- Department of Neurobiology, Care Sciences and Society (NVS)Karolinska InstitutetStockholmSweden
| | - Pauline Raaschou
- Department of Medicine Solna, Clinical Epidemiology Section & Clinical Pharmacology UnitKarolinska InstitutetSolnaStockholmSweden
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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] [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: 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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10
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Mak JKL, Karlsson IK, Tang B, Wang Y, Pedersen NL, Hägg S, Jylhävä J, Reynolds CA. Temporal dynamics of epigenetic aging and frailty from midlife to old age. J Gerontol A Biol Sci Med Sci 2023:glad251. [PMID: 37889476 DOI: 10.1093/gerona/glad251] [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: 08/24/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND DNA methylation-derived epigenetic clocks and frailty are well-established biological age measures capturing different aging processes. However, whether they are dynamically linked to each other across chronological age remains poorly understood. METHODS This analysis included 1,309 repeated measurements in 524 individuals aged 50 to 90 years from the Swedish Adoption/Twin Study of Aging. Frailty was measured using a validated 42-item frailty index (FI). Five epigenetic clocks were calculated, including four principal component (PC)-based clocks trained on chronological age (PCHorvathAge, PCHannumAge) and aging-related physiological conditions (PCPhenoAge, PCGrimAge), and a pace of aging clock (DunedinPACE). Using dual change score models, we examined the dynamic, bidirectional associations between each of the epigenetic clocks and the FI over age to test for potential causal associations. RESULTS The FI exhibited a nonlinear, accelerated increase across the older adulthood, whereas the epigenetic clocks mostly increased linearly with age. For PCHorvathAge, PCHannumAge, PCPhenoAge, and PCGrimAge, their associations with the FI were primarily due to correlated levels at age 50 but with no evidence of a dynamic longitudinal association. In contrast, we observed a unidirectional association between DunedinPACE and the FI, where a higher DunedinPACE predicted a subsequent increase in the FI, but not vice versa. CONCLUSION Our results highlight a temporal order between epigenetic aging and frailty such that changes in DunedinPACE precede changes in the FI. This potentially suggests that the pace of aging clock can be used as an early marker of the overall physiological decline at system level.
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Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Bowen Tang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Chandra A Reynolds
- Department of Psychology, University of California, Riverside, CA, USA
- Institute for Behavioral Genetics, University of Colorado Boulder, CO, USA
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11
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Bai G, Wang Y, Mak JKL, Ericsson M, Hägg S, Jylhävä J. Is Frailty Different in Younger Adults Compared to Old? Prevalence, Characteristics, and Risk Factors of Early-Life and Late-Life Frailty in Samples from Sweden and UK. Gerontology 2023; 69:1385-1393. [PMID: 37769628 DOI: 10.1159/000534131] [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: 01/03/2023] [Accepted: 09/11/2023] [Indexed: 10/03/2023] Open
Abstract
INTRODUCTION Although frailty is commonly considered as a syndrome of old individuals, recent studies show that it can affect younger adults, too. Whether and how frailty differs in younger adults compared to old is however unknown. To this end, we analyzed the prevalence, characteristics, and risk factors of early-life (aged <65) and late-life (aged ≥65) frailty. METHODS We analyzed individuals in the UK Biobank (N = 405,123) and Swedish Screening Across the Lifespan Twin (SALT; N = 43,641) study. Frailty index (FI) scores ≥0.21 were used to demarcate frailty. Characteristics of early-life versus late-life frailty were analyzed by collating the FI items (deficits) into domains and comparing the domain scores between younger and older frail individuals. Logistic regression was used to assess the risk factors of frailty. RESULTS The pooled prevalence rates of frailty were 10.3% (95% confidence interval [CI]: 2.7-32.7), 14.4% (95% CI: 4.5-37.2), 19.2% (95% CI: 2.5-68.5) in individuals aged ≤55, 55-64, 65-74, respectively. Younger frail adults (aged <65) had higher scores in immunological, mental wellbeing, and pain-related domains, whereas older frail adults (aged ≥65) had higher scores in cardiometabolic, cancer, musculoskeletal, and sensory-related domains. Higher age, female sex, smoking, lower alcohol consumption, lower education, obesity, overweight, low income, and maternal smoking were similarly associated with the risk of early-life and late-life frailty. CONCLUSION Frailty is prevalent also in younger age groups (aged <65) but differs in some of its characteristics from the old. The risk factors of frailty are nevertheless largely similar for early-life and late-life frailty.
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Affiliation(s)
- Ge Bai
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Malin Ericsson
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
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Mak JKL, Kananen L, Qin C, Kuja‐Halkola R, Tang B, Lin J, Wang Y, Jääskeläinen T, Koskinen S, Lu Y, Magnusson PKE, Hägg S, Jylhävä J. Unraveling the metabolic underpinnings of frailty using multicohort observational and Mendelian randomization analyses. Aging Cell 2023; 22:e13868. [PMID: 37184129 PMCID: PMC10410014 DOI: 10.1111/acel.13868] [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: 03/17/2023] [Revised: 04/26/2023] [Accepted: 04/29/2023] [Indexed: 05/16/2023] Open
Abstract
Identifying metabolic biomarkers of frailty, an age-related state of physiological decline, is important for understanding its metabolic underpinnings and developing preventive strategies. Here, we systematically examined 168 nuclear magnetic resonance-based metabolomic biomarkers and 32 clinical biomarkers for their associations with frailty. In up to 90,573 UK Biobank participants, we identified 59 biomarkers robustly and independently associated with the frailty index (FI). Of these, 34 associations were replicated in the Swedish TwinGene study (n = 11,025) and the Finnish Health 2000 Survey (n = 6073). Using two-sample Mendelian randomization, we showed that the genetically predicted level of glycoprotein acetyls, an inflammatory marker, was statistically significantly associated with an increased FI (β per SD increase = 0.37%, 95% confidence interval: 0.12-0.61). Creatinine and several lipoprotein lipids were also associated with increased FI, yet their effects were mostly driven by kidney and cardiometabolic diseases, respectively. Our findings provide new insights into the causal effects of metabolites on frailty and highlight the role of chronic inflammation underlying frailty development.
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Affiliation(s)
- Jonathan K. L. Mak
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Laura Kananen
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC)University of TampereTampereFinland
| | - Chenxi Qin
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Ralf Kuja‐Halkola
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Bowen Tang
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Jake Lin
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC)University of TampereTampereFinland
- Institute for Molecular Medicine Finland FIMM, Helsinki Institute of Life Science HiLIFE, University of HelsinkiHelsinkiFinland
| | - Yunzhang Wang
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Department of Clinical Sciences, Danderyd HospitalKarolinska InstitutetStockholmSweden
| | | | | | - Yi Lu
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Department of Global Public HealthKarolinska InstitutetStockholmSweden
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Sara Hägg
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC)University of TampereTampereFinland
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13
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Mak JKL, Religa D, Jylhävä J. Automated frailty scores: towards clinical implementation. Aging (Albany NY) 2023; undefined:204815. [PMID: 37294544 DOI: 10.18632/aging.204815] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 04/17/2023] [Indexed: 06/10/2023]
Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Dorota Religa
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
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14
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Haapanen M, Mikkola T, Kortelainen L, Jylhävä J, Wasenius N, Kajantie E, Eriksson J, von Bonsdorff M. Body Composition in Late Midlife as a Predictor of Accelerated Age-associated Deficit-accumulation From Late Midlife into Old Age: A Longitudinal Birth Cohort Study. J Gerontol A Biol Sci Med Sci 2023; 78:980-987. [PMID: 36434783 PMCID: PMC10235203 DOI: 10.1093/gerona/glac233] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [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: 07/02/2022] [Indexed: 09/26/2023] Open
Abstract
BACKGROUND Body mass index (BMI) may not be an optimal predictor of frailty as its constituents, lean and fat mass, may have opposite associations with frailty. METHODS A linear mixed model analysis was performed in the Helsinki Birth Cohort Study (n = 2 000) spanning from 57 to 84 years. A 39-item frailty index (FI) was calculated on three occasions over 17 years. Body composition in late midlife included BMI, percent body fat (%BF), waist-to-hip ratio (WHR), lean mass index (LMI), and fat mass index (FMI). RESULTS Mean FI levels increased by 0.28%/year among men and by 0.34%/year among women. Among women, per each kg/m2 higher BMI and each unit higher %BF the increases in FI levels per year were 0.013 percentage points (PP) steeper (95% CI = 0.004, 0.023) and 0.009 PP steeper (95% CI = 0.002, 0.016) from late midlife into old age. Among men, per each 0.1-unit greater WHR the increase in FI levels was 0.074 PP steeper per year (95% CI = -0.0004, 0.148). Cross-sectionally, greater FMI and LMI in late midlife were associated with higher FI levels but the direction of the association regarding LMI changed after adjustment for FMI. The categories "high FMI and high LMI" and "high FMI and low LMI" showed the highest FI levels relative to the category "low FMI and low LMI". CONCLUSIONS In late midlife, greater adiposity (%BF) among women and abdominal obesity (WHR) among men may predispose to higher levels of frailty from late midlife into old age. Greater lean mass alone may be protective of frailty, but not in the presence of high fat mass.
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Affiliation(s)
- Markus J Haapanen
- Folkhälsan Research Center, Helsinki, Finland
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tuija M Mikkola
- Folkhälsan Research Center, Helsinki, Finland
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Lauri Kortelainen
- Folkhälsan Research Center, Helsinki, Finland
- Department of Health and Social Management, University of Eastern Finland, Kuopio, Finland
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center, Tampere University, Tampere, Finland
| | - Niko S Wasenius
- Folkhälsan Research Center, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
| | - Eero Kajantie
- Department of Public Health and Welfare, Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- PEDEGO Research Unit, Medical Research Center Oulu, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Johan G Eriksson
- Folkhälsan Research Center, Helsinki, Finland
- Department of Obstetrics and Gynecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University Singapore, Singapore
| | - Mikaela B von Bonsdorff
- Folkhälsan Research Center, Helsinki, Finland
- Gerontology Research Center and Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
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15
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Mak JKL, McMurran CE, Kuja-Halkola R, Hall P, Czene K, Jylhävä J, Hägg S. Clinical biomarker-based biological aging and risk of cancer in the UK Biobank. Br J Cancer 2023:10.1038/s41416-023-02288-w. [PMID: 37120669 DOI: 10.1038/s41416-023-02288-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 04/14/2023] [Accepted: 04/18/2023] [Indexed: 05/01/2023] Open
Abstract
BACKGROUND Despite a clear link between aging and cancer, there has been inconclusive evidence on how biological age (BA) may be associated with cancer incidence. METHODS We studied 308,156 UK Biobank participants with no history of cancer at enrolment. Using 18 age-associated clinical biomarkers, we computed three BA measures (Klemera-Doubal method [KDM], PhenoAge, homeostatic dysregulation [HD]) and assessed their associations with incidence of any cancer and five common cancers (breast, prostate, lung, colorectal, and melanoma) using Cox proportional-hazards models. RESULTS A total of 35,426 incident cancers were documented during a median follow-up of 10.9 years. Adjusting for common cancer risk factors, 1-standard deviation (SD) increment in the age-adjusted KDM (hazard ratio = 1.04, 95% confidence interval = 1.03-1.05), age-adjusted PhenoAge (1.09, 1.07-1.10), and HD (1.02, 1.01-1.03) was significantly associated with a higher risk of any cancer. All BA measures were also associated with increased risks of lung and colorectal cancers, but only PhenoAge was associated with breast cancer risk. Furthermore, we observed an inverse association between BA measures and prostate cancer, although it was attenuated after removing glycated hemoglobin and serum glucose from the BA algorithms. CONCLUSIONS Advanced BA quantified by clinical biomarkers is associated with increased risks of any cancer, lung cancer, and colorectal cancer.
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Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Christopher E McMurran
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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16
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Tang B, Li X, Wang Y, Sjölander A, Johnell K, Thambisetty M, Ferrucci L, Reynolds CA, Finkel D, Jylhävä J, Pedersen NL, Hägg S. Longitudinal associations between use of antihypertensive, antidiabetic, and lipid-lowering medications and biological aging. GeroScience 2023:10.1007/s11357-023-00784-8. [PMID: 37032369 PMCID: PMC10400489 DOI: 10.1007/s11357-023-00784-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [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: 01/18/2023] [Accepted: 03/26/2023] [Indexed: 04/11/2023] Open
Abstract
Aging is a major risk factor for many chronic diseases. This study aimed to examine the effects of antihypertensive, lipid-lowering, and antidiabetic drugs on biological aging. We included 672 participants and 2746 repeated measurements from the Swedish Adoption/Twin Study of Aging. Self-reported medicine uses were categorized into antidiabetic, antihypertensive, and lipid-lowering drugs. A total of 12 biomarkers for biological aging (BA biomarkers) were included as outcomes. Conditional generalized estimating equations were applied conditioning on individuals to estimate the drug effect on BA biomarker level within the same person when using or not using the drug. Chronological age, body mass index, smoking status, number of multiple medication uses, blood pressure, blood glucose level, and apoB/apoA ratio were adjusted for as covariates in the model. Overall, using antihypertensive drugs was associated with a decrease in one DNA-methylation age (PCGrimAge: beta = - 0.39, 95%CI = - 0.67 to - 0.12). When looking into drug subcategories, calcium channel blockers (CCBs) were associated with a decrease in several DNA-methylation ages (PCHorvathAge beta = - 1.28, 95%CI = - 2.34 to - 0.21; PCSkin&bloodAge beta = - 1.34, 95%CI = - 2.61 to - 0.07; PCPhenoAge beta = - 1.74, 95%CI = - 2.58 to - 0.89; PCGrimAge beta = - 0.57, 95%CI = - 0.96 to - 0.17) and in functional biological ages (functional age index beta = - 2.18, 95%CI = - 3.65 to - 0.71; frailty index beta = - 1.31, 95%CI = - 2.43 to - 0.18). However, the results within other drug subcategories were inconsistent. Calcium channel blockers may decrease biological aging captured by the BA biomarkers measured at epigenetic and functional level. Future studies are warranted to confirm these effects and understand the underlying biological mechanisms.
