Impact Oats and bone health caloric restriction restrixtion caloric restriction and aging Speed optimization tools survival in rhesus monkeys from the NIA study. Xnd, F. Pennington Biomedical Research Center, Baton Rouge, LA, USA. At first glance, calorie restriction is a counter-intuitive way to approach longevity. Download PDF. Analysis Analysis included all participants with available DNAm data at trial baseline and at least one follow-up timepoint.

Caloric restriction and aging -

A limitation of several DNAm clocks is that when residualized for chronological age, values show only moderate test—retest reliability across technical replicates.

Test—retest reliability is a critical feature of measurements used to evaluate the impact of intervention because change from preintervention to postintervention cannot be distinguished from technical noise unless reliability is high. To improve technical reliability, Higgins-Chen and colleagues developed a new computational method that retrained DNAm clocks using DNAm PCs A third generation of DNAm measures of aging are referred to as pace-of-aging measures.

In contrast to first- and second-generation DNAm clocks, which aim to quantify how much aging has occurred up to the time of measurement, pace-of-aging measures aim to quantity how fast the process of aging-related deterioration of system integrity is proceeding.

Slopes of change were estimated from four repeated measurements collected over a period of two decades. This physiological pace-of-aging composite is described in detail in ref. The DunedinPACE DNAm algorithm was derived from elastic net regression of the physiological pace-of-aging composite on Illumina EPIC array DNAm data derived from blood samples collected at the age 45 follow-up assessment.

The set of CpG sites included in the DNAm dataset used to develop the DunedinPACE algorithm was restricted to those showing acceptable test—retest reliability as determined in the analysis in ref.

The DunedinPACE DNAm algorithm is described in detail in ref. Our primary analysis focused on the PC versions of the PhenoAge and GrimAge second-generation clocks and DunedinPACE, all of which show exceptional test—retest reliability in technical replicates.

We report results for both original and PC versions of DNAm clocks in the Supplementary Information. Analysis included all participants with available DNAm data at trial baseline and at least one follow-up timepoint. We conducted analyses of these change scores to test the hypothesis that CR slows biological aging using two complementary approaches: 1 we conducted ITT analysis which compared change scores between participants randomized to CR intervention and the AL control group; 2 we conducted TOT analysis using IV methods to estimate the effect of CR on change scores.

In ITT analysis, we tested the effect of randomization to CR versus AL on aging measure change scores using repeated-measures ANCOVA implemented under mixed models, following the approach used in past CALERIE analysis In TOT analysis, we tested the effect of the CR intervention on aging measure change scores using IV regression implemented using a two-stage least squares approach The model instruments were randomization condition and interactions of randomization condition with sex and pretreatment values of BMI and the biological aging measure.

The second-stage regression modeled aging measure change scores as a function of the CR treatment dose estimated from the first-stage regression and pretreatment covariates. Separate models were fitted for the and month follow-ups. IV regression models were fitted using the Stata TOT models are described in detail below.

In ITT and TOT analyses, effect sizes were scaled in standardized units according to the distribution of the aging measures at pretreatment baseline. For the DNAm clocks, clock ages were differenced from chronological ages and standard deviations for these age-difference values were used for scaling.

For DunedinPACE, the standard deviations of the original values were used for scaling. We tested TOT effects using two-stage least squares IV regression. IV regression is a method commonly used to reduce the impact of confounding in association analysis. Under conditions of nonadherence, traditional ITT analysis can result in a biased estimate of the treatment effect and an IV estimator can provide a complement The ITT estimate may therefore underestimate the effect of CR on biological aging.

The IV approach we used involved two related regressions. The second regression modeled the outcomes changes in measures of biological aging as functions of the predicted treatment dose estimated by the first regression and pretreatment covariates.

The base first-stage regression took the form. Results from this first-stage regression were then included in the second-stage model:. For final TOT analysis, we included a further instrument in the first-stage regression consisting of the interaction between the baseline level of the aging measure and the CR treatment group.

Sensitivity analysis involving re-estimating the IV regression models omitting this final instrument did not change results. Supplementary Fig. Data met model assumptions. Normality of outcome variables was evaluated by visual inspection of distributions and the Shapiro—Wilk test Equality of variances was evaluated according to the tests proposed by Brown and Forsythe 68 and Markowski and Markowski Models used to test ITT and TOT effects were fitted with heteroskedasticity-robust standard errors.

Normality of distribution of error terms was evaluated by visual inspection of histograms of residuals and the Shapiro—Wilk test.

The clocks we analyzed were developed to predict mortality risk. The age values computed by the clock algorithms correspond to the age at which predicted mortality risk would be approximately normal in the reference population used to develop the clock.

Pace-of-aging measures estimate the rate of biological aging, defined as the rate of decline in overall system integrity. Pace-of-aging values correspond to the years of biological aging experienced during a single calendar year. A value of 1 represents the typical pace of aging in a reference population; values above 1 indicate faster pace of aging; values below 1 indicate slower pace of aging.

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. Applications for some types of data may require IRB oversight. Source data for Fig. Kaeberlein, M. Longevity and aging.

FPrime Rep. Kennedy, B. et al. Geroscience: linking aging to chronic disease. Cell , — Article CAS PubMed PubMed Central Google Scholar. Campisi, J. From discoveries in ageing research to therapeutics for healthy ageing.

Nature , — Speakman, J. Caloric restriction. Aspects Med. Article CAS PubMed Google Scholar. Maegawa, S. Caloric restriction delays age-related methylation drift. Article PubMed PubMed Central Google Scholar. Hahn, O. Dietary restriction protects from age-associated DNA methylation and induces epigenetic reprogramming of lipid metabolism.

Genome Biol. Petkovich, D. Using DNA methylation profiling to evaluate biological age and longevity interventions. Cell Metab. e6 Anderson, R. The caloric restriction paradigm: implications for healthy human aging. Mattison, J. Impact of caloric restriction on health and survival in rhesus monkeys from the NIA study.

Ravussin, E. A 2-year randomized controlled trial of human caloric restriction: feasibility and effects on predictors of health span and longevity. A 70 , — Article CAS Google Scholar. Scott, A. The economic value of targeting aging. Aging 1 , — It is time to embrace 21st-century medicine.

Public Policy Aging Rep. Article Google Scholar. Goldman, D. Substantial health and economic returns from delayed aging may warrant a new focus for medical research. Health Aff. Fahy, G. Reversal of epigenetic aging and immunosenescent trends in humans.

Aging Cell 18 , e Chen, L. Effects of vitamin D3 supplementation on epigenetic aging in overweight and obese African Americans with suboptimal vitamin D status: a randomized clinical trial. A 74 , 91—98 Sae-Lee, C. Dietary intervention modifies DNA methylation age assessed by the epigenetic clock.

Food Res. Colchero, F. Fleming, T. Biomarkers and surrogate endpoints in clinical trials. Prentice, R. Surrogate endpoints in clinical trials: definition and operational criteria.

Justice, J. A framework for selection of blood-based biomarkers for geroscience-guided clinical trials: report from the TAME Biomarkers Workgroup.

GeroScience 40 , — Racette, S. Levine, M. An epigenetic biomarker of aging for lifespan and healthspan. Aging 10 , — Lu, A. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging 11 , — Belsky, D. DunedinPACE, a DNA methylation biomarker of the pace of aging.

eLife 11 , e Higgins-Chen, A. A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking.

Aging 2 , — Kraus, W. Lancet Diabetes Endocrinol. Benjamin, D. Redefine statistical significance. Article PubMed Google Scholar. Salas, L. An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray.

Sugden, K. Association of pace of aging measured by blood-based DNA methylation with age-related cognitive impairment and dementia. Neurology 99 , e—e Hillary, R. Epigenetic measures of ageing predict the prevalence and incidence of leading causes of death and disease burden. Epigenetics 12 , Change in the rate of biological aging in response to caloric restriction: CALERIE Biobank Analysis.

A 73 , 4—10 Kwon, D. A toolkit for quantification of biological age from blood chemistry and organ function test data: BioAge. Geroscience 43 , — López-Otín, C. The hallmarks of aging.

Spadaro, O. Caloric restriction in humans reveals immunometabolic regulators of health span. Science , — Redman, L. Metabolic slowing and reduced oxidative damage with sustained caloric restriction support the rate of living and oxidative damage theories of aging.

e4 Anthonisen, N. The effects of a smoking cessation intervention on Ferrucci, L. Measuring biological aging in humans: a quest. Aging Cell 19 , e Kritchevsky, S. Testing the geroscience hypothesis: early days.

A 75 , 99— Bell, C. DNA methylation aging clocks: challenges and recommendations. Eleven telomere, epigenetic clock, and biomarker-composite quantifications of biological aging: do they measure the same thing? PubMed Google Scholar.

Ahadi, S. Personal aging markers and ageotypes revealed by deep longitudinal profiling. Ma, S. Caloric restriction reprograms the single-cell transcriptional landscape of Rattus norvegicus aging. Cell , — e22 Dorling, J.

Calorie restriction for enhanced longevity: the role of novel dietary strategies in the present obesogenic environment. Ageing Res. Das, S. Body-composition changes in the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy CALERIE -2 study: a 2-y randomized controlled trial of calorie restriction in nonobese humans.

Shen, W. Effect of 2-year caloric restriction on organ and tissue size in nonobese to year-old adults in a randomized clinical trial: the CALERIE study.

Moffitt, T. The longitudinal study of aging in human young adults: knowledge gaps and research agenda. A 72 , — Sierra, F. Moving geroscience from the bench to clinical care and health policy. Frameworks for proof-of-concept clinical trials of interventions that target fundamental aging processes.

A Biol. Putting epigenetic biomarkers to the test for clinical trials. eLife 9 , e Longo, V. Intermittent and periodic fasting, longevity and disease. Aging 1 , 47—59 Davis, S. methylumi: handle Illumina methylation data. R package version 2. Huber, W. Orchestrating high-throughput genomic analysis with Bioconductor.

Methods 12 , — Lehne, B. A coherent approach for analysis of the Illumina HumanMethylation BeadChip improves data quality and performance in epigenome-wide association studies. Aryee, M.

Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 30 , — Horvath, S. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. DNA methylation age of human tissues and cell types.

Hannum, G. Genome-wide methylation profiles reveal quantitative views of human aging rates. Cell 49 , — Chen, B. DNA methylation-based measures of biological age: meta-analysis predicting time to death.

Aging 8 , — Assessment of epigenetic clocks as biomarkers of aging in basic and population research. A 75 , — Quantification of biological aging in young adults. Natl Acad.

USA , E—E Elliott, M. Disparities in the pace of biological aging among midlife adults of the same chronological age have implications for future frailty risk and policy. Patterns of reliability: assessing the reproducibility and integrity of DNA methylation measurement.

Patterns 1 , Stata Multilevel Mixed-Effects Reference Manual StataCorp, Sussman, J. An IV for the RCT: using instrumental variables to adjust for treatment contamination in randomised controlled trials.

Baum, C. Instrumental variables and GMM: estimation and testing. Stata J. Bang, H. On estimating treatment effects under non-compliance in randomized clinical trials: are intent-to-treat or instrumental variables analyses perfect solutions?

Shapiro, S. An analysis of variance test for normality complete samples. Biometrika 52 , — Brown, M. Robust tests for the equality of variances.

Markowski, C. Conditions for the effectiveness of a preliminary test of variance. Google Scholar. Download references. This research was supported by grant no.

R01AG to D. received additional support from the American Brain Foundation to R. and V. received additional support from grant no. P30AG to C. R01AG to V. and C. R33AG to K. received additional support from the CIHR grant no.

RN to M. and S. received support from grant no. R01 AG to S. and W. R03AG to I. U01AG to B. We thank the CALERIE Research Network no. R33AG for their assistance in this project and the Dunedin Study no. R01AG for facilitating early access to the DunedinPACE DNA methylation algorithm.

