Measure Of Biological Age Research Articles

Evaluation of T-cell aging-related immune phenotypes in the context of biological aging and multimorbidity in the Health and Retirement Study

BackgroundCellular changes in adaptive immune system accompany the process of aging and contribute to an aging-related immune phenotype (ARIP) characterized by decrease in naïve T-cells (TN) and increase in memory T-cells (TM). A population-representative marker of ARIP and its associations with biological aging and age-related chronic conditions have not been studied previously.MethodsWe developed two ARIP indicators based on well understood age-related changes in T cell distribution: TN/(TCM (Central Memory) + TEM (Effector Memory) + TEFF (Effector)) (referred as TN/TM) in CD4 + and CD8 + T-cells. We compared them with existing ARIP measures including CD4/CD8 ratio and CD8 + TN cells by evaluating associations with chronological age and the Klemera Doubal measure of biological age (measured in years) using linear regression, multimorbidity using multinomial logistic regression and two-year mortality using logistic regression.ResultsCD8 + TN and CD8 + TN/TM had the strongest inverse association with chronological age (beta estimates: -3.41 and -3.61 respectively; p-value < 0.0001) after adjustment for sex, race/ethnicity and CMV status. CD4 + TN/TM and CD4 + TN had the strongest inverse association with biological age (β = -0.23; p = 0.003 and β = -0.24; p = 0.004 respectively) after adjustment for age, sex, race/ethnicity and CMV serostatus. CD4/CD8 ratio was not associated with chronological age or biological age. CD4 + TN/TM and CD4 + TN was inversely associated with multimorbidity. For CD4 + TN/TM, people with 2 chronic conditions had an odds ratio of for 0.74 (95%CI: 0.63–0.86 p = 0.0003) compared to those without any chronic conditions while those with 3 chronic conditions had an odds ratio of 0.75 (95% CI: 0.63–0.90; p = 0.003) after adjustment for age, sex, race/ethnicity, CMV serostatus, smoking, and BMI. The results for the CD4 + TN subset were very similar to the associations seen with the CD4 + TN/TM. CD4 + TN/TM and CD4 + TN were both associated with two-year mortality (OR = 0.80 (95% CI: 0.67–0.95; p = 0.01) and 0.81 (0.70–0.94; p = 0.01), respectively).ConclusionCD4 + TN/TM and CD4 + TN had a stronger association with biological age, age-related morbidity and mortality compared to other ARIP measures. Future longitudinal studies are needed to evaluate the utility of the CD4 + subsets in predicting the risk of aging-related outcomes.

Re-examining age-related loyalty for low-involvement purchasing

PurposePrevious research on age-related loyalty is sparse, contradictory and suffers from methodological limitations and criticisms. This study aims to apply two methodological advances to fresh purchasing data to give a much clearer picture of age-related differences in brand loyalty.Design/methodology/approachAn online brand choice survey (n = 1,862) is used to examine age-related loyalty within three low-involvement categories in New Zealand. The polarisation index (φ) is adopted as the measure of loyalty to control for confounding influences present in prior research. Results for chronological age are validated through comparison with results for measures of cognitive, biological and sociological age, as well as household life cycle.FindingsContrary to prior research, age-related differences in loyalty are detected in two of the three low-involvement categories studied. The third category does not show detectable loyalty for any age group. Although differences in brand loyalty are broadly present across all age measures, no alternative measure outperforms chronological age in detecting variations in age-related loyalty.Research limitations/implicationsTo the best of the authors’ knowledge, this is the first evidence that age-related brand loyalty is present in low-involvement categories. However, effects are small and easily obscured by confounding factors. More research is needed to determine how results vary by category.Practical implicationsDespite showing minor differences in loyalty, older consumers still purchase from a wide portfolio of brands and so should not be ignored by marketers. Future research can investigate loyalty for older consumers by adopting the method of analysing differences in polarisation (φ) for chronological age groups.Originality/valuePrevious contradictory findings and methodological concerns about measurement of age-related loyalty are resolved through use of the polarisation index (φ) as a measure of loyalty and by confirmation that chronological age performs as well as any other age measure.

Association of Pace of Aging Measured by Blood-Based DNA Methylation With Age-Related Cognitive Impairment and Dementia.