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Affiliation(s)
- Bowen Tang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Xia Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | - Yunzhang Wang
- Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Solna, Sweden
| | - Arvid Sjölander
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Kristina Johnell
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Madhav Thambisetty
- Brain Aging and Behavior Section, National Institute on Aging, Baltimore, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, National Institute on Aging, Baltimore, USA
| | | | - Deborah Finkel
- Aging Research Network-Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden.
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17
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Ojalehto E, Zhan Y, Jylhävä J, Reynolds CA, Dahl Aslan AK, Karlsson IK. Genetically and environmentally predicted obesity in relation to cardiovascular disease: a nationwide cohort study. EClinicalMedicine 2023; 58:101943. [PMID: 37181410 PMCID: PMC10166783 DOI: 10.1016/j.eclinm.2023.101943] [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] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/17/2023] [Accepted: 03/17/2023] [Indexed: 05/16/2023] Open
Abstract
Background Evidence indicates that the adverse health effects of obesity differ between genetically and environmentally influenced obesity. We examined differences in the association between obesity and cardiovascular disease (CVD) between individuals with a genetically predicted low, medium, or high body mass index (BMI). Methods We used cohort data from Swedish twins born before 1959 who had BMI measured between the ages of 40-64 years (midlife) or at the age of 65 years or later (late-life), or both, and prospective CVD information from nationwide register linkage through 2016. A polygenic score for BMI (PGSBMI) was used to define genetically predicted BMI. Individuals missing BMI or covariate data, or diagnosed with CVD at first BMI measure, were excluded, leaving an analysis sample of 17,988 individuals. We applied Cox proportional hazard models to examine the association between BMI category and incident CVD, stratified by the PGSBMI. Co-twin control models were applied to adjust for genetic influences not captured by the PGSBMI. Findings Between 1984 and 2010, the 17,988 participants were enrolled in sub-studies of the Swedish Twin Registry. Midlife obesity was associated with a higher risk of CVD across all PGSBMI categories, but the association was stronger with genetically predicted lower BMI (hazard ratio from 1.55 to 2.08 for those with high and low PGSBMI, respectively). Within monozygotic twin pairs, the association did not differ by genetically predicted BMI, indicating genetic confounding not captured by the PGSBMI. Results were similar when obesity was measured in late-life, but suffered from low power. Interpretation Obesity was associated with CVD regardless of PGSBMI category, but obesity influenced by genetic predisposition (genetically predicted high BMI) was less harmful than obesity influenced by environmental factors (obesity despite genetically predicted low BMI). However, additional genetic factors, not captured by the PGSBMI, still influence the associations. Funding The Strategic Research Program in Epidemiology at Karolinska Institutet; Loo and Hans Osterman's Foundation; Foundation for Geriatric Diseases at Karolinska Institutet; the Swedish Research Council for Health, Working Life and Welfare; the Swedish Research Council; and the National Institutes of Health.
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Affiliation(s)
- Elsa Ojalehto
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yiqiang Zhan
- School of Public Health (Shenzhen), Sun Yat-Sen University, China
| | - 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
| | | | | | - Ida K. Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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18
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Mak JKL, Kuja-Halkola R, Wang Y, Hägg S, Jylhävä J. Can frailty scores predict the incidence of cancer? Results from two large population-based studies. GeroScience 2023:10.1007/s11357-023-00783-9. [PMID: 36997701 PMCID: PMC10400738 DOI: 10.1007/s11357-023-00783-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 03/24/2023] [Indexed: 04/01/2023] Open
Abstract
While chronological age is the single biggest risk factor for cancer, it is less clear whether frailty, an age-related state of physiological decline, may also predict cancer incidence. We assessed the associations of frailty index (FI) and frailty phenotype (FP) scores with the incidence of any cancer and five common cancers (breast, prostate, lung, colorectal, melanoma) in 453,144 UK Biobank (UKB) and 36,888 Screening Across the Lifespan Twin study (SALT) participants, who aged 38-73 years and had no cancer diagnosis at baseline. During a median follow-up of 10.9 and 10.7 years, 53,049 (11.7%) and 4,362 (11.8%) incident cancers were documented in UKB and SALT, respectively. Using multivariable-adjusted Cox models, we found a higher risk of any cancer in frail vs. non-frail UKB participants, when defined by both FI (hazard ratio [HR] = 1.22; 95% confidence interval [CI] = 1.17-1.28) and FP (HR = 1.16; 95% CI = 1.11-1.21). The FI in SALT similarly predicted risk of any cancer (HR = 1.31; 95% CI = 1.15-1.49). Moreover, frailty was predictive of lung cancer in UKB, although this association was not observed in SALT. Adding frailty scores to models including age, sex, and traditional cancer risk factors resulted in little improvement in C-statistics for most cancers. In a within-twin-pair analysis in SALT, the association between FI and any cancer was attenuated within monozygotic but not dizygotic twins, indicating that it may partly be explained by genetic factors. Our findings suggest that frailty scores are associated with the incidence of any cancer and lung cancer, although their clinical utility for predicting cancers may be limited.
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Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden.
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
- Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
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19
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Mak JKL, Kuja-Halkola R, Bai G, Hassing LB, Pedersen NL, Hägg S, Jylhävä J, Reynolds CA. Genetic and Environmental Influences on Longitudinal Frailty Trajectories From Adulthood into Old Age. J Gerontol A Biol Sci Med Sci 2023; 78:333-341. [PMID: 36124734 PMCID: PMC9951061 DOI: 10.1093/gerona/glac197] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [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: 05/07/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Frailty is a complex, dynamic geriatric condition, but limited evidence has shown how genes and environment may contribute to its longitudinal changes. We sought to investigate sources of individual differences in the longitudinal trajectories of frailty, considering potential selection bias when including a sample of oldest-old twins. METHODS Data were from 2 Swedish twin cohort studies: a younger cohort comprising 1 842 adults aged 29-96 years followed up to 15 waves, and an older cohort comprising 654 adults aged ≥79 years followed up to 5 waves. Frailty was measured using the frailty index (FI). Age-based latent growth curve models were used to examine longitudinal trajectories, and extended to a biometric analysis to decompose variability into genetic and environmental etiologies. RESULTS A bilinear model with an inflection point at age 75 best described the data, indicating a fourfold to fivefold faster FI increase after 75 years. Twins from the older cohort had significantly higher mean FI at baseline but slower rate of increase afterward. FI level at age 75 was moderately heritable in both men (42%) and women (55%). Genetic influences were relatively stable across age for men and increasing for women, although the most salient amplification in FI variability after age 75 was due to individual-specific environmental influences for both men and women; conclusions were largely consistent when excluding the older cohort. CONCLUSION Increased heterogeneity of frailty in late life is mainly attributable to environmental influences, highlighting the importance of targeting environmental risk factors to mitigate frailty in older adults.
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Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ge Bai
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Linda B Hassing
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden.,Centre for Ageing and Health, University of Gothenburg, Gothenburg, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Chandra A Reynolds
- Department of Psychology, University of California, Riverside, California, USA
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20
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Kananen L, Hong X, Annetorp M, Mak JKL, Jylhävä J, Eriksdotter M, Hägg S, Religa D. Health progression for Covid-19 survivors hospitalized in geriatric clinics in Sweden. PLoS One 2023; 18:e0283344. [PMID: 36947542 PMCID: PMC10032538 DOI: 10.1371/journal.pone.0283344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 03/07/2023] [Indexed: 03/23/2023] Open
Abstract
OBJECTIVE To analyse if the health progression of geriatric Covid-19 survivors three months after an acute Covid-19 infection was worse than in other geriatric patients. Specifically, we wanted to see if we could see distinct health profiles in the flow of re-admitted Covid-19 patients compared to re-admitted non-Covid-19 controls. DESIGN Matched cohort study. SETTING AND PARTICIPANTS Electronic medical records of geriatric patients hospitalised in geriatric clinics in Stockholm, Sweden, between March 2020 and January 2022. Patients readmitted three months after initial admission were selected for the analysis and Covid-19 survivors (n = 895) were compared to age-sex-Charlson comorbidity index (CCI)-matched non-Covid-19 controls (n = 2685). METHODS We assessed using binary logistic and Cox regression if a previous Covid-19 infection could be a risk factor for worse health progression indicated by the CCI, hospital frailty risk score (HFRS), mortality and specific comorbidities. RESULTS The patients were mostly older than 75 years and, already at baseline, had typically multiple comorbidities. The Covid-19 patients with readmission had mostly had their acute-phase infection in the 1st or 2nd pandemic waves before the vaccinations. The Covid-19 patients did not have worse health after three months compared to the matched controls according to the CCI (odds ratio, OR[95% confidence interval, CI] = 1.12[0.94-1.34]), HFRS (OR[95%CI] = 1.05[0.87-1.26]), 6-months (hazard ratio, HR[95%CI] = 1.04[0.70-1.52]) and 1-year-mortality risk (HR[95%CI] = 0.89[0.71-1.10]), adjusted for age, sex and health at baseline (the CCI and HFRS). CONCLUSIONS AND IMPLICATIONS The overall health progression of re-hospitalized geriatric Covid-19 survivors did not differ dramatically from other re-hospitalized geriatric patients with similar age, sex and health at baseline. Our results emphasize that Covid-19 was especially detrimental for geriatric patients in the acute-phase, but not in the later phase. Further studies including post-vaccination samples are needed.
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Affiliation(s)
- Laura Kananen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences), Gerontology Research Center, Tampere University, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Xu Hong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Martin Annetorp
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
- Research and Development Unit, Stockholms Sjukhem, Stockholm, Sweden
| | - Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences), Gerontology Research Center, Tampere University, Tampere, Finland
| | - Maria Eriksdotter
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Dorota Religa
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
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21
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Kananen L, Eriksdotter M, Boström A, Kivipelto M, Annetorp M, Metzner C, Bäck Jerlardtz V, Engström M, Johnson P, Lundberg L, Åkesson E, Sühl Öberg C, Hägg S, Religa D, Jylhävä J, Cederholm T. Body mass index and Mini Nutritional Assessment-Short Form as predictors of in-geriatric hospital mortality in older adults with COVID-19. Clin Nutr 2022; 41:2973-2979. [PMID: 34389208 PMCID: PMC8318666 DOI: 10.1016/j.clnu.2021.07.025] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [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: 05/10/2021] [Revised: 07/06/2021] [Accepted: 07/20/2021] [Indexed: 01/27/2023]
Abstract
BACKGROUND & AIMS Overweight and obesity have been consistently reported to carry an increased risk for poorer outcomes in coronavirus disease 2019 (COVID-19) in adults. Existing reports mainly focus on in-hospital and intensive care unit mortality in patient cohorts usually not representative of the population with the highest mortality, i.e. the very old and frail patients. Accordingly, little is known about the risk patterns related to body mass and nutrition in very old patients. Our aim was to assess the relationship between body mass index (BMI), nutritional status and in-geriatric hospital mortality among geriatric patients treated for COVID-19. As a reference, the analyses were performed also in patients treated for other diagnoses than COVID-19. METHODS We analyzed up to 10,031 geriatric patients with a median age of 83 years of which 1409 (14%) were hospitalized for COVID-19 and 8622 (86%) for other diagnoses in seven geriatric hospitals in the Stockholm region, Sweden during March 2020-January 2021. Data were available in electronic hospital records. The associations between 1) BMI and 2) nutritional status, assessed using the Mini-Nutritional Assessment - Short Form (MNA-SF) scale, and short-term in-geriatric hospital mortality were analyzed using logistic regression. RESULTS After adjusting for age, sex, comorbidity, polypharmacy, frailty and the wave of the pandemic (first vs. second), underweight defined as BMI<18.5 increased the risk of in-hospital mortality in COVID-19 patients (odds ratio [OR] = 2.30; confidence interval [CI] = 1.17-4.31). Overweight and obesity were not associated with in-hospital mortality. Malnutrition; i.e. MNA-SF 0-7 points, increased the risk of in-hospital mortality in patients treated for COVID-19 (OR = 2.03; CI = 1.16-3.68) and other causes (OR = 6.01; CI = 2.73-15.91). CONCLUSIONS Our results indicate that obesity is not a risk factor for very old patients with COVID-19, but emphasize the role of underweight and malnutrition for in-hospital mortality in geriatric patients with COVID-19.
