Biological Senescence: Loss of Integration and Resilience

1995 ◽  
Vol 14 (1) ◽  
pp. 106-120 ◽  
Author(s):  
F. Eugene Yates ◽  
Laurel A. Benton
Keyword(s):  
Degrees Of Freedom ◽  
Nonequilibrium Thermodynamics ◽  
Physical Basis ◽  
Biological Age ◽  
Chronological Age ◽  
Nonlinear Mechanics ◽  
Internal Time ◽  
Flow Of Time

ABSTRACTThe flow of time can be conceptualized either as a cycle or an arrow. We offer a combined view: a helix. Chronological age (geophysical time reference) is not necessarily identical to biological age (internal time reference), and aging does not necessarily imply senescence. A new scheme of senescence, based on homeodynamics (nonlinear mechanics and nonequilibrium thermodynamics), is introduced as a plausible physical basis for understanding senescence. We propose that energy throughput, initially constructive of forms and functions, becomes destructive once most of the available degrees of freedom have been “frozen out” by the construction. Senescence becomes manifested at that point.

scholarly journals De-standardising ageing? Shifting regimes of age measurement

2015 ◽  
Vol 36 (7) ◽  
pp. 1407-1433 ◽  
Author(s):  
TIAGO MOREIRA
Keyword(s):  
20Th Century ◽  
Sociological Theory ◽  
Biological Age ◽  
Chronological Age ◽  
Advanced Economies ◽  
Institutional Responses ◽  
Changing Role

ABSTRACTDeparting from the proposition that, in the sociological debate about whether there has been a shift towards a de-standardised lifecourse in advanced economies, little attention has been devoted to the infrastructural arrangements that would support such a transition, this paper explores the changing role of standards in the governance of ageing societies. In it, I outline a sociological theory of age standard substitution which suggests that contradictory rationalities used in the implementation of chronological age fuelled the emergence of a critique of chronological age within the diverse strands of gerontological knowledge during the 20th century. The paper analyses how these critiques were linked to a proliferation of substitute, ‘personalised’ age standards that aimed to conjoin individuals’ unique capacities or needs to roles or services. The paper suggests that this configuration of age standards’ production, characterised by uncertainty and an opening of moral and epistemic possibilities, has been shrouded by another, more recent formation where institutional responses to decentred processes of standardisation moved research and political investment towards an emphasis on biological age measurement.

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 in UK Biobank: biomarker composition and prediction of mortality, coronary heart disease and hospital admissions

2019 ◽  
Author(s):  
Mei Sum Chan ◽  
Matthew Arnold ◽  
Alison Offer ◽  
Imen Hammami ◽  
Marion Mafham ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Risk Factor ◽  
Heart Disease ◽  
Principal Components ◽  
Hospital Admissions ◽  
Principal Component ◽  
Age Effects ◽  
Biological Age ◽  
Chronological Age ◽  
Uk Biobank

AbstractBackgroundAge is the strongest risk factor for most chronic diseases, and yet individuals may age at different rates biologically. A biological age formed from biomarkers may be a stronger risk factor than chronological age and understanding what factors contribute to it could provide insight into new opportunities for disease prevention.Methods and findingsAmong 480,019 UK Biobank participants aged 40-70 recruited in 2006-2010 and followed up for 6-12 years via linked death registry and secondary care records, a subpopulation of 141,254 (29.4%) non-smoking adults in good health and with no medication use or disease history at baseline were identified. Independent components of 72 biomarkers measured at baseline were characterised by principal component analysis. The Klemera Doubal method (KDM), which derived a weighted sum of biomarker principal components based on the strengths of their linear associations with chronological age, was used to derive sex-specific biological ages in this healthy subpopulation. The proportions of the overall biological and chronological age effects on mortality, coronary heart disease and age-related non-fatal hospital admissions (based on a hospital frailty index) that were explained by biological age were assessed using log-likelihoods of proportional hazards models.Reduced lung function, reduced kidney function, slower reaction time, lower insulin-like-growth factor 1, lower hand grip strength and higher blood pressure were key contributors to biological age (explaining the highest percentages of its variance) in both men and women, while lower albumin, higher sex hormone-binding globulin and lower muscle mass in men, and higher liver enzymes, blood lipids and HbA1c in women were also important. Across both sexes, a 51-principal component biological age explained 66%, 80% and 63% of the age effects on mortality, coronary heart disease and hospital admissions, respectively. Restricting the biological age to the 12-13 key biomarkers corresponding to the 10 most importantly contributing principal components resulted in little change in these proportions for women, but a reduction to 53%, 63% and 50%, respectively, for men.ConclusionsThis study identified that markers of impaired function in a range of organs account for a substantial proportion of the apparent effect of age on disease and hospital admissions. It supports a broader, multi-system approach to research and prevention of diseases of ageing.

scholarly journals Selective effects of biological and chronological age on the development of cognitive abilities in adolescence

2021 ◽  
Author(s):  
Ilona Kovacs ◽  
Kristof Kovacs ◽  
Patricia Gervan ◽  
Katinka Utczas ◽  
Gyongyi Olah ◽  
...  
Keyword(s):  
Cognitive Abilities ◽  
Skeletal Maturity ◽  
Pubertal Timing ◽  
Working Memory Capacity ◽  
Bone Age ◽  
Gonadal Hormones ◽  
Individual Variability ◽  
Biological Age ◽  
Chronological Age ◽  
Biological Maturity

Adolescent development is not only shaped by the mere passing of time and accumulating experience, it also depends on pubertal timing and the cascade of maturational processes orchestrated by gonadal hormones. Although individual variability in puberty onset confounds adolescent studies, it has not been efficiently controlled for. Here we introduce ultrasonic bone age assessment to estimate biological maturity and disentangle the independent effects of chronological and biological age on adolescent cognitive abilities. Comparing cognitive performance of participants with different skeletal maturity we uncover the striking impact of biological age on both IQ and specific abilities. We find that biological age has a selective effect on abilities: more mature individuals within the same age group have higher working memory capacity and processing speed, while those with higher chronological age have better verbal abilities, independently of their maturity. Based on our findings, bone age is a promising biomarker for adolescent research.

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.

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 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.

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.

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