Background and ObjectivesDNA methylation algorithms are increasingly used to estimate biological aging; however, how these proposed measures of whole-organism biological aging relate to aging in the brain is not known. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Framingham Heart Study (FHS) Offspring Cohort to test the association between blood-based DNA methylation measures of biological aging and cognitive impairment and dementia in older adults.MethodsWe tested 3 “generations” of DNA methylation age algorithms (first generation: Horvath and Hannum clocks; second generation: PhenoAge and GrimAge; and third generation: DunedinPACE, Dunedin Pace of Aging Calculated from the Epigenome) against the following measures of cognitive impairment in ADNI: clinical diagnosis of dementia and mild cognitive impairment, scores on Alzheimer disease (AD) / Alzheimer disease and related dementias (ADRD) screening tests (Alzheimer's Disease Assessment Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment), and scores on cognitive tests (Rey Auditory Verbal Learning Test, Logical Memory test, and Trail Making Test). In an independent replication in the FHS Offspring Cohort, we further tested the longitudinal association between the DNA methylation algorithms and the risk of developing dementia.ResultsIn ADNI (N = 649 individuals), the first-generation (Horvath and Hannum DNA methylation age clocks) and the second-generation (PhenoAge and GrimAge) DNA methylation measures of aging were not consistently associated with measures of cognitive impairment in older adults. By contrast, a third-generation measure of biological aging, DunedinPACE, was associated with clinical diagnosis of Alzheimer disease (beta [95% CI] = 0.28 [0.08–0.47]), poorer scores on Alzheimer disease/ADRD screening tests (beta [Robust SE] = −0.10 [0.04] to 0.08[0.04]), and cognitive tests (beta [Robust SE] = −0.12 [0.04] to 0.10 [0.03]). The association between faster pace of aging, as measured by DunedinPACE, and risk of developing dementia was confirmed in a longitudinal analysis of the FHS Offspring Cohort (N = 2,264 individuals, hazard ratio [95% CI] = 1.27 [1.07–1.49]).DiscussionThird-generation blood-based DNA methylation measures of aging could prove valuable for measuring differences between individuals in the rate at which they age and in their risk for cognitive decline, and for evaluating interventions to slow aging.

Shifts in lifestyle and socioeconomic circumstances predict change—for better or worse—in speed of epigenetic aging: A study of middle-aged black women

BackgroundWhile numerous studies have documented the power of new generation epigenetic clocks to predict morbidity and mortality, research regarding the causes of variation in speed of epigenetic aging is in the early stages. To the extent that these epigenetic clocks are robust measures of biological aging, they should be sensitive to various nutritional, behavioral, ecological, and social factors that have been shown to affect health. ObjectiveInvestigate over an 11-year period the extent to which changes in socioeconomic stress and lifestyle predict changes in speed of epigenetic aging among a sample of middle-aged African American women. MethodsUsing data from the Family and Community Health Study, we investigated whether changes in socioeconomic stress, diet, smoking, exercise, alcohol consumption, and relationship status predict changes in speed of biological aging assessed with 3 s-generation epigenetic clocks: AccelGrimAge, DunedinPoAm, and AccelPhenoAge. The study was able to avoid the challenges associated with self-reports of diet and smoking by employing recently developed epigenetic measures. ResultsChanges in socioeconomic stress and diet were associated with changes in speed of biological aging as assessed by all three epigenetic clocks, and changes in smoking was related to changes in AccelGrimAge and DunedinPoAm. Analyses controlling for cell-type indicated that in large measure diet exerts its effect on aging through its impact on the immune system. ConclusionsThese findings suggest that adoption of a healthy diet and reduction in the use of tobacco are related to a decrease in epigenetic aging, whereas increased pressure relating to income, housing and economic independence are associated with an increase in the speed of aging. These effects were especially strong for the two epigenetic clocks AccelGrimAge and DunedinPoAm. Overall, the results indicate that stress and lifestyle changes may, for better or worse, influence the “biological weathering” often experienced by middle-aged African American women.

Epigenetic clocks and their association with trajectories in perceived discrimination and depressive symptoms among US middle-aged and older adults.

