Heritability of and mortality prediction with a longevity phenotype: the healthy aging index

A systematic review of phenotypic and epigenetic clocks used for aging and mortality quantification in humans

Aging is the leading driver of disease in humans and has profound impacts on mortality. Biological clocks are used to measure the aging process in the hopes of identifying possible interventions. Biological clocks may be categorized as phenotypic or epigenetic, where phenotypic clocks use easily measurable clinical biomarkers and epigenetic clocks use cellular methylation data. In recent years, methylation clocks have attained phenomenal performance when predicting chronological age and have been linked to various age-related diseases. Additionally, phenotypic clocks have been proven to be able to predict mortality better than chronological age, providing intracellular insights into the aging process. This review aimed to systematically survey all proposed epigenetic and phenotypic clocks to date, excluding mitotic clocks (i.e., cancer risk clocks) and those that were modeled using non-human samples. We reported the predictive performance of 33 clocks and outlined the statistical or machine learning techniques used. We also reported the most influential clinical measurements used in the included phenotypic clocks. Our findings provide a systematic reporting of the last decade of biological clock research and indicate possible avenues for future research.

Association of a healthy ageing index with health-related outcomes in a multi-ethnic cohort from Singapore

BACKGROUND

The global population is ageing rapidly and it is important to promote healthy ageing. The Healthy Ageing Index (HAI) is a comprehensive measure of health, but there is limited research on its association with other age-related outcomes. The management of an aging population necessitates considerations even among generally healthy adults, as age-related diseases often remain unaccounted for until later stages of life. This study explores the association of risk factors with HAI and its association with peripheral artery disease (PAD), muscle strength, health-related quality of life (HRQoL), and psychological distress in the Singapore Multi-Ethnic Cohort study.

METHODS

This cross-sectional study involved 1909 participants (median (Q1, Q3) age: 53 (48, 60) years and 59.3% females) from Singapore Multi-Ethnic Cohort study. The risk factors of HAI included age, gender, ethnicity, education level, smoking, alcohol consumption, employment, BMI and past medical histories. PAD was assessed using ankle-brachial index (ABI), handgrip strength (HGS), HRQoL with the EQ-5D-5 L questionnaire and psychological distress via the Kessler Psychological Distress Scale (K10). HAI components were assessed using relevant marker tests.

RESULTS

Older age, Malay and Indian ethnicities, unemployment, high BMI and histories of CHD, hypercholesterolaemia, tumours and TIA/stroke were associated with lower HAI scores indicative of poorer health. Higher HAI scores were associated with females and higher education levels. Lower HAI scores were significantly associated with low ABI, high K10 scores, mobility and anxiety/depression dimensions of EQ-5D-5 L.

CONCLUSION

The most important factors associated with HAI were age, sex, ethnicity, education, unemployment, BMI and a history of health conditions. Lower HAI scores were significantly associated with PAD, lower HRQoL and psychological distress. Thus, the HAI demonstrates promise as an evaluation method for assessing PAD, overall muscle strength and HRQoL in a population-based setting.

Predictive ability of both the healthy aging index and the frailty index for all-cause mortality

AIM

We aimed to develop and assess a modified healthy aging index (HAI) among Chileans aged 60 years and older and compare its predictive ability for all-cause mortality risk with the frailty index (FI).

METHODS

This prospective study analyzed data from the Chilean National Health Survey (CNHS) conducted in 2009-2010. We included 847 adults with complete data to construct the HAI and FI. The HAI comprised five indicators (lung function, systolic blood pressure, fasting glucose, cognitive status, and glomerular filtration rate), while the FI assessed frailty using a 36-item scale. HAI scores were calculated by summing the indicator scores, ranging from 0 to 10, with higher scores indicating poorer health. Receiver operating curves (ROC) and area under the curve (AUC) were used to assess predictive validity. Associations with all-cause mortality were assessed using Cox proportional hazard models adjusted by confounders.

RESULTS

The mean HAI score was 4.06, while the FI score was 0.24. The AUC for mortality was higher for the HAI than the FI (0.640, 95% confidence interval (CI) 0.601 to 0.679 vs. 0.586, 95% CI 0.545 to 0.627). After adjusting for confounders, the FI showed a higher mortality risk compared to the HAI (2.63, 95% CI 1.76 to 3.51 vs. 1.16, 95% CI 1.08 to 1.26).

CONCLUSION

The FI and HAI were valid predictors for all-cause mortality in the Chilean population. Integrating these indices into research and clinical practice can significantly enhance our capacity to identify at-risk individuals.

