SENESCENCE SECRETOME: BIOMARKERS OF BIOLOGICAL AGING AND POSTOPERATIVE OUTCOMES

Abstract Senescent cells drive age-related tissue dysfunction through their potent secretome, termed the senescence associated secretory phenotype (SASP). Circulating concentrations of SASP factors may reflect biological age and serve as clinically useful biomarkers of surgical risk and ultimately, surrogate endpoints in clinical trials. However, they remain largely uncharacterized. We tested associations between circulating concentrations of SASP proteins and biological age, as determined by the accumulation of age-related health deficits, and/or postoperative outcomes in a sample of residents in Olmstead County, MN, age 60-90 years (n = 115) and cohorts of older adults undergoing surgery for severe aortic stenosis (prospective; n = 97) or ovarian cancer (case-control; n = 36). Circulating concentrations of SASP factors were associated with biological age and adverse postoperative outcomes, including risk of any adverse event or rehospitalization within the year following surgery (aortic stenosis group) or admission to an intensive care unit within 30 days of hospital discharge (ovarian cancer group). Gradient boosting machine modeling revealed a panel of SASP factors that predicted adverse outcomes across both surgical groups better than biological age or chronological age and sex. This suggests that the circulating SASP is a robust indicator of age-related health status and may help guide clinical decision making. Furthermore, circulating SASP factors may be harnessed as a readily quantifiable biomarkers in senescence-targeting interventional human studies.

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

Frontiers in Aging ◽

10.3389/fragi.2021.708680 ◽

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.

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A New Monocyte Epigenetic Clock Reveals Effects of Alcohol Consumption on Epigenetic Aging in Three Independent Cohorts

10.1101/2021.03.22.436488 ◽

2021 ◽

Author(s):

Xiaoyu Liang ◽

Rajita Sinha ◽

Amy C. Justice ◽

Mardge H. Cohen ◽

Bradley E. Aouizerat ◽

...

Keyword(s):

Alcohol Consumption ◽

Hiv Infection ◽

Clinical Decision Making ◽

Clinical Decision ◽

Biological Age ◽

Biological Aging ◽

Epigenetic Clock ◽

Excessive Alcohol Consumption ◽

Epigenetic Age ◽

The Impact

AbstractBackgroundExcessive alcohol consumption increases the risk of aging-related comorbidities and mortality. Assessing the impact of alcohol consumption on biological age is important for clinical decision-making and prevention. Evidence shows that alcohol alters monocyte function, and age is associated with DNA methylome and transcriptomic changes among monocytes. However, no monocyte-based epigenetic clock is currently available. In this study, we developed a new monocyte-based DNA methylation clock (MonoDNAmAge) by using elastic net regularization. The MonoDNAmAge was validated by benchmarking using epigenetic age acceleration (EAA) in HIV infection. Using MonoDNAmAge clock as well as four established clocks (i.e., HorvathDNAmAge, HannumDNAmAge, PhenoDNAmAge, GrimDNAmAge), we then evaluated the effect of alcohol consumption on biological aging in three independent cohorts (N=2,242).ResultsMonoDNAmAge, comprised of 186 CpG sites, was highly correlated with chronological age (rtraining=0.96, p<2.20E-16; rtesting=0.86, p=1.55E-141). The MonoDNAmAge clock predicted an approximately 10-year age acceleration from HIV infection in two cohorts. Quadratic regression analysis showed a nonlinear relationship between MonoDNAmAge and alcohol consumption in the Yale Stress Center Community Study (YSCCS, pmodel=4.55E-08, px2 =7.80E-08) and in the Veteran Aging Cohort Study (VACS, pmodel=1.85E-02, px2 =3.46E-02). MonoDNAmAge and light alcohol consumption showed a negative linear relationship in the Women’s Interagency HIV Study (WIHS, β=-2.63, px=2.82E-06). Heavy consumption increased EAAMonoDNAmAge up to 1.60 years in the VACS while light consumption decreased EAAMonoDNAmAge to 2.66 years in the WIHS. These results were corroborated by the four established epigenetic clocks.ConclusionsWe observed a nonlinear effect of alcohol consumption on epigenetic age that is estimated by a novel monocyte-based “clock” in three distinct cohorts, highlighting the complex effects of alcohol consumption on biological age.

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

Innovation in Aging ◽

10.1093/geroni/igz038.1783 ◽

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.

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

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16173074 ◽

2019 ◽

Vol 16 (17) ◽

pp. 3074 ◽

Cited By ~ 5

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

10.1101/2020.07.10.20147777 ◽

2020 ◽

Cited By ~ 1

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.