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Affiliation(s)
- L. Kananen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,Faculty of Social Sciences (Health Sciences), Gerontology Research Center, Tampere University, Tampere, Finland,Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland,Corresponding author. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - M. Eriksdotter
- Division Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - A.M. Boström
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden,Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden,Research and Development Unit, Stockholms Sjukhem, Stockholm, Sweden
| | - M. Kivipelto
- Division Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden,Research and Development Unit, Stockholms Sjukhem, Stockholm, Sweden
| | - M. Annetorp
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - C. Metzner
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - V. Bäck Jerlardtz
- Department of Geriatric Medicine, Jakobsbergsgeriatriken, Stockholm, Sweden
| | - M. Engström
- Department of Geriatric Medicine, Sabbatsbergsgeriatriken, Stockholm, Sweden
| | - P. Johnson
- Department of Geriatric Medicine, Capio Geriatrik Nacka AB, Nacka, Sweden
| | - L.G. Lundberg
- Department of Geriatric Medicine, Dalengeriatriken Aleris Närsjukvård AB, Stockholm, Sweden
| | - E. Åkesson
- Research and Development Unit, Stockholms Sjukhem, Stockholm, Sweden
| | - C. Sühl Öberg
- Department of Geriatric Medicine, Handengeriatriken, Aleris Närsjukvård AB, Stockholm, Sweden
| | - S. Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - D. Religa
- Division Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - J. Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,Faculty of Social Sciences (Health Sciences), Gerontology Research Center, Tampere University, Tampere, Finland
| | - T. Cederholm
- Division Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden,Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
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22
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Mak JKL, Eriksdotter M, Annetorp M, Kuja-Halkola R, Kananen L, Boström AM, Kivipelto M, Metzner C, Bäck Jerlardtz V, Engström M, Johnson P, Lundberg LG, Åkesson E, Sühl Öberg C, Olsson M, Cederholm T, Hägg S, Religa D, Jylhävä J. Two Years with COVID-19: The Electronic Frailty Index Identifies High-Risk Patients in the Stockholm GeroCovid Study. Gerontology 2022; 69:396-405. [PMID: 36450240 PMCID: PMC9747746 DOI: 10.1159/000527206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/25/2022] [Indexed: 12/05/2022] Open
Abstract
<b><i>Introduction:</i></b> Frailty, a measure of biological aging, has been linked to worse COVID-19 outcomes. However, as the mortality differs across the COVID-19 waves, it is less clear whether a medical record-based electronic frailty index (eFI) that we have previously developed for older adults could be used for risk stratification in hospitalized COVID-19 patients. <b><i>Objectives:</i></b> The aim of the study was to examine the association of frailty with mortality, readmission, and length of stay in older COVID-19 patients and to compare the predictive accuracy of the eFI to other frailty and comorbidity measures. <b><i>Methods:</i></b> This was a retrospective cohort study using electronic health records (EHRs) from nine geriatric clinics in Stockholm, Sweden, comprising 3,980 COVID-19 patients (mean age 81.6 years) admitted between March 2020 and March 2022. Frailty was assessed using a 48-item eFI developed for Swedish geriatric patients, the Clinical Frailty Scale, and the Hospital Frailty Risk Score. Comorbidity was measured using the Charlson Comorbidity Index. We analyzed in-hospital mortality and 30-day readmission using logistic regression, 30-day and 6-month mortality using Cox regression, and the length of stay using linear regression. Predictive accuracy of the logistic regression and Cox models was evaluated by area under the receiver operating characteristic curve (AUC) and Harrell’s C-statistic, respectively. <b><i>Results:</i></b> Across the study period, the in-hospital mortality rate decreased from 13.9% in the first wave to 3.6% in the latest (Omicron) wave. Controlling for age and sex, a 10% increment in the eFI was significantly associated with higher risks of in-hospital mortality (odds ratio = 2.95; 95% confidence interval = 2.42–3.62), 30-day mortality (hazard ratio [HR] = 2.39; 2.08–2.74), 6-month mortality (HR = 2.29; 2.04–2.56), and a longer length of stay (β-coefficient = 2.00; 1.65–2.34) but not with 30-day readmission. The association between the eFI and in-hospital mortality remained robust across the waves, even after the vaccination rollout. Among all measures, the eFI had the best discrimination for in-hospital (AUC = 0.780), 30-day (Harrell’s C = 0.733), and 6-month mortality (Harrell’s C = 0.719). <b><i>Conclusion:</i></b> An eFI based on routinely collected EHRs can be applied in identifying high-risk older COVID-19 patients during the continuing pandemic.
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Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,
| | - Maria Eriksdotter
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Martin Annetorp
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Laura Kananen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Anne-Marie Boström
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
- Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Research and Development Unit, Stockholms Sjukhem, Stockholm, Sweden
| | - Miia Kivipelto
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Carina Metzner
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | | | - Malin Engström
- Department of Geriatric Medicine, Sabbatsbergsgeriatriken, Stockholm, Sweden
| | - Peter Johnson
- Department of Geriatric Medicine, Capio Geriatrik Nacka AB, Nacka, Sweden
| | - Lars Göran Lundberg
- Department of Geriatric Medicine, Dalengeriatriken Aleris Närsjukvård AB, Stockholm, Sweden
| | - Elisabet Åkesson
- Research and Development Unit, Stockholms Sjukhem, Stockholm, Sweden
- Division of Neurogeriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Carina Sühl Öberg
- Department of Geriatric Medicine, Handengeriatriken, Aleris Närsjukvård AB, Stockholm, Sweden
| | - Maria Olsson
- Department of Geriatric Medicine, Capio Geriatrik Löwet, Stockholm, Sweden
- Department of Geriatric Medicine, Capio Geriatrik Sollentuna, Stockholm, Sweden
| | - Tommy Cederholm
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Dorota Religa
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
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23
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Marttila S, Tamminen H, Rajić S, Mishra PP, Lehtimäki T, Raitakari O, Kähönen M, Kananen L, Jylhävä J, Hägg S, Delerue T, Peters A, Waldenberger M, Kleber ME, März W, Luoto R, Raitanen J, Sillanpää E, Laakkonen EK, Heikkinen A, Ollikainen M, Raitoharju E. Methylation status of VTRNA2-1/ nc886 is stable across populations, monozygotic twin pairs and in majority of tissues. Epigenomics 2022; 14:1105-1124. [PMID: 36200237 DOI: 10.2217/epi-2022-0228] [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] [Indexed: 11/21/2022] Open
Abstract
Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.
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Affiliation(s)
- Saara Marttila
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Gerontology Research Center, Tampere University, Tampere, 33014, Finland
| | - Hely Tamminen
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sonja Rajić
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku & Turku University Hospital, Turku, 20014, Finland.,Research Centre of Applied & Preventive Cardiovascular Medicine, University of Turku, Turku, 20014, Finland.,Department of Clinical Physiology & Nuclear Medicine, Turku University Hospital, Turku, 20014, Finland
| | - Mika Kähönen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Department of Clinical Physiology, Tampere University Hospital, Tampere, 33521, Finland
| | - Laura Kananen
- Faculty of Medicine & Health Technology, & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520,Finland.,Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Juulia Jylhävä
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sara Hägg
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,Competence Cluster for Nutrition & Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, 07743, Germany.,SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Augsburg, 86156, Germany.,Clinical Institute of Medical & Chemical Laboratory Diagnostics, Medical University of Graz, Graz, 8010, Austria
| | - Riitta Luoto
- The Social Insurance Institute of Finland (Kela), Helsinki, 00250, Finland.,The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland
| | - Jani Raitanen
- The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland.,Faculty of Social Sciences (Health Sciences), Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Elina Sillanpää
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland.,Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Eija K Laakkonen
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Emma Raitoharju
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
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24
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Kochar B, Jylhävä J, Söderling J, Ritchie CS, Ludvigsson JF, Khalili H, Olén O. Prevalence and Implications of Frailty in Older Adults With Incident Inflammatory Bowel Diseases: A Nationwide Cohort Study. Clin Gastroenterol Hepatol 2022; 20:2358-2365.e11. [PMID: 34999206 PMCID: PMC9294971 DOI: 10.1016/j.cgh.2022.01.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 12/20/2021] [Accepted: 01/02/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND AND AIMS We aimed to compare the risk of frailty in older adults with incident inflammatory bowel disease (IBD) and matched non-IBD comparators and assess the association between frailty and future hospitalizations and mortality. METHODS In a cohort of patients with incident IBD ≥60 years of age from 2007 to 2016 in Sweden identified using nationwide registers, we defined frailty using Hospital Frailty Risk Score. We compared prevalence of frailty in patients with IBD with age, sex, place of residency- and calendar year-matched population comparators. In the IBD cohort, we used Cox proportional hazards modeling to examine the associations between frailty risk and hospitalizations or mortality. RESULTS We identified 10,590 patients with IBD, 52% female with a mean age of 71 years of age, matched to 103,398 population-based comparators. Among patients with IBD, 39% had no risk for frailty, 49% had low risk for frailty, and 12% had higher risk for frailty. Mean Hospital Frailty Risk Score was 1.9 in IBD and 0.9 in matched comparators (P < .01). Older adults with IBD at higher risk for frailty had a 20% greater risk for mortality at 3 years compared with those who were not frail. Compared with nonfrail older patients with IBD, patients at higher risk for frailty had increased mortality (hazard ratio [HR], 3.22, 95% confidence interval [CI], 2.86-3.61), all-cause hospitalization (HR, 2.42; 95% CI, 2.24-2.61), and IBD-related hospitalization (HR, 1.50; 95% CI, 1.35-1.66). These associations were not attenuated after adjusting for comorbidities. CONCLUSIONS Frailty is more prevalent in older adults with IBD than in matched comparators. Among older patients with IBD, frailty is associated with increased risk for hospitalizations and mortality.
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Affiliation(s)
- Bharati Kochar
- Division of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts; Clinical Translational Epidemiology Unit, Mongan Institute, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Center for Aging and Serious Illness, Mongan Institute, Boston, Massachusetts
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jonas Söderling
- Division of Palliative Care and Geriatric Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Christine S Ritchie
- Harvard Medical School, Boston, Massachusetts; Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet Stockholm, Sweden; Center for Aging and Serious Illness, Mongan Institute, Boston, Massachusetts
| | - Jonas F Ludvigsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Pediatrics, Örebro University Hospital, Örebro, Sweden; Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom; Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Hamed Khalili
- Division of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts; Clinical Translational Epidemiology Unit, Mongan Institute, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.
| | - Ola Olén
- Division of Palliative Care and Geriatric Medicine, Massachusetts General Hospital, Boston, Massachusetts; Department of Pediatric Gastroenterology and Nutrition, Sachs' Children and Youth Hospital, Stockholm, Sweden; Department of Clinical Science and Education, Karolinska Institutet, Stockholm, Sweden
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25
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Kananen L, Hurme M, Bürkle A, Moreno-Villanueva M, Bernhardt J, Debacq-Chainiaux F, Grubeck-Loebenstein B, Malavolta M, Basso A, Piacenza F, Collino S, Gonos ES, Sikora E, Gradinaru D, Jansen EHJM, Dollé MET, Salmon M, Stuetz W, Weber D, Grune T, Breusing N, Simm A, Capri M, Franceschi C, Slagboom E, Talbot D, Libert C, Raitanen J, Koskinen S, Härkänen T, Stenholm S, Ala-Korpela M, Lehtimäki T, Raitakari OT, Ukkola O, Kähönen M, Jylhä M, Jylhävä J. Circulating cell-free DNA in health and disease - the relationship to health behaviours, ageing phenotypes and metabolomics. GeroScience 2022; 45:85-103. [PMID: 35864375 PMCID: PMC9886738 DOI: 10.1007/s11357-022-00590-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 05/06/2022] [Indexed: 02/03/2023] Open
Abstract
Circulating cell-free DNA (cf-DNA) has emerged as a promising biomarker of ageing, tissue damage and cellular stress. However, less is known about health behaviours, ageing phenotypes and metabolic processes that lead to elevated cf-DNA levels. We sought to analyse the relationship of circulating cf-DNA level to age, sex, smoking, physical activity, vegetable consumption, ageing phenotypes (physical functioning, the number of diseases, frailty) and an extensive panel of biomarkers including blood and urine metabolites and inflammatory markers in three human cohorts (N = 5385; 17-82 years). The relationships were assessed using correlation statistics, and linear and penalised regressions (the Lasso), also stratified by sex.cf-DNA levels were significantly higher in men than in women, and especially in middle-aged men and women who smoke, and in older more frail individuals. Correlation statistics of biomarker data showed that cf-DNA level was higher with elevated inflammation (C-reactive protein, interleukin-6), and higher levels of homocysteine, and proportion of red blood cells and lower levels of ascorbic acid. Inflammation (C-reactive protein, glycoprotein acetylation), amino acids (isoleucine, leucine, tyrosine), and ketogenesis (3-hydroxybutyrate) were included in the cf-DNA level-related biomarker profiles in at least two of the cohorts.In conclusion, circulating cf-DNA level is different by sex, and related to health behaviour, health decline and metabolic processes common in health and disease. These results can inform future studies where epidemiological and biological pathways of cf-DNA are to be analysed in details, and for studies evaluating cf-DNA as a potential clinical marker.