The coupling between healthspan and lifespan in Caenorhabditis depends on complex interactions between compound intervention and genetic background

Aging is characterized by declining health that results in decreased cellular resilience and neuromuscular function. The relationship between lifespan and health, and the influence of genetic background on that relationship, has important implications in the development of pharmacological anti-aging interventions. Here we assessed swimming performance as well as survival under thermal and oxidative stress across a nematode genetic diversity test panel to evaluate health effects for three compounds previously studied in the Caenorhabditis Intervention Testing Program and thought to promote longevity in different ways - NP1 (nitrophenyl piperazine-containing compound 1), propyl gallate, and resveratrol. Overall, we find the relationships among median lifespan, oxidative stress resistance, thermotolerance, and mobility vigor to be complex. We show that oxidative stress resistance and thermotolerance vary with compound intervention, genetic background, and age. The effects of tested compounds on swimming locomotion, in contrast, are largely species-specific. In this study, thermotolerance, but not oxidative stress or swimming ability, correlates with lifespan. Notably, some compounds exert strong impact on some health measures without an equally strong impact on lifespan. Our results demonstrate the importance of assessing health and lifespan across genetic backgrounds in the effort to identify reproducible anti-aging interventions, with data underscoring how personalized treatments might be required to optimize health benefits.

Associations of healthy aging index and all-cause and cause-specific mortality: a prospective cohort study of UK Biobank participants

The healthy aging index (HAI) has been recently developed as a surrogate measure of biological age. However, to what extent the HAI is associated with all-cause and cause-specific mortality and whether this association differs in younger and older adults remains unknown. We aimed to quantify the association between the HAI and mortality in a population of UK adults. In the prospective cohort study, data are obtained from the UK Biobank. Five HAI components (systolic blood pressure, reaction time, cystatin C, serum glucose, forced vital capacity) were scored 0 (healthiest), 1, and 2 (unhealthiest) according to sex-specific tertiles or clinically relevant cut-points and summed to construct the HAI (range 0-10). Cox proportional hazard regression models were used to estimate the associations of the HAI with the risk of all-cause and cause-specific mortality. 387,794 middle-aged and older participants were followed up for a median of 8.9 years (IQR 8.3-9.5). A total of 14,112 all-cause deaths were documented. After adjustments, each 1-point increase in the HAI was related to a higher risk of all-cause mortality (hazards ratio [HR], 1.17; 95%CI, 1.15-1.18). Such association was stronger among adults younger than 60 years (1.19, 1.17-1.21) than that among those 60 years and older (1.15, 1.14-1.17) (P interaction < 0.001). For each unit increment of the HAI, the multivariate-adjusted HRs for risk of death were 1.28 (1.25-1.31) for cardiovascular diseases, 1.09 (1.07-1.10) for cancer, 1.36 (1.29-1.44) for digestive disease, 1.42 (1.35-1.48) for respiratory disease, 1.42 (1.33-1.51) for infectious diseases, and 1.15 (1.09-1.21) for neurodegenerative disease, respectively. Our findings indicate that the HAI is positively associated with all-cause and cause-specific mortality independent of chronological age. Our results further underscore the importance of effective early-life interventions to slow aging and prevent premature death.

Measuring healthy ageing: current and future tools

Human ageing is a complex, multifactorial process characterised by physiological damage, increased risk of age-related diseases and inevitable functional deterioration. As the population of the world grows older, placing significant strain on social and healthcare resources, there is a growing need to identify reliable and easy-to-employ markers of healthy ageing for early detection of ageing trajectories and disease risk. Such markers would allow for the targeted implementation of strategies or treatments that can lessen suffering, disability, and dependence in old age. In this review, we summarise the healthy ageing scores reported in the literature, with a focus on the past 5 years, and compare and contrast the variables employed. The use of approaches to determine biological age, molecular biomarkers, ageing trajectories, and multi-omics ageing scores are reviewed. We conclude that the ideal healthy ageing score is multisystemic and able to encompass all of the potential alterations associated with ageing. It should also be longitudinal and able to accurately predict ageing complications at an early stage in order to maximize the chances of successful early intervention.

How does loneliness "get under the skin" to become biologically embedded?

Loneliness is linked to declining physical health across cardiovascular, inflammatory, metabolic, and cognitive domains. As a result, loneliness is increasingly being recognized as a public health threat, though the mechanisms that have been studied do not yet explain all loneliness-related health risk. Potential mechanisms include loneliness having 1.) direct, causal impacts on health, possibly maintained by epigenetic modification, 2.) indirect effects mediated through health-limiting behaviors, and 3.) artifactual associations perhaps related to genetic overlap and reverse causation. In this scoping review, we examine the evidence surrounding each of these pathways, with a particular emphasis on emerging research on epigenetic effects, in order to evaluate how loneliness becomes biologically embedded. We conclude that there are significant gaps in our knowledge of how psychosocial stress may lead to physiological changes, so more work is needed to understand if, how, and when loneliness has a direct influence on health. Hypothalamic-pituitary adrenocortical axis disruptions that lead to changes in gene expression through methylation and the activity of transcription factor proteins are one promising area of research but are confounded by a number of unmeasured factors. Therefore, wok is needed using causally informative designs, such as twin and family studies and intensively longitudinal diary studies.