Background: Perceived discrimination may be associated with accelerated aging later in life, with depressive symptoms acting as potential mediator.Methods: A nationally representative sample of older adults was used [Health and Retirement Study 2010–2016, Age: 50–100 y in 2016, N = 2,806, 55.6% female, 82.3% Non-Hispanic White (NHW)] to evaluate associations of perceived discrimination measures [Experience of discrimination or EOD; and Reasons for Perceived discrimination or RPD) and depressive symptoms (DEP)] with 13 DNAm-based measures of epigenetic aging. Group-based trajectory and four-way mediation analyses were used.Results: Overall, and mostly among female and NHW participants, greater RPD in 2010–2012 had a significant adverse total effect on epigenetic aging [2016: DNAm GrimAge, DunedinPoAm38 (MPOA), Levine (PhenoAge) and Horvath 2], with 20–50% of this effect being explained by a pure indirect effect through DEP in 2014–2016. Among females, sustained elevated DEP (2010–2016) was associated with greater LIN DNAm age (β ± SE: +1.506 ± 0.559, p = 0.009, reduced model), patterns observed for elevated DEP (high vs. low) for GrimAge and MPOA DNAm markers. Overall and in White adults, the relationship of the Levine clock with perceived discrimination in general (both EOD and RPD) was mediated through elevated DEP.Conclusions: Sustained elevations in DEP and RPD were associated with select biological aging measures, consistently among women and White adults, with DEP acting as mediator in several RPD-EPICLOCK associations.

Reliability of biological maturation analyses performed by equations predicting skeletal age and peak height velocity with hand and wrist X-ray results.

Hand-wrist radiography is the gold standard for the assessment of skeletal age (SA) and the assignment of biological maturation (BM) status. However, its practical use in the field is questioned, prompting the development of anthropometric equations to estimate BM. However, there is no consensus on the reliability of these equations in relation to hand-wrist X-rays. To test the reliability of the BM estimated from predictive equations with the results of hand-wrist X-rays. One-hundred forty-four young athletes (38%-males, 62%-females; 12.3 ± 1.4 years) were recruited. SA was assessed by analyzing X-rays of the hand-wrist using the Greulich-Pyle protocol. SA was predicted using the anthropometric equations of Cabral and Macêdo. By subtracting chronological age from SA, a measure of BM or biological age (BA) was computed. In addition, a BA of years from peak height velocity (PHV) was predicted using the anthropometric equations of Mirwald and Moore. Relative to X-ray, Cabral's equations showed high reliability in estimating BM in both sexes (p < .0001) while Macêdo's equations showed substantial reliability or males (p < .0001) only. Mirwald and Moore's equations showed weak reliability (p < .05 and p=.043, respectively). The prediction of SA using anthropometric equations was found to be reliable in categorizing individuals as late, synchronized, and/or early maturers in both sexes. However, the predictive equations of years from PHV only reliably categorized late and synchronized maturation stages in males and the synchronized maturers in females.

Measuring biological age using omics data.

Age is the key risk factor for diseases and disabilities of the elderly. Efforts to tackle age-related diseases and increase healthspan have suggested targeting the ageing process itself to 'rejuvenate' physiological functioning. However, achieving this aim requires measures of biological age and rates of ageing at the molecular level. Spurred by recent advances in high-throughput omics technologies, a new generation of tools to measure biological ageing now enables the quantitative characterization of ageing at molecular resolution. Epigenomic, transcriptomic, proteomic and metabolomic data can be harnessed with machine learning to build 'ageing clocks' with demonstrated capacity to identify new biomarkers of biological ageing.

Effect of Diet, Exercise, or Both on Biological Age and Healthy Aging in Older Adults with Obesity: Secondary Analysis of a Randomized Controlled Trial.

To determine the effect of diet, exercise, and diet-exercise in combination on measures of biological age. Secondary analysis of a 1-year randomized, controlled trial. University-based Medical Center. One-hundred-seven older (age≥65 yrs.) adults with obesity (BMI≥30 kg/m2) were randomized and 93 completed the study. Analyses used intention-to-treat. Participants were randomized to a control group, a weight-management (diet) group, an exercise group, or a weight-management-plus-exercise (diet-exercise) group. We calculated Klemera-Doubal Method (KDM) biological age, Homeostatic Dysregulation (HD) score, and Health Aging Index (HAI) score at baseline, and changes at 6- and 12-months. Diet and diet-exercise decreased KDM biological age more than exercise and control (-2.4±0.4, -2.2±0.3, -0.2±0.4, and 0.2±0.5, respectively, P<0.05 for the between group-differences). Diet and diet-exercise also decreased HD score more than exercise and control (-1.0±0.3, -1.1±0.3, 0.1±0.3, and 0.3±0.3 respectively, P<0.05). Moreover, diet-exercise decreased HAI score more than exercise, diet, or control (-1.1±0.2, -0.5±0.2, -0.5±0.2, and 0.0±0.2, respectively, P<0.05). These findings suggest that diet and diet-exercise are both effective methods of improving biological age, and that biological age may be a valuable method of assessing geroprotective interventions in older humans.

1075-P: Racial/Ethnic Differences in the Association between Frailty and Depression among Adults with Diabetes

Individuals with diabetes are at increased risk of developing depression. The prevalence of depression in non-Hispanic Blacks (NHB) with diabetes is about 25%, higher than the prevalence among non-Hispanic Whites (NHWs) . Frailty, a measure of biological age and one’s increased susceptibility to negative health outcomes and has been found to be associated with disability and dependency. The aim of this study was to examine the association between depression and frailty and to understand whether this association differs by race/ethnicity among adults with diabetes. Data on 3792 adults with diabetes from NHANES (2003-2005) were analyzed. Depression was assessed using scores from the 9-item Patient Health Questionnaire (PHQ-9) . Frailty index composed of 46 variables (comorbidities, disability, symptoms, labs, general health) was created ranging from 0 - 1 (frail&amp;gt;=0.21; not frail&amp;lt;0.21) . Unadjusted and adjusted linear regression models were used to assess the association between depression and frailty. Covariates included age, sex, education, income-to-poverty ratio, marry, insurance, employment, smoke, physical activity, and body mass index. All models were stratified by race/ethnicity. Unadjusted models showed an association depression and frailty across all racial/ethnic groups with those who were frail having significantly higher PHQ9 scores (NHW: b 2.63; 95%CI:1.36, 3.89; NHB: b 3.26; 95%CI:2.23, 4.23; Hispanic/Other (H/O) : b 1.33; 95%CI:0.52, 2.14) . The association remained significant across all groups in adjusted models (NHW: b 4.5; 95%CI:1.9, 7.1; NHB: b 6.3; 95%CI:4.2, 8.4; H/O: b 2.1; 95%CI:0.5, 3.7) .While depression was associated with frailty across all racial/ethnic groups, NHBs who were frail had the highest mean PHQ9 score. Additional research is needed to identify the key drivers of this relationship and potential targets for home-based lifestyle intervention to improve care provided to and outcomes for frail patients with diabetes. Disclosure L.E.Egede: None. A.Z.Dawson: None. J.A.Campbell: None. R.J.Walker: None. Funding American Diabetes Association (1-19-JDF-075) ; National Institute of Diabetes and Digestive and Kidney Diseases (grant K24DK093699, R01DK118038, R01DK120861, Principal Investigator (PI) : Leonard Egede, MD) National Institute on Minority Health and Health Disparities (R01MD013826, PI: Egede/Walker)

Redefining age-based screening and diagnostic guidelines: an opportunity for biological aging clocks in clinical medicine?

Clinicians often note that patients seem older or younger than their stated age to convey their appraisal of a patient's biological or physiological age and subsequent disease risks. Developments in ageing biomarkers, such as epigenetic clocks,1 offer a more objective method of molecularly quantifying how well an individual is ageing beyond subject assessment. However, it remains unclear how best to incorporate these measures of so-called biological age into clinical medicine. Both a benefit and dilemma of incorporating epigenetic aging in clinical medicine is its association with a plethora of disease states while simultaneously being associated with various physical and psychosocial risk factors.

Advancing understanding of maternal age: correlating epigenetic clocks in blood and myometrium