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Affiliation(s)
- Laura Kananen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. .,Faculty of Social Sciences (Health Sciences), and Gerontology Research Center, Tampere University, Tampere, Finland. .,Faculty of Medicine and Health Technology, and Gerontology Research Center, Tampere University, Tampere, Finland.
| | - Mikko Hurme
- grid.502801.e0000 0001 2314 6254Faculty of Medicine and Health Technology, and Gerontology Research Center, Tampere University, Tampere, Finland
| | - Alexander Bürkle
- grid.9811.10000 0001 0658 7699Molecular Toxicology Group, University of Konstanz, Konstanz, Germany
| | - Maria Moreno-Villanueva
- grid.9811.10000 0001 0658 7699Molecular Toxicology Group, University of Konstanz, Konstanz, Germany
| | | | - Florence Debacq-Chainiaux
- grid.6520.10000 0001 2242 8479URBC-Narilis, University of Namur, Rue de Bruxelles, 61, B-5000 Namur, Belgium
| | - Beatrix Grubeck-Loebenstein
- grid.5771.40000 0001 2151 8122Research Institute for Biomedical Aging Research, University of Innsbruck, Rennweg, 10, 6020 Innsbruck, Austria
| | - Marco Malavolta
- Advanced Technology Center for Aging Research, Scientific Technological Area, IRCCS INRCA, Ancona, Italy
| | - Andrea Basso
- Advanced Technology Center for Aging Research, Scientific Technological Area, IRCCS INRCA, Ancona, Italy
| | - Francesco Piacenza
- Advanced Technology Center for Aging Research, Scientific Technological Area, IRCCS INRCA, Ancona, Italy
| | - Sebastiano Collino
- grid.5333.60000000121839049Nestlé Research, Nestlé Institute of Health Sciences, EPFL Innovation Park, 1015 Lausanne, Switzerland
| | - Efstathios S. Gonos
- grid.22459.380000 0001 2232 6894Institute of Biology, Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece
| | - Ewa Sikora
- grid.419305.a0000 0001 1943 2944Laboratory of the Molecular Bases of Ageing, Nencki Institute of Experimental Biology, Polish Academy of Sciences, 3 Pasteur street, 02-093 Warsaw, Poland
| | - Daniela Gradinaru
- grid.8194.40000 0000 9828 7548Department of Biochemistry, Faculty of Pharmacy, “Carol Davila” University of Medicine and Pharmacy, 020956 Bucharest, Romania
| | - Eugene H. J. M. Jansen
- grid.31147.300000 0001 2208 0118National Institute for Public Health and the Environment (RIVM), Centre for Health Protection, P.O. Box 1, 3720 BA Bilthoven, The Netherlands
| | - Martijn E. T. Dollé
- grid.31147.300000 0001 2208 0118National Institute for Public Health and the Environment (RIVM), Centre for Health Protection, P.O. Box 1, 3720 BA Bilthoven, The Netherlands
| | - Michel Salmon
- grid.425994.7Straticell, Science Park Crealys, Rue Jean Sonet 10, 5032 Les Isnes, Belgium
| | - Wolfgang Stuetz
- grid.9464.f0000 0001 2290 1502Institute of Nutritional Sciences (140), University of Hohenheim, 70593 Stuttgart, Germany
| | - Daniela Weber
- grid.418213.d0000 0004 0390 0098Department of Molecular Toxicology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany
| | - Tilman Grune
- grid.418213.d0000 0004 0390 0098Department of Molecular Toxicology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany ,grid.10420.370000 0001 2286 1424Department of Physiological Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria ,grid.9464.f0000 0001 2290 1502Institute of Nutritional Medicine (180), University of Hohenheim, 70593 Stuttgart, Germany
| | - Nicolle Breusing
- grid.9464.f0000 0001 2290 1502Institute of Nutritional Medicine (180), University of Hohenheim, 70593 Stuttgart, Germany
| | - Andreas Simm
- grid.461820.90000 0004 0390 1701Department of Cardiothoracic Surgery, University Hospital Halle, Ernst-Grube Str. 40, 06120 Halle (Saale), Germany
| | - Miriam Capri
- grid.6292.f0000 0004 1757 1758DIMES- Department of Experimental, Diagnostic and Specialty Medicine,
Interdepartmental Center “Alma Mater Research Institute On Global Challenges and Climate Change (Alma Climate)”,
Alma Mater Studiorum, University of Bologna, 40126 Bologna, Italy
| | - Claudio Franceschi
- grid.6292.f0000 0004 1757 1758DIMES- Department of Experimental, Diagnostic and Specialty Medicine,
Interdepartmental Center “Alma Mater Research Institute On Global Challenges and Climate Change (Alma Climate)”,
Alma Mater Studiorum, University of Bologna, 40126 Bologna, Italy
| | - Eline Slagboom
- grid.10419.3d0000000089452978Section of Molecular Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Duncan Talbot
- Unilever Science and Technology, Beauty and Personal Care, Sharnbrook, UK
| | - Claude Libert
- grid.11486.3a0000000104788040Center for Inflammation Research, VIB, Ghent, Belgium ,grid.5342.00000 0001 2069 7798Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Jani Raitanen
- grid.502801.e0000 0001 2314 6254Faculty of Social Sciences (Health Sciences), and Gerontology Research Center, Tampere University, Tampere, Finland
| | - Seppo Koskinen
- grid.14758.3f0000 0001 1013 0499National Institute for Health and Welfare, Helsinki, Finland
| | - Tommi Härkänen
- grid.14758.3f0000 0001 1013 0499National Institute for Health and Welfare, Helsinki, Finland
| | - Sari Stenholm
- grid.1374.10000 0001 2097 1371Department of Public Health, University of Turku and Turku University Hospital, Turku, Finland ,grid.1374.10000 0001 2097 1371Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Mika Ala-Korpela
- grid.10858.340000 0001 0941 4873Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland ,grid.10858.340000 0001 0941 4873Center for Life Course Health Research, University of Oulu, Oulu, Finland ,grid.9668.10000 0001 0726 2490NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Terho Lehtimäki
- grid.502801.e0000 0001 2314 6254Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland ,grid.502801.e0000 0001 2314 6254Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland ,grid.511163.10000 0004 0518 4910Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Olli T. Raitakari
- grid.1374.10000 0001 2097 1371Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland ,grid.1374.10000 0001 2097 1371Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland ,grid.410552.70000 0004 0628 215XDepartment of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Olavi Ukkola
- grid.10858.340000 0001 0941 4873Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Mika Kähönen
- grid.502801.e0000 0001 2314 6254Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland ,grid.502801.e0000 0001 2314 6254Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland ,grid.412330.70000 0004 0628 2985Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Marja Jylhä
- grid.502801.e0000 0001 2314 6254Faculty of Social Sciences (Health Sciences), and Gerontology Research Center, Tampere University, Tampere, Finland
| | - Juulia Jylhävä
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden ,grid.502801.e0000 0001 2314 6254Faculty of Social Sciences (Health Sciences), and Gerontology Research Center, Tampere University, Tampere, Finland
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26
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Mak JKL, Hägg S, Eriksdotter M, Annetorp M, Kuja-Halkola R, Kananen L, Boström AM, Kivipelto M, Metzner C, Bäck Jerlardtz V, Engström M, Johnson P, Lundberg LG, Åkesson E, Öberg CS, Olsson M, Cederholm T, Jylhävä J, Religa D. Development of an electronic frailty index for hospitalized older adults in Sweden. J Gerontol A Biol Sci Med Sci 2022; 77:2311-2319. [PMID: 35303746 PMCID: PMC9678204 DOI: 10.1093/gerona/glac069] [Citation(s) in RCA: 6] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Frailty assessment in the Swedish health system relies on the Clinical Frailty Scale (CFS), but it requires training, in-person evaluation, and is often missing in medical records. We aimed to develop an electronic frailty index (eFI) from routinely collected electronic health records (EHRs) and assess its association with adverse outcomes in hospitalized older adults. METHODS EHRs were extracted for 18,225 patients with unplanned admissions between 1 March 2020 and 17 June 2021 from nine geriatric clinics in Stockholm, Sweden. A 48-item eFI was constructed using diagnostic codes, functioning and other health indicators, and laboratory data. The CFS, Hospital Frailty Risk Score, and Charlson Comorbidity Index were used for comparative assessment of the eFI. We modelled in-hospital mortality and 30-day readmission using logistic regression; 30-day and 6-month mortality using Cox regression; and length of stay using linear regression. RESULTS 13,188 patients were included in analyses (mean age 83.1 years). A 0.03 increment in the eFI was associated with higher risks of in-hospital (odds ratio: 1.65; 95% confidence interval: 1.54-1.78), 30-day (hazard ratio [HR]: 1.43; 1.38-1.48), and 6-month mortality (HR: 1.34; 1.31-1.37) adjusted for age and sex. Of the frailty and comorbidity measures, the eFI had the highest area under receiver operating characteristic curve for in-hospital mortality of 0.813. Higher eFI was associated with longer length of stay, but had a rather poor discrimination for 30-day readmission. CONCLUSIONS An EHR-based eFI has robust associations with adverse outcomes, suggesting that it can be used in risk stratification in hospitalized older adults.
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Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Maria Eriksdotter
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Martin Annetorp
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Laura Kananen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Anne-Marie Boström
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden.,Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Research and Development Unit, Stockholms Sjukhem, Stockholm, Sweden
| | - Miia Kivipelto
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Carina Metzner
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | | | - Malin Engström
- Department of Geriatric Medicine, Sabbatsbergsgeriatriken, Stockholm, Sweden
| | - Peter Johnson
- Department of Geriatric Medicine, Capio Geriatrik Nacka AB, Nacka, Sweden
| | - Lars Göran Lundberg
- Department of Geriatric Medicine, Dalengeriatriken Aleris Närsjukvård AB, Stockholm, Sweden
| | - Elisabet Åkesson
- Research and Development Unit, Stockholms Sjukhem, Stockholm, Sweden.,Division of Neurogeriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Carina Sühl Öberg
- Department of Geriatric Medicine, Handengeriatriken, Aleris Närsjukvård AB, Stockholm, Sweden
| | - Maria Olsson
- Department of Geriatric Medicine, Capio Geriatrik Löwet, Stockholm, Sweden.,Department of Geriatric Medicine, Capio Geriatrik Sollentuna, Stockholm, Sweden
| | - Tommy Cederholm
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden.,Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Dorota Religa
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
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27
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Haapanen MJ, Jylhävä J, Kortelainen L, Mikkola TM, Salonen M, Wasenius NS, Kajantie E, Eriksson JG, von Bonsdorff MB. Early life factors as predictors of age-associated deficit accumulation across 17 years from midlife into old age. J Gerontol A Biol Sci Med Sci 2022; 77:2281-2287. [PMID: 35018457 DOI: 10.1093/gerona/glac007] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [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: 10/01/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Early life exposures have been associated with the risk of frailty in old age. We investigated whether early life exposures predict the level and rate of change in a frailty index (FI) from midlife into old age. METHODS A linear mixed model analysis was performed using data from three measurement occasions over 17 years in participants from the Helsinki Birth Cohort Study (n=2000) aged 57-84 years. A 41-item FI was calculated on each occasion. Information on birth size, maternal body mass index (BMI), growth in infancy and childhood, childhood socioeconomic status (SES), and early life stress (wartime separation from both parents), was obtained from registers and healthcare records. RESULTS At age 57 years the mean FI level was 0.186 and the FI levels increased by 0.34 percent/year from midlife into old age. Larger body size at birth associated with a slower increase in FI levels from midlife into old age. Per 1kg greater birth weight the increase in FI levels per year was -0.087 percentage points slower (95% CI=-0.163, -0.011; p=0.026). Higher maternal BMI was associated with a higher offspring FI level in midlife and a slower increase in FI levels into old age. Larger size, faster growth from infancy to childhood, and low SES in childhood were all associated with a lower FI level in midlife but not with its rate of change. CONCLUSIONS Early life factors seem to contribute to disparities in frailty from midlife into old age. Early life factors may identify groups that could benefit from frailty prevention, optimally initiated early in life.