Development of a composite healthy ageing score: evidence from middle-to-older aged Australians

We developed and validated a composite healthy ageing score (HAS) to address the absence of a definitive composite score comprising multiple health domains that measure healthy ageing in epidemiology. The HAS is developed from 13 health domains reported to influence healthy ageing. Data to measure these domains was extracted from the 45 and Up Study baseline. We applied best practices for scale validation and development. Physical functioning, cognitive function, mental health, sleep, quality of life, balance, social connections and overall health were retained. Functional capacity and resilience were uncovered as underlying latent structures. The HAS ranges from 0 to 16 with higher scores indicating a better health profile. This research contributes a comprehensive measuring tool, HAS, It enables examination and comparison of individual or collective health profiles and the investigation of the factors that influence their chances of living healthy for longer.

Measuring healthy ageing: current and future tools

Human ageing is a complex, multifactorial process characterised by physiological damage, increased risk of age-related diseases and inevitable functional deterioration. As the population of the world grows older, placing significant strain on social and healthcare resources, there is a growing need to identify reliable and easy-to-employ markers of healthy ageing for early detection of ageing trajectories and disease risk. Such markers would allow for the targeted implementation of strategies or treatments that can lessen suffering, disability, and dependence in old age. In this review, we summarise the healthy ageing scores reported in the literature, with a focus on the past 5 years, and compare and contrast the variables employed. The use of approaches to determine biological age, molecular biomarkers, ageing trajectories, and multi-omics ageing scores are reviewed. We conclude that the ideal healthy ageing score is multisystemic and able to encompass all of the potential alterations associated with ageing. It should also be longitudinal and able to accurately predict ageing complications at an early stage in order to maximize the chances of successful early intervention.

60 years of healthy aging: On definitions, biomarkers, scores and challenges

BACKGROUND AND OBJECTIVE

As the proportion of aging people in our population increases steadily, global strategies accompanied by extensive research are necessary to tackle society and health service challenges. The World Health Organization recently published an action plan: "Decade of healthy aging 2020-2030", which calls for concerted collaboration to prevent poverty of older people to provide quality education, job opportunities, and an age-inclusive infrastructure. However, scientists worldwide still struggle to find definitions and appropriate measurements of aging per se and healthy aging in particular. This literature review aims to compile concepts of healthy aging and provide a condensed overview of the challenges in defining and measuring it, along with suggestions for further research.

MATERIALS AND METHODS

We conducted three independent systematic literature searches covering the main scopes addressed in this review: (1) concepts and definitions of healthy aging, (2) outcomes and measures in (healthy) aging studies and (3) scores and indices of healthy aging. For each scope, the retrieved literature body was screened and subsequently synthesized.

RESULTS

We provide a historical overview of the concepts of healthy aging over the past 60 years. Furthermore, we identifiy current difficulties in identifying healthy agers, including dichotomous measurements, illness-centered views, study populations & designs. Secondly, markers and measures of healthy aging are discussed, including points to consider, like plausibility, consistency, and robustness. Finally, we present healthy aging scores as measurements, which combine multiple aspects to avoid a dichotomous categorization and display the bio-psycho-social concept of healthy aging.

DISCUSSION AND CONCLUSION

When deducting research, scientists need to consider the diverse challenges in defining and measuring healthy aging. Considering that, we recommend scores that combine multiple aspects of healthy aging, such as the Healthy Ageing Index or the ATHLOS score, among others. Further efforts are to be made on a harmonized definition of healthy aging and validated measuring instruments that are modular, easy to apply and provide comparable results in different studies and cohorts to enhance the generalization of results.

Quality of death certification based on the documented underlying cause of death: A retrospective study

BACKGROUND

The underlying cause of death (UCOD) documented in the death certificate is a cornerstone in the mortality data that has significant impact on national policies, health system, and socioeconomics. However, a wide range of inaccuracies have been reported worldwide and were linked to multiple factors, including sociodemographic development and lack of physician training. Hence, this study aimed to assess the quality of death certification by reviewing the reported UCOD in the death certificate and study the potential factors that might be associated with inaccuracies.

METHODS

All in-patient deaths that occurred in the Sultan Qaboos University Hospital from January 2020 to 31 December 2020 were included in this retrospective study. The study investigators reviewed all death certifications that were recorded during the study period for the accuracy of the documented UCOD using a systemic framework recommended by the World Health Organization.

RESULTS

The study included 384 mortality cases. The mean age at the time of death was 55.7 ± 27.1 years, and 209 (54.3%) cases were men. Approximately 80% (95% confidence interval: 84-76%) of the deceased patients had inaccurate data on the UCOD. Old age (58.1 ± 25.8 vs 46.5 ± 30.1, p < 0.001), death certification by doctor in training (70.8% vs 51.9%, p = 0.001), and admission under the Department of Medicine (68.5% vs 54.4%, p = 0.019) were more common in mortality cases with inaccurate data on the UCOD. Regression analysis confirmed that old age, male sex, and certification by doctor in training were independent predictors of inaccurate data on the UCOD.

