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Kuiper LM, Smit AP, Bizzarri D, van den Akker EB, Reinders MJT, Ghanbari M, van Rooij JGJ, Voortman T, Rivadeneira F, Dollé MET, Herber GCM, Rietman ML, Picavet HSJ, van Meurs JBJ, Verschuren WMM. Lifestyle factors and metabolomic aging biomarkers: Meta-analysis of cross-sectional and longitudinal associations in three prospective cohorts. Mech Ageing Dev 2024; 220:111958. [PMID: 38950629 DOI: 10.1016/j.mad.2024.111958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 06/18/2024] [Accepted: 06/24/2024] [Indexed: 07/03/2024]
Abstract
Biological age uses biophysiological information to capture a person's age-related risk of adverse outcomes. MetaboAge and MetaboHealth are metabolomics-based biomarkers of biological age trained on chronological age and mortality risk, respectively. Lifestyle factors contribute to the extent chronological and biological age differ. The association of lifestyle factors with MetaboAge and MetaboHealth, potential sex differences in these associations, and MetaboAge's and MetaboHealth's sensitivity to lifestyle changes have not been studied yet. Linear regression analyses and mixed-effect models were used to examine the cross-sectional and longitudinal associations of scaled lifestyle factors with scaled MetaboAge and MetaboHealth in 24,332 middle-aged participants from the Doetinchem Cohort Study, Rotterdam Study, and UK Biobank. Random-effect meta-analyses were performed across cohorts. Repeated metabolomics measurements had a ten-year interval in the Doetinchem Cohort Study and a five-year interval in the UK Biobank. In the first study incorporating longitudinal information on MetaboAge and MetaboHealth, we demonstrate associations between current smoking, sleeping ≥8 hours/day, higher BMI, and larger waist circumference were associated with higher MetaboHealth, the latter two also with higher MetaboAge. Furthermore, adhering to the dietary and physical activity guidelines were inversely associated with MetaboHealth. Lastly, we observed sex differences in the associations between alcohol use and MetaboHealth.
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Affiliation(s)
- L M Kuiper
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands; Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - A P Smit
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - D Bizzarri
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands
| | - E B van den Akker
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands
| | - M J T Reinders
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands
| | - M Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - J G J van Rooij
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - T Voortman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Meta-Research Innovation Center at Stanford (METRICS), Stanford University, California, USA
| | - F Rivadeneira
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - M E T Dollé
- Center for Health Protection, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands
| | - G C M Herber
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands
| | - M L Rietman
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands
| | - H S J Picavet
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands
| | - J B J van Meurs
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Orthopaedics & Sports, Erasmus Medical Center, Rotterdam, the Netherlands
| | - W M M Verschuren
- Center for Prevention, Lifestyle and Health, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
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Martínez-Magaña JJ, Hurtado-Soriano J, Rivero-Segura NA, Montalvo-Ortiz JL, Garcia-delaTorre P, Becerril-Rojas K, Gomez-Verjan JC. Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology. Arch Med Res 2024; 55:103033. [PMID: 38955096 DOI: 10.1016/j.arcmed.2024.103033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 05/10/2024] [Accepted: 06/17/2024] [Indexed: 07/04/2024]
Abstract
Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.
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Affiliation(s)
- José Jaime Martínez-Magaña
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; U.S. Department of Veterans Affairs National Center for Post-Traumatic Stress Disorder, Clinical Neuroscience Division, West Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | | | | | - Janitza L Montalvo-Ortiz
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; U.S. Department of Veterans Affairs National Center for Post-Traumatic Stress Disorder, Clinical Neuroscience Division, West Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | - Paola Garcia-delaTorre
- Unidad de Investigación Epidemiológica y en Servicios de Salud, Área de Envejecimiento, Centro Médico Nacional, Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
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3
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Maunakea AK, Phankitnirundorn K, Peres R, Dye C, Juarez R, Walsh C, Slavens C, Park SL, Wilkens LR, Le Marchand L. Socioeconomic Status, Lifestyle, and DNA Methylation Age Among Racially and Ethnically Diverse Adults: NIMHD Social Epigenomics Program. JAMA Netw Open 2024; 7:e2421889. [PMID: 39073814 PMCID: PMC11287425 DOI: 10.1001/jamanetworkopen.2024.21889] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 05/09/2024] [Indexed: 07/30/2024] Open
Abstract
Importance Variation in DNA methylation at specific loci estimates biological age, which is associated with morbidity, mortality, and social experiences. Aging estimates known as epigenetic clocks, including the Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE), were trained on data predominately from individuals of European ancestry; however, limited research has explored DunedinPACE in underrepresented populations experiencing health disparities. Objective To investigate associations of neighborhood and individual sociobehavioral factors with biological aging in a racially and ethnically diverse population. Design, Setting, and Participants This cohort study, part of the Multiethnic Cohort study conducted from May 1993 to September 1996 to examine racial and ethnic disparities in chronic diseases, integrated biospecimen and self-reported data collected between April 2004 and November 2005 from healthy Hawaii residents aged 45 to 76 years. These participants self-identified as of Japanese American, Native Hawaiian, or White racial and ethnic background. Data were analyzed from January 2022 to May 2024. Main Outcomes and Measures DNA methylation data were generated from monocytes enriched from cryopreserved lymphocytes and used to derive DunedinPACE scores from November 2017 to June 2021. Neighborhood social economic status (NSES) was estimated from 1990 US Census Bureau data to include factors such as educational level, occupation, and income. Individual-level factors analyzed included educational level, body mass index (BMI), physical activity (PA), and diet quality measured by the Healthy Eating Index (HEI). Linear regression analysis of DunedinPACE scores was used to examine their associations with NSES and sociobehavioral variables. Results A total of 376 participants were included (113 [30.1%] Japanese American, 144 [38.3%] Native Hawaiian, and 119 [31.6%] White; 189 [50.3%] were female). Mean (SE) age was 57.81 (0.38) years. Overall, mean (SE) DunedinPACE scores were significantly higher among females than among males (1.28 [0.01] vs 1.25 [0.01]; P = .005); correlated negatively with NSES (R = -0.09; P = .08), HEI (R = -0.11; P = .03), and educational attainment (R = -0.15; P = .003) and positively with BMI (R = 0.31; P < .001); and varied by race and ethnicity. Native Hawaiian participants exhibited a higher mean (SE) DunedinPACE score (1.31 [0.01]) compared with Japanese American (1.25 [0.01]; P < .001) or White (1.22 [0.01]; P < .001) participants. Controlling for age, sex, HEI, BMI, and NSES, linear regression analyses revealed a negative association between educational level and DunedinPACE score among Japanese American (β, -0.005 [95% CI, -0.013 to 0.002]; P = .03) and Native Hawaiian (β, -0.003 [95% CI, -0.011 to 0.005]; P = .08) participants, yet this association was positive among White participants (β, 0.007; 95% CI, -0.001 to 0.015; P = .09). Moderate to vigorous PA was associated with lower DunedinPACE scores only among Native Hawaiian participants (β, -0.006; 95% CI, -0.011 to -0.001; P = .005), independent of NSES. Conclusions and Relevance In this study of a racially and ethnically diverse sample of 376 adults, low NSES was associated with a higher rate of biological aging measured by DunedinPACE score, yet individual-level factors such as educational level and physical activity affected this association, which varied by race and ethnicity. These findings support sociobehavioral interventions in addressing health inequities.
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Affiliation(s)
- Alika K. Maunakea
- Department of Anatomy, Biochemistry, and Physiology, University of Hawaii at Manoa, John A. Burns School of Medicine, Honolulu
| | - Krit Phankitnirundorn
- Department of Anatomy, Biochemistry, and Physiology, University of Hawaii at Manoa, John A. Burns School of Medicine, Honolulu
| | - Rafael Peres
- Department of Anatomy, Biochemistry, and Physiology, University of Hawaii at Manoa, John A. Burns School of Medicine, Honolulu
| | - Christian Dye
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York
| | - Ruben Juarez
- Department of Economics, University of Hawaii at Manoa, Honolulu
| | - Catherine Walsh
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
| | - Connor Slavens
- Department of Anatomy, Biochemistry, and Physiology, University of Hawaii at Manoa, John A. Burns School of Medicine, Honolulu
| | - S. Lani Park
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
| | - Lynne R. Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
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Miao K, Hong X, Cao W, Lv J, Yu C, Huang T, Sun D, Liao C, Pang Y, Hu R, Pang Z, Yu M, Wang H, Wu X, Liu Y, Gao W, Li L. Association between epigenetic age and type 2 diabetes mellitus or glycemic traits: A longitudinal twin study. Aging Cell 2024; 23:e14175. [PMID: 38660768 PMCID: PMC11258448 DOI: 10.1111/acel.14175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 03/18/2024] [Accepted: 04/04/2024] [Indexed: 04/26/2024] Open
Abstract
Epigenetic clocks based on DNA methylation have been known as biomarkers of aging, including principal component (PC) clocks representing the degree of aging and DunedinPACE representing the pace of aging. Prior studies have shown the associations between epigenetic aging and T2DM, but the results vary by epigenetic age metrics and people. This study explored the associations between epigenetic age metrics and T2DM or glycemic traits, based on 1070 twins (535 twin pairs) from the Chinese National Twin Registry. It also explored the temporal relationships of epigenetic age metrics and glycemic traits in 314 twins (157 twin pairs) who participated in baseline and follow-up visits after a mean of 4.6 years. DNA methylation data were used to calculate epigenetic age metrics, including PCGrimAge acceleration (PCGrimAA), PCPhenoAge acceleration (PCPhenoAA), DunedinPACE, and the longitudinal change rate of PCGrimAge/PCPhenoAge. Mixed-effects and cross-lagged modelling assessed the cross-sectional and temporal relationships between epigenetic age metrics and T2DM or glycemic traits, respectively. In the cross-sectional analysis, positive associations were identified between DunedinPACE and glycemic traits, as well as between PCPhenoAA and fasting plasma glucose, which may be not confounded by shared genetic factors. Cross-lagged models revealed that glycemic traits (fasting plasma glucose, HbA1c, and TyG index) preceded DunedinPACE increases, and TyG index preceded PCGrimAA increases. Glycemic traits are positively associated with epigenetic age metrics, especially DunedinPACE. Glycemic traits preceded the increases in DunedinPACE and PCGrimAA. Lowering the levels of glycemic traits may reduce DunedinPACE and PCGrimAA, thereby mitigating age-related comorbidities.
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Affiliation(s)
- Ke Miao
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Runhua Hu
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Zengchang Pang
- Qingdao Center for Disease Control and PreventionQingdaoChina
| | - Min Yu
- Zhejiang Center for Disease Control and PreventionHangzhouChina
| | - Hua Wang
- Jiangsu Center for Disease Control and PreventionNanjingChina
| | - Xianping Wu
- Sichuan Center for Disease Control and PreventionChengduChina
| | - Yu Liu
- Heilongjiang Center for Disease Control and PreventionHarbinChina
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public HealthPeking UniversityBeijingChina
- Key Laboratory of Epidemiology of Major Diseases (Peking University)Ministry of EducationBeijingChina
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5
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Lu WH. Effect of Modifiable Lifestyle Factors on Biological Aging. JAR LIFE 2024; 13:88-92. [PMID: 38855439 PMCID: PMC11161669 DOI: 10.14283/jarlife.2024.13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Accepted: 05/31/2024] [Indexed: 06/11/2024]
Abstract
Biological age is a concept that uses bio-physiological parameters to account for individual heterogeneity in the biological processes driving aging and aims to enhance the prediction of age-related clinical conditions compared to chronological age. Although engaging in healthy lifestyle behaviors has been linked to a lower mortality risk and a reduced incidence of chronic diseases, it remains unclear to what extent these health benefits result from slowing the pace of the biological aging process. This short review summarized how modifiable lifestyle factors - including diet, physical activity, smoking, alcohol consumption, and the aggregate of multiple healthy behaviors - were associated with established estimates of biological age based on clinical or cellular/molecular markers, including Klemera-Doubal Method biological age, homeostatic dysregulation, phenotypic age, DNA methylation age, and telomere length. In brief, the available studies tend to show a consistent association of lifestyle factors with physiological measures of biological age, while findings regarding molecular-based metrics vary. The limited evidence highlights the need for further research in this field, particularly with a life-course approach.
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Affiliation(s)
- W-H Lu
- IHU HealthAge, Toulouse, France
- Institute on Aging, Toulouse University Hospital (CHU Toulouse), Toulouse, France
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da Silva Rodrigues G, Noma IHY, Noronha NY, Watanabe LM, da Silva Sobrinho AC, de Lima JGR, Sae-Lee C, Benjamim CJR, Nonino CB, Bueno CR. Eight Weeks of Physical Training Decreases 2 Years of DNA Methylation Age of Sedentary Women. RESEARCH QUARTERLY FOR EXERCISE AND SPORT 2024; 95:405-415. [PMID: 37466924 DOI: 10.1080/02701367.2023.2228388] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 06/06/2023] [Indexed: 07/20/2023]
Abstract
Purpose: The acceleration of epigenetic age is a predictor of mortality and contributes to the increase in chronic diseases. Adherence to a healthy lifestyle is a strategy to reduce epigenetic age. The present study aimed to determine whether eight weeks of combined (aerobic and strength) training (CT) can influence the epigenetic age of women between 50 and 70 years old and the differences in sites and methylated regions. Methods: Eighteen women (AARLow: lower age acceleration residual, n = 10; AARHigh: higher age acceleration residual, n = 8) participated in a combined exercise training program (60 minutes, 3× a week) for eight weeks. DNA was extracted from whole blood using the salting out technique. DNA methylation was performed using the array technique (Illumina's Infinium Methylation BeadChip 850k). We used the DNA Methylation Age Calculator platform to calculate the biological epigenetic age. Two-way ANOVA followed by FISHER LSD posthoc was Applied, adopting p < .05. Results: After eight weeks of CT, there were no changes to the epigenetic age acceleration for the AARLow group (PRE: -2.3 ± 3.2 to POST: -2.3 ± 3.6). However, the AARHigh group significantly decreased the age acceleration (PRE: 3.6 ± 2.6 to POST: 2.2 ± 2.7) (group effect, p = .01; time effect, p = .31; group vs. time effect, p = .005). Conclusion: CT for eight weeks benefits the epigenetic clock of women with the most accelerated age.