BackgroundAdvanced maternal age is currently a term defined by chronological age. However, a group of biomarkers known as epigenetic clocks, which can predict morbidity and mortality, has been used to estimate measures of biological aging. Uterine myometrial function during the process of parturition may be influenced by aging, as labor dystocia, unplanned intrapartum cesarean birth, and postpartum hemorrhage are more common in older individuals. The purpose of this study was to evaluate the use of epigenetic clocks in maternal myometrium and blood for predicting age and to evaluate the correlation of epigenetic age between the tissues.ResultsWe compared epigenetic age in blood and myometrial samples provided by women undergoing planned cesarean birth at term gestation. Chronological age ranged from 20 to 50 with a median (IQR) age of 35.5(8) years. The MethylationEPIC BeadChip was used to obtain DNA methylation data, and then epigenetic age was calculated using the Horvath, Hannum, GrimAge, and PhenoAge clocks. Spearman correlations of epigenetic age with chronological age were calculated. We tested the relationship of epigenetic age in maternal blood to epigenetic age in myometrium. Age acceleration, for each clock, was also correlated between tissues. Twenty-seven participants provided samples, and 21 matched specimens were included in the final analysis after quality control. Spearman correlation between maternal chronological age and epigenetic age were significant in three of the four clocks (pan-tissue Horvath, Hannum, and GrimAge), for both myometrium and blood samples. Correlations between blood epigenetic age and maternal age ranged from 0.72 to 0.87 (all p < 0.001). Correlations between myometrial epigenetic age and maternal age were also significant (0.62–0.70, p = 0.002), though lower than correlations seen in blood. Maternal blood epigenetic age also correlated with epigenetic age in myometrium with each of these three clocks 0.60 (p = 0.004, Horvath), 0.63 (p = 0.003, Hannum), and 0.80 (p < 0.001, GrimAge). GrimAge age acceleration had the highest correlation between tissues among the clocks (0.49, p = 0.02).ConclusionsGiven the limited sample, this study provides insight into the potential use of epigenetic age derived from blood as a proxy for myometrial epigenetic age, which may be a useful biomarker in estimating myometrial biological age in relationship to myometrial dysfunction. GrimAge outperformed the other tested clocks in terms of concordance of epigenetic age and age acceleration between tissues; however, the Horvath and Hannum clocks may be useful depending on the outcome of interest in pregnancy.

Ageing and cancer: a research gap to fill.

The complex mechanisms of ageing biology are increasingly understood. Interventions to reduce or delay ageing‐associated diseases are emerging. Cancer is one of the diseases promoted by tissue ageing. A clockwise mutational signature is identified in many tumours. Ageing might be a modifiable cancer risk factor. To reduce the incidence of ageing‐related cancer and to detect the disease at earlier stages, we need to understand better the links between ageing and tumours. When a cancer is established, geriatric assessment and measures of biological age might help to generate evidence‐based therapeutic recommendations. In this approach, patients and caregivers would include the respective weight to give to the quality of life and survival in the therapeutic choices. The increasing burden of cancer in older patients requires new generations of researchers and geriatric oncologists to be trained, to properly address disease complexity in a multidisciplinary manner, and to reduce health inequities in this population of patients. In this review, we propose a series of research challenges to tackle in the next few years to better prevent, detect and treat cancer in older patients while preserving their quality of life.

Social mobility and biological aging among older adults in the United States.

Lower socioeconomic status is associated with faster biological aging, the gradual and progressive decline in system integrity that accumulates with advancing age. Efforts to promote upward social mobility may, therefore, extend healthy lifespan. However, recent studies suggest that upward mobility may also have biological costs related to the stresses of crossing social boundaries. We tested associations of life-course social mobility with biological aging using data from participants in the 2016 Health and Retirement Study (HRS) Venous Blood Study who provided blood-chemistry (n = 9,255) and/or DNA methylation (DNAm) data (n = 3,976). We quantified social mobility from childhood to later-life using data on childhood family characteristics, educational attainment, and wealth accumulation. We quantified biological aging using 3 DNAm “clocks” and 3 blood-chemistry algorithms. We observed substantial social mobility among study participants. Those who achieved upward mobility exhibited less-advanced and slower biological aging. Associations of upward mobility with less-advanced and slower aging were consistent for blood-chemistry and DNAm measures of biological aging, and were similar for men and women and for Black and White Americans (Pearson-r effect-sizes ∼0.2 for blood-chemistry measures and the DNAm GrimAge clock and DunedinPoAm pace-of-aging measures; effect-sizes were smaller for the DNAm PhenoAge clock). Analysis restricted to educational mobility suggested differential effects by racial identity; mediating links between educational mobility and healthy aging may be disrupted by structural racism. In contrast, mobility producing accumulation of wealth appeared to benefit White and Black Americans equally, suggesting economic intervention to reduce wealth inequality may have potential to heal disparities in healthy aging.