CONCLUSION

Inaccurate data on the UCOD is a prevalent issue in many healthcare settings, especially in the developing countries. Introduction of death certification training in the medical curriculum for medical doctors, implementation of periodic auditing, and provision of feedback are among the evidence-based approaches that are likely to improve the overall accuracy of mortality data.

Associations of Modified Healthy Aging Index With Major Adverse Cardiac Events, Major Coronary Events, and Ischemic Heart Disease

Background The Healthy Aging Index (HAI) has been regarded as useful in capturing the health status of multiple organ systems. However, to what extent the HAI is associated with major cardiovascular events remains largely unknown. The authors constructed a modified HAI (mHAI) to quantify the association of physiological aging with major vascular events and explored how the effects of a healthy lifestyle can modify this association. Methods and Results The participants with either missing values of any individual mHAI component or major illnesses such as heart attack, angina and stroke, and self-reported cancer at baseline were excluded. The mHAI components include systolic blood pressure, reaction time, forced vital capacity, serum cystatin c, and serum glucose. The authors used Cox proportional hazard models to quantify the association of mHAI with major adverse cardiac events, major coronary events, and ischemic heart disease. Cumulative incidence at 5 and 10 years was estimated, and joint analyses were stratified by age group and 4 mHAI categories. The mHAI was significantly correlated with major cardiovascular events, which is a better reflection of the aging level of the body than chronological age. An mHAI was calculated in 338 044 participants aged 38 to 73 years in the UK Biobank. Each point increase in the mHAI was associated with a 44% higher risk of major adverse cardiac events (adjusted hazard ratio [aHR], 1.44 [95% CI, 1.40-1.49]), 44% higher risk of major coronary events (aHR, 1.44 [95% CI, 1.40-1.48]), and 36% higher risk of ischemic heart disease (aHR, 1.36 [95% CI, 1.33-1.39]). The percentage of population-attribution risk was 51% (95% CI, 47-55) for major adverse cardiac events, 49% (95% CI, 45-53) for major coronary events, and 47% (95% CI, 44-50) for ischemic heart disease, which means that a substantial portion of these events could be prevented. Systolic blood pressure was the factor most significantly associated with major adverse cardiac events (aHR, 1.94 [95% CI, 1.82-2.08]; percentage of population-attribution risk, 36%), major coronary events (aHR, 2.01 [95% CI, 1.85-2.17]; percentage of population-attribution risk, 38%), and ischemic heart disease (aHR, 1.80 [95% CI, 1.71-1.89]; percentage of population-attribution risk, 32%). A healthy lifestyle significantly attenuated mHAI associations with incidence of vascular events. Conclusions Our findings indicate that higher mHAI is associated with increased major vascular events. A healthy lifestyle may attenuate these associations.

Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study

BACKGROUND

Predicting healthy physiological aging is of major interest within public health research. However, longitudinal studies into predictors of healthy physiological aging that include numerous exposures from different domains (i.e. the exposome) are scarce. Our aim is to identify the most important exposome-related predictors of healthy physiological aging over the life course and across generations.

METHODS

Data were used from 2815 participants from four generations (generation 1960s/1950s/1940s/1930s aged respectively 20-29/30-39/40-49/50-59 years old at baseline, wave 1) of the Doetinchem Cohort Study who were measured every 5 years for 30 years. The Healthy Aging Index, a physiological aging index consisting of blood pressure, glucose, creatinine, lung function, and cognitive functioning, was measured at age 46-85 years (wave 6). The average exposure and trend of exposure over time of demographic, lifestyle, environmental, and biological exposures were included, resulting in 86 exposures. Random forest was used to identify important predictors.

RESULTS

The most important predictors of healthy physiological aging were overweight-related (BMI, waist circumference, waist/hip ratio) and cholesterol-related (using cholesterol lowering medication, HDL and total cholesterol) measures. Diet and educational level also ranked in the top of important exposures. No substantial differences were observed in the predictors of healthy physiological aging across generations. The final prediction model's performance was modest with an R² of 17%.

CONCLUSIONS

Taken together, our findings suggest that longitudinal cardiometabolic exposures (i.e. overweight- and cholesterol-related measures) are most important in predicting healthy physiological aging. This finding was similar across generations. More work is needed to confirm our findings in other study populations.