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Biological Aging Predicts Vulnerability to COVID-19 Severity in UK Biobank Participants

Innovation in Aging ◽

10.1093/geroni/igab046.2535 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

pp. 678-678

Author(s):

Chia-Ling Kuo ◽

Luke Pilling ◽

Janice Atkins ◽

Jane Masoli ◽

João Delgado ◽

...

Keyword(s):

Biological Age ◽

Biological Aging ◽

Assessment Centers ◽

Uk Biobank ◽

Logistic Regression Models ◽

Age Related ◽

Inpatient Settings ◽

The Uk ◽

Related Mortality

Abstract Age and disease prevalence are the two biggest risk factors for COVID-19 symptom severity and death. We therefore hypothesized that increased biological age, beyond chronological age, may be driving disease-related trends in COVID-19 severity. Using the UK Biobank England data, we tested whether a biological age estimate (PhenoAge) measured more than a decade prior to the COVID-19 pandemic was predictive of two COVID-19 severity outcomes (inpatient test positivity and COVID-19 related mortality with inpatient test-confirmed COVID-19). Logistic regression models were used with adjustment for age at the pandemic, sex, ethnicity, baseline assessment centers, and pre-existing diseases/conditions. 613 participants tested positive at inpatient settings between March 16 and April 27, 2020, 154 of whom succumbed to COVID-19. PhenoAge was associated with increased risks of inpatient test positivity and COVID-19 related mortality (ORMortality=1.63 per 5 years, 95% CI: 1.43-1.86, p=4.7x10E-13) adjusting for demographics including age at the pandemic. Further adjustment for pre-existing disease s/conditions at baseline (OR_M=1.50, 95% CI: 1.30-1.73 per 5 years, p=3.1x10E-8) and at the early pandemic (OR_M=1.21, 95% CI: 1.04-1.40 per 5 years, p=0.011) decreased the association. PhenoAge measured in 2006-2010 was associated with COVID-19 severity outcomes more than 10 years later. These associations were partly accounted for by prevalent chronic diseases proximate to COVID-19 infection. Overall, our results suggest that aging biomarkers, like PhenoAge may capture long-term vulnerability to diseases like COVID-19, even before the accumulation of age-related comorbid conditions.

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Biological age is a universal marker of aging, stress, and frailty

10.1101/578245 ◽

2019 ◽

Cited By ~ 1

Author(s):

Timothy V. Pyrkov ◽

Peter O. Fedichev

Keyword(s):

Large Scale ◽

Systematic Investigation ◽

Biological Age ◽

Biological Aging ◽

Physical And Mental Health ◽

Mortality And Morbidity ◽

Markers Of Inflammation ◽

Biomarkers Of Aging ◽

Age Related

SummaryWe carried out a systematic investigation of supervised learning techniques for biological age modeling. The biological aging acceleration is associated with the remaining health- and life-span. Artificial Deep Neural Networks (DNN) could be used to reduce the error of chronological age predictors, though often at the expense of the ability to distinguish health conditions. Mortality and morbidity hazards models based on survival follow-up data showed the best performance. Alternatively, logistic regression trained to identify chronic diseases was shown to be a good approximation of hazards models when data on survival follow-up times were unavailable. In all models, the biological aging acceleration was associated with disease burden in persons with diagnosed chronic age-related conditions. For healthy individuals, the same quantity was associated with molecular markers of inflammation (such as C-reactive protein), smoking, current physical, and mental health (including sleeping troubles, feeling tired or little interest in doing things). The biological age thus emerged as a universal biomarker of age, frailty and stress for applications involving large scale studies of the effects of longevity drugs on risks of diseases and quality of life.To be published as Chapter 2 in “Biomarkers of aging”, ed. A. Moskalev, Springer, 2019.

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Mitochondrial Dysfunction and Aging: Insights from the Analysis of Extracellular Vesicles

International Journal of Molecular Sciences ◽

10.3390/ijms20040805 ◽

2019 ◽

Vol 20 (4) ◽

pp. 805 ◽

Cited By ~ 26

Author(s):

Anna Picca ◽

Flora Guerra ◽

Riccardo Calvani ◽

Cecilia Bucci ◽

Maria Lo Monaco ◽

...