Telomere length in patients with anorexia nervosa

Patients with anorexia nervosa (AN) experience substantial physical and psychological stress exerted on the body as part of the condition. Telomere length (TL) provides a measure of normal biological ageing that can be further reduced by additional stressors. We sought to test the following hypotheses: (1) TL is reduced in patients with AN compared to healthy controls, and (2) TL is reduced with increasing duration of illness. For this cross-sectional study, we assessed TL in whole blood DNA collected from patients with AN ( n ​= ​23; 21 females; mean age 30.3 years, SD 13.1) and age- and sex-matched healthy controls ( n ​= ​33; 32 females, mean age 30.6 years, SD 12.2) using quantitative real-time polymerase chain reaction. Clinical characteristics were obtained. Our results indicate that TL is significantly longer in patients with AN compared to healthy controls, both before and after adjusting for age, sex, level of educational attainment, smoking status, body mass index and antipsychotic use. TL was not associated with duration of illness after adjusting for age. Contrary to our hypotheses, our results indicate that TL does not reflect accelerated biological ageing in patients with AN. Further investigation may identify the reason for increased TL in those with AN. • Patients with anorexia nervosa have significantly longer telomeres in comparison to healthy controls. • Results remained statistically significant after adjusting for covariates. • Telomere length was not associated with duration of illness.

Association of Treatable Health Conditions During Adolescence With Accelerated Aging at Midlife

Biological aging is a distinct construct from health; however, people who age quickly are more likely to experience poor health. Identifying pediatric health conditions associated with accelerated aging could help develop treatment approaches to slow midlife aging and prevent poor health in later life. To examine the association between 4 treatable health conditions in adolescence and accelerated aging at midlife. This cohort study analyzed data from participants in the Dunedin Study, a longitudinal investigation of health and behavior among a birth cohort born between April 1, 1972, and March 31, 1973, in Dunedin, New Zealand, and followed up until age 45 years. Participants underwent an assessment at age 45 years and had data for at least 1 adolescent health condition (asthma, smoking, obesity, and psychological disorders) and outcome measure (pace of aging, gait speed, brain age, and facial age). Data analysis was performed from February 11 to September 27, 2021. Asthma, cigarette smoking, obesity, and psychological disorders were assessed at age 11, 13, and 15 years. The outcome was a midlife aging factor composite score comprising 4 measures of biological aging: pace of aging, gait speed, brain age (specifically, BrainAGE score), and facial age. A total of 910 participants (459 men [50.4%]) met the inclusion criteria, including an assessment at age 45 years. Participants who had smoked daily (0.61 [95% CI, 0.43-0.79] SD units), had obesity (0.82 [95% CI, 0.59-1.06] SD units), or had a psychological disorder diagnosis (0.43 [95% CI, 0.29-0.56] SD units) during adolescence were biologically older at midlife compared with participants without these conditions. Participants with asthma were not biologically older at midlife (0.02 [95% CI, -0.14 to 0.19] SD units) compared with those without asthma. These results remained unchanged after adjusting for childhood risk factors such as poor health, socioeconomic disadvantage, and adverse experiences. This study found that adolescent smoking, obesity, and psychological disorder diagnoses were associated with older biological age at midlife. These health conditions could be treated during adolescence to reduce the risk of accelerated biological aging later in life.

Integrating DNA Methylation Measures of Biological Aging into Social Determinants of Health Research.

Acceleration of biological processes of aging is hypothesized to drive excess morbidity and mortality in socially disadvantaged populations. DNA methylation measures of biological aging provide tools for testing this hypothesis. Next-generation DNA methylation measures of biological aging developed to predict mortality risk and physiological decline are more predictive of morbidity and mortality than the original epigenetic clocks developed to predict chronological age. These new measures show consistent evidence of more advanced and faster biological aging in people exposed to socioeconomic disadvantage and may be able to record the emergence of socially determined health inequalities as early as childhood. Next-generation DNA methylation measures of biological aging also indicate race/ethnic disparities in biological aging. More research is needed on these measures in samples of non-Western and non-White populations. New DNA methylation measures of biological aging open opportunities for refining inference about the causes of social disparities in health and devising policies to eliminate them. Further refining measures of biological aging by including more diversity in samples used for measurement development is a critical priority for the field.