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Kawamura T, Higuchi M, Ito T, Kawakami R, Usui C, McGreevy KM, Horvath S, Zsolt R, Torii S, Suzuki K, Ishii K, Sakamoto S, Oka K, Muraoka I, Tanisawa K. Healthy Japanese dietary pattern is associated with slower biological aging in older men: WASEDA'S health study. Front Nutr 2024; 11:1373806. [PMID: 38854166 PMCID: PMC11157009 DOI: 10.3389/fnut.2024.1373806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Accepted: 05/14/2024] [Indexed: 06/11/2024] Open
Abstract
Aging is the greatest risk factor for numerous diseases and mortality, and establishing geroprotective interventions targeting aging is required. Previous studies have suggested that healthy dietary patterns, such as the Mediterranean diet, are associated with delayed biological aging; however, these associations depend on nationality and sex. Therefore, this study aimed to investigate the relationship between dietary patterns identified through principal component analysis and biological aging in older men of Japan, one of the countries with the longest life expectancies. Principal component analysis identified two dietary patterns: a healthy Japanese dietary pattern and a Western-style dietary pattern. Eight epigenetic clocks, some of the most accurate aging biomarkers, were identified using DNA methylation data from whole-blood samples. Correlation analyses revealed that healthy Japanese dietary patterns were significantly negatively or positively correlated with multiple epigenetic age accelerations (AgeAccel), including AgeAccelGrim, FitAgeAccel, and age-adjusted DNAm-based telomere length (DNAmTLAdjAge). Conversely, the Western-style dietary pattern was observed not to correlate significantly with any of the examined AgeAccels or age-adjusted values. After adjusting for covariates, the healthy Japanese dietary pattern remained significantly positively correlated with DNAmTLAdjAge. Regression analysis showed that healthy Japanese dietary pattern contributed less to epigenetic age acceleration than smoking status. These findings suggest that a Western-style dietary pattern may not be associated with biological aging, whereas a healthy Japanese dietary pattern is associated with delayed biological aging in older Japanese men. Our findings provide evidence that healthy dietary patterns may have mild beneficial effects on delayed biological aging in older Japanese men.
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Affiliation(s)
- Takuji Kawamura
- Waseda Institute for Sport Sciences, Waseda University, Saitama, Japan
- Research Center for Molecular Exercise Science, Hungarian University of Sports Science, Budapest, Hungary
| | - Mitsuru Higuchi
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
| | - Tomoko Ito
- Waseda Institute for Sport Sciences, Waseda University, Saitama, Japan
- Department of Food and Nutrition, Tokyo Kasei University, Tokyo, Japan
| | - Ryoko Kawakami
- Waseda Institute for Sport Sciences, Waseda University, Saitama, Japan
- Physical Fitness Research Institute, Meiji Yasuda Life Foundation of Health and Welfare, Tokyo, Japan
| | - Chiyoko Usui
- Waseda Institute for Sport Sciences, Waseda University, Saitama, Japan
- Center for Liberal Education and Learning, Sophia University, Tokyo, Japan
| | - Kristen M. McGreevy
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States
| | - Steve Horvath
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Altos Labs, San Diego Institute of Science, San Diego, CA, United States
| | - Radak Zsolt
- Research Center for Molecular Exercise Science, Hungarian University of Sports Science, Budapest, Hungary
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
| | - Suguru Torii
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
| | | | - Kaori Ishii
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
| | - Shizuo Sakamoto
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
- Faculty of Sport Science, Surugadai University, Saitama, Japan
| | - Koichiro Oka
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
| | - Isao Muraoka
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
| | - Kumpei Tanisawa
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
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8
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Folger AT, Ding L, Yolton K, Ammerman RT, Ji H, Frey JR, Bowers KA. Association between maternal prenatal depressive symptoms and offspring epigenetic aging at 3-5 weeks. Ann Epidemiol 2024; 93:1-6. [PMID: 38479709 PMCID: PMC11031304 DOI: 10.1016/j.annepidem.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 02/26/2024] [Accepted: 03/08/2024] [Indexed: 04/21/2024]
Abstract
Epigenetic clocks are emerging as tools for assessing acceleration and deceleration of biological age during childhood. Maternal depression during pregnancy may affect the biological aging of offspring and related development. In a low-income cohort of mother-child dyads, we investigated the relationship between prenatal maternal depressive symptoms and infant epigenetic age residuals, which represent the deviation (acceleration or deceleration) that exists between predicted biological age and chronological age. The epigenetic age residuals were derived from a pediatric-specific buccal epithelial clock. We hypothesized that maternal depressive symptoms, both sub-clinical and elevated (clinical level), would be associated with estimated biological age deceleration in offspring during early infancy. We analyzed data from 94 mother-child dyads using the Edinburgh Postnatal Depression Scale (EPDS) and DNA methylation derived from offspring buccal cells collected at 3-5 weeks of age. There was a significant non-linear association between the EPDS score and epigenetic age residual (β = -0.017, 95% confidence interval: -0.03,-0.01, P = <0.01). The results indicated that infants of mothers with sub-clinical depressive symptoms had the lowest infant epigenetic age residuals while infants of mothers with no-to-low depressive symptoms had the highest and experienced biological age acceleration. Maternal depressive symptoms may influence the biological aging of offspring living in poverty.
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Affiliation(s)
- Alonzo T Folger
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States.
| | - Lili Ding
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Kimberly Yolton
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Robert T Ammerman
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Hong Ji
- Department of Anatomy Physiology and Cell biology, School of Veterinary Medicine, California National Primate Research Center, University of California Davis, Davis, CA, United States
| | - Jennifer R Frey
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Katherine A Bowers
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
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9
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Sun X, Chen W, Razavi AC, Shi M, Pan Y, Li C, Argos M, Layden BT, Daviglus ML, He J, Carmichael OT, Bazzano LA, Kelly TN. Associations of Epigenetic Age Acceleration With CVD Risks Across the Lifespan: The Bogalusa Heart Study. JACC Basic Transl Sci 2024; 9:577-590. [PMID: 38984046 PMCID: PMC11228118 DOI: 10.1016/j.jacbts.2024.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 01/09/2024] [Accepted: 01/09/2024] [Indexed: 07/11/2024]
Abstract
Although epigenetic age acceleration (EAA) might serve as a molecular signature of childhood cardiovascular disease (CVD) risk factors and further promote midlife subclinical CVD, few studies have comprehensively examined these life course associations. This study sought to test whether childhood CVD risk factors predict EAA in adulthood and whether EAA mediates the association between childhood CVD risks and midlife subclinical disease. Among 1,580 Bogalusa Heart Study participants, we estimated extrinsic EAA, intrinsic EAA, PhenoAge acceleration (PhenoAgeAccel), and GrimAge acceleration (GrimAgeAccel) during adulthood. We tested prospective associations of longitudinal childhood body mass index (BMI), blood pressure, lipids, and glucose with EAAs using linear mixed effects models. After confirming EAAs with midlife carotid intima-media thickness and carotid plaque, structural equation models examined mediating effects of EAAs on associations of childhood CVD risk factors with subclinical CVD measures. After stringent multiple testing corrections, each SD increase in childhood BMI was significantly associated with 0.6-, 0.9-, and 0.5-year increases in extrinsic EAA, PhenoAgeAccel, and GrimAgeAccel, respectively (P < 0.001 for all 3 associations). Likewise, each SD increase in childhood log-triglycerides was associated with 0.5- and 0.4-year increases in PhenoAgeAccel and GrimAgeAccel (P < 0.001 for both), respectively, whereas each SD increase in childhood high-density lipoprotein cholesterol was associated with a 0.3-year decrease in GrimAgeAccel (P = 0.002). Our findings indicate that PhenoAgeAccel mediates an estimated 27.4% of the association between childhood log-triglycerides and midlife carotid intima-media thickness (P = 0.022). Our data demonstrate that early life CVD risk factors may accelerate biological aging and promote subclinical atherosclerosis.
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Affiliation(s)
- Xiao Sun
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Wei Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Alexander C Razavi
- Emory Clinical Cardiovascular Research Institute, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Mengyao Shi
- Department of Epidemiology, School of Public Health, and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases Medical College of Soochow University, Jiangsu, China
| | - Yang Pan
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Maria Argos
- Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois Chicago, Chicago, Illinois, USA
| | - Brian T Layden
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | | | - Lydia A Bazzano
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Tanika N Kelly
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
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10
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Noroozi R, Rudnicka J, Pisarek A, Wysocka B, Masny A, Boroń M, Migacz-Gruszka K, Pruszkowska-Przybylska P, Kobus M, Lisman D, Zielińska G, Iljin A, Wiktorska JA, Michalczyk M, Kaczka P, Krzysztofik M, Sitek A, Ossowski A, Spólnicka M, Branicki W, Pośpiech E. Analysis of epigenetic clocks links yoga, sleep, education, reduced meat intake, coffee, and a SOCS2 gene variant to slower epigenetic aging. GeroScience 2024; 46:2583-2604. [PMID: 38103096 PMCID: PMC10828238 DOI: 10.1007/s11357-023-01029-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/23/2023] [Indexed: 12/17/2023] Open
Abstract
DNA methylation (DNAm) clocks hold promise for measuring biological age, useful for guiding clinical interventions and forensic identification. This study compared the commonly used DNAm clocks, using DNA methylation and SNP data generated from nearly 1000 human blood or buccal swab samples. We evaluated different preprocessing methods for age estimation, investigated the association of epigenetic age acceleration (EAA) with various lifestyle and sociodemographic factors, and undertook a series of novel genome-wide association analyses for different EAA measures to find associated genetic variants. Our results highlighted the Skin&Blood clock with ssNoob normalization as the most accurate predictor of chronological age. We provided novel evidence for an association between the practice of yoga and a reduction in the pace of aging (DunedinPACE). Increased sleep and physical activity were associated with lower mortality risk score (MRS) in our dataset. University degree, vegetable consumption, and coffee intake were associated with reduced levels of epigenetic aging, whereas smoking, higher BMI, meat consumption, and manual occupation correlated well with faster epigenetic aging, with FitAge, GrimAge, and DunedinPACE clocks showing the most robust associations. In addition, we found a novel association signal for SOCS2 rs73218878 (p = 2.87 × 10-8) and accelerated GrimAge. Our study emphasizes the importance of an optimized DNAm analysis workflow for accurate estimation of epigenetic age, which may influence downstream analyses. The results support the influence of genetic background on EAA. The associated SOCS2 is a member of the suppressor of cytokine signaling family known for its role in human longevity. The reported association between various risk factors and EAA has practical implications for the development of health programs to improve quality of life and reduce premature mortality associated with age-related diseases.
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Affiliation(s)
- Rezvan Noroozi
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Krakow, Poland
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joanna Rudnicka
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Krakow, Poland
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
| | - Aleksandra Pisarek
- Institute of Zoology and Biomedical Research of the Jagiellonian University, Krakow, Poland
| | - Bożena Wysocka
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | | | - Michał Boroń
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | | | | | - Magdalena Kobus
- Institute of Biological Sciences, Faculty of Biology and Environmental Sciences, Cardinal Stefan Wyszynski University in Warsaw, Warsaw, Poland
| | - Dagmara Lisman
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Grażyna Zielińska
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Aleksandra Iljin
- Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Lodz, Lodz, Poland
| | | | - Małgorzata Michalczyk
- Department of Sport Nutrition, The Jerzy Kukuczka Academy of Physical Education in Katowice, Katowice, Poland
| | - Piotr Kaczka
- Department of Sport Nutrition, The Jerzy Kukuczka Academy of Physical Education in Katowice, Katowice, Poland
| | - Michał Krzysztofik
- Department of Sport Nutrition, The Jerzy Kukuczka Academy of Physical Education in Katowice, Katowice, Poland
| | - Aneta Sitek
- Department of Anthropology, University of Lodz, Lodz, Poland
| | - Andrzej Ossowski
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | | | - Wojciech Branicki
- Institute of Zoology and Biomedical Research of the Jagiellonian University, Krakow, Poland
- Institute of Forensic Research, Krakow, Poland
| | - Ewelina Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland.
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11
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Moore AZ, Simonsick EM, Landman B, Schrack J, Wanigatunga AA, Ferrucci L. Correlates of life course physical activity in participants of the Baltimore longitudinal study of aging. Aging Cell 2024; 23:e14078. [PMID: 38226778 PMCID: PMC11019133 DOI: 10.1111/acel.14078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/17/2024] Open
Abstract
Physical activity is consistently associated with better health and longer life spans. However, the extent to which length and intensity of exercise across the life course impact health outcomes relative to current activity is undefined. Participants of the Baltimore Longitudinal Study of Aging were asked to categorize their level of physical activity in each decade of life from adolescence to the current decade. In linear mixed effects models, self-reported past levels of physical activity were significantly associated with activity assessed at study visits in the corresponding decade of life either by questionnaire or accelerometry. A pattern of life course physical activity (LCPA) derived by ranking participants on reported activity intensity across multiple decades was consistent with the trajectories of activity estimated from standard physical activity questionnaires assessed at prior study visits. In multivariable linear regression models LCPA was associated with clinical characteristics, measures of body composition and indicators of physical performance independent of current physical activity. After adjustment for minutes of high intensity exercise, LCPA remained significantly associated with peak VO2, fasting glucose, thigh muscle area and density, abdominal subcutaneous fat, usual gait speed, lower extremity performance, and multimorbidity (all p < 0.01) at the index visit. The observed associations suggest that an estimate of physical activity across decades provides complementary information to information on current activity and reemphasizes the importance of consistently engaging in physical activity over the life course.
