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The geroscience hypothesis posits that therapies to slow biological processes of aging can prevent disease and extend healthy years of life. To test such "geroprotective" therapies in humans, outcome measures are needed that can assess extension of disease-free life span. This need has spurred development of different methods to quantify biological aging. But different methods have not been systematically compared in the same humans. We implemented 7 methods to quantify biological aging using repeated-measures physiological and genomic data in 964 middle-aged humans in the Dunedin Study (New Zealand; persons born 1972-1973). We studied 11 measures in total: telomere-length and erosion, 3 epigenetic-clocks and their ticking rates, and 3 biomarker-composites. Contrary to expectation, we found low agreement between different measures of biological aging. We next compared associations between biological aging measures and outcomes that geroprotective therapies seek to modify: physical functioning, cognitive decline, and subjective signs of aging, including aged facial appearance. The 71-cytosine-phosphate-guanine epigenetic clock and biomarker composites were consistently related to these aging-related outcomes. However, effect sizes were modest. Results suggested that various proposed approaches to quantifying biological aging may not measure the same aspects of the aging process. Further systematic evaluation and refinement of measures of biological aging is needed to furnish outcomes for geroprotector trials.

Antiaging therapies show promise in model organism research. Translation to humans is needed to address the challenges of an aging global population. Interventions to slow human aging will need to be applied to still-young individuals. However, most human aging research examines older adults, many with chronic disease. As a result, little is known about aging in young humans. We studied aging in 954 young humans, the Dunedin Study birth cohort, tracking multiple biomarkers across three time points spanning their third and fourth decades of life. We developed and validated two methods by which aging can be measured in young adults, one cross-sectional and one longitudinal. Our longitudinal measure allows quantification of the pace of coordinated physiological deterioration across multiple organ systems (e.g., pulmonary, periodontal, cardiovascular, renal, hepatic, and immune function). We applied these methods to assess biological aging in young humans who had not yet developed age-related diseases. Young individuals of the same chronological age varied in their "biological aging" (declining integrity of multiple organ systems). Already, before midlife, individuals who were aging more rapidly were less physically able, showed cognitive decline and brain aging, self-reported worse health, and looked older. Measured biological aging in young adults can be used to identify causes of aging and evaluate rejuvenation therapies.

Background: Socioeconomic disadvantage is a well-established predictor of morbidity and mortality, and is thought to accelerate the aging process. This study examined associations between life-course socioeconomic conditions and the Pace of Aging, a longitudinal measure of age-related physiological decline.Methods: Data were drawn from a Swiss population-based cohort of individuals originally recruited between 2003 and 2006, and followed up for 11 years (2 834 women, 2 475 men aged 35-75 years [mean 52]). Pace of Aging was measured using 3 repeated assessments of 12 biomarkers reflecting multiple body systems. Analysis tested associations of socioeconomic conditions with physiological status at baseline and with the Pace of Aging.Results: Participants with more life-course socioeconomic disadvantage were physiologically older at baseline and experienced faster Pace of Aging. Effect sizes (β) for associations of childhood socioeconomic disadvantage with baseline physiological status ranged from 0.1 to 0.2; for adulthood socioeconomic disadvantage, effect sizes ranged from 0.2 to 0.3. Effect sizes were smaller for associations with the Pace of Aging (<0.05 for childhood disadvantage, 0.05-0.1 for adulthood disadvantage). Those who experienced disadvantaged socioeconomic conditions from childhood to adulthood aged 10% faster over the 11 years of follow-up as compared with those who experienced consistently advantaged socioeconomic conditions. Covariate adjustment for health behaviors attenuated associations, but most remained statistically significant.Conclusions: Socioeconomic inequalities contribute to a faster Pace of Aging, partly through differences in health behaviors. Intervention to slow aging in at-risk individuals is needed by midlife, before etiology of aging-related diseases become established. [ABSTRACT FROM AUTHOR]