A time-series analysis of blood-based biomarkers within a 25-year longitudinal dolphin cohort

Causal interactions and correlations between clinically-relevant biomarkers are important to understand, both for informing potential medical interventions as well as predicting the likely health trajectory of any individual as they age. These interactions and correlations can be hard to establish in humans, due to the difficulties of routine sampling and controlling for individual differences (e.g., diet, socio-economic status, medication). Because bottlenose dolphins are long-lived mammals that exhibit several age-related phenomena similar to humans, we analyzed data from a well controlled 25-year longitudinal cohort of 144 dolphins. The data from this study has been reported on earlier, and consists of 44 clinically relevant biomarkers. This time-series data exhibits three starkly different influences: (A) directed interactions between biomarkers, (B) sources of biological variation that can either correlate or decorrelate different biomarkers, and (C) random observation-noise which combines measurement error and very rapid fluctuations in the dolphin's biomarkers. Importantly, the sources of biological variation (type-B) are large in magnitude, often comparable to the observation errors (type-C) and larger than the effect of the directed interactions (type-A). Attempting to recover the type-A interactions without accounting for the type-B and type-C variation can result in an abundance of false-positives and false-negatives. Using a generalized regression which fits the longitudinal data with a linear model accounting for all three influences, we demonstrate that the dolphins exhibit many significant directed interactions (type-A), as well as strong correlated variation (type-B), between several pairs of biomarkers. Moreover, many of these interactions are associated with advanced age, suggesting that these interactions can be monitored and/or targeted to predict and potentially affect aging.

Co-Inheritance of Variation in All-Cause Mortality and Biochemical Risk Factors

Biomarkers may be useful endophenotypes for genetic studies if they share genetic sources of variation with the outcome, for example, with all-cause mortality. Australian adult study participants who had reported their parental survival information were included in the study: 14,169 participants had polygenic risk scores (PRS) from genotyping and up to 13,365 had biomarker results. We assessed associations between participants' biomarker results and parental survival, and between biomarker results and eight parental survival PRS at varying p-value cut-offs. Survival in parents was associated with participants' serum bilirubin, C-reactive protein, HDL cholesterol, triglycerides and uric acid, and with LDL cholesterol for participants' fathers but not for their mothers. PRS for all-cause mortality were associated with liver function tests (alkaline phosphatase, butyrylcholinesterase, gamma-glutamyl transferase), metabolic tests (LDL and HDL cholesterol, triglycerides, uric acid), and acute-phase reactants (C-reactive protein, globulins). Association between offspring biomarker results and parental survival demonstrates the existence of familial effects common to both, while associations between biomarker results and PRS for mortality favor at least a partial genetic cause of this covariation. Identification of genetic loci affecting mortality-associated biomarkers offers a route to the identification of additional loci affecting mortality.

The Relationship Between Successful Aging and All-Cause Mortality Risk in Older Adults: A Systematic Review and Meta-Analysis of Cohort Studies

Background

This meta-analysis aimed to explore the effect of successful aging (SA) on all-cause mortality risk in older people to provide a theoretical basis for promoting SA.

Methods

PubMed, Embase, CINAHL, CNKI, and WanFang databases (inception to March 4, 2021) were searched for cohort studies to evaluate the relationship between SA and mortality in older people. A random-effects model was used to synthesis hazard ratio and 95% confidence intervals. Quality assessment was performed using the Newcastle–Ottawa scale. All statistical analyses were conducted in STATA 16.0.

Results

In total, 21,158 older adults from 10 studies were included in the current systematic review and meta-analysis. The SA group tended to have 50% lower risk of all-cause mortality than the non-SA group (pooled hazard ratio = 0.50, 95% confidence intervals: 0.35–0.65, P < 0.001; I² = 58.3%). The risk of all-cause mortality in older people increased by 17% for each unit increment in the healthy aging index (HAI) (I² = 0%, P = 0.964). Compared with the reference group (HAI 0-2), older people with HAI 3-4, HAI 5-6, and HAI 7-10 had 1.31-fold, 1.73-fold, and 2.58-fold greater risk of all-cause mortality, respectively. Subgroup analysis did not reveal possible sources of heterogeneity.

Conclusions

This meta-analysis suggests that older adults with SA reduced the risk of all-cause mortality by 50%. However, few interventional studies have been conducted. Therefore, healthcare providers must be aware of the relationship between SA and mortality risk and actively develop intervention methods for helping old people achieve SA.

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

OBJECTIVES

To determine the effect of diet, exercise, and diet-exercise in combination on measures of biological age.

DESIGN

Secondary analysis of a 1-year randomized, controlled trial.

SETTING

University-based Medical Center.

PARTICIPANTS

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.

INTERVENTIONS

Participants were randomized to a control group, a weight-management (diet) group, an exercise group, or a weight-management-plus-exercise (diet-exercise) group.

MAIN OUTCOME MEASURES

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.

RESULTS

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).

CONCLUSIONS

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.