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Affiliation(s)
- Markus J Haapanen
- Folkhälsan Research Center, Helsinki, Finland.,Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Faculty of Social Sciences (Health Sciences) and Gerontology Research Center, Tampere University, Tampere, Finland
| | | | - Tuija M Mikkola
- Folkhälsan Research Center, Helsinki, Finland.,Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Minna Salonen
- Department of Public Health and Welfare, Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Niko S Wasenius
- Folkhälsan Research Center, Helsinki, Finland.,Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
| | - Eero Kajantie
- Department of Public Health and Welfare, Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland.,PEDEGO Research Unit, Medical Research Center Oulu, Oulu University Hospital, University of Oulu, Oulu, Finland.,Children's Hospital, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.,Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Johan G Eriksson
- Folkhälsan Research Center, Helsinki, Finland.,Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland.,Yong Loo Lin School of Medicine, Department of obstetrics and gynecology and Human Potential Translational Research Programme, National University Singapore, Singapore.,Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Mikaela B von Bonsdorff
- Folkhälsan Research Center, Helsinki, Finland.,Gerontology Research Center and Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
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Karlsson IK, Zhan Y, Wang Y, Li X, Jylhävä J, Hägg S, Dahl Aslan AK, Gatz M, Pedersen NL, Reynolds CA. Adiposity and the risk of dementia: mediating effects from inflammation and lipid levels. Eur J Epidemiol 2022; 37:1261-1271. [PMID: 36192662 PMCID: PMC9792412 DOI: 10.1007/s10654-022-00918-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 09/18/2022] [Indexed: 12/31/2022]
Abstract
While midlife adiposity is a risk factor for dementia, adiposity in late-life appears to be associated with lower risk. What drives the associations is poorly understood, especially the inverse association in late-life. Using results from genome-wide association studies, we identified inflammation and lipid metabolism as biological pathways involved in both adiposity and dementia. To test if these factors mediate the effect of midlife and/or late-life adiposity on dementia, we then used cohort data from the Swedish Twin Registry, with measures of adiposity and potential mediators taken in midlife (age 40-64, n = 5999) or late-life (age 65-90, n = 7257). Associations between body-mass index (BMI), waist-hip ratio (WHR), C-reactive protein (CRP), lipid levels, and dementia were tested in survival and mediation analyses. Age was used as the underlying time scale, and sex and education included as covariates in all models. Fasting status was included as a covariate in models of lipids. One standard deviation (SD) higher WHR in midlife was associated with 25% (95% CI 2-52%) higher dementia risk, with slight attenuation when adjusting for BMI. No evidence of mediation through CRP or lipid levels was present. After age 65, one SD higher BMI, but not WHR, was associated with 8% (95% CI 1-14%) lower dementia risk. The association was partly mediated by higher CRP, and suppressed when high-density lipoprotein levels were low. In conclusion, the negative effects of midlife adiposity on dementia risk were driven directly by factors associated with body fat distribution, with no evidence of mediation through inflammation or lipid levels. There was an inverse association between late-life adiposity and dementia risk, especially where the body's inflammatory response and lipid homeostasis is intact.
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Affiliation(s)
- Ida K. Karlsson
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 1177 Stockholm, Sweden ,grid.118888.00000 0004 0414 7587Aging Research Network – Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Yiqiang Zhan
- grid.12981.330000 0001 2360 039XSchool of Public Health, Sun Yat-Sen University, Shenzhen, China
| | - Yunzhang Wang
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 1177 Stockholm, Sweden
| | - Xia Li
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 1177 Stockholm, Sweden
| | - Juulia Jylhävä
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 1177 Stockholm, Sweden
| | - Sara Hägg
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 1177 Stockholm, Sweden
| | - Anna K. Dahl Aslan
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 1177 Stockholm, Sweden ,grid.412798.10000 0001 2254 0954School of Health Sciences, University of Skövde, Skövde, Sweden
| | - Margaret Gatz
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 1177 Stockholm, Sweden ,grid.42505.360000 0001 2156 6853Center for Economic and Social Research, University of Southern California, Los Angeles, USA
| | - Nancy L. Pedersen
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 1177 Stockholm, Sweden ,grid.42505.360000 0001 2156 6853Department of Psychology, University of Southern California, Los Angeles, USA
| | - Chandra A. Reynolds
- grid.266097.c0000 0001 2222 1582Department of Psychology, University of California, Riverside, USA
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Wennberg AM, Yin W, Fang F, Pedersen NL, Hägg S, Jylhävä J, Modig K. Comparison of two different frailty scales in the longitudinal Swedish Adoption/Twin Study of Aging (SATSA). Scand J Public Health 2021:14034948211059958. [PMID: 34904462 DOI: 10.1177/14034948211059958] [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] [Indexed: 11/15/2022]
Abstract
AIMS Although up to 25% of older adults are frail, assessing frailty can be difficult, especially in registry data. This study evaluated the utility of a code-based frailty score in registry data by comparing it to a gold-standard frailty score to understand how frailty can be quantified in population data and perhaps better addressed in healthcare. METHODS We compared the Hospital Frailty Risk Score (HFRS), a frailty measure based on 109 ICD codes, to a modified version of the Frailty Index (FI) Frailty Index (FI), a self-report frailty measure, and their associations with all-cause mortality both cross-sectionally and longitudinally (follow-up = 36 years) in a Swedish cohort study (n = 1368). RESULTS The FI and HFRS were weakly correlated (rho = 0.11, p < 0.001). Twenty-two percent (n = 297) of participants were considered frail based on published cut-offs of either measure. Only 3% (n = 35) of participants were classified as frail by both measures; 4% (n = 60) of participants were considered frail by only the HFRS; and 15% (n = 202) of participants were considered frail based only on the FI. Frailty as measured by the HFRS showed greater variance and no clear increase or decrease with age, while frailty as measured by the FI increased steadily with age. In adjusted Cox proportional hazard models, baseline HFRS frailty (HR = 1.17, 95% CI 0.92, 1.49) was not statistically significantly associated with mortality, while FI frailty was (HR = 2.89, 95% CI 1.61, 2.23). These associations were modified by age and sex. CONCLUSIONS The HFRS may not capture the full spectrum of frailty among community-dwelling individuals, particularly at younger ages, in Swedish registry data.
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Affiliation(s)
- Alexandra M Wennberg
- Unit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Sweden
| | - Weiyao Yin
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Sweden
| | - Fang Fang
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Sweden
| | - Nancy L Pedersen
- The Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - Sara Hägg
- The Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - Juulia Jylhävä
- The Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - Karin Modig
- Unit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Sweden
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Tomata Y, Wang Y, Hägg S, Jylhävä J. Protein Nutritional Status and Frailty: A Mendelian Randomization Study. J Nutr 2021; 152:269-275. [PMID: 34601600 PMCID: PMC8754580 DOI: 10.1093/jn/nxab348] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [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: 06/13/2021] [Revised: 07/22/2021] [Accepted: 09/23/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Observational studies have suggested that better protein nutritional status may contribute to prevention of frailty. OBJECTIVE We sought to examine this hypothesis using a Mendelian randomization (MR) analysis. METHODS We conducted a two-sample MR study using GWAS summary statistics data of the UK Biobank. We applied genetically predicted serum albumin as a primary exposure measure and serum total protein as a secondary exposure measure. The outcome measure was the Rockwood frailty index (FI) based on 49 deficits from 356,432 individuals (53.3% of them were women, with a mean ± SD age of 56.7 ± 8.0 y. The association between serum protein measures and FI was mainly analyzed by use of the inverse variance weighted method. RESULTS A genetically predicted serum albumin concentration was not statistically significantly associated with FI in the full sample. However, in women, we observed a preventive association between genetically predicted serum albumin and FI (β = -0.172 per g/L; 95% CI: -0.336, -0.007; P = 0.041). In the full sample, genetically predicted serum total protein was inversely associated with FI (β: -0.153 per g/L; 95% CI: -0.251, -0.056; P = 0.002). In both women and men, higher serum total protein was significantly inversely associated with FI; regression coefficients were -0.148 per g/L (95% CI: -0.287, -0.009; P = 0.037) for women, -0.154 per g/L (95% CI: -0.290, -0.018; P = 0.027) for men. CONCLUSIONS The present MR study implies that better protein nutritional status modestly contributes to reducing the risk of frailty.
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Affiliation(s)
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden,Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
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Bai G, Szwajda A, Wang Y, Li X, Bower H, Karlsson IK, Johansson B, Dahl Aslan AK, Pedersen NL, Hägg S, Jylhävä J. Frailty trajectories in three longitudinal studies of aging: Is the level or the rate of change more predictive of mortality? Age Ageing 2021; 50:2174-2182. [PMID: 34120182 PMCID: PMC8581383 DOI: 10.1093/ageing/afab106] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [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: 11/26/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND frailty shows an upward trajectory with age, and higher levels increase the risk of mortality. However, it is less known whether the shape of frailty trajectories differs by age at death or whether the rate of change in frailty is associated with mortality. OBJECTIVES to assess population frailty trajectories by age at death and to analyse whether the current level of the frailty index (FI) i.e. the most recent measurement or the person-specific rate of change is more predictive of mortality. METHODS 3,689 individuals from three population-based cohorts with up to 15 repeated measurements of the Rockwood frailty index were analysed. The FI trajectories were assessed by stratifying the sample into four age-at-death groups: <70, 70-80, 80-90 and >90 years. Generalised survival models were used in the survival analysis. RESULTS the FI trajectories by age at death showed that those who died at <70 years had a steadily increasing trajectory throughout the 40 years before death, whereas those who died at the oldest ages only accrued deficits from age ~75 onwards. Higher level of FI was independently associated with increased risk of mortality (hazard ratio 1.68, 95% confidence interval 1.47-1.91), whereas the rate of change was no longer significant after accounting for the current FI level. The effect of the FI level did not weaken with time elapsed since the last measurement. CONCLUSIONS Frailty trajectories differ as a function of age-at-death category. The current level of FI is a stronger marker for risk stratification than the rate of change.
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Affiliation(s)
- Ge Bai
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Agnieszka Szwajda
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Xia Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Hannah Bower
- Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Health and Welfare, Institute of Gerontology and Aging Research Network—Jönköping (ARN-J), Jönköping University, Jönköping, Sweden
| | - Boo Johansson
- Department of Psychology, Centre for Ageing and Health (AgeCap), University of Gothenburg, Gothenburg, Sweden
| | - Anna K Dahl Aslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Health Sciences, University of Skövde, Skövde, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Tomata Y, Wang Y, Hägg S, Jylhävä J. Fatty Acids and Frailty: A Mendelian Randomization Study. Nutrients 2021; 13:nu13103539. [PMID: 34684540 PMCID: PMC8541183 DOI: 10.3390/nu13103539] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 10/01/2021] [Accepted: 10/06/2021] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Observational studies have suggested that fatty acids such as higher levels of n-3 polyunsaturated fatty acids (PUFAs) may prevent frailty. By using Mendelian randomization analysis, we examined the relationship between fatty acids and frailty. METHODS We used summary statistics data for single-nucleotide polymorphisms associated with plasma levels of saturated fatty acids (palmitic acid, stearic acid), mono-unsaturated fatty acids (MUFAs) (palmitoleic acid, oleic acid), n-6 PUFAs (linoleic acid, arachidonic acid), and n-3 PUFAs (alpha-linolenic acid, eicosapentaenoic acid, docosapentaenoic acid, docosahexaenoic acid), and the corresponding data for frailty index (FI) in 356,432 individuals in the UK Biobank. RESULTS Although there were no robust associations on the MUFAs or the PUFAs, genetically predicted higher plasma stearic acid level (one of saturated fatty acids) was statistically significantly associated with higher FI (β = 0.178; 95% confidence interval = -0.050 to 0.307; p = 0.007). Such a relationship was also observed in a multivariate MR (β = 0.361; 95% confidence interval = 0.155 to 0.567; p = 0.001). Genetically predicted higher palmitic acid was also significantly associated with higher FI (β = 0.288; 95% confidence interval = 0.128 to 0.447; p < 0.001) in the multivariate MR analysis. CONCLUSIONS The present MR study implies that saturated fatty acids, especially stearic acid, is a risk factor of frailty.
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Affiliation(s)
- Yasutake Tomata
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 171 77 Stockholm, Sweden; (Y.W.); (S.H.); (J.J.)
- Faculty of Health and Social Services, School of Nutrition and Dietetics, Kanagawa University of Human Services, Yokosuka 238-8522, Japan
- Correspondence: ; Tel.: +46-08-524-800-00
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 171 77 Stockholm, Sweden; (Y.W.); (S.H.); (J.J.)
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 171 77 Stockholm, Sweden; (Y.W.); (S.H.); (J.J.)
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 171 77 Stockholm, Sweden; (Y.W.); (S.H.); (J.J.)
- Gerontology Research Center (GEREC), Faculty of Social Sciences (Health Sciences), University of Tampere, 33014 Tampere, Finland
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Atkins JL, Jylhävä J, Pedersen NL, Magnusson PK, Lu Y, Wang Y, Hägg S, Melzer D, Williams DM, Pilling LC. A genome-wide association study of the frailty index highlights brain pathways in ageing. Aging Cell 2021; 20:e13459. [PMID: 34431594 PMCID: PMC8441299 DOI: 10.1111/acel.13459] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [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: 09/23/2019] [Revised: 07/14/2021] [Accepted: 08/06/2021] [Indexed: 12/16/2022] Open
Abstract
Frailty is a common geriatric syndrome and strongly associated with disability, mortality and hospitalization. Frailty is commonly measured using the frailty index (FI), based on the accumulation of a number of health deficits during the life course. The mechanisms underlying FI are multifactorial and not well understood, but a genetic basis has been suggested with heritability estimates between 30 and 45%. Understanding the genetic determinants and biological mechanisms underpinning FI may help to delay or even prevent frailty. We performed a genome-wide association study (GWAS) meta-analysis of a frailty index in European descent UK Biobank participants (n = 164,610, 60-70 years) and Swedish TwinGene participants (n = 10,616, 41-87 years). FI calculation was based on 49 or 44 self-reported items on symptoms, disabilities and diagnosed diseases for UK Biobank and TwinGene, respectively. 14 loci were associated with the FI (p < 5*10-8 ). Many FI-associated loci have established associations with traits such as body mass index, cardiovascular disease, smoking, HLA proteins, depression and neuroticism; however, one appears to be novel. The estimated single nucleotide polymorphism (SNP) heritability of the FI was 11% (0.11, SE 0.005). In enrichment analysis, genes expressed in the frontal cortex and hippocampus were significantly downregulated (adjusted p < 0.05). We also used Mendelian randomization to identify modifiable traits and exposures that may affect frailty risk, with a higher educational attainment genetic risk score being associated with a lower degree of frailty. Risk of frailty is influenced by many genetic factors, including well-known disease risk factors and mental health, with particular emphasis on pathways in the brain.
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Affiliation(s)
- Janice L. Atkins
- Epidemiology and Public Health GroupUniversity of Exeter Medical SchoolExeterUK
| | - Juulia Jylhävä
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Department of PsychologyUniversity of Southern CaliforniaLos AngelesCAUSA
| | - Patrik K. Magnusson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Yi Lu
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Sara Hägg
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - David Melzer
- Epidemiology and Public Health GroupUniversity of Exeter Medical SchoolExeterUK
- Center on AgingUniversity of ConnecticutFarmingtonCTUSA
| | - Dylan M. Williams
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- MRC Unit for Lifelong Health and Ageing at UCLUniversity College LondonLondonUK
| | - Luke C. Pilling
- Epidemiology and Public Health GroupUniversity of Exeter Medical SchoolExeterUK
- Center on AgingUniversity of ConnecticutFarmingtonCTUSA
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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35
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van Dongen J, Hagenbeek FA, Suderman M, Roetman PJ, Sugden K, Chiocchetti AG, Ismail K, Mulder RH, Hafferty JD, Adams MJ, Walker RM, Morris SW, Lahti J, Küpers LK, Escaramis G, Alemany S, Jan Bonder M, Meijer M, Ip HF, Jansen R, Baselmans BML, Parmar P, Lowry E, Streit F, Sirignano L, Send TS, Frank J, Jylhävä J, Wang Y, Mishra PP, Colins OF, Corcoran DL, Poulton R, Mill J, Hannon E, Arseneault L, Korhonen T, Vuoksimaa E, Felix JF, Bakermans-Kranenburg MJ, Campbell A, Czamara D, Binder E, Corpeleijn E, Gonzalez JR, Grazuleviciene R, Gutzkow KB, Evandt J, Vafeiadi M, Klein M, van der Meer D, Ligthart L, Kluft C, Davies GE, Hakulinen C, Keltikangas-Järvinen L, Franke B, Freitag CM, Konrad K, Hervas A, Fernández-Rivas A, Vetro A, Raitakari O, Lehtimäki T, Vermeiren R, Strandberg T, Räikkönen K, Snieder H, Witt SH, Deuschle M, Pedersen NL, Hägg S, Sunyer J, Franke L, Kaprio J, Ollikainen M, Moffitt TE, Tiemeier H, van IJzendoorn MH, Relton C, Vrijheid M, Sebert S, Jarvelin MR, Caspi A, Evans KL, McIntosh AM, Bartels M, Boomsma DI. DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan. Mol Psychiatry 2021; 26:2148-2162. [PMID: 33420481 PMCID: PMC8263810 DOI: 10.1038/s41380-020-00987-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [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: 01/27/2020] [Revised: 11/04/2020] [Accepted: 12/04/2020] [Indexed: 01/06/2023]
Abstract
DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10-7; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.
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Affiliation(s)
- Jenny van Dongen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Matthew Suderman
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Peter J Roetman
- Curium-LUMC, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Oegstgeest, The Netherlands
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Andreas G Chiocchetti
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe-Universität, Frankfurt am Main, Germany
| | - Khadeeja Ismail
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Rosa H Mulder
- Institute of Education and Child Studies, Leiden University, Leiden, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jari Lahti
- Turku Institute for Advanced Studies, University of Turku, Turku, Finland
- Department of Psychology and logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Leanne K Küpers
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Georgia Escaramis
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
- Department of Biomedical Science, Faculty of Medicine and Health Science, University of Barcelona, Barcelona, Spain
- Research Group on Statistics, Econometrics and Health (GRECS), UdG, Girona, Spain
| | - Silvia Alemany
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Marc Jan Bonder
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Mandy Meijer
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Hill F Ip
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bart M L Baselmans
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Priyanka Parmar
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Biocenter Oulu, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
| | - Estelle Lowry
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Queen's University Belfast, Belfast, UK
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tabea S Send
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Pashupati Prasad Mishra
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33520, Finland
| | - Olivier F Colins
- Curium-LUMC, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Oegstgeest, The Netherlands
- Department of Special Needs Education, Ghent University, Ghent, Belgium
| | - David L Corcoran
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Louise Arseneault
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Janine F Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany
| | - Elisabeth Binder
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 12 Executive Park Dr, Atlanta, GA, 30329, USA
| | - Eva Corpeleijn
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Juan R Gonzalez
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Regina Grazuleviciene
- Department of Environmental Sciences, Vytautas Magnus University, K. Donelaicio str. 58, 44248, Kaunas, Lithuania
| | - Kristine B Gutzkow
- Department of Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Jorunn Evandt
- Department of Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Marina Vafeiadi
- Department of Social Medicine, University of Crete, Heraklion, Greece
| | - Marieke Klein
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- University Medical Center Utrecht, UMC Utrecht Brain Center, Department of Psychiatry, Utrecht, The Netherlands
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Lannie Ligthart
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Gareth E Davies
- Avera Institute for Human Genetics, 3720 W. 69th Street, Sioux Falls, SD, 57108, USA
| | - Christian Hakulinen
- Department of Psychology and logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christine M Freitag
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe-Universität, Frankfurt am Main, Germany
| | - Kerstin Konrad
- University Hospital, RWTH Aachen, Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Aachen, Germany
- JARA-Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), RWTH Aachen & Research Centre Juelich, Juelich, Germany
| | - Amaia Hervas
- Hospital Universitario Mutua de Terrassa, Child and Adolescent Mental Health Service, Barcelona, Spain
| | | | - Agnes Vetro
- Szeged University, Department of Pediatrics and Pediatrics health center, Child and Adolescent Psychiatry, Szeged, Hungary
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33520, Finland
| | - Robert Vermeiren
- Curium-LUMC, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Oegstgeest, The Netherlands
- Youz, Parnassia Group, The Hague, The Netherlands
| | - Timo Strandberg
- Helsinki University Central Hospital, Geriatrics, Helsinki, Finland
| | - Katri Räikkönen
- Department of Psychology and logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Harold Snieder
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Michael Deuschle
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jordi Sunyer
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Lude Franke
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, USA
| | - Marinus H van IJzendoorn
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Department of Clinical, Educational and Health Psychology, UCL, University of London, London, UK
| | - Caroline Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Biocenter Oulu, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Section of Genomics of Common Disease, Department of Medicine, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Marjo-Riitta Jarvelin
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Biocenter Oulu, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- MRC-PHE Centre for Environment and Health, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | | | - Meike Bartels
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Abstract
Aging is a complex biological process characterized by hallmark features accumulating over the life course, shaping the individual's aging trajectory and subsequent disease risks. There is substantial individual variability in the aging process between men and women. In general, women live longer than men, consistent with lower biological ages as assessed by molecular biomarkers, but there is a paradox. Women are frailer and have worse health at the end of life, while men still perform better in physical function examinations. Moreover, many age-related diseases show sex-specific patterns. In this review, we aim to summarize the current knowledge on sexual dimorphism in human studies, with support from animal research, on biological aging and illnesses. We also attempt to place it in the context of the theories of aging, as well as discuss the explanations for the sex differences, for example, the sex-chromosome linked mechanisms and hormonally driven differences.
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Affiliation(s)
- Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska InstitutetStockholmSweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska InstitutetStockholmSweden
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Karlsson IK, Ericsson M, Wang Y, Jylhävä J, Hägg S, Dahl Aslan AK, Reynolds CA, Pedersen NL. Epigenome-wide association study of level and change in cognitive abilities from midlife through late life. Clin Epigenetics 2021; 13:85. [PMID: 33883019 PMCID: PMC8061224 DOI: 10.1186/s13148-021-01075-9] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 04/12/2021] [Indexed: 11/18/2022] Open
Abstract
Background Epigenetic mechanisms are important in aging and may be involved in late-life changes in cognitive abilities. We conducted an epigenome-wide association study of leukocyte DNA methylation in relation to level and change in cognitive abilities, from midlife through late life in 535 Swedish twins.
Results Methylation levels were measured with the Infinium Human Methylation 450 K or Infinium MethylationEPIC array, and all sites passing quality control on both arrays were selected for analysis (n = 250,816). Empirical Bayes estimates of individual intercept (age 65), linear, and quadratic change were obtained from latent growth curve models of cognitive traits and used as outcomes in linear regression models. Significant sites (p < 2.4 × 10–7) were followed up in between-within twin pair models adjusting for familial confounding and full-growth modeling. We identified six significant associations between DNA methylation and level of cognitive abilities at age 65: cg18064256 (PPP1R13L) with processing speed and spatial ability; cg04549090 (NRXN3) with spatial ability; cg09988380 (POGZ), cg25651129 (-), and cg08011941 (ENTPD8) with working memory. The genes are involved in neuroinflammation, neuropsychiatric disorders, and ATP metabolism. Within-pair associations were approximately half that of between-pair associations across all sites. In full-growth curve models, associations between DNA methylation and cognitive level at age 65 were of small effect sizes, and associations between DNA methylation and longitudinal change in cognitive abilities of very small effect sizes. Conclusions Leukocyte DNA methylation was associated with level, but not change in cognitive abilities. The associations were substantially attenuated in within-pair analyses, indicating they are influenced in part by genetic factors. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01075-9.
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Affiliation(s)
- Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. .,Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden.
| | - Malin Ericsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna K Dahl Aslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden.,Department of Health Sciences, School of Health Sciences and Welfare, University of Skövde, Skövde, Sweden
| | | | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Department of Psychology, University of Southern California, Los Angeles, CA, USA
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Li X, Ploner A, Wang Y, Zhan Y, Pedersen NL, Magnusson PK, Jylhävä J, Hägg S. Clinical biomarkers and associations with healthspan and lifespan: Evidence from observational and genetic data. EBioMedicine 2021; 66:103318. [PMID: 33813140 PMCID: PMC8047464 DOI: 10.1016/j.ebiom.2021.103318] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [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: 01/25/2021] [Revised: 03/15/2021] [Accepted: 03/16/2021] [Indexed: 11/30/2022] Open
Abstract
Background Biomarker-disease relationships are extensively investigated. However, associations between common clinical biomarkers and healthspan, the disease-free lifespan, are largely unknown. We aimed to explore the predictive values of ten biomarkers on healthspan and lifespan, and to identify putative causal mechanisms. Methods Using data from 12,098 Swedish individuals aged 47–94 years, we examined both serum concentrations and genetically predicted levels of ten glycemic, lipid-, inflammatory, and hematological biomarkers. During a follow-up period of up to 16 years, 3681 incident cases of any chronic disease (i.e., end of healthspan) and 2674 deaths (i.e., end of lifespan) were documented. Cox regression models were applied to estimate the associations of a one standard deviation increase in biomarkers with healthspan and lifespan. Findings Seven out of ten serum biomarkers were significantly associated with risks of any chronic disease and death; elevated glycemic biomarkers and high-density lipoprotein-related biomarkers showed the strongest detrimental (hazard ratio [HR] 1·29 [95% CI 1·24–1·34]) and protective effects (HR 0·92 [95% CI 0·89–0·96]), respectively. Genetic predisposition to elevated fasting blood glucose (FBG) was associated with increased risks of any chronic disease (HR 1·05 [95% CI 1·02–1·09]); genetically determined higher C-reactive protein correlated with lower death risks (HR 0·91 [95% CI 0·87–0·95]). Notably, the genetically proxied FBG-healthspan association was largely explained by serum FBG concentration. Interpretation Circulating concentrations of glycemic, lipid-, and inflammatory biomarkers are predictive of healthspan and lifespan. Glucose control is a putative causal mechanism and a potential intervention target for healthspan maintenance. Funding This study was supported by the Swedish Research Council (2015–03,255, 2018–02,077), FORTE (2013–2292), the Loo & Hans Osterman Foundation, the Foundation for Geriatric Diseases, the Magnus Bergwall Foundation, the Strategic Research Program in Epidemiology at Karolinska Institutet (SH, JJ), the China Scholarship Council, and the Swedish National Graduate School for Competitive Science on Ageing and Health. The Swedish Twin Registry is managed by Karolinska Institutet and receives funding as an infrastructure through the Swedish Research Council, 2017–00,641.
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Affiliation(s)
- Xia Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Alexander Ploner
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yiqiang Zhan
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik Ke Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
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Mak JKL, Kuja-Halkola R, Wang Y, Hägg S, Jylhävä J. Frailty and comorbidity in predicting community COVID-19 mortality in the U.K. Biobank: The effect of sampling. J Am Geriatr Soc 2021; 69:1128-1139. [PMID: 33619733 PMCID: PMC8013405 DOI: 10.1111/jgs.17089] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [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: 12/14/2020] [Revised: 02/05/2021] [Accepted: 02/08/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND/OBJECTIVES Frailty has been linked to increased risk of COVID-19 mortality, but evidence is mainly limited to hospitalized older individuals. This study aimed to assess and compare predictive abilities of different frailty and comorbidity measures for COVID-19 mortality in a community sample and COVID-19 inpatients. DESIGN Population-based cohort study. SETTING Community. PARTICIPANTS We analyzed (i) the full sample of 410,199 U.K. Biobank participants in England, aged 49-86 years, and (ii) a subsample of 2812 COVID-19 inpatients with COVID-19 data from March 1 to November 30, 2020. MEASUREMENTS Frailty was defined using the physical frailty phenotype (PFP), frailty index (FI), and Hospital Frailty Risk Score (HFRS), and comorbidity using the Charlson Comorbidity Index (CCI). PFP and FI were available at baseline, whereas HFRS and CCI were assessed both at baseline and concurrently with the start of the pandemic. Inpatient COVID-19 cases were confirmed by PCR and/or hospital records. COVID-19 mortality was ascertained from death registers. RESULTS Overall, 514 individuals died of COVID-19. In the full sample, all frailty and comorbidity measures were associated with higher COVID-19 mortality risk after adjusting for age and sex. However, the associations were stronger for the concurrent versus baseline HFRS and CCI, with odds ratios of 20.40 (95% confidence interval = 16.24-25.63) comparing high (>15) to low (<5) concurrent HFRS risk category and 1.53 (1.48-1.59) per point increase in concurrent CCI. Moreover, only the concurrent HFRS or CCI significantly improved predictive ability of a model including age and sex, yielding areas under the receiver operating characteristic curve (AUC) >0.8. When restricting analyses to COVID-19 inpatients, similar improvement in AUC was not observed. CONCLUSION HFRS and CCI constructed from medical records concurrent with the start of the pandemic can be used in COVID-19 mortality risk stratification at the population level, but they show limited added value in COVID-19 inpatients.
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Affiliation(s)
- Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Pirazzini C, Azevedo T, Baldelli L, Bartoletti-Stella A, Calandra-Buonaura G, Dal Molin A, Dimitri GM, Doykov I, Gómez-Garre P, Hägg S, Hällqvist J, Halsband C, Heywood W, Jesús S, Jylhävä J, Kwiatkowska KM, Labrador-Espinosa MA, Licari C, Maturo MG, Mengozzi G, Meoni G, Milazzo M, Periñán-Tocino MT, Ravaioli F, Sala C, Sambati L, Schade S, Schreglmann S, Spasov S, Tenori L, Williams D, Xumerle L, Zago E, Bhatia KP, Capellari S, Cortelli P, Garagnani P, Houlden H, Liò P, Luchinat C, Delledonne M, Mills K, Mir P, Mollenhauer B, Nardini C, Pedersen NL, Provini F, Strom S, Trenkwalder C, Turano P, Bacalini MG, Franceschi C. A geroscience approach for Parkinson's disease: Conceptual framework and design of PROPAG-AGEING project. Mech Ageing Dev 2021; 194:111426. [PMID: 33385396 DOI: 10.1016/j.mad.2020.111426] [Citation(s) in RCA: 7] [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] [Received: 08/28/2020] [Revised: 12/07/2020] [Accepted: 12/22/2020] [Indexed: 12/12/2022]
Abstract
Advanced age is the major risk factor for idiopathic Parkinson's disease (PD), but to date the biological relationship between PD and ageing remains elusive. Here we describe the rationale and the design of the H2020 funded project "PROPAG-AGEING", whose aim is to characterize the contribution of the ageing process to PD development. We summarize current evidences that support the existence of a continuum between ageing and PD and justify the use of a Geroscience approach to study PD. We focus in particular on the role of inflammaging, the chronic, low-grade inflammation characteristic of elderly physiology, which can propagate and transmit both locally and systemically. We then describe PROPAG-AGEING design, which is based on the multi-omic characterization of peripheral samples from clinically characterized drug-naïve and advanced PD, PD discordant twins, healthy controls and "super-controls", i.e. centenarians, who never showed clinical signs of motor disability, and their offspring. Omic results are then validated in a large number of samples, including in vitro models of dopaminergic neurons and healthy siblings of PD patients, who are at higher risk of developing PD, with the final aim of identifying the molecular perturbations that can deviate the trajectories of healthy ageing towards PD development.
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Affiliation(s)
- Chiara Pirazzini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Tiago Azevedo
- Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom
| | - Luca Baldelli
- Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | | | - Giovanna Calandra-Buonaura
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | | | - Giovanna Maria Dimitri
- Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom
| | - Ivan Doykov
- Centre for Inborn Errors of Metabolism, UCL Institute of Child Health, London, United Kingdom
| | - Pilar Gómez-Garre
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jenny Hällqvist
- Centre for Inborn Errors of Metabolism, UCL Institute of Child Health, London, United Kingdom
| | - Claire Halsband
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Göttingen, Germany; Department of Gerontopsychiatry, Rhein-Mosel-Fachklinik, Andernach, Germany
| | - Wendy Heywood
- Centre for Inborn Errors of Metabolism, UCL Institute of Child Health, London, United Kingdom; NIHR Great Ormond Street Biomedical Research Centre, Great Ormond Street Hospital and UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Silvia Jesús
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - Miguel A Labrador-Espinosa
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Cristina Licari
- CERM, University of Florence, Sesto Fiorentino, Florence, Italy
| | - Maria Giovanna Maturo
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Giacomo Mengozzi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | | | - Maddalena Milazzo
- Department of Experimental, Diagnostic, and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
| | - Maria Teresa Periñán-Tocino
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Francesco Ravaioli
- Department of Experimental, Diagnostic, and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
| | - Claudia Sala
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Luisa Sambati
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | - Sebastian Schade
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Göttingen, Germany
| | - Sebastian Schreglmann
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Simeon Spasov
- Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom
| | - Leonardo Tenori
- Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Florence, Italy
| | - Dylan Williams
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | | | - Kailash P Bhatia
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Sabina Capellari
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | - Pietro Cortelli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | - Paolo Garagnani
- Department of Experimental, Diagnostic, and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
| | - Henry Houlden
- Department of Neuromuscular Disorders, UCL Queen Square Institute of Neurology, London, WC1N 3BG, United Kingdom
| | - Pietro Liò
- Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom
| | - Claudio Luchinat
- CERM, University of Florence, Sesto Fiorentino, Florence, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Italy
| | | | - Kevin Mills
- Centre for Inborn Errors of Metabolism, UCL Institute of Child Health, London, United Kingdom; NIHR Great Ormond Street Biomedical Research Centre, Great Ormond Street Hospital and UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Pablo Mir
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel, Germany; Department of Neurology, University Medical Centre Goettingen, Goettingen, Germany
| | - Christine Nardini
- Istituto per le Applicazioni del Calcolo Mauro Picone, CNR, Roma, Italy
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Federica Provini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | - Stephen Strom
- Department of Laboratory Medicine, Karolinska Institute and Karolinska Universitetssjukhuset, 171 76, Stockholm, Sweden
| | - Claudia Trenkwalder
- Paracelsus-Elena-Klinik, Kassel, Germany; Department of Neurosurgery, University Medical Center Göttingen, Germany
| | - Paola Turano
- CERM, University of Florence, Sesto Fiorentino, Florence, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Italy
| | | | - Claudio Franceschi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Laboratory of Systems Medicine of Healthy Aging and Department of Applied Mathematics, Lobachevsky University, Nizhny Novgorod, Russia
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Raymond E, Reynolds CA, Dahl Aslan AK, Finkel D, Ericsson M, Hägg S, Pedersen NL, Jylhävä J. Drivers of Frailty from Adulthood into Old Age: Results from a 27-Year Longitudinal Population-Based Study in Sweden. J Gerontol A Biol Sci Med Sci 2021; 75:1943-1950. [PMID: 32348465 PMCID: PMC7518563 DOI: 10.1093/gerona/glaa106] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [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: 11/12/2019] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Frailty is a strong predictor of adverse outcomes. However, longitudinal drivers of frailty are not well understood. This study aimed at investigating the longitudinal trajectories of a frailty index (FI) from adulthood to late life and identifying the factors associated with the level and rate of change in FI. METHODS An age-based latent growth curve analysis was performed in the Swedish Adoption/Twin Study of Aging (N = 1,842; aged 29-102 years) using data from up to 15 measurement waves across 27 years. A 42-item FI was used to measure frailty at each wave. RESULTS A bilinear, two-slope model with a turning point at age 65 best described the age-related change in FI, showing that the increase in frailty was more than twice as fast after age 65. Underweight, obesity, female sex, overweight, being separated from one's co-twin during childhood, smoking, poor social support, and low physical activity were associated with a higher FI at age 65, with underweight having the largest effect size. When tested as time-varying covariates, underweight and higher social support were associated with a steeper increase in FI before age 65, whereas overweight and obesity were associated with less steep increase in FI after age 65. CONCLUSIONS Factors associated with the level and rate of change in frailty are largely actionable and could provide targets for intervention. As deviations from normal weight showed the strongest associations with frailty, future public health programs could benefit from monitoring of individuals with abnormal BMI, especially those who are underweight.
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Affiliation(s)
- Emma Raymond
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - Anna K Dahl Aslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Sweden
| | - Deborah Finkel
- Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Sweden.,Department of Psychology, Indiana University Southeast, New Albany
| | - Malin Ericsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - 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
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42
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Affiliation(s)
- Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 65, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 65, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 65, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 65, Stockholm, Sweden
| | - Felix Grassmann
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 65, Stockholm, Sweden.
- Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK.
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43
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Hägg S, Jylhävä J, Wang Y, Xu H, Metzner C, Annetorp M, Garcia-Ptacek S, Khedri M, Boström AM, Kadir A, Johansson A, Kivipelto M, Eriksdotter M, Cederholm T, Religa D. Age, Frailty, and Comorbidity as Prognostic Factors for Short-Term Outcomes in Patients With Coronavirus Disease 2019 in Geriatric Care. J Am Med Dir Assoc 2020; 21:1555-1559.e2. [PMID: 32978065 PMCID: PMC7427570 DOI: 10.1016/j.jamda.2020.08.014] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [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: 06/30/2020] [Revised: 08/12/2020] [Accepted: 08/13/2020] [Indexed: 12/21/2022]
Abstract
Objectives To analyze whether frailty and comorbidities are associated with in-hospital mortality and discharge to home in older adults hospitalized for coronavirus disease 2019 (COVID-19). Design Single-center observational study. Setting and Participants Patients admitted to geriatric care in a large hospital in Sweden between March 1 and June 11, 2020; 250 were treated for COVID-19 and 717 for other diagnoses. Methods COVID-19 diagnosis was clinically confirmed by positive reverse transcription polymerase chain reaction test or, if negative, by other methods. Patient data were extracted from electronic medical records, which included Clinical Frailty Scale (CFS), and were further used for assessments of the Hospital Frailty Risk Score (HFRS) and the Charlson Comorbidity Index (CCI). In-hospital mortality and home discharge were followed up for up to 25 and 28 days, respectively. Multivariate Cox regression models adjusted for age and sex were used. Results Among the patients with COVID-19, in-hospital mortality rate was 24% and home discharge rate was 44%. Higher age was associated with in-hospital mortality (hazard ratio [HR] 1.05 per each year, 95% confidence interval [CI] 1.01‒1.08) and lower probability of home discharge (HR 0.97, 95% CI 0.95‒0.99). CFS (>5) and CCI, but not HFRS, were predictive of in-hospital mortality (HR 1.93, 95% CI 1.02‒3.65 and HR 1.27, 95% CI 1.02‒1.58, respectively). Patients with CFS >5 had a lower probability of being discharged home (HR 0.38, 95% CI 0.25‒0.58). CCI and HFRS were not associated with home discharge. In general, effects were more pronounced in men. Acute kidney injury was associated with in-hospital mortality and hypertension with discharge to home. Other comorbidities (diabetes, cardiovascular disease, lung diseases, chronic kidney disease and dementia) were not associated with either outcome. Conclusions and Implications Of all geriatric patients with COVID-19, 3 out of 4 survived during the study period. Our results indicate that in addition to age, the level of frailty is a useful predictor of short-term COVID-19 outcomes in geriatric patients.