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Affiliation(s)
- Ann Zenobia Moore
- Translational Gerontology Branch, Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Eleanor M. Simonsick
- Translational Gerontology Branch, Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Bennett Landman
- Department of Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Jennifer Schrack
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Center on Aging and HealthJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Amal A. Wanigatunga
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Center on Aging and HealthJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Luigi Ferrucci
- Translational Gerontology Branch, Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
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12
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Li DL, Hodge AM, Cribb L, Southey MC, Giles GG, Milne RL, Dugué PA. Body Size, Diet Quality, and Epigenetic Aging: Cross-Sectional and Longitudinal Analyses. J Gerontol A Biol Sci Med Sci 2024; 79:glae026. [PMID: 38267386 PMCID: PMC10953795 DOI: 10.1093/gerona/glae026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Indexed: 01/26/2024] Open
Abstract
Epigenetic age is an emerging marker of health that is highly predictive of disease and mortality risk. There is a lack of evidence on whether lifestyle changes are associated with changes in epigenetic aging. We used data from 1 041 participants in the Melbourne Collaborative Cohort Study with blood DNA methylation measures at baseline (1990-1994, mean age: 57.4 years) and follow-up (2003-2007, mean age: 68.8 years). The Alternative Healthy Eating Index-2010 (AHEI-2010), the Mediterranean Dietary Score, and the Dietary Inflammatory Index were used as measures of diet quality, and weight, waist circumference, and waist-to-hip ratio as measures of body size. Five age-adjusted epigenetic aging measures were considered: GrimAge, PhenoAge, PCGrimAge, PCPhenoAge, and DunedinPACE. Multivariable linear regression models including restricted cubic splines were used to assess the cross-sectional and longitudinal associations of body size and diet quality with epigenetic aging. Associations between weight and epigenetic aging cross-sectionally at both time points were positive and appeared greater for DunedinPACE (per SD: β ~0.24) than for GrimAge and PhenoAge (β ~0.10). The longitudinal associations with weight change were markedly nonlinear (U-shaped) with stable weight being associated with the lowest epigenetic aging at follow-up, except for DunedinPACE, for which only weight gain showed a positive association. We found negative, linear associations for AHEI-2010 both cross-sectionally and longitudinally. Other adiposity measures and dietary scores showed similar results. In middle-aged to older adults, declining diet quality and weight gain may increase epigenetic age, while the association for weight loss may require further investigation. Our study sheds light on the potential of weight management and dietary improvement in slowing aging processes.
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Affiliation(s)
- Danmeng Lily Li
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Allison M Hodge
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Lachlan Cribb
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Graham G Giles
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Roger L Milne
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Pierre-Antoine Dugué
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
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13
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Wu D, Qu C, Huang P, Geng X, Zhang J, Shen Y, Rao Z, Zhao J. Better Life's Essential 8 contributes to slowing the biological aging process: a cross-sectional study based on NHANES 2007-2010 data. Front Public Health 2024; 12:1295477. [PMID: 38544722 PMCID: PMC10965682 DOI: 10.3389/fpubh.2024.1295477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 02/07/2024] [Indexed: 05/03/2024] Open
Abstract
Objective To investigate the relationship between Life's Essential 8 (LE8) and Phenotypic Age Acceleration (PhenoAgeAccel) in United States adults and to explore the impact of LE8 on phenotypic biological aging, thereby providing references for public health policies and health education. Methods Utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2010, this cross-sectional study analyzed 7,339 adults aged 20 and above. Comprehensive assessments of LE8, PhenoAgeAccel, and research covariates were achieved through the integration of Demographics Data, Dietary Data, Laboratory Data, and Questionnaire Data derived from NHANES. Weighted generalized linear regression models and restricted cubic spline plots were employed to analyze the linear and non-linear associations between LE8 and PhenoAgeAccel, along with gender subgroup analysis and interaction effect testing. Results (1) Dividing the 2007-2010 NHANES cohort into quartiles based on LE8 unveiled significant disparities in age, gender, race, body mass index, education level, marital status, poverty-income ratio, smoking and drinking statuses, diabetes, hypertension, hyperlipidemia, phenotypic age, PhenoAgeAccel, and various biological markers (p < 0.05). Mean cell volume demonstrated no intergroup differences (p > 0.05). (2) The generalized linear regression weighted models revealed a more pronounced negative correlation between higher quartiles of LE8 (Q2, Q3, and Q4) and PhenoAgeAccel compared to the lowest LE8 quartile in both crude and fully adjusted models (p < 0.05). This trend was statistically significant (p < 0.001) in the full adjustment model. Gender subgroup analysis within the fully adjusted models exhibited a significant negative relationship between LE8 and PhenoAgeAccel in both male and female participants, with trend tests demonstrating significant results (p < 0.001 for males and p = 0.001 for females). (3) Restricted cubic spline (RCS) plots elucidated no significant non-linear trends between LE8 and PhenoAgeAccel overall and in gender subgroups (p for non-linear > 0.05). (4) Interaction effect tests denoted no interaction effects between the studied stratified variables such as age, gender, race, education level, and marital status on the relationship between LE8 and PhenoAgeAccel (p for interaction > 0.05). However, body mass index and diabetes manifested interaction effects (p for interaction < 0.05), suggesting that the influence of LE8 on PhenoAgeAccel might vary depending on an individual's BMI and diabetes status. Conclusion This study, based on NHANES data from 2007-2010, has revealed a significant negative correlation between LE8 and PhenoAgeAccel, emphasizing the importance of maintaining a healthy lifestyle in slowing down the biological aging process. Despite the limitations posed by the study's design and geographical constraints, these findings provide a scientific basis for the development of public health policies focused on healthy lifestyle practices. Future research should further investigate the causal mechanisms underlying the relationship between LE8 and PhenoAgeAccel and consider cross-cultural comparisons to enhance our understanding of healthy aging.
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Affiliation(s)
- Dongzhe Wu
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
| | - Chaoyi Qu
- Physical Education College, Hebei Normal University, Shijiazhuang, China
| | - Peng Huang
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
| | - Xue Geng
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
| | | | - Yulin Shen
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
| | - Zhijian Rao
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
- College of Physical Education, Shanghai Normal University, Shanghai, China
| | - Jiexiu Zhao
- Exercise Biological Center, China Institute of Sport Science, Beijing, China
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14
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Li J, Wang W, Yang Z, Qiu L, Ren Y, Wang D, Li M, Li W, Gao F, Zhang J. Causal association of obesity with epigenetic aging and telomere length: a bidirectional mendelian randomization study. Lipids Health Dis 2024; 23:78. [PMID: 38475782 DOI: 10.1186/s12944-024-02042-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 02/05/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND In observational studies, there exists an association between obesity and epigenetic age as well as telomere length. However, varying and partially conflicting outcomes have notably arisen from distinct studies on this topic. In the present study, two-way Mendelian randomization was used to identify potential causal associations between obesity and epigenetic age and telomeres. METHODS A genome-wide association study was conducted using data from individuals of European ancestry to investigate bidirectional Mendelian randomization (MR) regarding the causal relationships between obesity, as indicated by three obesity indicators (body mass index or BMI, waist circumference adjusted for BMI or WCadjBMI, and waist-to-hip ratio adjusted for BMI or WHRadjBMI), and four epigenetic age measures (HannumAge, HorvathAge, GrimAge, PhenoAge), as well as telomere length. To assess these causal associations, various statistical methods were employed, including Inverse Variance Weighted (IVW), Weighted Median, MR Egger, Weighted Mode, and Simple Mode. To address the issue of multiple testing, we applied the Bonferroni correction. These methods were used to determine whether there is a causal link between obesity and epigenetic age, as well as telomere length, and to explore potential bidirectional relationships. Forest plots and scatter plots were generated to show causal associations between exposures and outcomes. For a comprehensive visualization of the results, leave-one-out sensitivity analysis plots, individual SNP-based forest plots for MR analysis, and funnel plots were included in the presentation of the results. RESULTS A strong causal association was identified between obesity and accelerated HannumAge, GrimAge, PhenoAge and telomere length shrinkage. The causal relationship between WCadjBMI and PhenoAge acceleration (OR: 2.099, 95%CI: 1.248-3.531, p = 0.005) was the strongest among them. However, only the p-values for the causal associations of obesity with GrimAge, PhenoAge, and telomere length met the criteria after correction using the Bonferroni multiple test. In the reverse MR analysis, there were statistically significant causal associations between HorvathAge, PhenoAge and GrimAge and BMI, but these associations exhibited lower effect sizes, as indicated by their Odds Ratios (ORs). Notably, sensitivity analysis revealed the robustness of the study results. CONCLUSIONS The present findings reveal a causal relationship between obesity and the acceleration of epigenetic aging as well as the reduction of telomere length, offering valuable insights for further scientific investigations aimed at developing strategies to mitigate the aging process in humans.
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Affiliation(s)
- Jixin Li
- Chinese Academy of Traditional Chinese Medicine, Xiyuan Hospital, Beijing, China
| | - Wenru Wang
- Chinese Academy of Traditional Chinese Medicine, Xiyuan Hospital, Beijing, China
| | - Zhenyu Yang
- Heilongjiang University Of Chinese Medicine, Harbin, China
| | - Linjie Qiu
- Chinese Academy of Traditional Chinese Medicine, Xiyuan Hospital, Beijing, China
| | - Yan Ren
- Chinese Academy of Traditional Chinese Medicine, Xiyuan Hospital, Beijing, China
| | - Dongling Wang
- Chinese Academy of Traditional Chinese Medicine, Xiyuan Hospital, Beijing, China
| | - Meijie Li
- Chinese Academy of Traditional Chinese Medicine, Xiyuan Hospital, Beijing, China
| | - Wenjie Li
- Chinese Academy of Traditional Chinese Medicine, Xiyuan Hospital, Beijing, China
| | - Feng Gao
- Chinese Academy of Traditional Chinese Medicine, Xiyuan Hospital, Beijing, China.
| | - Jin Zhang
- Chinese Academy of Traditional Chinese Medicine, Xiyuan Hospital, Beijing, China.
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15
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Saarinen A, Marttila S, Mishra PP, Lyytikäinen L, Raitoharju E, Mononen N, Sormunen E, Kähönen M, Raitakari O, Hietala J, Keltikangas‐Järvinen L, Lehtimäki T. Polygenic risk for schizophrenia, social dispositions, and pace of epigenetic aging: Results from the Young Finns Study. Aging Cell 2024; 23:e14052. [PMID: 38031635 PMCID: PMC10928579 DOI: 10.1111/acel.14052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/26/2023] [Accepted: 11/15/2023] [Indexed: 12/01/2023] Open
Abstract
Schizophrenia is often regarded as a disorder of premature aging. We investigated (a) whether polygenic risk for schizophrenia (PRSsch ) relates to pace of epigenetic aging and (b) whether personal dispositions toward active and emotionally close relationships protect against accelerated epigenetic aging in individuals with high PRSsch . The sample came from the population-based Young Finns Study (n = 1348). Epigenetic aging was measured with DNA methylation aging algorithms such as AgeAccelHannum , EEAAHannum , IEAAHannum , IEAAHorvath , AgeAccelHorvath , AgeAccelPheno , AgeAccelGrim , and DunedinPACE. A PRSsch was calculated using summary statistics from the most comprehensive genome-wide association study of schizophrenia to date. Social dispositions were assessed in terms of extraversion, sociability, reward dependence, cooperativeness, and attachment security. We found that PRSsch did not have a statistically significant effect on any studied indicator of epigenetic aging. Instead, PRSsch had a significant interaction with reward dependence (p = 0.001-0.004), cooperation (p = 0.009-0.020), extraversion (p = 0.019-0.041), sociability (p = 0.003-0.016), and attachment security (p = 0.007-0.014) in predicting AgeAccelHannum , EEAAHannum , or IEAAHannum . Specifically, participants with high PRSsch appeared to display accelerated epigenetic aging at higher (vs. lower) levels of extraversion, sociability, attachment security, reward dependence, and cooperativeness. A rather opposite pattern was evident for those with low PRSsch . No such interactions were evident when predicting the other indicators of epigenetic aging. In conclusion, against our hypothesis, frequent social interactions may relate to accelerated epigenetic aging in individuals at risk for psychosis. We speculate that this may be explained by social-cognitive impairments (perceiving social situations as overwhelming or excessively arousing) or ending up in less supportive or deviant social groups.
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Affiliation(s)
- Aino Saarinen
- Department of Psychology and Logopedics, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
- Helsinki University Central HospitalAdolescent Psychiatry Outpatient ClinicHelsinkiFinland
| | - Saara Marttila
- Department of Molecular Epidemiology, Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Gerontology Research CenterTampere UniversityTampereFinland
| | - Pashupati P. Mishra
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical ChemistryFimlab LaboratoriesTampereFinland
- Finnish Cardiovascular Research CenterTampereFinland
| | - Leo‐Pekka Lyytikäinen
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical ChemistryFimlab LaboratoriesTampereFinland
- Finnish Cardiovascular Research CenterTampereFinland
- Department of Cardiology, Heart CenterTampere University HospitalTampereFinland
| | - Emma Raitoharju
- Department of Molecular Epidemiology, Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Cardiovascular Research Center Tampere, Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
| | - Nina Mononen
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical ChemistryFimlab LaboratoriesTampereFinland
- Finnish Cardiovascular Research CenterTampereFinland
- Cardiovascular Research Center Tampere, Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
| | - Elina Sormunen
- Department of PsychiatryUniversity of TurkuTurkuFinland
- Turku University HospitalTurkuFinland
| | - Mika Kähönen
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical PhysiologyTampere University HospitalTampereFinland
| | - Olli Raitakari
- Turku University HospitalTurkuFinland
- Research Centre of Applied and Preventive Cardiovascular MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchUniversity of TurkuTurkuFinland
- Department of Clinical Physiology and Nuclear MedicineTurku University HospitalTurkuFinland
| | - Jarmo Hietala
- Department of PsychiatryUniversity of TurkuTurkuFinland
- Turku University HospitalTurkuFinland
- Department of MedicineUniversity of TurkuTurkuFinland
- Division of MedicineTurku University HospitalTurkuFinland
| | | | - Terho Lehtimäki
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical ChemistryFimlab LaboratoriesTampereFinland
- Finnish Cardiovascular Research CenterTampereFinland
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16
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Gao T, Zheng Y, Joyce BT, Kho M, Terry JG, Wang J, Nannini D, Carr JJ, Nair S, Zhang K, Zhao W, Jacobs DR, Schreiner PJ, Greenland P, Lloyd-Jones D, Smith JA, Hou L. Epigenetic Aging Is Associated With Measures of Midlife Muscle Volume and Attenuation in CARDIA Study. J Gerontol A Biol Sci Med Sci 2024; 79:glad261. [PMID: 37956337 PMCID: PMC10876078 DOI: 10.1093/gerona/glad261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND GrimAge acceleration (GAA), an epigenetic marker that represents physiologic aging, is associated with age-related diseases including cancer and cardiovascular diseases. However, the associations between GAA and muscle mass and function are unknown. METHODS We estimated measures of GAA in 1 118 Black and White participants from the Coronary Artery Risk Development in Young Adults (CARDIA) Study at exam years (Y) 15 (2000-2001) and 20 (2005-2006). Abdominal muscle composition was measured using CT scans at the Y25 (2010-2011) visit. We used multivariate regression models to examine associations of GAA estimates with muscle imaging measurements. RESULTS In the CARDIA study, each 1-year higher GAA was associated with an average 1.1% (95% confidence interval [CI]: 0.6%, 1.5%) higher intermuscular adipose tissue (IMAT) volume for abdominal muscles. Each 1-year higher GAA was associated with an average -0.089 Hounsfield unit (HU; 95% CI: -0.146, -0.032) lower lean muscle attenuation and an average -0.049 HU (95% CI: -0.092, -0.007) lower IMAT attenuation for abdominal muscles. Stratified analyses showed that GAA was more strongly associated with higher abdominal muscle IMAT volume in females and significantly associated with lower lean muscle attenuation for White participants only. CONCLUSIONS Higher GAA is associated with higher abdominal muscle IMAT volume and lower lean muscle attenuation in a midlife population.