NIA Long Life Family Study: Objectives, Design, and Heritability of Cross Sectional and Longitudinal Phenotypes

The NIA Long Life Family Study (LLFS) is a longitudinal, multicenter, multinational, population-based multigenerational family study of the genetic and nongenetic determinants of exceptional longevity and healthy aging. The Visit 1 in-person evaluation (2006–2009) recruited 4 953 individuals from 539 two-generation families, selected from the upper 1% tail of the Family Longevity Selection Score (FLoSS, which quantifies the degree of familial clustering of longevity). Demographic, anthropometric, cognitive, activities of daily living, ankle-brachial index, blood pressure, physical performance, and pulmonary function, along with serum, plasma, lymphocytes, red cells, and DNA, were collected. A Genome Wide Association Scan (GWAS) (Ilumina Omni 2.5M chip) followed by imputation was conducted. Visit 2 (2014–2017) repeated all Visit 1 protocols and added carotid ultrasonography of atherosclerotic plaque and wall thickness, additional cognitive testing, and perceived fatigability. On average, LLFS families show healthier aging profiles than reference populations, such as the Framingham Heart Study, at all age/sex groups, for many critical healthy aging phenotypes. However, participants are not uniformly protected. There is considerable heterogeneity among the pedigrees, with some showing exceptional cognition, others showing exceptional grip strength, others exceptional pulmonary function, etc. with little overlap in these families. There is strong heritability for key healthy aging phenotypes, both cross-sectionally and longitudinally, suggesting that at least some of this protection may be genetic. Little of the variance in these heritable phenotypes is explained by the common genome (GWAS + Imputation), which may indicate that rare protective variants for specific phenotypes may be running in selected families.

Housing Poverty and Healthy Aging in China: Evidence from the China Health and Retirement Longitudinal Study

BACKGROUND

Although prior research on the housing-health linkage suggested that those with poor housing conditions are more likely to report poor health, it is dominated by Western studies and offers little evidence on the housing-health relation in China. Scarce is empirical evidence on the potentially detrimental impact of either qualitative or quantitative housing poverty on health outcomes, especially for seniors in China. This paper aims to fill this void by using data from the 2011-2015 China Health and Retirement Longitudinal Study (CHARLS) to provide a comprehensive analysis of the demographic, socioeconomic, and behavioral factors that contribute to changes in healthy aging among Chinese adults aged 60 and over.

METHODS

Data collected from 8839 adults aged 60 and over in the 2011 and 2015 CHARLS (3732 in 2011 and 5107 in 2015) were used. We first used six blood-based biomarkers to construct a composite measure of the Chinese Healthy Aging Index (CHAI, ranging from 0 (healthiest) to 12 (unhealthiest)) and then assessed the psychometric properties of the CHAI score, including acceptability, internal consistency, convergent validity, discriminative validity and precision. In addition, we employed both mean-based Blinder-Oaxaca and unconditional quantile regression decomposition to decompose the change in healthy aging within the 2011-2015 period.

RESULTS

We overall identified a decrease in CHAI score from 5.69 in 2011 to 5.20 in 2015, which implies an improvement in healthy aging during this period. Our linear decomposition revealed that dependent on the type of measure used (whether quality, quantity, or combined quality-quantity), housing poverty explained 4-8% of the differences in CHAI score. Our distributional decompositions also highlighted an important role for housing poverty in the change in healthy aging, accounting for approximately 7-23% of the explained portion. Within this latter, the relative contribution of housing quantity and quality poverty was more pronounced at the median and upper end of the CHAI distribution. We also found household expenditure to be significantly associated with healthy aging among older Chinese adults and made the largest contribution to the improvement in healthy aging over time.

CONCLUSIONS

The association between housing poverty and CHAI is independent of household expenditure. Regardless of type, housing poverty is positively associated with a decrease in healthy aging. Thus, improved housing conditions boost healthy aging, and housing amelioration initiatives may offer the most effective solution for augmenting healthy aging in China. Improvement of flush toilets and the access to potable water and a separate kitchen require particular attention. Since high-density congested housing has a negative impact on healthy aging, more attention can also be paid to improvements in the available space for older people. Especially at an institutional level, the government may extend the housing policy from a homeownership scheme to a housing upgrading scheme by improving housing conditions.

Biological age in healthy elderly predicts aging-related diseases including dementia

Application of biological age as a measure of an individual´s health status offers new perspectives into extension of both lifespan and healthspan. While algorithms predicting mortality and most aging-related morbidities have been reported, the major shortcoming has been an inability to predict dementia. We present a community-based cohort study of 1930 participants with a mean age of 72 years and a follow-up period of over 7 years, using two variants of a phenotypic blood-based algorithm that either excludes (BioAge1) or includes (BioAge2) neurofilament light chain (NfL) as a neurodegenerative marker. BioAge1 and BioAge2 predict dementia equally well, as well as lifespan and healthspan. Each one-year increase in BioAge1/2 was associated with 11% elevated risk (HR 1.11; 95%CI 1.08-1.14) of mortality and 7% elevated risk (HR 1.07; 95%CI 1.05-1.09) of first morbidities. We additionally tested the association of microRNAs with age and identified 263 microRNAs significantly associated with biological and chronological age alike. Top differentially expressed microRNAs based on biological age had a higher significance level than those based on chronological age, suggesting that biological age captures aspects of aging signals at the epigenetic level. We conclude that accelerated biological age for a given age is a predictor of major age-related morbidity, including dementia, among healthy elderly.