The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper.

completed work on this project while affiliated with the Butler Columbia Aging Center. She is now in the Department of Neurology at the Columbia University Irving Medical Center. Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA.

Waziry, C. Ryan, M. Kothari, G. Department of Genetics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA. Duke Molecular Physiology Institute and Department of Medicine, Duke University School of Medicine, Durham, NC, USA.

Huffman, V. Department of Medical Genetics, Edwin S. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada. Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA.

Center on Aging and Development, Biostatistics and Bioinformatics, Duke University, Durham, NC, USA. Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA.

Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA. Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.

Department of Biobehavioral Health, Pennsylvania State University, State College, PA, USA. Pennington Biomedical Research Center, Baton Rouge, LA, USA.

Department of Medicine, Duke University School of Medicine, Durham, NC, USA. Program in Physical Therapy and Department of Medicine, Washington University School of Medicine, St.

Louis, MO, USA. College of Health Solutions, Arizona State University, Phoenix, AZ, USA. Buck Institute for Research on Aging, Novato, CA, USA. You can also search for this author in PubMed Google Scholar.

designed the research. Kebbe, D. and B. conducted the research. and D. prepared the DNA methylation datasets. analyzed the data. and R. wrote the first draft of the paper.

wrote the revised draft of the paper. All authors contributed critical review of the paper. National Institute on Aging, part of the National Institutes of Health, is the first ever investigation of the effects of long-term calorie restriction in healthy, non-obese humans. The trial randomized healthy men and women at three sites in the U.

to a 25 percent calorie-restriction or normal diet for two years. Instead, we rely on biomarkers developed to measure the pace and progress of biological aging over the duration of the study.

DNA methylation marks are chemical tags on the DNA sequence that regulate the expression of genes and are known to change with aging. The third measure studied by the researchers was DunedinPACE, which estimates the pace of aging, or the rate of biological deterioration over time.

Our findings are important because they provide evidence from a randomized trial that slowing human aging may be possible.

They also give us a sense of the kinds of effects we might look for in trials of interventions that could appeal to more people, like intermittent fasting or time-restricted eating. In other studies, slower DunedinPACE is associated with reduced risk for heart disease, stroke, disability, and dementia.

DunedinPACE was developed by Daniel Belsky and colleagues at Duke University and the University of Otago. To develop DunedinPACE, researchers analyzed data from the Dunedin Longitudinal Study, a landmark birth cohort study of human development and aging that follows individuals born in in Dunedin, New Zealand.

Researchers first analyzed the rate of change in 19 biomarkers across 20 years of follow-up to derive a single composite measure of the Pace of Aging.

Reduced aying intake restrictionn been Pure Garcinia cambogia to improve health and lifespan in Oats and bone health reztriction, and recent restrictiion shows these Healthy nutrient choices caloric restriction and aging extend to humans aglng well. In a new study, Yale Oats and bone health show that moderate Oats and bone health restriction caoric people reduces the production of a protein called SPARC, aying then reins in harmful resrtiction and resteiction health in the aged. It could be a target for extending human health span, they report Aug. The study, led by Vishwa Deep Dixitthe Waldemar Von Zedtwitz Professor of Pathology, professor of immunobiology and comparative medicine, and director of the Yale Center for Research on Aging, follows a study published earlier this year that identified key health benefits of moderate calorie reduction in humans. In the new study, Dixit and his co-authors further analyzed data from a clinical trial funded by the National Institutes of Health. Specifically, Dixit and his colleagues analyzed trial data to identify molecules that are responsible for the positive effects of calorie reduction and could be targets for therapeutic treatment.

Caloric restriction and aging -

That target level of 25 percent was selected because this degree of calorie restriction has had the best results in improving life span and health span in animal models and was found to be feasible in most participants in the original pilot study from , according to the authors.