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Affiliation(s)
- Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Hong Xu
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden; Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden
| | - Carina Metzner
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Martin Annetorp
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Sara Garcia-Ptacek
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden; Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden
| | - Masih Khedri
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Anne-Marie Boström
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden; Division of Nursing, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden; Research and Development Unit, Stockholms Sjukhem, Stockholm, Sweden
| | - Ahmadul Kadir
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden; Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden
| | - Anna Johansson
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Miia Kivipelto
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden; Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden
| | - Maria Eriksdotter
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden; Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden
| | - Tommy Cederholm
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden; Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden; Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Dorota Religa
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden; Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden
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Reynolds CA, Tan Q, Munoz E, Jylhävä J, Hjelmborg J, Christiansen L, Hägg S, Pedersen NL. A decade of epigenetic change in aging twins: Genetic and environmental contributions to longitudinal DNA methylation. Aging Cell 2020; 19:e13197. [PMID: 32710526 PMCID: PMC7431820 DOI: 10.1111/acel.13197] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [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] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 06/07/2020] [Accepted: 06/28/2020] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Epigenetic changes may result from the interplay of environmental exposures and genetic influences and contribute to differences in age-related disease, disability, and mortality risk. However, the etiologies contributing to stability and change in DNA methylation have rarely been examined longitudinally. METHODS We considered DNA methylation in whole blood leukocyte DNA across a 10-year span in two samples of same-sex aging twins: (a) Swedish Adoption Twin Study of Aging (SATSA; N = 53 pairs, 53% female; 62.9 and 72.5 years, SD = 7.2 years); (b) Longitudinal Study of Aging Danish Twins (LSADT; N = 43 pairs, 72% female, 76.2 and 86.1 years, SD=1.8 years). Joint biometrical analyses were conducted on 358,836 methylation probes in common. Bivariate twin models were fitted, adjusting for age, sex, and country. RESULTS Overall, results suggest genetic contributions to DNA methylation across 358,836 sites tended to be small and lessen across 10 years (broad heritability M = 23.8% and 18.0%) but contributed to stability across time while person-specific factors explained emergent influences across the decade. Aging-specific sites identified from prior EWAS and methylation age clocks were more heritable than background sites. The 5037 sites that showed the greatest heritable/familial-environmental influences (p < 1E-07) were enriched for immune and inflammation pathways while 2020 low stability sites showed enrichment in stress-related pathways. CONCLUSIONS Across time, stability in methylation is primarily due to genetic contributions, while novel experiences and exposures contribute to methylation differences. Elevated genetic contributions at age-related methylation sites suggest that adaptions to aging and senescence may be differentially impacted by genetic background.
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Affiliation(s)
| | - Qihua Tan
- University of Southern DenmarkOdenseDenmark
| | - Elizabeth Munoz
- University of California ‐ RiversideRiversideCAUSA
- Present address:
University of Texas at AustinAustinTXUSA
| | | | | | - Lene Christiansen
- University of Southern DenmarkOdenseDenmark
- Copenhagen University Hospital, RigshospitaletCopenhagenDenmark
| | - Sara Hägg
- Karolinska InstitutetStockholmSweden
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Nyberg A, Larsson A, Jylhävä J, Hurme M, Sperber J, Lipcsey M, Castegren M. Lung-protective ventilation suppresses systemic and hepatic vein levels of cell-free DNA in porcine experimental post-operative sepsis. BMC Pulm Med 2020; 20:206. [PMID: 32736620 PMCID: PMC7393331 DOI: 10.1186/s12890-020-01239-y] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 07/17/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Plasma levels of cell-free DNA (cf-DNA) are known to be elevated in sepsis and high levels are associated with a poor prognosis. Mechanical ventilation affects systemic inflammation in which lung-protective ventilation attenuates the inflammatory response. The aim was to study the effect of a lung protective ventilator regime on arterial and organ-specific venous blood as well as on trans-organ differences in cf-DNA levels in a porcine post-operative sepsis model. METHOD One group of anaesthetised, domestic-breed, 9-12 weeks old, pigs were ventilated with protective ventilation (VT 6 mL x kg- 1, PEEP 10 cmH2O) n = 20. Another group, ventilated with a medium high tidal volume and lower PEEP, served as a control group (VT 10 mL x kg- 1, PEEP 5 cm H2O) n = 10. Blood samples were taken from four sources: artery, hepatic vein, portal vein and, jugular bulb. A continuous endotoxin infusion at 0.25 μg x kg- 1 x h- 1 for 5 h was started following 2 h of laparotomy, which simulated a surgical procedure. Inflammatory cytokines and cf-DNA in plasma were analysed and trans-organ differences calculated. RESULTS The protective ventilation group had lower levels of cf-DNA in arterial (p = 0.02) and hepatic venous blood (p = 0.03) compared with the controls. Transhepatic differences in cf-DNA were lower in the protective group, compared with the controls (p = 0.03). No differences between the groups were noted as regards the transcerebral, transsplanchnic or the transpulmonary cf-DNA differences. CONCLUSIONS Protective ventilation suppresses arterial levels of cf-DNA. The liver seems to be a net contributor to the systemic cf-DNA levels, but this effect is attenuated by protective ventilation.
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Affiliation(s)
- Axel Nyberg
- Department of Anaesthesiology & Intensive Care, Centre for Clinical Research, Sörmland, Uppsala University, Mälarsjukhuset, SE-631 88 Eskilstuna, Uppsala, Sweden. .,Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
| | - Alexander Larsson
- Centre for Clinical Research, Region of Västmanland, Uppsala University, Uppsala, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Mikko Hurme
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jesper Sperber
- Department of Anaesthesiology & Intensive Care, Centre for Clinical Research, Sörmland, Uppsala University, Mälarsjukhuset, SE-631 88 Eskilstuna, Uppsala, Sweden.,Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Miklós Lipcsey
- Hedenstierna laboratory, CIRRUS, Anesthesiology and Intensive Care, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Markus Castegren
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden.,Perioperative Medicine and Intensive Care (PMI), Karolinska University Hospital and CLINTEC, Karolinska Institute, Stockholm, Sweden
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46
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Finkel D, Sternäng O, Jylhävä J, Bai G, Pedersen NL. Functional Aging Index Complements Frailty in Prediction of Entry Into Care and Mortality. J Gerontol A Biol Sci Med Sci 2020; 74:1980-1986. [PMID: 31222213 DOI: 10.1093/gerona/glz155] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND The aim of this study was to develop a functional aging index (FAI) that taps four body systems: sensory (vision and hearing), pulmonary, strength (grip strength), and movement (gait speed) and to test the predictive value of FAI for entry into care and mortality. METHOD Growth curve models and Cox regression models were applied to data from 1,695 individuals from three Swedish longitudinal studies of aging. Participants were aged 45-93 at intake and data from up to eight follow-up waves were available. RESULTS The rate of change in FAI was twice as fast after age 75 as before, women demonstrated higher mean FAI, but no sex differences in rates of change with chronological age were identified. FAI predicted entry into care and mortality, even when chronological age and a frailty index were included in the models. Hazard ratios indicated that FAI was a more important predictor of entry into care for men than women, whereas it was a stronger predictor of mortality for men than women. CONCLUSIONS Measures of biological aging and functional aging differ in their predictive value for entry into care and mortality for men and women, suggesting that both are necessary for a complete picture of the aging process across genders.
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Affiliation(s)
- Deborah Finkel
- Department of Psychology, Indiana University Southeast, New Albany.,Institute for Gerontology, Jönköping University
| | - Ola Sternäng
- Institute for Gerontology, Jönköping University.,Department of Social Sciences, Södertörn University, Huddinge
| | - Juulia Jylhävä
- Department of Medical Epidemiological and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ge Bai
- Department of Medical Epidemiological and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiological and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Department of Psychology, University of Southern California, Los Angeles
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Meryk A, Pangrazzi L, Hagen M, Hatzmann F, Jenewein B, Jakic B, Hermann-Kleiter N, Baier G, Jylhävä J, Hurme M, Trieb K, Grubeck-Loebenstein B. Fcμ receptor as a Costimulatory Molecule for T Cells. Cell Rep 2020; 26:2681-2691.e5. [PMID: 30840890 DOI: 10.1016/j.celrep.2019.02.024] [Citation(s) in RCA: 12] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Revised: 01/28/2019] [Accepted: 02/07/2019] [Indexed: 11/17/2022] Open
Abstract
Fc receptor for IgM (FcμR)-deficient mice display dysregulated function of neutrophils, dendritic cells, and B cells. The relevance of FcμR to human T cells is still unknown. We show that FcμR is mostly stored inside the cell and that surface expression is tightly regulated. Decreased surface expression on T cells from elderly individuals is associated with alterations in the methylation pattern of the FCMR gene. Binding and internalization of IgM stimulate transport of FcμR to the cell surface to ensure sustained IgM uptake. Concurrently, IgM accumulates within the cell, and the surface expression of other receptors increases, among them the T cell receptor (TCR) and costimulatory molecules. This leads to enhanced TCR signaling, proliferation, and cytokine release, in response to low, but not high, doses of antigen. Our findings indicate that FcμR is an important regulator of T cell function and reveal an additional mode of interaction between B and T cells.
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Affiliation(s)
- Andreas Meryk
- Department of Immunology, Institute for Biomedical Aging Research, University of Innsbruck, 6020 Innsbruck, Austria.
| | - Luca Pangrazzi
- Department of Immunology, Institute for Biomedical Aging Research, University of Innsbruck, 6020 Innsbruck, Austria
| | - Magdalena Hagen
- Department of Immunology, Institute for Biomedical Aging Research, University of Innsbruck, 6020 Innsbruck, Austria
| | - Florian Hatzmann
- Department of Immunology, Institute for Biomedical Aging Research, University of Innsbruck, 6020 Innsbruck, Austria
| | - Brigitte Jenewein
- Department of Immunology, Institute for Biomedical Aging Research, University of Innsbruck, 6020 Innsbruck, Austria
| | - Bojana Jakic
- Division of Translational Cell Genetics, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Natascha Hermann-Kleiter
- Division of Translational Cell Genetics, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Gottfried Baier
- Division of Translational Cell Genetics, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 17177 Stockholm, Sweden
| | - Mikko Hurme
- Faculty of Medicine and Life Sciences, University of Tampere, Tampere 33014, Finland
| | - Klemens Trieb
- Department of Orthopedic Surgery, Hospital Wels-Grieskirchen, 4600 Wels, Austria
| | - Beatrix Grubeck-Loebenstein
- Department of Immunology, Institute for Biomedical Aging Research, University of Innsbruck, 6020 Innsbruck, Austria
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48
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Hägg S, Jylhävä J. Should we invest in biological age predictors to treat colorectal cancer in older adults? Eur J Surg Oncol 2020; 46:316-320. [DOI: 10.1016/j.ejso.2019.11.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 09/09/2019] [Accepted: 11/06/2019] [Indexed: 02/06/2023] Open
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49
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Li X, Ploner A, Wang Y, Magnusson PKE, Reynolds C, Finkel D, Pedersen NL, Jylhävä J, Hägg S. Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up. eLife 2020; 9:e51507. [PMID: 32041686 PMCID: PMC7012595 DOI: 10.7554/elife.51507] [Citation(s) in RCA: 124] [Impact Index Per Article: 31.0] [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] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 12/24/2019] [Indexed: 12/21/2022] Open
Abstract
Biological age measurements (BAs) assess aging-related physiological change and predict health risks among individuals of the same chronological age (CA). Multiple BAs have been proposed and are well studied individually but not jointly. We included 845 individuals and 3973 repeated measurements from a Swedish population-based cohort and examined longitudinal trajectories, correlations, and mortality associations of nine BAs across 20 years follow-up. We found the longitudinal growth of functional BAs accelerated around age 70; average levels of BA curves differed by sex across the age span (50-90 years). All BAs were correlated to varying degrees; correlations were mostly explained by CA. Individually, all BAs except for telomere length were associated with mortality risk independently of CA. The largest effects were seen for methylation age estimators (GrimAge) and the frailty index (FI). In joint models, two methylation age estimators (Horvath and GrimAge) and FI remained predictive, suggesting they are complementary in predicting mortality.
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Affiliation(s)
- Xia Li
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Alexander Ploner
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Patrik KE Magnusson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Chandra Reynolds
- Department of PsychologyUniversity of California, RiversideRiversideUnited States
| | - Deborah Finkel
- Department of PsychologyIndiana University SoutheastNew AlbanyUnited States
- Institute for GerontologyJönköping UniversityJönköpingSweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Sara Hägg
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
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Abstract
Background Frailty indices (FIs) measure variation in health between aging individuals. Researching FIs in resources with large-scale genetic and phenotypic data will provide insights into the causes and consequences of frailty. Thus, we aimed to develop an FI using UK Biobank data, a cohort study of 500,000 middle-aged and older adults. Methods An FI was calculated using 49 self-reported questionnaire items on traits covering health, presence of diseases and disabilities, and mental well-being, according to standard protocol. We used multiple imputation to derive FI values for the entire eligible sample in the presence of missing item data (N = 500,336). To validate the measure, we assessed associations of the FI with age, sex, and risk of all-cause mortality (follow-up ≤ 9.7 years) using linear and Cox proportional hazards regression models. Results Mean FI in the cohort was 0.125 (SD = 0.075), and there was a curvilinear trend toward higher values in older participants. FI values were also marginally higher on average in women than in men. In survival models, 10% higher baseline frailty (ie, a 0.1 FI increment) was associated with higher risk of death (hazard ratio = 1.65; 95% confidence interval: 1.62–1.68). Associations were stronger in younger participants than in older participants, and in men than in women (hazard ratios: 1.72 vs. 1.56, respectively). Conclusions The FI is a valid measure of frailty in UK Biobank. The cohort’s data are open access for researchers to use, and we provide script for deriving this tool to facilitate future studies on frailty.
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Affiliation(s)
- Dylan M Williams
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Department of Psychology, University of Southern California, Los Angeles
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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