Abstract 73: Blood-based Biological Aging Measures Are Easy-to-access Biomarkers For Detection Of Incident Stroke

Introduction: The relationship between biological age and stroke remains unclear. We assessed the role of six DNA methylation and physiology-based biological aging measures as biomarkers of stroke risk. Methods: Participants (N=3520, mean age=69±9 years) in the US Health and Retirement Study’s 2016 Venous Blood and DNA methylation studies. Biological aging measures included: Horvath, Hannum, GrimAge, Levine, Pace of Aging (POA) and Phenotypic Age. The clocks and POA were based on DNA methylation and Phenotypic age was based on serum physiology biomarkers (albumin, creatinine, glucose, C reactive protein, lymphocyte percent, mean cell volume, red blood cell distribution width, alkaline phosphatase, and white blood cell count). All measures were regressed on chronological age and residual values were computed. Multivariable logistic regression and three-way decomposition models were conducted. Total, direct and indirect effect of modifiable risk factors (smoking, BMI, blood pressure, diabetes mellitus, and education) on stroke through biological aging was assessed. Results: A total of 291 incident strokes were included. Individuals who were biologically older had higher odds of stroke with statistically significant estimates for GrimAge (DNA methylation-based) OR (95%CI): 1.32(1.07, 1.62), P=0.009 and PhenoAge (physiology-based) OR: 1.39(1.15, 1.69), P=0.001. In tertiles analysis (lowest tertile as reference), the odds of a new stroke were two to three times higher in biologically older individuals: GrimAge OR 3rd tertile: 2.42(1.08, 5.42), P=0.03; PhenoAge OR: 3.49(1.60, 7.65), P=0.002. Modifiable factors that showed highly significant indirect effect on incident stroke through biological aging are smoking, high blood pressure, diabetes mellitus and education (college or above). Conclusions: Biologically older individuals have 2 to 3 folds higher odds of new stroke occurrence compared to biologically younger individuals. The time lag between biological aging acceleration and manifestation of clinical disease is an opportunity for interventions targeted towards primary stroke prevention.

The metabolome as a biomarker of aging in Drosophila melanogaster.

Many biomarkers have been shown to be associated not only with chronological age but also with functional measures of biological age. In human populations, it is difficult to show whether variation in biological age is truly predictive of life expectancy, as such research would require longitudinal studies over many years, or even decades. We followed adult cohorts of 20 Drosophila Genetic Reference Panel (DGRP) strains chosen to represent the breadth of lifespan variation, obtain estimates of lifespan, baseline mortality, and rate of aging, and associate these parameters with age‐specific functional traits including fecundity and climbing activity and with age‐specific targeted metabolomic profiles. We show that activity levels and metabolome‐wide profiles are strongly associated with age, that numerous individual metabolites show a strong association with lifespan, and that the metabolome provides a biological clock that predicts not only sample age but also future mortality rates and lifespan. This study with 20 genotypes and 87 metabolites, while relatively small in scope, establishes strong proof of principle for the fly as a powerful experimental model to test hypotheses about biomarkers and aging and provides further evidence for the potential value of metabolomic profiles as biomarkers of aging.

Associations Between Blood Pressure and Accelerated DNA Methylation Aging.

BackgroundIndividuals of the same chronological age may exhibit diverse susceptibilities to death. However, few studies have investigated the associations between blood pressure and the accelerated aging.Methods and ResultsA cross‐sectional study was conducted in 288 adults aged ≥50 years. We assessed the DNA methylation‐based measures of biological age using CpG sites on the Illumina HumanMethylationEPIC BeadChip. Epigenetic age acceleration metrics were derived by regressing residuals (ΔAge) and ratios (aging rate) of DNA methylation age on chronological age. Dose‐response relationships between blood pressure and epigenetic age acceleration were quantified using multiple linear regression and restricted cubic regression models. We found that each 10–mm Hg increase in systolic blood pressure was associated with 0.608 (95% CI, 0.231–0.984) years increase in ΔAge and 0.007 (95% CI, 0.002–0.012) increase in aging rate; meanwhile, for pulse pressure, the increase was 1.12 (95% CI, 0.625–1.61) years for ΔAge and 0.013 (95% CI, 0.007–0.020) for aging rate. Subgroup analysis showed that the significant associations of systolic blood pressure and pulse pressure with epigenetic age acceleration appeared to be limited to women, although interactions between blood pressure and sex were not significant (P values for interaction >0.05). The combination of women and hypertension was associated with a much higher increase in ΔAge (β [95% CI], 4.05 [1.07–7.02]) and aging rate (β [95% CI], 0.047 [0.008–0.087]), compared with male participants without hypertension.ConclusionsOur findings suggested that high systolic blood pressure and pulse pressure were associated with the epigenetic age acceleration, providing important clues for relationships between blood pressure and epigenetic aging.

Healthy eating patterns and epigenetic measures of biological age

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. To determine whether healthy eating patterns are associated with methylation-based measures of biological age. 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. 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<2.5h/wk of exercise). 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.