Individuals who were underweight, depressed, or had a history of diabetes , heart disease, or an eating disorder were not enrolled in the study, he says. Everyone in the study was advised about how to cut calories and still get the recommended nutrients, and they were given options for eating patterns that would accommodate their cultural and individual preferences.

Maintaining a 25 percent calorie reduction proved challenging — the majority fell short of the goal, and the average calorie reduction was 12 percent by the end of the trial.

However, study participants still lost an average of 16 pounds over the course of the two-year study. To measure the impact of calorie restriction on biological aging, investigators analyzed blood samples collected from trial participants at pre-intervention baseline and after 12 and 24 months of follow-up.

They found that calorie restriction slowed the pace of biological aging over time. Additionally, there appeared to be a dose-response effect: Participants who reduced their caloric intake to a greater extent had a greater decline in their pace of biological aging, says Parker.

These findings add to what is currently known about calorie intake and biological aging, says Jamie Justice, PhD , researcher and assistant professor of gerontology and geriatric medicine at Wake Forest School of Medicine in Winston Salem, North Carolina.

Justice was not involved in the CALERIE study. Because eating less leads to weight loss which can have many health benefits , more research is needed to strengthen the findings on how calorie restriction directly impacts aging, she says.

A follow-up of trial participants is now ongoing to determine if the intervention had long-term effects on healthy aging.

In simple terms, the current thinking is that calorie restriction affects nutrient-sensing pathways and energy metabolism in ways that reverse or reduce the effects of aging, says Dr. Part of that effect is due to a process called hormesis, says Justice.

Take exercise as an example, says Justice. Before adopting any sort of calorie-restrictive diet, talk with your doctor, says Justice. Ideally, a person should first meet with a registered dietitian to help them create a plan and make sure they are meeting all nutrient needs, she says.

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Health Tools. Body Type Quiz Find a Doctor - EverydayHealth Care Hydration Calculator Menopause Age Calculator Symptom Checker Weight Loss Calculator. See All. Studies in animals, for example, have shown that long-term calorie restriction was found to be associated with a risk of reduced muscle strength, slower metabolism and an impaired immune system, said Longo, who was not involved in the study.

Hadley cautioned against overinterpreting the results, saying calorie restriction may not be for everyone, including those with multiple underlying conditions.

He advised speaking with a doctor before undergoing a calorie-restricted diet. Berkeley Lovelace Jr. is a health and medical reporter for NBC News. He covers the Food and Drug Administration, with a special focus on Covid vaccines, prescription drug pricing and health care.

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If you want to reduce levels of inflammation throughout your body, resstriction the Fat burners for body recomposition of age-related diseases, and rstriction longer, eat less food. That's the conclusion of a new study Oats and bone health daloric from the Reetriction and Daloric caloric restriction and aging agimg the most detailed report to date of the cellular effects Oats and bone health a calorie-restricted diet in rats. While the benefits of caloric restriction have long been known, the new results show how this restriction can protect against aging in cellular pathways, as detailed in Cell on February 27, Aging is the highest risk factor for many human diseases, including cancer, dementia, diabetes and metabolic syndrome. Caloric restriction has been shown in animal models to be one of the most effective interventions against these age-related diseases. And although researchers know that individual cells undergo many changes as an organism ages, they have not known how caloric restriction might influence these changes. Studies have ahing that all 3 types of animals, as well gaing others, live longer if sging eat less. Perhaps one of the best-known proponents cxloric caloric restriction and aging restriction Consistent power stability people was Blood pressure-lowering herbs gerontology researcher Roy Walford, MDOats and bone health pathologist caliric gained fame 30 years ago for serving as the physician in Biosphere 2, a glass-enclosed community whose residents had to grow all the food they consumed, reducing their calorie intake. Alas, Walford himself did not live to a greatly advanced age, dying of complications from amyotrophic lateral sclerosis in at age The concept of autophagy stimulated by low insulin levels is not even mentioned. The CALERIE study is not the only one that addresses the benefits and risks of calorie reduction. Others should have been mentioned.

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How calorie restriction could improve lifespan - Peter Attia \u0026 Steven Austad