Background: Dysregulation of some metabolic factors increases the risk of dementia. It remains unclear if overall metabolic dysregulation, or only certain components, contribute to cognitive aging and if these associations are sex specific.Methods: Data from the 2006-2016 waves of the Health and Retirement Study (HRS) was used to analyze 7 103 participants aged 65 and older at baseline (58% women). We created a metabolic-dysregulation risk score (MDRS) composed of blood pressure/hypertension status, glycosylated hemoglobin (HbA1c)/diabetes status, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and waist circumference, and assessed cognitive trajectories from repeated measures of the HRS-Telephone Interview for Cognitive Status (HRS-TICS) over 10 years of follow-up. Linear mixed-effects models estimated associations between MDRS or individual metabolic factors (biomarkers) with mean and change in HRS-TICS scores and assessed sex-modification of these associations.Results: Participants with higher MDRSs had lower mean HRS-TICS scores, but there were no statistically significant differences in rate of decline. Sex stratification showed this association was present for women only. MDRS biomarkers revealed heterogeneity in the strength and direction of associations with HRS-TICS. Lower HRS-TICS levels were associated with hypertension, higher HbA1c/diabetes, and lower HDL-C and TC, whereas faster rate of cognitive decline was associated with hypertension, higher HbA1c/diabetes, and higher TC. Participants with higher HbA1c/diabetes presented worse cognitive trajectories. Sex differences indicated that women with higher HbA1c/diabetes to have lower HRS-TICS levels, whereas hypertensive males presented better cognitive trajectory.Conclusions: Our results demonstrate that metabolic dysregulation is more strongly associated with cognition in women compared with men, though sex differences vary by individual biomarker. [ABSTRACT FROM AUTHOR]

Background: Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously, we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al., 2020). Here, we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome). Methods: We used data from the Dunedin Study 1972-1973 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNAmethylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named Dunedin- PACE, in five additional datasets. Results: DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge. Conclusions: DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience. [ABSTRACT FROM AUTHOR]

Many studies have shown that estimates of biological age (BA) can predict health-related outcomes in older adults. Often, researchers employ multiple measures belonging to a variety of biological/physiological systems, and assess the validity of BA estimates by how well they approximate chronological age (CA). However, it is not clear whether this is the best approach for judging a BA estimate, or whether certain groups of measures are more informative to this end. Using data from the Canadian Longitudinal Study on Aging, we composed panels of biological measures based on the physiological systems/domains they belong to (blood, organ function, physical/cognitive performance), and also composed a panel of measures that optimized the association of BA with CA. We then compared BA estimates for each according to their association with CA and health-related outcomes, including frailty, multimorbidity, chronic condition domains, disability, and health care utilization. Although BA estimated using all 40 measures (r = 0.74) or our age-optimized panel (r = 0.77) most closely approximated CA, the strength of associations to health-related outcomes was comparable or weaker than that of our panel composed only of physical performance measures (CA r = 0.59). All BA estimates were significantly associated to the outcomes considered, with exception to the neurological and musculoskeletal disease domains, and only varied slightly by sex. In summary, while the approximation of CA is important to consider when estimating BA, the strength of associations to prospective outcomes may be of greater importance. Hence, the context in which BA is estimated should be influenced by an investigator's specific research goals. [ABSTRACT FROM AUTHOR]

Quantification of biological aging is of interest in gerontology as a means to surveil aging rates in the population and to evaluate the effects of interventions to increase healthy life span. Analysis of proposed methods to quantify biological aging has focused on samples of midlife or mixed-age adults in the West. Research is needed to test whether quantifications of biological aging can differentiate aging rates among older adults and if quantifications of biological aging developed in Western samples can differentiate aging rates in non-Western populations. We conducted analysis of Klemera-Doubal method (KDM) Biological Age and homeostatic dysregulation measures of biological aging developed in the U.S. NHANES and tested in a sample of older Taiwanese adults in the Social Environment and Biomarkers of Aging Study. We conducted analysis of physical and cognitive function and mortality, comparing quantifications of biological aging to a biomarker index based on norms within our analysis sample and to participants' ratings of their own health. Results showed that quantifications of biological aging (a) predicted differences in physical and cognitive function and in mortality risk among Taiwanese older adults and (b) performed as well as a traditional biomarker index and participant self-rated health for prediction of these outcomes. [ABSTRACT FROM AUTHOR]

Background: Childhood risk factors are associated with elevated inflammatory biomarkers in adulthood, but it is unknown whether these risk factors are associated with increased adult levels of the chronic inflammation marker soluble urokinase plasminogen activator receptor (suPAR). We aimed to test the hypothesis that childhood exposure to risk factors for adult disease is associated with elevated suPAR in adulthood and to compare suPAR with the oft‐reported inflammatory biomarker C‐reactive protein (CRP). Methods: Prospective study of a population‐representative 1972–1973 birth cohort; the Dunedin Multidisciplinary Health and Development Study observed participants to age 38 years. Main childhood predictors were poor health, socioeconomic disadvantage, adverse childhood experiences (ACEs), low IQ, and poor self‐control. Main adult outcomes were adulthood inflammation measured as suPAR and high‐sensitivity CRP (hsCRP). Results: Participants with available plasma samples at age 38 were included (N = 837, 50.5% male). suPAR (mean 2.40 ng/ml; SD 0.91) was positively correlated with hsCRP (r 0.15, p < .001). After controlling for sex, body mass index (BMI), and smoking, children who experienced more ACEs, lower IQ, or had poorer self‐control showed elevated adult suPAR. When the five childhood risks were aggregated into a Cumulative Childhood Risk index, and controlling for sex, BMI, and smoking, Cumulative Childhood Risk was associated with higher suPAR (b 0.10; SE 0.03; p = .002). Cumulative Childhood Risk predicted elevated suPAR, after controlling for hsCRP (b 0.18; SE 0.03; p < .001). Conclusions: Exposure to more childhood risk factors was associated with higher suPAR levels, independent of CRP. suPAR is a useful addition to studies connecting childhood risk to adult inflammatory burden. [ABSTRACT FROM AUTHOR]

Biological aging measures have been proposed as proxies for extension of healthy life span in trials of geroprotective therapies that aim to slow aging. Several methods to measure biological aging show promise but it is not known if these methods are sensitive to changes caused by geroprotective therapy. We conducted analysis of two proposed methods to quantify biological aging using data from a recently concluded trial of an established geroprotector, caloric restriction. We obtained data from the National Institute on Aging CALERIE randomized trial through its public-access biobank (https://calerie.duke.edu/). The CALERIE trial randomized N = 220 nonobese adults to 25% caloric restriction (n = 145; 11.7% caloric restriction was achieved, on average) or to maintain current diet (n = 75) for 2 years. We analyzed biomarker data collected at baseline, 12-, and 24-month follow-up assessments. We applied published biomarker algorithms to these data to calculate two biological age measures, Klemera-Doubal Method Biological Age and homeostatic dysregulation. Intent-to-treat analysis using mixed-effects growth models of within-person change over time tested if caloric restriction slowed increase in measures of biological aging across follow-up. Analyses of both measures indicated caloric restriction slowed biological aging. Weight loss did not account for the observed effects. Results suggest future directions for testing of geroprotective therapies in humans. [ABSTRACT FROM AUTHOR]

Intervention studies in animals suggest molecular changes underlying age-related disease and disability can be slowed or reversed. To speed translation of these so-called "geroprotective" therapies to prevent age-related disease and disability in humans, biomarkers are needed that can track changes in the rate of human aging over the course of intervention trials. Algorithm methods that measure biological processes of aging from combinations of DNA methylation marks or clinical biomarkers show promise. To identify next steps for establishing utility of these algorithm-based measures of biological aging for geroprotector trials, we considered the history a candidate biomarker of aging that has received substantial research attention, telomere length. Although telomere length possesses compelling biology to recommend it as a biomarker of aging, mixed research findings have impeded clinical and epidemiologic translation. Strengths of telomeres that should be established for algorithm biomarkers of aging are correlation with chronological age across the lifespan, prediction of disease, disability, and early death, and responsiveness to risk and protective exposures. Key challenges in telomere research that algorithm biomarkers of aging must address are measurement precision and reliability, establishing links between longitudinal rates of change across repeated measurements and aging outcomes, and clarity over whether the biomarker is a causal mechanism of aging. These strengths and challenges suggest a research agenda to advance translation of algorithm-based aging biomarkers: establish validity in young-adult and midlife individuals; test responsiveness to exposures that shorten or extend healthy lifespan; and conduct repeated-measures longitudinal studies to test differential rates of change. [ABSTRACT FROM AUTHOR]

Objectives: Early-life intelligence has been shown to predict multiple causes of death in populations around the world. This finding suggests that intelligence might influence mortality through its effects on a general process of physiological deterioration (i.e., individual variation in "biological age"). We examined whether intelligence could predict measures of aging at midlife before the onset of most age-related disease. Methods: We tested whether intelligence assessed in early childhood, middle childhood, and midlife predicted midlife biological age in members of the Dunedin Study, a population-representative birth cohort. Results: Lower intelligence predicted more advanced biological age at midlife as captured by perceived facial age, a 10-biomarker algorithm based on data from the National Health and Nutrition Examination Survey (NHANES), and Framingham heart age (r = 0.1-0.2). Correlations between intelligence and telomere length were less consistent. The associations between intelligence and biological age were not explained by differences in childhood health or parental socioeco-nomic status, and intelligence remained a significant predictor of biological age even when intelligence was assessed before Study members began their formal schooling. Discussion: These results suggest that accelerated aging may serve as one of the factors linking low early-life intelligence to increased rates of morbidity and mortality. [ABSTRACT FROM AUTHOR]

Caloric restriction (CR) improves markers of aging in humans; but it is not known if the fat mass and obesity-associated gene (FTO) rs9939609 single nucleotide polymorphism (SNP), which is associated with appetite and energy intake, influences adherence to prolonged CR. Utilizing data from the two-year Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE™) phase 2 randomized controlled trial, we tested whether the FTO rs9939609 SNP was associated with adherence to CR in healthy adults without obesity. As secondary aims, we assessed whether the FTO rs9939609 SNP was associated with changes in body composition, biomarkers of aging, and eating behaviors. Participants were randomized into either a CR group that targeted a 25% reduction in energy intake compared to the habitual energy intake at baseline, or an ad libitum (AL) control group. Participants were genotyped for the FTO rs9939609 SNP. Dietary adherence was determined through changes in energy intake using doubly labeled water and changes in body composition at baseline, month 12, and month 24 in both the CR and AL condition. Weight, body composition, resting metabolic rate (RMR), adiponectin, insulin, leptin, and eating behaviors were measured at the same timepoints. A total of 144 participants (91 CR and 53 AL, age: 38.6 ± 7.1 years; body mass index: 25.3 ± 1.7 kg/m2) were studied. Of these, 27 were homozygous for the 'obesity-risk' A allele (AA), while 44 were homozygous for the T allele (TT) and 73 were heterozygotes (AT). By design, the CR group exhibited greater percent CR compared to the AL group during the trial (P < 0.01), but no genotype-by-treatment interaction was observed for change in energy intake or percent CR (P ≥ 0.40). The FTO rs9939609 SNP was also negligibly associated with change in most other endpoints (P ≥ 0.13), though AAs showed a reduction in RMR adjusted for body composition change over the 24 months relative to TTs (genotype-by-treatment interaction: P = 0.03). In a two-year CR intervention delivered to healthy individuals without obesity, the FTO rs9939609 SNP was not associated with adherence to CR and did not alter improvements in most aging biomarkers. [ABSTRACT FROM AUTHOR]

With the rapid expansion of aging biology research, the identification and evaluation of longevity interventions in humans have become key goals of this field. Biomarkers of aging are critically important tools in achieving these objectives over realistic time frames. However, the current lack of standards and consensus on the properties of a reliable aging biomarker hinders their further development and validation for clinical applications. Here, we advance a framework for the terminology and characterization of biomarkers of aging, including classification and potential clinical use cases. We discuss validation steps and highlight ongoing challenges as potential areas in need of future research. This framework sets the stage for the development of valid biomarkers of aging and their ultimate utilization in clinical trials and practice. [ABSTRACT FROM AUTHOR]