Keyword(s):

Quality Control ◽

Mitochondrial Dysfunction ◽

Extracellular Vesicles ◽

Cell Function ◽

Nutrient Sensing ◽

Adverse Outcomes ◽

Biological Aging ◽

Low Grade ◽

Mitochondrial Quality Control ◽

Age Related

The progressive decline of cell function and integrity, manifesting clinically as increased vulnerability to adverse outcomes and death, is core to biological aging. Mitochondrial dysfunction, oxidative stress, altered intercellular communication (including chronic low-grade inflammation), genomic instability, telomere attrition, loss of proteostasis, altered nutrient sensing, epigenetic alterations, and stem cell exhaustion have been proposed as hallmarks of aging. These “aging pillars” are not mutually exclusive, making the matter intricate and leaving numerous unanswered questions. The characterization of circulating extracellular vesicles (EVs) has recently allowed specific secretory phenotypes associated with aging to be identified. As such, EVs may serve as novel biomarkers for capturing the complexity of aging. Besides the mitochondrial–lysosomal axis, EV trafficking has been proposed as an additional layer in mitochondrial quality control. Indeed, disruption of the mitochondrial–lysosomal axis coupled with abnormal EV secretion may play a role in the pathogenesis of aging and several disease conditions. Here, we discuss (1) the mechanisms of EV generation; (2) the relationship between the mitochondrial–lysosomal axis and EV trafficking in the setting of mitochondrial quality control; and (3) the prospect of using EVs as aging biomarkers and as delivery systems for therapeutics against age-related conditions.

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Can Blood-Circulating Factors Unveil and Delay Your Biological Aging?

Biomedicines ◽

10.3390/biomedicines8120615 ◽

2020 ◽

Vol 8 (12) ◽

pp. 615

Author(s):

Natalia Rybtsova ◽

Tatiana Berezina ◽

Alexander Kagansky ◽

Stanislav Rybtsov

Keyword(s):

Cell Activity ◽

Developed Countries ◽

Medical Intervention ◽

Premature Aging ◽

Biological Age ◽

Cellular Damage ◽

World Health ◽

Biological Aging ◽

Age Related ◽

Blood Factors

According to the World Health Organization, the population of over 60 will double in the next 30 years in the developed countries, which will enforce a further raise of the retirement age and increase the burden on the healthcare system. Therefore, there is an acute issue of maintaining health and prolonging active working longevity, as well as implementation of early monitoring and prevention of premature aging and age-related disorders to avoid early disability. Traditional indicators of biological age are not always informative and often require extensive and expensive analysis. The study of blood factors is a simple and easily accessible way to assess individual health and supplement the traditional indicators of a person’s biological age with new objective criteria. With age, the processes of growth and development, tissue regeneration and repair decline; they are gradually replaced by enhanced catabolism, inflammatory cell activity, and insulin resistance. The number of senescent cells supporting the inflammatory loop rises; cellular clearance by autophagy and mitophagy slows down, resulting in mitochondrial and cellular damage and dysfunction. Monitoring of circulated blood factors not only reflects these processes, but also allows suggesting medical intervention to prevent or decelerate the development of age-related diseases. We review the age-related blood factors discussed in recent publications, as well as approaches to slowing aging for healthy and active longevity.

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REVISITING THE HALLMARKS OF AGING TO IDENTIFY MARKERS OF BIOLOGICAL AGE

Journal of Prevention of Alzheimer's Disease ◽

10.14283/jpad.2019.50 ◽

2019 ◽

pp. 1-9

Author(s):

F. Guerville ◽

P. De Souto Barreto ◽

I. Ader ◽

S. Andrieu ◽

L. Casteilla ◽

...

Keyword(s):

Life Expectancy ◽

Clinical Outcomes ◽

Chronic Diseases ◽

Healthy Aging ◽

Predictive Biomarkers ◽

Adverse Outcomes ◽

Biological Aging ◽

Biological Processes ◽

Biomarkers Of Aging ◽

Age Related

The Geroscience aims at a better understanding of the biological processes of aging, to prevent and/or delay the onset of chronic diseases and disability as well as to reduce the severity of these adverse clinical outcomes. Geroscience thus open up new perspectives of care to live a healthy aging, that is to say without dependency. To date, life expectancy in healthy aging is not increasing as fast as lifespan. The identification of biomarkers of aging is critical to predict adverse outcomes during aging, to implement interventions to reduce them, and to monitor the response to these interventions. In this narrative review, we gathered information about biomarkers of aging under the perspective of Geroscience. Based on the current literature, for each hallmark of biological aging, we proposed a putative biomarker of healthy aging, chosen for their association with mortality, age-related chronic diseases, frailty and/or functional loss. We also discussed how they could be validated as useful predictive biomarkers.

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