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Affiliation(s)
- Tao Gao
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Brian T Joyce
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - James G Terry
- Department of Radiology, Vanderbilt University Medicine Center, Nashville, Tennessee, USA
| | - Jun Wang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Drew Nannini
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - John Jeffrey Carr
- Department of Radiology, Vanderbilt University Medicine Center, Nashville, Tennessee, USA
| | - Sangeeta Nair
- Department of Radiology, Vanderbilt University Medicine Center, Nashville, Tennessee, USA
| | - Kai Zhang
- Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Albany, New York, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - David R Jacobs
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Donald Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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17
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Dalecka A, Bartoskova Polcrova A, Pikhart H, Bobak M, Ksinan AJ. Living in poverty and accelerated biological aging: evidence from population-representative sample of U.S. adults. BMC Public Health 2024; 24:458. [PMID: 38350911 PMCID: PMC10865704 DOI: 10.1186/s12889-024-17960-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 02/01/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Biological aging reflects a decline in the functions and integrity of the human body that is closely related to chronological aging. A variety of biomarkers have been found to predict biological age. Biological age higher than chronological age (biological age acceleration) indicates an accelerated state of biological aging and a higher risk of premature morbidity and mortality. This study investigated how socioeconomic disadvantages influence biological aging. METHODS The data from the National Health and Nutrition Examination Survey (NHANES) IV, including 10 nationally representative cross-sectional surveys between 1999-2018, were utilized. The analytic sample consisted of N = 48,348 individuals (20-84 years). We used a total of 11 biomarkers for estimating the biological age. Our main outcome was biological age acceleration, indexed by PhenoAge acceleration (PAA) and Klemera-Doubal biological age acceleration (KDM-A). Poverty was measured as a ratio of family income to the poverty thresholds defined by the U.S. Census Bureau, adjusted annually for inflation and family size (5 categories). The PAA and KDM-A were regressed on poverty levels, age, their interaction, education, sex, race, and a data collection wave. Sample weights were used to make the estimates representative of the U.S. adult population. RESULTS The results showed that higher poverty was associated with accelerated biological aging (PAA: unstandardized coefficient B = 1.38 p <.001, KDM: B = 0.96, p = .026 when comparing the highest and the lowest poverty level categories), above and beyond other covariates. The association between PAA and KDM-A and age was U-shaped. Importantly, there was an interaction between poverty levels and age (p <.001), as the effect of poverty was most pronounced in middle-aged categories while it was modest in younger and elderly groups. CONCLUSION In a nationally representative US adult population, we found that higher poverty was positively associated with the acceleration of biological age, particularly among middle-aged persons.
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Affiliation(s)
- Andrea Dalecka
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno, Czech Republic
| | | | - Hynek Pikhart
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno, Czech Republic
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Martin Bobak
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno, Czech Republic
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Albert J Ksinan
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno, Czech Republic.
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18
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Kawamura T, Radak Z, Tabata H, Akiyama H, Nakamura N, Kawakami R, Ito T, Usui C, Jokai M, Torma F, Kim H, Miyachi M, Torii S, Suzuki K, Ishii K, Sakamoto S, Oka K, Higuchi M, Muraoka I, McGreevy KM, Horvath S, Tanisawa K. Associations between cardiorespiratory fitness and lifestyle-related factors with DNA methylation-based ageing clocks in older men: WASEDA'S Health Study. Aging Cell 2024; 23:e13960. [PMID: 37584423 PMCID: PMC10776125 DOI: 10.1111/acel.13960] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/31/2023] [Accepted: 08/02/2023] [Indexed: 08/17/2023] Open
Abstract
DNA methylation-based age estimators (DNAm ageing clocks) are currently one of the most promising biomarkers for predicting biological age. However, the relationships between cardiorespiratory fitness (CRF), measured directly by expiratory gas analysis, and DNAm ageing clocks are largely unknown. We investigated the relationships between CRF and the age-adjusted value from the residuals of the regression of DNAm ageing clock to chronological age (DNAmAgeAcceleration: DNAmAgeAccel) and attempted to determine the relative contribution of CRF to DNAmAgeAccel in the presence of other lifestyle factors. DNA samples from 144 Japanese men aged 65-72 years were used to appraise first- (i.e., DNAmHorvath and DNAmHannum) and second- (i.e., DNAmPhenoAge, DNAmGrimAge, and DNAmFitAge) generation DNAm ageing clocks. Various surveys and measurements were conducted, including physical fitness, body composition, blood biochemical parameters, nutrient intake, smoking, alcohol consumption, disease status, sleep status, and chronotype. Both oxygen uptake at ventilatory threshold (VO2 /kg at VT) and peak oxygen uptake (VO2 /kg at Peak) showed a significant negative correlation with GrimAgeAccel, even after adjustments for chronological age and smoking and drinking status. Notably, VO2 /kg at VT and VO2 /kg at Peak above the reference value were also associated with delayed GrimAgeAccel. Multiple regression analysis showed that calf circumference, serum triglyceride, carbohydrate intake, and smoking status, rather than CRF, contributed more to GrimAgeAccel and FitAgeAccel. In conclusion, although the contribution of CRF to GrimAgeAccel and FitAgeAccel is relatively low compared to lifestyle-related factors such as smoking, the results suggest that the maintenance of CRF is associated with delayed biological ageing in older men.
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Affiliation(s)
- Takuji Kawamura
- Waseda Institute for Sport Sciences, Waseda UniversitySaitamaJapan
- Research Centre for Molecular Exercise ScienceHungarian University of Sports ScienceBudapestHungary
| | - Zsolt Radak
- Research Centre for Molecular Exercise ScienceHungarian University of Sports ScienceBudapestHungary
- Faculty of Sport SciencesWaseda UniversitySaitamaJapan
| | - Hiroki Tabata
- Waseda Institute for Sport Sciences, Waseda UniversitySaitamaJapan
- Sportology CentreJuntendo University Graduate School of MedicineTokyoJapan
| | - Hiroshi Akiyama
- Graduate School of Sport SciencesWaseda UniversitySaitamaJapan
| | | | - Ryoko Kawakami
- Waseda Institute for Sport Sciences, Waseda UniversitySaitamaJapan
- Physical Fitness Research Institute, Meiji Yasuda Life Foundation of Health and WelfareTokyoJapan
| | - Tomoko Ito
- Waseda Institute for Sport Sciences, Waseda UniversitySaitamaJapan
- Department of Food and NutritionTokyo Kasei UniversityTokyoJapan
| | - Chiyoko Usui
- Faculty of Sport SciencesWaseda UniversitySaitamaJapan
| | - Matyas Jokai
- Research Centre for Molecular Exercise ScienceHungarian University of Sports ScienceBudapestHungary
| | - Ferenc Torma
- Faculty of Health and Sport SciencesUniversity of TsukubaIbarakiJapan
| | - Hyeon‐Ki Kim
- Research Centre for Molecular Exercise ScienceHungarian University of Sports ScienceBudapestHungary
| | | | - Suguru Torii
- Faculty of Sport SciencesWaseda UniversitySaitamaJapan
| | | | - Kaori Ishii
- Faculty of Sport SciencesWaseda UniversitySaitamaJapan
| | - Shizuo Sakamoto
- Faculty of Sport SciencesWaseda UniversitySaitamaJapan
- Faculty of Sport ScienceSurugadai UniversitySaitamaJapan
| | - Koichiro Oka
- Faculty of Sport SciencesWaseda UniversitySaitamaJapan
| | | | - Isao Muraoka
- Faculty of Sport SciencesWaseda UniversitySaitamaJapan
| | - Kristen M. McGreevy
- Department of Biostatistics, Fielding School of Public HealthUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Steve Horvath
- Department of Biostatistics, Fielding School of Public HealthUniversity of California Los AngelesLos AngelesCaliforniaUSA
- Department of Human Genetics, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesCaliforniaUSA
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19
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Kresovich JK, O’Brien KM, Xu Z, Weinberg CR, Sandler DP, Taylor JA. Changes in methylation-based aging in women who do and do not develop breast cancer. J Natl Cancer Inst 2023; 115:1329-1336. [PMID: 37467056 PMCID: PMC10637033 DOI: 10.1093/jnci/djad117] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 06/09/2023] [Accepted: 06/16/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND Breast cancer survivors have increased incidence of age-related diseases, suggesting that some survivors may experience faster biological aging. METHODS Among 417 women enrolled in the prospective Sister Study cohort, DNA methylation data were generated on paired blood samples collected an average of 7.7 years apart and used to calculate 3 epigenetic metrics of biological aging (PhenoAgeAccel, GrimAgeAccel, and Dunedin Pace of Aging Calculated from the Epigenome [DunedinPACE]). Approximately half (n = 190) the women sampled were diagnosed and treated for breast cancer between blood draws, whereas the other half (n = 227) remained breast cancer-free. Breast tumor characteristics and treatment information were abstracted from medical records. RESULTS Among women who developed breast cancer, diagnoses occurred an average of 3.5 years after the initial blood draw and 4 years before the second draw. After accounting for covariates and biological aging metrics measured at baseline, women diagnosed and treated for breast cancer had higher biological aging at the second blood draw than women who remained cancer-free as measured by PhenoAgeAccel (standardized mean difference [β] = 0.13, 95% confidence interval [CI) = 0.00 to 0.26), GrimAgeAccel (β = 0.14, 95% CI = 0.03 to 0.25), and DunedinPACE (β = 0.37, 95% CI = 0.24 to 0.50). In case-only analyses assessing associations with different breast cancer therapies, radiation had strong positive associations with biological aging (PhenoAgeAccel: β = 0.39, 95% CI = 0.19 to 0.59; GrimAgeAccel: β = 0.29, 95% CI = 0.10 to 0.47; DunedinPACE: β = 0.25, 95% CI = 0.02 to 0.48). CONCLUSIONS Biological aging is accelerated following a breast cancer diagnosis and treatment. Breast cancer treatment modalities appear to differentially contribute to biological aging.
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Affiliation(s)
- Jacob K Kresovich
- Departments of Cancer Epidemiology & Breast Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Katie M O’Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
- Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
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20
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McCarthy K, O'Halloran AM, Fallon P, Kenny RA, McCrory C. Metabolic syndrome accelerates epigenetic ageing in older adults: Findings from The Irish Longitudinal Study on Ageing (TILDA). Exp Gerontol 2023; 183:112314. [PMID: 37883858 DOI: 10.1016/j.exger.2023.112314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/29/2023] [Accepted: 10/16/2023] [Indexed: 10/28/2023]
Abstract
Metabolic syndrome (MetS) is a risk factor for the development of diabetes, cardiovascular disease, and all-cause mortality. It has an estimated prevalence of 40 % among older adults. Epigenetic clocks, which measure biological age based on DNA methylation (DNAm) patterns, are a candidate biomarker for ageing. GrimAge is one such clock which is based on levels of DNAm at 100 Cytosine-phosphate-Guanine (CpG) sites. This study hypothesised that those with MetS have 'accelerated ageing' (biological age greater than their chronological age) as indexed by GrimAge. This study examined MetS's association with GrimAge age acceleration (AA) using data from a subsample of 469 participants of the Irish Longitudinal Study on Ageing (TILDA). MetS was defined by National Cholesterol Education Program Third Adult Treatment Panel (ATP III) and International Diabetes Foundation (IDF) criteria, operationalised using the conventional binary cut-off, and as a count variable ranging from 0 to 5, based on the presence of individual components. This study also explored inflammation (as measured by C reactive protein) and metabolic dysfunction (as measured by adiponectin) as possible mediating factors between MetS and GrimAge AA. We found that MetS as defined by IDF criteria was associated with GrimAge AA of 0.63 years. When MetS was treated as a count, each unit increase in MetS score was associated with over 0.3 years GrimAge AA for both ATP III and IDF criteria. Inflammation mediated approximately one third of the association between MetS and GrimAge AA, suggesting that chronic subclinical inflammation observed in MetS has a relationship with DNAm changes consistent with a faster pace of ageing. Metabolic dysfunction mediated the association between MetS and GrimAge AA to a lesser extent (16 %). These data suggest that chronic subclinical inflammation observed in MetS has a relationship with DNAm changes consistent with a greater pace of ageing.
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Affiliation(s)
- Kevin McCarthy
- School of Medicine, Trinity College Dublin, Dublin 2, Ireland; Mercer's Institute for Successful Ageing, St James's Hospital, Dublin 8, Ireland.
| | | | - Padraic Fallon
- School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Rose Anne Kenny
- School of Medicine, Trinity College Dublin, Dublin 2, Ireland; Mercer's Institute for Successful Ageing, St James's Hospital, Dublin 8, Ireland
| | - Cathal McCrory
- School of Medicine, Trinity College Dublin, Dublin 2, Ireland
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21
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Waterfield S, Richardson TG, Davey Smith G, O’Keeffe LM, Bell JA. Life course effects of genetic susceptibility to higher body size on body fat and lean mass: prospective cohort study. Int J Epidemiol 2023; 52:1377-1387. [PMID: 36952292 PMCID: PMC10555894 DOI: 10.1093/ije/dyad029] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 02/27/2023] [Indexed: 03/24/2023] Open
Abstract
BACKGROUND/OBJECTIVES Different genetic variants are associated with larger body size in childhood vs adulthood. Whether and when these variants predominantly influence adiposity are unknown. We examined how genetic variants influence total body fat and total lean mass trajectories. METHODS Data were from the Avon Longitudinal Study of Parents and Children birth cohort (N = 6926). Sex-specific genetic risk scores (GRS) for childhood and adulthood body size were generated, and dual-energy X-ray absorptiometry scans measured body fat and lean mass six times between the ages of 9 and 25 years. Multilevel linear spline models examined associations of GRS with fat and lean mass trajectories. RESULTS In males, the sex-specific childhood and adulthood GRS were associated with similar differences in fat mass from 9 to 18 years; 8.3% [95% confidence interval (CI) 5.1, 11.6] and 7.5% (95% CI 4.3, 10.8) higher fat mass at 18 years per standard deviation (SD) higher childhood and adulthood GRS, respectively. In males, the sex-combined childhood GRS had stronger effects at ages 9 to 15 than the sex-combined adulthood GRS. In females, associations for the sex-specific childhood GRS were almost 2-fold stronger than the adulthood GRS from 9 to 18 years: 10.5% (95% CI 8.5, 12.4) higher fat mass at 9 years per SD higher childhood GRS compared with 5.1% (95% CI 3.2, 6.9) per-SD higher adulthood GRS. In females, the sex-combined GRS had similar effects, with slightly larger effect estimates. Lean mass effect sizes were much smaller. CONCLUSIONS Genetic variants for body size are more strongly associated with adiposity than with lean mass. Sex-combined childhood variants are more strongly associated with increased adiposity until early adulthood. This may inform future studies that use genetics to investigate the causes and impact of adiposity at different life stages.
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Affiliation(s)
- Scott Waterfield
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Cancer Research UK Integrative Cancer Epidemiology Programme, University of Bristol, Bristol, UK
| | - Tom G Richardson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Linda M O’Keeffe
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- School of Public Health, University College Cork, Cork, Ireland
| | - Joshua A Bell
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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22
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Thomas A, Belsky D, Gu Y. Healthy Lifestyle Behaviors and Biological Aging in the U.S. National Health and Nutrition Examination Surveys 1999-2018. J Gerontol A Biol Sci Med Sci 2023; 78:1535-1542. [PMID: 36896965 PMCID: PMC10460553 DOI: 10.1093/gerona/glad082] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Indexed: 03/11/2023] Open
Abstract
People who have a balanced diet and engage in more physical activity live longer, healthier lives. This study aimed to test the hypothesis that these associations reflect a slowing of biological processes of aging. We analyzed data from 42 625 participants (aged 20-84 years, 51% female participants) from the National Health and Nutrition Examination Surveys (NHANES), 1999-2018. We calculated adherence to a Mediterranean diet (MeDi) and level of leisure time physical activity (LTPA) using standard methods. We measured biological aging by applying the PhenoAge algorithm, developed using clinical and mortality data from NHANES-III (1988-94), to clinical chemistries measured from a blood draw at the time of the survey. We tested the associations of diet and physical activity measures with biological aging, explored synergies between these health behaviors, and tested heterogeneity in their associations across strata of age, sex, and body mass index. Participants who adhered to the MeDi and who did more LTPA had younger biological ages compared with those who had less-healthy lifestyles (high vs low MeDi tertiles: β = 0.14 standard deviation [SD] [95% confidence interval {CI}: -0.18, -0.11]; high vs sedentary LTPA, β = 0.12 SD [-0.15, -0.09]), in models controlled for demographic and socioeconomic characteristics. Healthy diet and regular physical activity were independently associated with lower clinically defined biological aging, regardless of age, sex, and BMI category.
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Affiliation(s)
- Aline Thomas
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Daniel W Belsky
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, New York, USA
- Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Yian Gu
- Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, New York, USA
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Gertrude H. Sergievsky Center, and Department of Neurology, Columbia University, New York, New York, USA
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23
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Galkin F, Kovalchuk O, Koldasbayeva D, Zhavoronkov A, Bischof E. Stress, diet, exercise: Common environmental factors and their impact on epigenetic age. Ageing Res Rev 2023; 88:101956. [PMID: 37211319 DOI: 10.1016/j.arr.2023.101956] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 05/13/2023] [Accepted: 05/15/2023] [Indexed: 05/23/2023]
Abstract
Epigenetic aging clocks have gained significant attention as a tool for predicting age-related health conditions in clinical and research settings. They have enabled geroscientists to study the underlying mechanisms of aging and assess the effectiveness of anti-aging therapies, including diet, exercise and environmental exposures. This review explores the effects of modifiable lifestyle factors' on the global DNA methylation landscape, as seen by aging clocks. We also discuss the underlying mechanisms through which these factors contribute to biological aging and provide comments on what these findings mean for people willing to build an evidence-based pro-longevity lifestyle.
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Affiliation(s)
| | - Olga Kovalchuk
- Department of Biological Sciences, University of Lethbridge, Canada
| | | | - Alex Zhavoronkov
- Deep Longevity, Hong Kong; Insilico Medicine, Hong Kong; Buck Institute for Research on Aging, Novato, CA, USA
| | - Evelyne Bischof
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Department of Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China; Shanghai University of Medicine and Health Sciences, Shanghai, China; Division of Cardiology, Department of Advanced Biomedical Sciences, Federico II University, Via S. Pansini, 580131, Naples, Italy
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24
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Kankaanpää A, Tolvanen A, Joensuu L, Waller K, Heikkinen A, Kaprio J, Ollikainen M, Sillanpää E. The associations of long-term physical activity in adulthood with later biological ageing and all-cause mortality - a prospective twin study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.02.23290916. [PMID: 37333101 PMCID: PMC10274991 DOI: 10.1101/2023.06.02.23290916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Objectives The association between leisure-time physical activity (LTPA) and a lower risk of mortality is susceptible to bias from multiple sources. We investigated the potential of biological ageing to mediate the association between long-term LTPA and mortality and whether the methods used to account for reverse causality affect the interpretation of this association. Methods Study participants were twins from the older Finnish Twin Cohort (n=22,750; 18-50 years at baseline). LTPA was assessed using questionnaires in 1975, 1981 and 1990. The mortality follow-up lasted until 2020 and biological ageing was assessed using epigenetic clocks in a subsample (n=1,153) with blood samples taken during the follow-up. Using latent profile analysis, we identified classes with distinct longitudinal LTPA patterns and studied differences in biological ageing between these classes. We employed survival models to examine differences in total, short-term and long-term all-cause mortality, and multilevel models for twin data to control for familial factors. Results We identified four classes of long-term LTPA: sedentary, moderately active, active and highly active. Although biological ageing was accelerated in sedentary and highly active classes, after adjusting for other lifestyle-related factors, the associations mainly attenuated. Physically active classes had a maximum 7% lower risk of total mortality over the sedentary class, but this association was consistent only in the short term and could largely be accounted for by familial factors. LTPA exhibited less favourable associations when prevalent diseases were exclusion criteria rather than covariate. Conclusion Being active may reflect a healthy phenotype instead of causally reducing mortality.
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Affiliation(s)
- Anna Kankaanpää
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Asko Tolvanen
- Methodology Center for Human Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Laura Joensuu
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Katja Waller
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Elina Sillanpää
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
- Wellbeing services county of Central Finland, Jyväskylä, Finland
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Lohman T, Bains G, Cole S, Gharibvand L, Berk L, Lohman E. High-Intensity interval training reduces transcriptomic age: A randomized controlled trial. Aging Cell 2023; 22:e13841. [PMID: 37078430 PMCID: PMC10265161 DOI: 10.1111/acel.13841] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 03/22/2023] [Accepted: 03/25/2023] [Indexed: 04/21/2023] Open
Abstract
While the relationship between exercise and life span is well-documented, little is known about the effects of specific exercise protocols on modern measures of biological age. Transcriptomic age (TA) predictors provide an opportunity to test the effects of high-intensity interval training (HIIT) on biological age utilizing whole-genome expression data. A single-site, single-blinded, randomized controlled clinical trial design was utilized. Thirty sedentary participants (aged 40-65) were assigned to either a HIIT group or a no-exercise control group. After collecting baseline measures, HIIT participants performed three 10 × 1 HIIT sessions per week for 4 weeks. Each session lasted 23 min, and total exercise duration was 276 min over the course of the 1-month exercise protocol. TA, PSS-10 score, PSQI score, PHQ-9 score, and various measures of body composition were all measured at baseline and again following the conclusion of exercise/control protocols. Transcriptomic age reduction of 3.59 years was observed in the exercise group while a 3.29-years increase was observed in the control group. Also, PHQ-9, PSQI, BMI, body fat mass, and visceral fat measures were all improved in the exercise group. A hypothesis-generation gene expression analysis suggested exercise may modify autophagy, mTOR, AMPK, PI3K, neurotrophin signaling, insulin signaling, and other age-related pathways. A low dose of HIIT can reduce an mRNA-based measure of biological age in sedentary adults between the ages of 40 and 65 years old. Other changes in gene expression were relatively modest, which may indicate a focal effect of exercise on age-related biological processes.
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Affiliation(s)
- Trevor Lohman
- Loma Linda University School of Allied Health ProfessionsLoma LindaCaliforniaUSA
| | - Gurinder Bains
- Loma Linda University School of Allied Health ProfessionsLoma LindaCaliforniaUSA
| | - Steve Cole
- UCLA David Geffen School of MedicineLos AngelesCaliforniaUSA
| | - Lida Gharibvand
- Loma Linda University School of Allied Health ProfessionsLoma LindaCaliforniaUSA
| | - Lee Berk
- Loma Linda University School of Allied Health Professions, and School of MedicineLoma LindaCaliforniaUSA
| | - Everett Lohman
- Loma Linda University School of Allied Health ProfessionsLoma LindaCaliforniaUSA
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Kresovich JK, Sandler DP, Taylor JA. Methylation-Based Biological Age and Hypertension Prevalence and Incidence. Hypertension 2023; 80:1213-1222. [PMID: 36974720 PMCID: PMC10192055 DOI: 10.1161/hypertensionaha.122.20796] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 03/08/2023] [Indexed: 03/29/2023]
Abstract
BACKGROUND Hypertension is common in older individuals and is a major risk factor for cardiovascular disease. Blood DNA methylation profiles have been used to derive metrics of biological age that capture age-related physiological change, disease risk, and mortality. The relationships between hypertension and DNA methylation-based biological age metrics have yet to be carefully described. METHODS Among 4419 women enrolled in the prospective Sister Study cohort, DNA methylation data generated from whole blood samples collected at baseline were used to calculate 3 biological age metrics (PhenoAgeAccel, GrimAgeAccel, DunedinPACE). Women were classified as hypertensive at baseline if they had high blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg) or reported current use of antihypertensive medication. New incident cases of hypertension during follow-up were identified via self-report on annual health questionnaires. RESULTS All 3 DNA methylation metrics of biological age were positively associated with prevalent hypertension at baseline (per 1-SD increase; PhenoAgeAccel, adjusted odds ratio, 1.16 [95% CI, 1.05-1.28]; GrimAgeAccel, adjusted odds ratio, 1.28 [95% CI, 1.14-1.45]; DunedinPACE, adjusted odds ratio, 1.16 [95% CI, 1.03-1.30]). Among 2610 women who were normotensive at baseline, women with higher biological age were more likely to be diagnosed with incident hypertension (per 1-SD increase; PhenoAgeAccel, adjusted hazard ratio, 1.09 [95% CI, 0.97-1.23]; GrimAgeAccel, adjusted hazard ratio, 1.16 [95% CI, 0.99-1.36]; DunedinPACE, adjusted hazard ratio, 1.16 [95% CI, 1.01-1.33]). CONCLUSIONS Methylation-based biological age metrics increase before a hypertension diagnosis and appear to remain elevated in the years after clinical diagnosis and treatment.
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Affiliation(s)
- Jacob K Kresovich
- Departments of Cancer Epidemiology & Breast Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL (J.K.K.)
| | - Dale P Sandler
- Epidemiology Branch (D.P.S., J.A.T.), National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC
| | - Jack A Taylor
- Epigenetic and Stem Cell Biology Laboratory (J.A.T.), National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC
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Wang H, Bakulski KM, Blostein F, Porath BR, Dou J, Tejera CH, Ware EB. Depressive symptoms are associated with DNA methylation age acceleration in a cross-sectional analysis of adults over age 50 in the United States. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.24.23289052. [PMID: 37162942 PMCID: PMC10168518 DOI: 10.1101/2023.04.24.23289052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Background Major depressive disorder affects mental well-being and accelerates DNA methylation age, a marker of biological aging. Subclinical depressive symptoms and DNA methylation aging have not been explored. Objective To assess the cross-sectional association between depressive symptoms and accelerated DNA methylation aging among United States adults over age 50. Methods We included 3,793 participants from the 2016 wave of the Health and Retirement Study. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression scale and operationalized as high versus low/no. Blood DNA methylation GrimAge was regressed on chronologic age to obtain acceleration. Multiple linear regression assessed the relationship between high depressive symptoms and GrimAge acceleration, controlling for demographic factors, health behaviors, and cell type proportions. We investigated sex and race/ethnicity stratified associations. Results Participants were 42% male, 14% had high depressive symptoms, 44% had accelerated GrimAge, and were mean age 70 years. In our fully adjusted model, those with high depressive symptoms had 0.40 (95%CI: 0.06, 0.73) years accelerated GrimAge, compared to those with low/no depressive symptoms. The association between depressive symptoms and GrimAge acceleration was larger in male participants ( P = 0.04). Conclusion Higher depressive symptoms were associated with accelerated DNA methylation age among older adults.
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28
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Laviano A. Sarcopenia, biological age and treatment eligibility in patients with cancer. Curr Opin Clin Nutr Metab Care 2023; 26:59-63. [PMID: 36542536 DOI: 10.1097/mco.0000000000000888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
PURPOSE OF REVIEW Cancer incidence will dramatically increase, especially among older adults, during the next few decades. This may lead to bankruptcy of the healthcare systems worldwide if the current approach to treatment eligibility is not improved. In fact, current treatment personalization is mostly focusing on the genetic and molecular characteristics of cancer cells, whereas clinical characterization of patients is still dependent on gross variables (i.e. chronological age, BMI, comorbidities, Performance Status and so on). This could have contributed to the poor performance of many anticancer drugs in the real-world setting when compared with the results obtained in prospective, randomized clinical trials. RECENT FINDINGS The role of chronological age in identifying patients with increased likelihood to respond to therapies has been challenged, pointing to biological age (i.e. accumulated damage to biological systems over the life course, leading to loss of reserve and capacity to respond to challenges) as a robust predictor of outcome encompassing genetic, phenotypic and clinical factors. Sarcopenia has been proposed as a reliable clinical index of biological age, but the complexity of body composition changes occurring during tumour growth appears to preclude its routine use when assessing eligibility in cancer patients. SUMMARY Integration of sarcopenia measures within scores of allostatic load may further increase the clinical relevance of changes of body composition, highlight its sensitivity to early nutritional intervention leading to mitigation of accelerated ageing, and contribute to wide delivery of precision oncology.
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Affiliation(s)
- Alessandro Laviano
- Department of Translational and Precision Medicine, Sapienza University, Rome, Italy
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29
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Kresovich JK, Xu Z, O'Brien KM, Parks CG, Weinberg CR, Sandler DP, Taylor JA. Peripheral Immune Cell Composition is Altered in Women Before and After a Hypertension Diagnosis. Hypertension 2023; 80:43-53. [PMID: 36259385 PMCID: PMC9742333 DOI: 10.1161/hypertensionaha.122.20001] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 09/29/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND The development and consequences of hypertension involve multiple biological systems that may include changes in immune profiles. Whether hypertension is related to peripheral immune cell composition has not been examined in large human cohorts. METHODS We estimated circulating proportions of 12 leukocyte subsets from the lymphoid and myeloid lineages by deconvolving cell-type-specific DNA methylation data from 4124 women. Hypertension status at baseline was defined by current use of antihypertensive medication and blood pressure measurements while new incident cases were identified during follow-up via annual health questionnaires. RESULTS Among hypertension-free women at baseline, higher B cell and lower naïve CD4+ helper T cell proportions were associated with subsequent increased hazard of hypertension incidence (B cells; adjusted HR: 1.17 [95% CI: 1.02-1.35]; P=0.03; naïve CD4+ T cell, adjusted HR: 0.88 [95% CI: 0.78-0.99]; P=0.04). Blood pressure measurements at baseline were similarly positively associated with B cells and inversely associated with naïve CD4+ helper T cells. Compared to normotensive women, women with hypertension had higher circulating proportions of neutrophils (adjusted odds ratio: 1.18 [95% CI: 1.07-1.31]; P=0.001) and lower proportions of CD4+ helper T cells (adjusted odds ratio: 0.90 [95% CI: 0.81-1.00] P=0.05), natural killers (adjusted odds ratio: 0.82 [95% CI: 0.74-0.91]; P<0.001), and B cells (adjusted odds ratio: 0.84 [95% CI: 0.74-0.96]; P=0.01). CONCLUSIONS These observations suggest that shifts in lymphocyte subsets occur before hypertension development, followed by later changes to neutrophils and additional lymphocytes.
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Affiliation(s)
- Jacob K Kresovich
- Departments of Cancer Epidemiology and Breast Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL (J.K.K.)
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC (J.K.K., Z.X., K.M.O., C.G.P., D.P.S., J.A.T.)
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC (J.K.K., Z.X., K.M.O., C.G.P., D.P.S., J.A.T.)
| | - Katie M O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC (J.K.K., Z.X., K.M.O., C.G.P., D.P.S., J.A.T.)
| | - Christine G Parks
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC (J.K.K., Z.X., K.M.O., C.G.P., D.P.S., J.A.T.)
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC (C.R.W.)
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC (J.K.K., Z.X., K.M.O., C.G.P., D.P.S., J.A.T.)
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC (J.K.K., Z.X., K.M.O., C.G.P., D.P.S., J.A.T.)
- Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC (J.A.T.)
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Evaluation of Epigenetic Age Acceleration Scores and Their Associations with CVD-Related Phenotypes in a Population Cohort. BIOLOGY 2022; 12:biology12010068. [PMID: 36671760 PMCID: PMC9855929 DOI: 10.3390/biology12010068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/19/2022] [Accepted: 12/22/2022] [Indexed: 01/04/2023]
Abstract
We evaluated associations between nine epigenetic age acceleration (EAA) scores and 18 cardiometabolic phenotypes using an Eastern European ageing population cohort richly annotated for a diverse set of phenotypes (subsample, n = 306; aged 45-69 years). This was implemented by splitting the data into groups with positive and negative EAAs. We observed strong association between all EAA scores and sex, suggesting that any analysis of EAAs should be adjusted by sex. We found that some sex-adjusted EAA scores were significantly associated with several phenotypes such as blood levels of gamma-glutamyl transferase and low-density lipoprotein, smoking status, annual alcohol consumption, multiple carotid plaques, and incident coronary heart disease status (not necessarily the same phenotypes for different EAAs). We demonstrated that even after adjusting EAAs for sex, EAA-phenotype associations remain sex-specific, which should be taken into account in any downstream analysis involving EAAs. The obtained results suggest that in some EAA-phenotype associations, negative EAA scores (i.e., epigenetic age below chronological age) indicated more harmful phenotype values, which is counterintuitive. Among all considered epigenetic clocks, GrimAge was significantly associated with more phenotypes than any other EA scores in this Russian sample.
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31
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Hu Y, Wang X, Huan J, Zhang L, Lin L, Li Y, Li Y. Effect of dietary inflammatory potential on the aging acceleration for cardiometabolic disease: A population-based study. Front Nutr 2022; 9:1048448. [PMID: 36532557 PMCID: PMC9755741 DOI: 10.3389/fnut.2022.1048448] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 11/18/2022] [Indexed: 09/16/2023] Open
Abstract
BACKGROUND/AIM Optimized dietary patterns have been considered an important determinant of delaying aging in cardiometabolic disease (CMD). Dietary pattern with high-level dietary inflammatory potential is a key risk factor for cardiometabolic disease, and has drawn increasing attention. The aim of this study was to investigate whether dietary pattern with high dietary inflammatory potential was associated with aging acceleration in cardiometabolic disease. MATERIALS AND METHODS We analyzed the cross-sectional data from six survey cycles (1999-2000, 2001-2002, 2003-2004, 2005-2006, 2007-2008, and 2009-2010) of the National Health and Nutritional Examination Surveys (NHANES). A total of 16,681 non-institutionalized adults and non-pregnant females with CMD were included in this study. Dietary inflammatory index (DII) was used to assess the dietary inflammatory potential. The two age acceleration biomarkers were calculated by the residuals from regressing chronologic age on Klemera-Doubal method biological age (KDM BioAge) or Phenotypic Age (PhenoAge), termed "KDMAccel" and "PhenoAgeAccel." A multivariable linear regression accounting for multistage survey design and sampling weights was used in different models to investigate the association between DII and aging acceleration. Four sensitivity analyses were used to ensure the robustness of our results. Besides, we also analyzed the anti-aging effects of DASH-type dietary pattern and "Life's Simple 7". RESULTS For 16,681 participants with CMD, compared with the first tertile of DII after adjusting for all potential confounders, the patients with second tertile of DII showed a 1.02-years increase in KDMAccel and 0.63-years increase in PhenoAgeAccel (KDMAccel, β = 1.02, 95% CI = 0.64 to 1.41, P < 0.001; PhenoAgeAccel, β = 0.63, 95% CI = 0.44 to 0.82, P < 0.001), while the patients with the third tertile of DII showed a 1.48-years increase in KDMAccel and 1.22-years increase in PhenoAgeAccel (KDMAccel, β = 1.48, 95% CI = 1.02 to 1.94, P < 0.001; PhenoAgeAccel, β = 1.22, 95% CI = 1.01 to 1.43, P < 0.001). In addition, DASH-type dietary pattern was associated with a 0.57-years reduction in KDMAccel (β = -0.57, 95% CI = -1.08 to -0.06, P = 0.031) and a 0.54-years reduction in PhenoAgeAccel (β = -0.54, 95% CI = -0.80 to -0.28, P < 0.001). The each one-unit increase in CVH score was associated with a 1.58-years decrease in KDMAccel (β = -1.58, 95% CI = -1.68 to -1.49, P < 0.001) and a 0.36-years in PhenoAgeAccel (β = -0.36, 95% CI = -0.41 to -0.31, P < 0.001). CONCLUSION Among CMD, the dietary pattern with high dietary inflammatory potential was association with aging acceleration, and the anti-aging potential of DASH-type dietary pattern and "Life's Simple 7" should also be given attention, but these observations require future prospective validation.
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Affiliation(s)
- Yuanlong Hu
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Shandong Province Engineering Laboratory of Traditional Chinese Medicine Precise Diagnosis and Treatment of Cardiovascular Disease, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Xiaojie Wang
- Shandong Province Engineering Laboratory of Traditional Chinese Medicine Precise Diagnosis and Treatment of Cardiovascular Disease, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, Macau, China
| | - Jiaming Huan
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Lei Zhang
- Shandong Province Engineering Laboratory of Traditional Chinese Medicine Precise Diagnosis and Treatment of Cardiovascular Disease, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Lin Lin
- Shandong Province Engineering Laboratory of Traditional Chinese Medicine Precise Diagnosis and Treatment of Cardiovascular Disease, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yuan Li
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Key Laboratory of Traditional Chinese Medicine Classical Theory, Ministry of Education, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Shandong Provincial Key Laboratory of Traditional Chinese Medicine for Basic Research, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Yunlun Li
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Shandong Province Engineering Laboratory of Traditional Chinese Medicine Precise Diagnosis and Treatment of Cardiovascular Disease, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
- Department of Cardiovascular, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
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Lundgren S, Kuitunen S, Pietiläinen KH, Hurme M, Kähönen M, Männistö S, Perola M, Lehtimäki T, Raitakari O, Kaprio J, Ollikainen M. BMI is positively associated with accelerated epigenetic aging in twin pairs discordant for body mass index. J Intern Med 2022; 292:627-640. [PMID: 35699258 PMCID: PMC9540898 DOI: 10.1111/joim.13528] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
BACKGROUND Obesity is a heritable complex phenotype that can increase the risk of age-related outcomes. Biological age can be estimated from DNA methylation (DNAm) using various "epigenetic clocks." Previous work suggests individuals with elevated weight also display accelerated aging, but results vary by epigenetic clock and population. Here, we utilize the new epigenetic clock GrimAge, which closely correlates with mortality. OBJECTIVES We aimed to assess the cross-sectional association of body mass index (BMI) with age acceleration in twins to limit confounding by genetics and shared environment. METHODS AND RESULTS Participants were from the Finnish Twin Cohort (FTC; n = 1424), including monozygotic (MZ) and dizygotic (DZ) twin pairs, and DNAm was measured using the Illumina 450K array. Multivariate linear mixed effects models including MZ and DZ twins showed an accelerated epigenetic age of 1.02 months (p-value = 6.1 × 10-12 ) per one-unit BMI increase. Additionally, heavier twins in a BMI-discordant MZ twin pair (ΔBMI >3 kg/m2 ) had an epigenetic age 5.2 months older than their lighter cotwin (p-value = 0.0074). We also found a positive association between log (homeostatic model assessment of insulin resistance) and age acceleration, confirmed by a meta-analysis of the FTC and two other Finnish cohorts (overall effect = 0.45 years, p-value = 4.1 × 10-25 ) from adjusted models. CONCLUSION We identified significant associations of BMI and insulin resistance with age acceleration based on GrimAge, which were not due to genetic effects on BMI and aging. Overall, these results support a role of BMI in aging, potentially in part due to the effects of insulin resistance.
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Affiliation(s)
- Sara Lundgren
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Sara Kuitunen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Obesity Center, Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Mikko Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland.,Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Satu Männistö
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Markus Perola
- Finnish Institute for Health and Welfare, Helsinki, Finland.,Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - 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
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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Franzago M, Pilenzi L, Di Rado S, Vitacolonna E, Stuppia L. The epigenetic aging, obesity, and lifestyle. Front Cell Dev Biol 2022; 10:985274. [PMID: 36176280 PMCID: PMC9514048 DOI: 10.3389/fcell.2022.985274] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 08/22/2022] [Indexed: 11/25/2022] Open
Abstract
The prevalence of obesity has dramatically increased worldwide over the past decades. Aging-related chronic conditions, such as type 2 diabetes and cardiovascular disease, are more prevalent in individuals with obesity, thus reducing their lifespan. Epigenetic clocks, the new metrics of biological age based on DNA methylation patterns, could be considered a reflection of the state of one’s health. Several environmental exposures and lifestyle factors can induce epigenetic aging accelerations, including obesity, thus leading to an increased risk of age-related diseases. The insight into the complex link between obesity and aging might have significant implications for the promotion of health and the mitigation of future disease risk. The present narrative review takes into account the interaction between epigenetic aging and obesity, suggesting that epigenome may be an intriguing target for age-related physiological changes and that its modification could influence aging and prolong a healthy lifespan. Therefore, we have focused on DNA methylation age as a clinical biomarker, as well as on the potential reversal of epigenetic age using a personalized diet- and lifestyle-based intervention.