A Biomarker-based Biological Age in UK Biobank: Composition and Prediction of Mortality and Hospital Admissions

Background

Chronological age is the strongest risk factor for most chronic diseases. Developing a biomarker-based age and understanding its most important contributing biomarkers may shed light on the effects of age on later-life health and inform opportunities for disease prevention.

Methods

A subpopulation of 141 254 individuals healthy at baseline were studied, from among 480 019 UK Biobank participants aged 40–70 recruited in 2006–2010, and followed up for 6–12 years via linked death and secondary care records. Principal components of 72 biomarkers measured at baseline were characterized and used to construct sex-specific composite biomarker ages using the Klemera Doubal method, which derived a weighted sum of biomarker principal components based on their linear associations with chronological age. Biomarker importance in the biomarker ages was assessed by the proportion of the variation in the biomarker ages that each explained. The proportions of the overall biomarker and chronological age effects on mortality and age-related hospital admissions explained by the biomarker ages were compared using likelihoods in Cox proportional hazard models.

Results

Reduced lung function, kidney function, reaction time, insulin-like growth factor 1, hand grip strength, and higher blood pressure were key contributors to the derived biomarker age in both men and women. The biomarker ages accounted for >65% and >84% of the apparent effect of age on mortality and hospital admissions for the healthy and whole populations, respectively, and significantly improved prediction of mortality (p < .001) and hospital admissions (p < 1 × 10⁻¹⁰) over chronological age alone.

Conclusions

This study suggests that a broader, multisystem approach to research and prevention of diseases of aging warrants consideration.

Immune age and biological age as determinants of vaccine responsiveness among elderly populations: the Human Immunomics Initiative research program

The Human Immunomics Initiative (HII), a joint project between the Harvard T.H. Chan School of Public Health and the Human Vaccines Project (HVP), focuses on studying immunity and the predictability of immuneresponsiveness to vaccines in aging populations. This paper describes the hypotheses and methodological approaches of this new collaborative initiative. Central to our thinking is the idea that predictors of age-related non-communicable diseases are the same as predictors for infectious diseases like COVID-19 and influenza. Fundamental to our approach is to differentiate between chronological, biological and immune age, and to use existing large-scale population cohorts. The latter provide well-typed phenotypic data on individuals’ health status over time, readouts of routine clinical biochemical biomarkers to determine biological age, and bio-banked plasma samples to deep phenotype humoral immune responses as biomarkers of immune age. The first phase of the program involves 1. the exploration of biological age, humoral biomarkers of immune age, and genetics in a large multigenerational cohort, and 2. the subsequent development of models of immunity in relation to health status in a second, prospective cohort of an aging population. In the second phase, vaccine responses and efficacy of licensed COVID-19 vaccines in the presence and absence of influenza-, pneumococcal- and pertussis vaccines routinely offered to elderly, will be studied in older aged participants of prospective population-based cohorts in different geographical locations who will be selected for representing distinct biological and immune ages. The HII research program is aimed at relating vaccine responsiveness to biological and immune age, and identifying aging-related pathways crucial to enhance vaccine effectiveness in aging populations.

The Modified Healthy Ageing Index Is Associated with Mortality and Disability: The Rugao Longevity and Ageing Study

INTRODUCTION

The Healthy Ageing Index (HAI) has been shown not only to have wider applicability and predictive ability but also to adequately predict mortality in Western populations. There is still a lack of studies validating the applicability of the HAI in China.

OBJECTIVE

To evaluate the applicability of the HAI and validate whether the HAI is suitable for monitoring ageing in the elderly population in China.

METHODS

Data were obtained from the Rugao Longevity and Ageing Study. The modified HAI was constructed based on systolic blood pressure, chronic pulmonary diseases, cognitive function, fasting glucose, and kidney function. It was calculated in 1719 individuals aged 70-84 years at baseline. The adverse outcomes were mortality and disability. Demographic, physiologic, and clinical data were collected. Cox proportional hazards and logistic regression models were used to analyze the relationship between the modified HAI and adverse outcomes.

RESULTS

A total of 1,719 older adults were analyzed in our study. A total of 793 (46.13%) males were recruited. The mean age was 75.69 ± 3.93 years. At the 5-year follow-up, there were 266 deaths and 275 individuals with disabilities. In the multivariable models, the modified HAI was associated with mortality (hazard ratio = 1.11, 95% confidence interval [CI]: 1.03-1.20) and disability (odds ratio = 1.11, 95% CI: 1.05-1.18). In the sensitivity analyses, similar associations remained after imputing missing data using multiple imputation and excluding participants with major cardiovascular disease at baseline.

CONCLUSION

The modified HAI was a robust and independent predictor of adverse outcomes. It is a valid and feasible tool for monitoring ageing in older adults.

In Vivo Quasi-Elastic Light Scattering Eye Scanner Detects Molecular Aging in Humans

The absence of clinical tools to evaluate individual variation in the pace of aging represents a major impediment to understanding aging and maximizing health throughout life. The human lens is an ideal tissue for quantitative assessment of molecular aging in vivo. Long-lived proteins in lens fiber cells are expressed during fetal life, do not undergo turnover, accumulate molecular alterations throughout life, and are optically accessible in vivo. We used quasi-elastic light scattering (QLS) to measure age-dependent signals in lenses of healthy human subjects. Age-dependent QLS signal changes detected in vivo recapitulated time-dependent changes in hydrodynamic radius, protein polydispersity, and supramolecular order of human lens proteins during long-term incubation (~1 year) and in response to sustained oxidation (~2.5 months) in vitro. Our findings demonstrate that QLS analysis of human lens proteins provides a practical technique for noninvasive assessment of molecular aging in vivo.

The change and correlates of healthy ageing among Chinese older adults: findings from the China health and retirement longitudinal study

Background

This study tentatively constructs a composite measure of Chinese Healthy Ageing Index (CHAI) among older adults aged 60+ and investigates change of CHAI during 2011–2015 and its association with sociodemographic characteristics.

Methods

Data collected from 8182 old adults aged 60+ in the 2011 and 2015 China Health and Retirement Longitudinal Study (CHARLS, a nationally representative sample) were used. Six medical measures of blood pressure, peak expiratory flow, cognitive status score, fasting glucose, kidney function and C-reactive function were used to construct CHAI (range 0–12, 0–2 = healthiest, 7–12 = unhealthiest). Ordinary least squares, logistic and random effects models examined social and spatial determinants of CHAI score and the prevalence of the ideal CHAI. Unconditional quantile regression tested heterogeneous impacts of sociodemographic determinants of CHAI score.

Results

Mean CHAI score declined from 5.7 to 5.2, and the proportion of the ideal CHAI (CHAI score = 0–2) increased from 5.6 to 9.4% during 2011–2015, indicating an improvement in healthy ageing over time. During 2011–2015, the highest rates of the ideal CHAI were in Southeast and East of China. Older adults, male, living in the Center and West, smoking, obesity/overweight and having chronic diseases were positively associated with total CHAI score and negatively with a higher prevalence of the ideal CHAI. Being married, having high education and regular social activities were associated with a higher rate of the ideal CHAI. The positive predictors for total CHAI were stronger in those with worse CHAI status.

Conclusions

In China healthy ageing has improved during 2011–2015, but substantial geographical and sociodemographic heterogeneities exist in the improvements, suggesting health equality remains a challenge in China. Future policies and interventions should especially focus on men, those in Central and West China, and combat health problems like obesity, chronic diseases and unhealthy behaviors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02026-y.

TIP60 in aging and neurodegeneration

Epigenetic modification of chromatin, including histone methylation and acetylation, plays critical roles in eukaryotic cells and has a significant impact on chromatin structure/accessibility, gene regulation and, susceptibility to aging, neurodegenerative disease, cancer, and other age-related diseases. This article reviews the current advances on TIP60/KAT5, a major histone acetyltransferase with diverse functions in eukaryotes, with emphasis on its regulation of autophagy, proteasome-dependent protein turnover, RNA transcription, DNA repair, circadian rhythms, learning and memory, and other neurological functions implicated in aging and neurodegeneration. Moreover, the promising therapeutic potential of TIP60 is discussed to target Alzheimer's disease and other neurological diseases.

Aging mechanisms-A perspective mostly from Drosophila

A mechanistic understanding of the natural aging process, which is distinct from aging-related disease mechanisms, is essential for developing interventions to extend lifespan or healthspan. Here, we discuss current trends in aging research and address conceptual and experimental challenges in the field. We examine various molecular markers implicated in aging with an emphasis on the role of heterochromatin and epigenetic changes. Studies in model organisms have been advantageous in elucidating conserved genetic and epigenetic mechanisms and assessing interventions that affect aging. We highlight the use of Drosophila, which allows controlled studies for evaluating genetic and environmental contributors to aging conveniently. Finally, we propose the use of novel methodologies and future strategies using Drosophila in aging research.

Proteomic assessment of serum biomarkers of longevity in older men

The biological bases of longevity are not well understood, and there are limited biomarkers for the prediction of long life. We used a high-throughput, discovery-based proteomics approach to identify serum peptides and proteins that were associated with the attainment of longevity in a longitudinal study of community-dwelling men age ≥65 years. Baseline serum in 1196 men were analyzed using liquid chromatography-ion mobility-mass spectrometry, and lifespan was determined during ~12 years of follow-up. Men who achieved longevity (≥90% expected survival) were compared to those who died earlier. Rigorous statistical methods that controlled for false positivity were utilized to identify 25 proteins that were associated with longevity. All these proteins were in lower abundance in long-lived men and included a variety involved in inflammation or complement activation. Lower levels of longevity-associated proteins were also associated with better health status, but as time to death shortened, levels of these proteins increased. