scholarly journals COMPARABILITY OF BIOLOGICAL AGING MEASURES IN THE NATIONAL HEALTH AND NUTRITION EXAMINATION STUDY, 1999-2002

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S479-S479
Author(s):  
Waylon J Hastings ◽  
Daniel Belsky ◽  
Idan Shalev
Keyword(s):  
Risk Factors ◽  
Telomere Length ◽  
Cellular Level ◽  
Biological Age ◽  
Effect Sizes ◽  
Chronological Age ◽  
Biological Aging ◽  
Patient Level ◽  
Age Related ◽  
Level Information

Abstract Biological processes of aging are thought to be modifiable causes of many chronic diseases. Measures of biological aging could provide sensitive endpoints for studies of risk factors hypothesized to shorten healthy lifespan and/or interventions that extend it. However, uncertainty remains about how to measure biological aging and if proposed measures assess the same thing. We tested four proposed measures of biological aging with available data from NHANES 1999-2002: Klemera-Doubal method (KDM) Biological Age, homeostatic dysregulation, Levine Method (LM) Biological Age, and leukocyte telomere length. All measures of biological aging were correlated with chronological age. KDM Biological Age, homeostatic dysregulation, and LM Biological Age were all significantly associated with each other, but were each not associated with telomere length. NHANES participants with older biological ages performed worse on tests of physical, cognitive, perceptual, and subjective functions known to decline with advancing chronological age and thought to mediate age-related disability. Further, NHANES participants with higher levels of exposure to life-course risk factors were measured as having older biological ages. In both sets of analyses, effect-sizes tended to be larger for KDM Biological Age, homeostatic dysregulation, and LM Biological Age as compared to telomere length. Composite measures combining cellular- and patient-level information tended to have the largest effect-sizes. The cellular-level aging biomarker telomere length may measure different aspects of the aging process relative to the patient-level physiological measures. Studies aiming to test if risk factors accelerate aging or if interventions may slow aging should not treat proposed measures of biological aging as interchangeable.

scholarly journals Exploring Epigenetic Age in Response to Intensive Relaxing Training: A Pilot Study to Slow Down Biological Age

2019 ◽  
Vol 16 (17) ◽  
pp. 3074 ◽  
Author(s):  
Pavanello ◽  
Campisi ◽  
Tona ◽  
Lin ◽  
Iliceto
Keyword(s):  
Myocardial Infarction ◽  
Age Estimation ◽  
Healthy Subjects ◽  
Molecular Mechanisms ◽  
Biological Age ◽  
Chronological Age ◽  
Biological Aging ◽  
Epigenetic Clock ◽  
Age Related ◽  
Epigenetic Age

DNA methylation (DNAm) is an emerging estimator of biological aging, i.e., the often-defined “epigenetic clock”, with a unique accuracy for chronological age estimation (DNAmAge). In this pilot longitudinal study, we examine the hypothesis that intensive relaxing training of 60 days in patients after myocardial infarction and in healthy subjects may influence leucocyte DNAmAge by turning back the epigenetic clock. Moreover, we compare DNAmAge with another mechanism of biological age, leucocyte telomere length (LTL) and telomerase. DNAmAge is reduced after training in healthy subjects (p = 0.053), but not in patients. LTL is preserved after intervention in healthy subjects, while it continues to decrease in patients (p = 0.051). The conventional negative correlation between LTL and chronological age becomes positive after training in both patients (p < 0.01) and healthy subjects (p < 0.05). In our subjects, DNAmAge is not associated with LTL. Our findings would suggest that intensive relaxing practices influence different aging molecular mechanisms, i.e., DNAmAge and LTL, with a rejuvenating effect. Our study reveals that DNAmAge may represent an accurate tool to measure the effectiveness of lifestyle-based interventions in the prevention of age-related diseases.

scholarly journals COVID-19 severity is predicted by earlier evidence of accelerated aging

2020 ◽  
Author(s):  
Chia-Ling Kuo ◽  
Luke C. Pilling ◽  
Janice L Atkins ◽  
Jane AH Masoli ◽  
João Delgado ◽  
...  
Keyword(s):  
Clinical Chemistry ◽  
Accelerated Aging ◽  
Biological Age ◽  
Chronological Age ◽  
Biological Aging ◽  
Severe Illness ◽  
Mortality Data ◽  
Age Related ◽  
Underlying Mechanisms ◽  
The Uk

AbstractWith no known treatments or vaccine, COVID-19 presents a major threat, particularly to older adults, who account for the majority of severe illness and deaths. The age-related susceptibility is partly explained by increased comorbidities including dementia and type II diabetes [1]. While it is unclear why these diseases predispose risk, we hypothesize that increased biological age, rather than chronological age, may be driving disease-related trends in COVID-19 severity with age. To test this hypothesis, we applied our previously validated biological age measure (PhenoAge) [2] composed of chronological age and nine clinical chemistry biomarkers to data of 347,751 participants from a large community cohort in the United Kingdom (UK Biobank), recruited between 2006 and 2010. Other data included disease diagnoses (to 2017), mortality data (to 2020), and the UK national COVID-19 test results (to May 31, 2020) [3]. Accelerated aging 10-14 years prior to the start of the COVID-19 pandemic was associated with test positivity (OR=1.15 per 5-year acceleration, 95% CI: 1.08 to 1.21, p=3.2×10−6) and all-cause mortality with test-confirmed COVID-19 (OR=1.25, per 5-year acceleration, 95% CI: 1.09 to 1.44, p=0.002) after adjustment for demographics including current chronological age and pre-existing diseases or conditions. The corresponding areas under the curves were 0.669 and 0.803, respectively. Biological aging, as captured by PhenoAge, is a better predictor of COVID-19 severity than chronological age, and may inform risk stratification initiatives, while also elucidating possible underlying mechanisms, particularly those related to inflammaging.

PREMATURE AGING INDICES IN PATIENTS WITH MODERATE CARDIOVASCULAR RISK

2021 ◽  
pp. 5-9
Author(s):  
A. O. Radchenko ◽  
T. M. Bondar ◽  
A. V. Potapenko
Keyword(s):  
Risk Factors ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Telomere Length ◽  
Age Groups ◽  
The Body ◽  
Premature Aging ◽  
Biological Age ◽  
Associated Diseases ◽  
Age Related

Aging is characterized with a gradual aggravation of organ function throughout life and can occur both physiologically and prematurely. With premature aging there is an early decrease in the adaptive mechanisms of all physiological systems of the body, there is a significant reduction in physical and mental activities, that contributes to the early development of age−related pathology. Genetic and epigenetic factors, as well as environmental ones can be the causes of different rates of aging. It is not possible to accurately determine the onset of old age by biological characteristics, because people with the same calendar age are not always the same as for biological one. To establish the association of age−related disease factors with the markers of premature aging and biological age in the patients of various age groups, a study was performed in the patients aged 25−44 and 45−59 years with moderate cardiovascular risk in accordance with the SCORE scale. The primary task for predicting and preventing the age−associated diseases is to identify genetic, molecular and cellular factors that determine the rate of aging and increase the risk of age−associated diseases. The role of cardiovascular risk factors in premature aging has been determined. It is established that the most important factors that lead to an increase in biological age and formation of age−associated diseases are the disorders of lipid and carbohydrate metabolism and level of oxidative stress, importance of which progresses with age. The relationship between cardiovascular risk factors and biological age, estimated with different methods, their influence on telomere length, that allows the designing of an algorithm to determine the markers of premature aging in different age groups for early and effective prevention of metabolic−associated diseases, has been established. Key words: biological age, cardiovascular risk, premature aging, telomere length.

scholarly journals Epigenetic clocks predict prevalence and incidence of leading causes of death and disease burden

2020 ◽  
Author(s):  
Robert F. Hillary ◽  
Anna J. Stevenson ◽  
Daniel L. McCartney ◽  
Archie Campbell ◽  
Rosie M. Walker ◽  
...  
Keyword(s):  
Risk Factors ◽  
Telomere Length ◽  
Disease Burden ◽  
Self Report ◽  
Health Study ◽  
Chronological Age ◽  
Common Disease ◽  
Prevalence Odds Ratio ◽  
Epigenetic Markers ◽  
Age Related

AbstractIndividuals of the same chronological age display different rates of biological ageing. A number of measures of biological age have been proposed which harness age-related changes in DNA methylation profiles. These include methylation-based predictors of chronological age (HorvathAge, HannumAge), all-cause mortality (DNAm PhenoAge, DNAm GrimAge) and telomere length (DNAm Telomere Length). In this study, we test the association between these epigenetic markers of ageing and the prevalence and incidence of the leading causes of disease burden and mortality in high-income countries. Furthermore, we test the clocks’ relationships with phenotypic measures associated with these conditions, including spirometric and biochemical traits. We carry out these analyses in 9,537 individuals from the Generation Scotland: Scottish Family Health Study. We find that DNAm GrimAge outperforms other epigenetic clocks in its associations with self-report disease prevalence and related clinical traits. DNAm GrimAge associates with chronic obstructive pulmonary disease (COPD) prevalence (Odds Ratio = 3.29, P = 3.0 × 10-4) and pulmonary spirometry tests (β = [-0.10 to −0.15], P = [1.4 × 10-4 to 1.4 × 10-6]) at study baseline after adjusting for possibly confounding risk factors including alcohol, body mass index, deprivation, education and smoking. After adjusting for these confounding risk factors, DNAm GrimAge, DNAm PhenoAge and DNAm Telomere Length, measured at study baseline, predict incidence of ICD-10-coded disease states including COPD, type 2 diabetes and cardiovascular disease after thirteen years of follow-up (Hazard Ratios = [0.80 (telomere length) to 2.19 (GrimAge)], P = [9.9 × 10-4, 1.9 × 10-14]). Our data show that despite accounting for several possible confounding variables, epigenetic markers of ageing predict incidence of common disease. This may have significant implications for their potential utility in clinical settings to complement gold-standard methods of clinical assessment and management.

scholarly journals Diabetes mellitus correlates with increased biological age as indicated by clinical biomarkers

GeroScience ◽  
2021 ◽  
Author(s):  
Nadine Bahour ◽  
Briana Cortez ◽  
Hui Pan ◽  
Hetal Shah ◽  
Alessandro Doria ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Cellular Level ◽  
Biological Age ◽  
Chronological Age ◽  
Mortality Data ◽  
Diabetes Mortality ◽  
Clinical Biomarkers ◽  
Gender And Age

AbstractChronological age (CA) is determined by time of birth, whereas biological age (BA) is based on changes on a cellular level and strongly correlates with morbidity, mortality, and longevity. Type 2 diabetes (T2D) associates with increased morbidity and mortality; thus, we hypothesized that BA would be increased and calculated it from biomarkers collected at routine clinical visits. Deidentified data was obtained from three cohorts of patients (20–80 years old)—T2D, type 1 diabetes (T1D), and prediabetes—and compared to gender- and age-matched non-diabetics. Eight clinical biomarkers that correlated with CA in people without diabetes were used to calculate BA using the Klemera and Doubal method 1 (KDM1) and multiple linear regression (MLR). The phenotypic age (PhAge) formula was used with its predetermined biomarkers. BA of people with T2D was, on average, 12.02 years higher than people without diabetes (p < 0.0001), while BA in T1D was 16.32 years higher (p < 0.0001). Results were corroborated using MLR and PhAge. The biomarkers with the strongest correlation to increased BA in T2D using KDM were A1c (R2 = 0.23, p < 0.0001) and systolic blood pressure (R2 = 0.21, p < 0.0001). BMI had a positive correlation to BA in non-diabetes subjects but disappeared in those with diabetes. Mortality data using the ACCORD trial was used to validate our results and showed a significant correlation between higher BA and decreased survival. In conclusion, BA is increased in people with diabetes, irrespective of pathophysiology, and to a lesser extent in prediabetes.

scholarly journals Biological Age Prediction From Wearable Device Movement Data Identifies Nutritional and Pharmacological Interventions for Healthy Aging

2021 ◽  
Vol 2 ◽  
Author(s):  
Rebecca L. McIntyre ◽  
Mizanur Rahman ◽  
Siva A. Vanapalli ◽  
Riekelt H. Houtkooper ◽  
Georges E. Janssens
Keyword(s):  
Healthy Aging ◽  
Machine Learning Algorithms ◽  
Biological Age ◽  
Wearable Device ◽  
Biological Aging ◽  
Accelerometer Data ◽  
Pharmacological Interventions ◽  
C Elegans ◽  
Movement Data ◽  
Age Related

Intervening in aging processes is hypothesized to extend healthy years of life and treat age-related disease, thereby providing great benefit to society. However, the ability to measure the biological aging process in individuals, which is necessary to test for efficacy of these interventions, remains largely inaccessible to the general public. Here we used NHANES physical activity accelerometer data from a wearable device and machine-learning algorithms to derive biological age predictions for individuals based on their movement patterns. We found that accelerated biological aging from our “MoveAge” predictor is associated with higher all-cause mortality. We further searched for nutritional or pharmacological compounds that associate with decelerated aging according to our model. A number of nutritional components peak in their association to decelerated aging later in life, including fiber, magnesium, and vitamin E. We additionally identified one FDA-approved drug associated with decelerated biological aging: the alpha-blocker doxazosin. We show that doxazosin extends healthspan and lifespan in C. elegans. Our work demonstrates how a biological aging score based on relative mobility can be accessible to the wider public and can potentially be used to identify and determine efficacy of geroprotective interventions.

Abstract 160: DNA-Methylation and Aging. Contribution of Biological Age to Recovery After Ischemic Stroke

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Jordi Jimenez-Conde ◽  
Carolina Soriano-Tarraga ◽  
Eva Giralt-Steinhauer ◽  
Marina Mola ◽  
Rosa Vivanco-Hidalgo ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Ischemic Stroke ◽  
Functional Status ◽  
Biological Age ◽  
Chronological Age ◽  
Bivariate Analysis ◽  
Stroke Severity ◽  
Age Related ◽  
Recovery Capacity ◽  
The Impact

Background: Stroke has a great impact in functional status of patients, although there are substantial interindividual differences in recovery capacity. Apart from stroke severity, age is considered an important predictor of outcome after stroke, but aging is not only due to chronological age. There are age-related DNA-methylation changes in multiple CpG sites across the genome that can be used to estimate the biological age (b-Age), and we seek to analyze the impact of this b-Age in recovery after an ischemic stroke. Methods: We include 600 individuals with acute ischemic stroke assessed in Hospital del Mar (Barcelona). Demographic and clinical data such as chronological age (c-Age), vascular risk factors, NIHSS at admission, recanalization treatment (rtPA or endovascular treatment), previous modified Rankin scale (p-mRS) and 3 months post stroke functional status (3-mRS) were registered. Biological age (b-Age) was estimated with Hannumm algorithm, based on DNA methylation in 71 CpGs. Results: The bivariate analyses for association with 3-mRS showed a significant results of NIHSS, c-Age, b-Age, p-mRS, and current smoking (all with p<0.001). Recanalization treatment showed no significant differences in bivariate analysis. In multivariate ordinal models, b-Age kept its significance (p=0.025) nullifying c-Age (p=0.84). Initial NIHSS, p-mRS and recanalization treatment kept also significant results (p<0.001). Conclusions: Biological Age, estimated by DNA methylation, is an independent predictor of stroke prognosis, irrespective to chronological age. "Healthy aging” affects the capacity of recovering after an ischemic stroke.

Abstract TMP57: The Influence of Telomere Length on Ischemic Stroke Risk and Phenotype

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Ezgi Yetim ◽  
Mehmet A Topcuoglu ◽  
Nuket Yurur Kutlay ◽  
Ajlan Tukun ◽  
Kader K Oguz ◽  
...  
Keyword(s):  
Risk Factors ◽  
Ischemic Stroke ◽  
Telomere Length ◽  
Significant Relationship ◽  
Stroke Risk ◽  
Prior History ◽  
Lesion Volume ◽  
Nihss Score ◽  
Stroke Etiology ◽  
Age Related

Background: Telomeres are specific nucleotide repeats that play a central role in control of DNA damage related to cell division and aging. The degree of telomere shortening that occurs as part of aging is associated with age-related non-cancer diseases like hypertension, diabetes mellitus and coronary artery disease. Although a number of studies have highlighted that a similar relationship might exist with ischemic stroke, contradictory reports are also present in the literature. In this study we investigated the association between telomere length and ischemic stroke, not only in terms of stroke risk in general, but also from the perspective of stroke etiology and severity. Methods: In a Caucasian cohort, telomere length was determined by Southern blot from peripheral blood leukocytes in 163 consecutive ischemic stroke patients, and 210 controls without any prior history of ischemic stroke. Univariate and multivariate analyses were performed to determine the contribution of telomere length to stroke risk, stroke etiology, admission NIHSS score and DWI lesion volume. Results: The median (interquartile range) telomere length was 7.0 (5.5-9.0) kb in the overall population. Expectedly, telomere length was negatively correlated with aging (r=-0.23; p<0.001). A short telomere length (i.e. lowest quartile; ≤5.5 kb) was significantly associated with ischemic stroke (OR 3.0, 95%CI 1.8-5.1) when adjusted for age, gender and cardiovascular risk factors. This significant relationship persisted for all stroke etiologies, except for other rare causes of stroke. There was no significant relationship between admission lesion volume and telomere length; however, patients with short telomeres presented with more severe strokes (NIHSS score ≥16) when adjusted for age, risk factors, stroke etiology and infarct volume (OR 7.0; 95%CI 1.7-28.7). Conclusion: Almost all etiologic subtypes of ischemic stroke are related to shortened telomere length, irrespective of the age of the subject. Furthermore, presence of short telomeres negatively influences the tolerance of brain to ischemia, thereby causing more severe clinical phenotypes in these patients in the setting of ischemic stroke.

scholarly journals Telomere Length as a Biomarker of Biological Aging in Shift Workers

2020 ◽  
Vol 10 (8) ◽  
pp. 2764 ◽  
Author(s):  
Caterina Ledda ◽  
Carla Loreto ◽  
Venerando Rapisarda
Keyword(s):  
Telomere Length ◽  
Biological Aging ◽  
Work Schedule ◽  
Shift Workers ◽  
Daily Work ◽  
Occupational Physicians ◽  
Age Related ◽  
Health Advice ◽  
Basic Biology ◽  
Biology Of Aging

Shift work (SW) comprises a work schedule that involves recurring times of nonstandard work hours balanced to a fixed daily work plan with regular day work times and has been evaluated as “probably carcinogenic to humans” (Group 2A) by IARC. SW may result in increased age acceleration. This systematic review aims to elucidate the usefulness of telomere length as a biomarker of biological aging in shift workers. All studies analyzed underline a shortening of telomere length in SW, and aging in shift workers and duration of work. Methodologies to measure biological aging are possible to advance efforts to clarify the basic biology of aging and provide clinicians an instrument to communicate complex health advice to workers. Telomere length measures can also give an instrument for precision medicine, useful for occupational physicians in age-related screening conditions.

scholarly journals Risk stratification by means of biological age-related factors better predicts cancer-specific survival than chronological age in patients with upper tract urothelial carcinoma: a multi-institutional database study

2018 ◽  
Vol 10 (12) ◽  
pp. 403-410 ◽  
Author(s):  
Teruo Inamoto ◽  
Hideyasu Matsuyama ◽  
Naokazu Ibuki ◽  
Kazumasa Komura ◽  
Kiyohide Fujimoto ◽  
...  
Keyword(s):  
Urothelial Carcinoma ◽  
Clinical Response ◽  
Treatment Options ◽  
Upper Tract Urothelial Carcinoma ◽  
Biological Age ◽  
Chronological Age ◽  
Related Factors ◽  
Cancer Specific Survival ◽  
Upper Tract ◽  
Age Related

Background: Chronological age is an important factor in determining the treatment options and clinical response of patients with upper tract urothelial carcinoma (UTUC). Much evidence suggests that chronological age alone is an inadequate indicator to predict the clinical response to radical nephroureterectomy (RNU). Patients and methods: We retrospectively reviewed the data from 1510 patients with UTUC (Ta-4) treated by surgery. White blood cell (WBC) count, neutrophil-to-lymphocyte ratio, hemoglobin (Hb), platelets, albumin, alkaline phosphatase, lactate dehydrogenase, creatinine, and corrected calcium were tested by the Spearman correlation to indicate the direction of association with chronological age, which yielded significant, negative associations of Hb ( p < 0.001) and WBC ( p = 0.010) with chronological age. For scoring, we assigned points for these categories as follows; point ‘0’ for Hb >14 (reference) and 13–13.9 [odds ratio (OR): 1.533], point ‘1’ for 12–12.9 (OR: 2.391), point ‘2’ for 11–11.9 (OR: 3.015), and point ‘3’ for <11 (OR: 3.584). For WBC, point ‘1’ was assigned for >9200 (OR: 2.541) and ‘0’ was assigned for the rest; 9200–8500 (reference), 8499–6000 (OR: 0.873), 5999–4500 (OR: 0.772), 4499–3200 (OR: 0.486), and <3200 (OR: 1.277). Results: The 10-year cancer-specific survival (CSS) in the higher risk group with scores of 4 or higher in patients age <60 years was worse than a score of 0, or 1 in age >80 years [mean estimated survival 69.7 months, confidence interval (CI): 33.3–106 versus 103.5. CI: 91–115.9]. The concordance index between biological age scoring and chronological age was 0.704 for CSS and 0.798 for recurrence-free survival. The limitation of the present study is the retrospective nature of the cohort included. Conclusions: The biological age scoring developed for patients with UTUC undergoing RNU. It was applicable to those with localized disease and performed well in diverse age populations.

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