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Affiliation(s)
- Marica Franzago
- Department of Medicine and Aging, School of Medicine and Health Sciences, G. d’Annunzio University, Chieti, Italy
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
| | - Lucrezia Pilenzi
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
- Department of Psychological Health and Territorial Sciences, School of Medicine and Health Sciences, G. d’Annunzio University, Chieti, Italy
| | - Sara Di Rado
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
| | - Ester Vitacolonna
- Department of Medicine and Aging, School of Medicine and Health Sciences, G. d’Annunzio University, Chieti, Italy
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
| | - Liborio Stuppia
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
- Department of Psychological Health and Territorial Sciences, School of Medicine and Health Sciences, G. d’Annunzio University, Chieti, Italy
- *Correspondence: Liborio Stuppia,
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Cao X, Ma C, Zheng Z, He L, Hao M, Chen X, Crimmins EM, Gill TM, Levine ME, Liu Z. Contribution of life course circumstances to the acceleration of phenotypic and functional aging: A retrospective study. EClinicalMedicine 2022; 51:101548. [PMID: 35844770 PMCID: PMC9284373 DOI: 10.1016/j.eclinm.2022.101548] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/27/2022] [Accepted: 06/20/2022] [Indexed: 10/28/2022] Open
Abstract
Background Accelerated aging leads to increasing burdens of chronic diseases in late life, posing a huge challenge to the society. With two well-developed aging measures (i.e., physiological dysregulation [PD] and frailty index [FI]), this study aimed to evaluate the relative contributions of life course circumstances (e.g., childhood and adulthood socioeconomic status) to variance in aging. Methods We assembled data for 6224 middle-aged and older adults in China from the 2014 life course survey (June to December 2014), the 2015 biomarker collection (July 2015 to January 2016), and the 2015 main survey (July 2015 to January 2016) of the China Health and Retirement Longitudinal Study. Two aging measures (PD and FI) were calculated, with a higher value indicating more accelerated aging. Life course circumstances included childhood (i.e., socioeconomic status, war, health, trauma, relationship, and parents' health) and adulthood circumstances (i.e., socioeconomic status, adversity, and social support), demographics, and behaviours. The Shapley value decomposition, hierarchical clustering, and general linear regression models were performed. Findings The Shapley value decomposition revealed that all included life course circumstances accounted for about 6·3% and 29·7% of variance in PD and FI, respectively. We identified six subpopulations who shared similar patterns in terms of childhood and adulthood circumstances. The most disadvantaged subpopulation (i.e., subpopulation 6 [more childhood trauma and adulthood adversity]) consistently exhibited accelerated aging indicated by the two aging measures. Relative to the most advantaged subpopulation (i.e., subpopulation 1 [less childhood trauma and adulthood adversity]), PD and FI in the most disadvantaged subpopulation were increased by an average of 0·14 (i.e., coefficient, by one-standard deviation, 95% confidence interval [CI] 0·06-0·21; p < 0·0001) and 0·10 (by one-point, 95% CI 0·09-0·11; p < 0·0001), respectively. Interpretation Our findings highlight the different contributions of life course circumstances to phenotypic and functional aging. Special attention should be given to promoting health for the disadvantaged subpopulation and narrowing their health gap with advantaged counterparts. Funding National Natural Science Foundation of China, Milstein Medical Asian American Partnership Foundation, Natural Science Foundation of Zhejiang Province, Fundamental Research Funds for the Central Universities, National Institute on Aging, National Centre for Advancing Translational Sciences, and Yale Alzheimer's Disease Research Centre.
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Affiliation(s)
- Xingqi Cao
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Chao Ma
- School of Economics and Management, Southeast University, Nanjing 211189, Jiangsu, China
| | - Zhoutao Zheng
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Liu He
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Meng Hao
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Xi Chen
- Department of Health Policy and Management, Yale School of Public Health, New Haven, CT 06520, USA
- Department of Economics, Yale University, New Haven, CT 06520, USA
| | - Eileen M. Crimmins
- Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Thomas M. Gill
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520, USA
| | - Morgan E. Levine
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA
| | - Zuyun Liu
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
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Ling C, Bacos K, Rönn T. Epigenetics of type 2 diabetes mellitus and weight change - a tool for precision medicine? Nat Rev Endocrinol 2022; 18:433-448. [PMID: 35513492 DOI: 10.1038/s41574-022-00671-w] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/29/2022] [Indexed: 12/12/2022]
Abstract
Pioneering studies performed over the past few decades demonstrate links between epigenetics and type 2 diabetes mellitus (T2DM), the metabolic disorder with the most rapidly increasing prevalence in the world. Importantly, these studies identified epigenetic modifications, including altered DNA methylation, in pancreatic islets, adipose tissue, skeletal muscle and the liver from individuals with T2DM. As non-genetic factors that affect the risk of T2DM, such as obesity, unhealthy diet, physical inactivity, ageing and the intrauterine environment, have been associated with epigenetic modifications in healthy individuals, epigenetics probably also contributes to T2DM development. In addition, genetic factors associated with T2DM and obesity affect the epigenome in human tissues. Notably, causal mediation analyses found DNA methylation to be a potential mediator of genetic associations with metabolic traits and disease. In the past few years, translational studies have identified blood-based epigenetic markers that might be further developed and used for precision medicine to help patients with T2DM receive optimal therapy and to identify patients at risk of complications. This Review focuses on epigenetic mechanisms in the development of T2DM and the regulation of body weight in humans, with a special focus on precision medicine.
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Affiliation(s)
- Charlotte Ling
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden.
| | - Karl Bacos
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Tina Rönn
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
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Zhang J, Cao X, Chen C, He L, Ren Z, Xiao J, Han L, Wu X, Liu Z. Predictive Utility of Mortality by Aging Measures at Different Hierarchical Levels and the Response to Modifiable Life Style Factors: Implications for Geroprotective Programs. Front Med (Lausanne) 2022; 9:831260. [PMID: 35530042 PMCID: PMC9072659 DOI: 10.3389/fmed.2022.831260] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/14/2022] [Indexed: 01/01/2023] Open
Abstract
Background Aging, as a multi-dimensional process, can be measured at different hierarchical levels including biological, phenotypic, and functional levels. The aims of this study were to: (1) compare the predictive utility of mortality by three aging measures at three hierarchical levels; (2) develop a composite aging measure that integrated aging measures at different hierarchical levels; and (3) evaluate the response of these aging measures to modifiable life style factors. Methods Data from National Health and Nutrition Examination Survey 1999–2002 were used. Three aging measures included telomere length (TL, biological level), Phenotypic Age (PA, phenotypic level), and frailty index (FI, functional level). Mortality information was collected until December 2015. Cox proportional hazards regression and multiple linear regression models were performed. Results A total of 3,249 participants (20–84 years) were included. Both accelerations (accounting for chronological age) of PA and FI were significantly associated with mortality, with HRs of 1.67 [95% confidence interval (CI) = 1.41–1.98] and 1.59 (95% CI = 1.35–1.87), respectively, while that of TL showed non-significant associations. We thus developed a new composite aging measure (named PC1) integrating the accelerations of PA and FI, and demonstrated its better predictive utility relative to each single aging measure. PC1, as well as the accelerations of PA and FI, were responsive to several life style factors including smoking status, body mass index, alcohol consumption, and leisure-time physical activity. Conclusion This study demonstrates that both phenotypic (i.e., PA) and functional (i.e., FI) aging measures can capture mortality risk and respond to modifiable life style factors, despite their inherent differences. Furthermore, the PC1 that integrated phenotypic and functional aging measures outperforms in predicting mortality risk in comparison with each single aging measure, and strongly responds to modifiable life style factors. The findings suggest the complementary of aging measures at different hierarchical levels and highlight the potential of life style-targeted interventions as geroprotective programs.
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Affiliation(s)
- Jingyun Zhang
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Xingqi Cao
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Chen Chen
- National Institute of Environmental and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Liu He
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Ziyang Ren
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Junhua Xiao
- College of Chemistry, Chemical Engineering and Biotechnology, Donghua University, Shanghai, China
| | - Liyuan Han
- Department of Global Health, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
- Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Xifeng Wu
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
- Xifeng Wu
| | - Zuyun Liu
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
- *Correspondence: Zuyun Liu ;
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Moturi S, Ghosh-Choudhary SK, Finkel T. Cardiovascular disease and the biology of aging. J Mol Cell Cardiol 2022; 167:109-117. [PMID: 35421400 DOI: 10.1016/j.yjmcc.2022.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 04/02/2022] [Accepted: 04/07/2022] [Indexed: 10/18/2022]
Abstract
The incidence and prevalence of a wide range of cardiovascular diseases increases as a function of age. This well-established epidemiological relationship suggests that chronological aging might contribute or increase susceptibility to varied conditions such as atherosclerosis, vascular stiffening or heart failure. Here, we explore the mechanistic links that connect both rare and common cardiovascular conditions to the basic biology of aging. These links provide a rational basis to begin to develop a new set of therapeutics targeting the fundamental mechanisms underlying the aging process and suggest that in the near future, age itself might become a modifiable cardiovascular risk factor.
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Affiliation(s)
- Shria Moturi
- Aging Institute, University of Pittsburgh School of Medicine/UPMC, Pittsburgh, PA 15219, United States of America
| | - Shohini K Ghosh-Choudhary
- Aging Institute, University of Pittsburgh School of Medicine/UPMC, Pittsburgh, PA 15219, United States of America
| | - Toren Finkel
- Aging Institute, University of Pittsburgh School of Medicine/UPMC, Pittsburgh, PA 15219, United States of America.
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Foley KE, Diemler CA, Hewes AA, Garceau DT, Sasner M, Howell GR. APOE
ε4 and exercise interact in a sex‐specific manner to modulate dementia risk factors. ALZHEIMER'S & DEMENTIA: TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2022; 8:e12308. [PMID: 35783454 PMCID: PMC9241167 DOI: 10.1002/trc2.12308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 04/23/2022] [Accepted: 05/02/2022] [Indexed: 12/01/2022]
Abstract
Introduction Apolipoprotein E (APOE) ε4 is the strongest genetic risk factor for Alzheimer's disease and related dementias (ADRDs), affecting many different pathways that lead to cognitive decline. Exercise is one of the most widely proposed prevention and intervention strategies to mitigate risk and symptomology of ADRDs. Importantly, exercise and APOE ε4 affect similar processes in the body and brain. While both APOE ε4 and exercise have been studied extensively, their interactive effects are not well understood. Methods To address this, male and female APOE ε3/ε3, APOE ε3/ε4, and APOE ε4/ε4 mice ran voluntarily from wean (1 month) to midlife (12 months). Longitudinal and cross‐sectional phenotyping were performed on the periphery and the brain, assessing markers of risk for dementia such as weight, body composition, circulating cholesterol composition, murine daily activities, energy expenditure, and cortical and hippocampal transcriptional profiling. Results Data revealed chronic running decreased age‐dependent weight gain, lean and fat mass, and serum low‐density lipoprotein concentration dependent on APOE genotype. Additionally, murine daily activities and energy expenditure were significantly influenced by an interaction between APOE genotype and running in both sexes. Transcriptional profiling of the cortex and hippocampus predicted that APOE genotype and running interact to affect numerous biological processes including vascular integrity, synaptic/neuronal health, cell motility, and mitochondrial metabolism, in a sex‐specific manner. Discussion These data in humanized mouse models provide compelling evidence that APOE genotype should be considered for population‐based strategies that incorporate exercise to prevent ADRDs and other APOE‐relevant diseases.
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Affiliation(s)
- Kate E. Foley
- The Jackson Laboratory Bar Harbor Maine USA
- School of Graduate Biomedical Sciences Tufts University School of Medicine Boston Massachusetts USA
| | | | - Amanda A. Hewes
- The Jackson Laboratory Bar Harbor Maine USA
- Department of Psychology University of Maine Orono Maine USA
| | | | | | - Gareth R. Howell
- The Jackson Laboratory Bar Harbor Maine USA
- School of Graduate Biomedical Sciences Tufts University School of Medicine Boston Massachusetts USA
- Graduate School of Biomedical Sciences and Engineering University of Maine Orono Maine USA
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Wright ML, Widen EM. Is high dietary quality the real fountain of youth? Am J Clin Nutr 2021; 115:6-7. [PMID: 35022666 PMCID: PMC8755151 DOI: 10.1093/ajcn/nqab356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
| | - Elizabeth M Widen
- Department of Nutritional Sciences, Dell Medical School, Department of Women's Health & Pediatrics, University of Texas at Austin, Austin, TX, USA
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40
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Kresovich JK, Park YMM, Keller JA, Sandler DP, Taylor JA. Healthy eating patterns and epigenetic measures of biological age. Am J Clin Nutr 2021; 115:171-179. [PMID: 34637497 PMCID: PMC8754996 DOI: 10.1093/ajcn/nqab307] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 09/02/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Healthy eating is associated with lower risks of disease and mortality, but the mechanisms underlying these associations are unclear. Age is strongly related to health outcomes, and biological age can be estimated using the blood methylome. OBJECTIVES To determine whether healthy eating patterns are associated with methylation-based measures of biological age. METHODS Among women in the Sister Study, we calculated scores on 4 recommendation-based healthy eating indexes [Dietary Approaches to Stop Hypertension diet, Healthy Eating Index-2015, Alternative Healthy Eating Index (aHEI-2010), and the Alternative Mediterranean diet] using a validated 110-item Block FFQ completed at enrollment. Genome-wide DNA methylation data were generated using the HumanMethylation450 BeadChip on whole blood samples collected at enrollment from a case-cohort sample of 2694 women and were used to calculate 4 measures of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, and GrimAgeAccel). Linear regression models, adjusted for covariates and cohort sampling weights, were used to examine cross-sectional associations between eating patterns and measures of biological age. RESULTS All 4 healthy eating indexes had inverse associations with epigenetic age acceleration, most notably with PhenoAgeAccel and GrimAgeAccel. Of these, the strongest associations were for aHEI-2010 [per 1-SD increase in diet quality, PhenoAgeAccel β = -0.5 y (95% CI: -0.8 to -0.2 y) and GrimAgeAccel β = -0.4 y (95% CI: -0.6 to -0.3 y)]. Although effect modification was not observed for most lifestyle factors, in analyses stratified by physical activity, the benefits of a healthy diet on epigenetic age acceleration were more pronounced among women who did not meet physical activity guidelines (reporting <2.5 h/wk of exercise). CONCLUSIONS Higher diet quality is inversely associated with methylation-based measures of biological age. Improving diet could have the most benefits in lowering biological age among women with lower levels of physical activity. This trial was registered at clinicaltrials.gov as NCT00047970.
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Affiliation(s)
- Jacob K Kresovich
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Yong-Moon Mark Park
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA,Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | | | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
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Kresovich JK, Bulka CM. Low serum klotho associated with all-cause mortality among a nationally representative sample of American adults. J Gerontol A Biol Sci Med Sci 2021; 77:452-456. [PMID: 34628493 DOI: 10.1093/gerona/glab308] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Indexed: 11/14/2022] Open
Abstract
α-Klotho (klotho) is a protein involved in suppressing oxidative stress and inflammation. In animal models, it is reported to underlie numerous aging phenotypes and longevity. Among a nationally representative sample of adults aged 40 to 79 in the United States, we investigated whether circulating concentrations of klotho is a marker of mortality risk. Serum klotho was measured by ELISA on 10,069 individuals enrolled in the National Health and Nutrition Examination Survey between 2007-2014. Mortality follow-up data based on the National Death Index were available through December 31, 2015. After a mean follow-up of 58 months (range: 1-108), 616 incident deaths occurred. Using survey-weighted Cox regression models adjusted for age, sex and survey cycle, low serum klotho concentration (< 666 pg/mL) was associated with a 31% higher risk of death (compared to klotho concentration > 985 pg/mL, HR: 1.31, 95% CI: 1.00, 1.71, P= 0.05). Associations were consistent for mortality caused by heart disease or cancer. Associations of klotho with all-cause mortality did not appear to differ by most participant characteristics. However, we observed effect modification by physical activity, such that low levels of serum klotho were more strongly associated with mortality among individuals who did not meet recommendation-based physical activity guidelines. Our findings suggest that, among the general population of American adults, circulating levels of klotho may serve as a marker of mortality risk.
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Affiliation(s)
- Jacob K Kresovich
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC
| | - Catherine M Bulka
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
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42
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Lin WY, Wang YC, Teng IH, Liu C, Lou XY. Associations of five obesity metrics with epigenetic age acceleration: Evidence from 2,474 Taiwan Biobank participants. Obesity (Silver Spring) 2021; 29:1731-1738. [PMID: 34472716 DOI: 10.1002/oby.23255] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/16/2021] [Accepted: 06/18/2021] [Indexed: 12/23/2022]
Abstract
OBJECTIVE Obesity is associated with epigenetic age acceleration (EAA), resulting in an increased risk of many age-related disorders. However, most studies have focused on the relationship of EAA with BMI. Whether any other obesity metric is more relevant to EAA remains unknown. METHODS Here, the methylation ages of 2,474 Taiwan Biobank (TWB) participants were calculated according to Levine's phenotypic age (PhenoAge) and Lu's GrimAge. Residuals from regressing methylation age on chronological age were used to quantify PhenoEAA and GrimEAA. Five obesity metrics were evaluated, namely BMI, body fat percentage, waist circumference, hip circumference, and waist-hip ratio. Sex-stratified EAA was regressed on each of the five obesity metrics. RESULTS For male individuals, an increase of one SD in waist-hip ratio (0.06) was associated with a 0.602-year PhenoEAA (p = 6.3E-6) and a 0.481-year GrimEAA (p = 1.2E-8). For female individuals, every SD increase in BMI (3.7 kg/m2 ) was associated with a 0.600-year PhenoEAA (p = 3.3E-5) and a 0.305-year GrimEAA (p = 3.1E-5). CONCLUSIONS "Abdominal obesity" and "general obesity" are significantly associated with male and female EAA, respectively. The prevention of abdominal obesity and general obesity is associated with a lower risk of EAA in men and women, respectively.
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Affiliation(s)
- Wan-Yu Lin
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
- Master of Public Health Degree Program, College of Public Health, National Taiwan University, Taipei, Taiwan
- Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Yu-Cyuan Wang
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - I-Hsuan Teng
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chi Liu
- Master Program in Statistics, National Taiwan University, Taipei, Taiwan
| | - Xiang-Yang Lou
- Department of Biostatistics, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA
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Föhr T, Törmäkangas T, Lankila H, Viljanen A, Rantanen T, Ollikainen M, Kaprio J, Sillanpää E. The association between epigenetic clocks and physical functioning in older women: a three-year follow-up. J Gerontol A Biol Sci Med Sci 2021; 77:1569-1576. [PMID: 34543398 PMCID: PMC9373966 DOI: 10.1093/gerona/glab270] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Indexed: 01/16/2023] Open
Abstract
Background Epigenetic clocks are composite markers developed to predict chronological age or mortality risk from DNA methylation (DNAm) data. The present study investigated the associations between 4 epigenetic clocks (Horvath’s and Hannum’s DNAmAge and DNAm GrimAge and PhenoAge) and physical functioning during a 3-year follow-up. Method We studied 63- to 76-year-old women (N = 413) from the Finnish Twin Study on Aging. DNAm was measured from blood samples at baseline. Age acceleration (AgeAccel), that is, discrepancy between chronological age and DNAm age, was determined as residuals from linear model. Physical functioning was assessed under standardized laboratory conditions at baseline and at follow-up. A cross-sectional analysis was performed with path models, and a longitudinal analysis was conducted with repeated measures linear models. A nonrandom missing data analysis was performed. Results In comparison to the other clocks, GrimAgeAccel was more strongly associated with physical functioning. At baseline, GrimAgeAccel was associated with lower performance in the Timed Up and Go (TUG) test and the 6-minute walk test. At follow-up, significant associations were observed between GrimAgeAccel and lowered performance in the TUG, 6-minute and 10-m walk tests, and knee extension and ankle plantar flexion strength tests. Conclusions The DNAm GrimAge, a novel estimate of biological aging, associated with decline in physical functioning over the 3-year follow-up in older women. However, associations between chronological age and physical function phenotypes followed similar pattern. Current epigenetic clocks do not provide strong benefits in predicting the decline of physical functioning at least during a rather short follow-up period and restricted age range.
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Affiliation(s)
- Tiina Föhr
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Timo Törmäkangas
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Hannamari Lankila
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Anne Viljanen
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Taina Rantanen
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Elina Sillanpää
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland.,Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
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Kresovich JK, Xu Z, O'Brien KM, Shi M, Weinberg CR, Sandler DP, Taylor JA. Blood DNA methylation profiles improve breast cancer prediction. Mol Oncol 2021; 16:42-53. [PMID: 34411412 PMCID: PMC8732352 DOI: 10.1002/1878-0261.13087] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 06/24/2021] [Accepted: 08/18/2021] [Indexed: 12/21/2022] Open
Abstract
Although blood DNA methylation (DNAm) profiles are reported to be associated with breast cancer incidence, they have not been widely used in breast cancer risk assessment. Among a breast cancer case–cohort of 2774 women (1551 cases) in the Sister Study, we used candidate CpGs and DNAm estimators of physiologic characteristics to derive a methylation‐based breast cancer risk score, mBCRS. Overall, 19 CpGs and five DNAm estimators were selected using elastic net regularization to comprise mBCRS. In a test set, higher mBCRS was positively associated with breast cancer incidence, showing similar strength to the polygenic risk score (PRS) based on 313 single nucleotide polymorphisms (313 SNPs). Area under the curve for breast cancer prediction was 0.60 for self‐reported risk factors (RFs), 0.63 for PRS, and 0.63 for mBCRS. Adding mBCRS to PRS and RFs improved breast cancer prediction from 0.66 to 0.71. mBCRS findings were replicated in a nested case–control study within the EPIC‐Italy cohort. These results suggest that mBCRS, a risk score derived using blood DNAm, can be used to enhance breast cancer prediction.
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Affiliation(s)
- Jacob K Kresovich
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Katie M O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Min Shi
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA.,Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
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45
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Xu R, Li S, Li S, Wong EM, Southey MC, Hopper JL, Abramson MJ, Guo Y. Surrounding Greenness and Biological Aging Based on DNA Methylation: A Twin and Family Study in Australia. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:87007. [PMID: 34460342 PMCID: PMC8404778 DOI: 10.1289/ehp8793] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 08/06/2021] [Accepted: 08/10/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND High surrounding greenness has many health benefits and might contribute to slower biological aging. However, very few studies have evaluated this from the perspective of epigenetics. OBJECTIVES We aimed to evaluate the association between surrounding greenness and biological aging based on DNA methylation. METHODS We derived Horvath's DNA methylation age (DNAmAge), Hannum's DNAmAge, PhenoAge, and GrimAge based on DNA methylation measured in peripheral blood samples from 479 Australian women in 130 families. Measures of DNAmAge acceleration (DNAmAgeAC) were derived from the residuals after regressing each DNAmAge metric on chronological age. Greenness was represented by satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) metrics within 300-, 500-, 1,000-, and 2,000-m buffers surrounding participant addresses. Greenness-DNAmAgeAC associations were estimated using a within-sibship design fitted by linear mixed effect models, adjusting for familial clustering and important covariates. RESULTS Greenness metrics were associated with significantly lower DNAmAgeAC based on GrimAge acceleration, suggesting slower biological aging with higher greenness based on both NDVI and EVI in 300-2,000m buffer areas. For example, each interquartile range increase in NDVI within 1,000m was associated with a 0.59 (95% CI: 0.18, 1.01)-year decrease in GrimAge acceleration. Greenness was also inversely associated with three of the eight components of GrimAge, specifically, DNA methylation-based surrogates of serum cystatin-C, serum growth differentiation factor 15, and smoking pack years. Associations between greenness and biological aging measured by Horvath's and Hannum's DNAmAgeAC were less consistent, and depended on neighborhood socioeconomic status. No significant associations were estimated for PhenoAge acceleration. DISCUSSION Higher surrounding greenness was associated with slower biological aging, as indicated by GrimAge age acceleration, in Australian women. Associations were also evident for three individual components of GrimAge, but were inconsistent for other measures of biological aging. Additional studies are needed to confirm our results. https://doi.org/10.1289/EHP8793.
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Affiliation(s)
- Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Victoria, Australia
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Michael J. Abramson
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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Tekola-Ayele F. Invited Commentary: Epigenetic Clocks and Obesity-Towards the Next Frontier Using Integrative Approaches and Early-Life Models. Am J Epidemiol 2021; 190:994-997. [PMID: 33693471 DOI: 10.1093/aje/kwaa252] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 10/13/2020] [Accepted: 11/04/2020] [Indexed: 12/20/2022] Open
Abstract
Why people of the same age show differences in age-related functional decline and whether biological aging can be slowed down through lifestyle changes and therapeutics are active research topics. Molecular tools that predict biological age based on DNA methylation markers, known as epigenetic clocks, are facilitating these efforts. In this issue, Kresovich et al. (Am J Epidemiol. 2021;190(6):984-993) investigated a cohort of non-Hispanic White women, demonstrating positive relationships between adiposity measures and the ticking rate of epigenetic clocks in blood. This commentary emphasizes that integrating molecular and genetic epidemiology approaches is crucial to dissecting the complex relationship between obesity and epigenetic aging. The early-life period is explored as a unique opportunity to gain novel insights into links between developmental processes and aging in later life. Last, the landscape of the next frontier in aging research is described in light of the imperative for transdisciplinary approaches to outline a shared vision and public health implementation dilemmas.
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47
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Kresovich JK, Martinez Lopez AM, Garval EL, Xu Z, White AJ, Sander DP, Taylor JA. Alcohol consumption and methylation-based measures of biological age. J Gerontol A Biol Sci Med Sci 2021; 76:2107-2111. [PMID: 34038541 DOI: 10.1093/gerona/glab149] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Indexed: 12/12/2022] Open
Abstract
Epigenetic age acceleration is considered a measure of biological aging based on genome-wide patterns of DNA methylation. Although age acceleration has been associated with incidence of diseases and death, less is known about how it is related to lifestyle behaviors. Among 2,316 women, we evaluate associations between self-reported alcohol consumption and various metrics of epigenetic age acceleration. Recent average alcohol consumption was defined as the mean number of drinks consumed per week within the past year; lifetime average consumption was estimated as the mean number of drinks per year drinking. Whole blood genome-wide DNA methylation was measured with HumanMethylation450 BeadChips and used to assess four epigenetic clocks (Hannum, Horvath, PhenoAge, GrimAge) and their corresponding metrics of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, GrimAgeAccel). Although alcohol consumption showed little association with most age acceleration metrics, both lifetime and recent average consumption measures were positively associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: β=0.30 years, 95% CI: 0.11, 0.48, p=0.002; recent, per additional 5 drinks/week: β=0.19 years, 95% CI: 0.01, 0.37, p=0.04). In a mutually adjusted model, only average lifetime alcohol consumption remained associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: β=0.27 years, 95% CI: 0.04, 0.50, p=0.02; recent, per 5 additional drinks/week: β=0.05 years, 95% CI: -0.16, 0.26, p=0.64). Although alcohol use does not appear to be strongly associated with biological age measured by most epigenetic clocks, lifetime average consumption is associated with higher biological age assessed by the GrimAge epigenetic clock.
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Affiliation(s)
- Jacob K Kresovich
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC
| | | | - Emma L Garval
- Keck Science Department, Scripps College, Claremont, CA
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC
| | - Alexandra J White
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC
| | - Dale P Sander
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC.,Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC
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48
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Sillanpää E, Heikkinen A, Kankaanpää A, Paavilainen A, Kujala UM, Tammelin TH, Kovanen V, Sipilä S, Pietiläinen KH, Kaprio J, Ollikainen M, Laakkonen EK. Blood and skeletal muscle ageing determined by epigenetic clocks and their associations with physical activity and functioning. Clin Epigenetics 2021; 13:110. [PMID: 34001218 PMCID: PMC8127311 DOI: 10.1186/s13148-021-01094-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 04/26/2021] [Indexed: 12/14/2022] Open
Abstract
The aim of this study was to investigate the correspondence of different biological ageing estimates (i.e. epigenetic age) in blood and muscle tissue and their associations with physical activity (PA), physical function and body composition. Two independent cohorts (N = 139 and N = 47) were included, whose age span covered adulthood (23–69 years). Whole blood and m. vastus lateralis samples were collected, and DNA methylation was analysed. Four different DNA methylation age (DNAmAge) estimates were calculated using genome-wide methylation data and publicly available online tools. A novel muscle-specific methylation age was estimated using the R-package ‘MEAT’. PA was measured with questionnaires and accelerometers. Several tests were conducted to estimate cardiorespiratory fitness and muscle strength. Body composition was estimated by dual-energy X-ray absorptiometry. DNAmAge estimates from blood and muscle were highly correlated with chronological age, but different age acceleration estimates were weakly associated with each other. The monozygotic twin within-pair similarity of ageing pace was higher in blood (r = 0.617–0.824) than in muscle (r = 0.523–0.585). Associations of age acceleration estimates with PA, physical function and body composition were weak in both tissues and mostly explained by smoking and sex. The muscle-specific epigenetic clock MEAT was developed to predict chronological age, which may explain why it did not associate with functional phenotypes. The Horvath’s clock and GrimAge were weakly associated with PA and related phenotypes, suggesting that higher PA would be linked to accelerated biological ageing in muscle. This may, however, be more reflective of the low capacity of epigenetic clock algorithms to measure functional muscle ageing than of actual age acceleration. Based on our results, the investigated epigenetic clocks have rather low value in estimating muscle ageing with respect to the physiological adaptations that typically occur due to ageing or PA. Thus, further development of methods is needed to gain insight into muscle tissue-specific ageing and the underlying biological pathways.
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Affiliation(s)
- Elina Sillanpää
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland. .,Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Anna Kankaanpää
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Aini Paavilainen
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Tuija H Tammelin
- LIKES Research Centre for Physical Activity and Health, Jyväskylä, Finland
| | - Vuokko Kovanen
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Sarianna Sipilä
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Obesity Center, Endocrinology, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Eija K Laakkonen
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
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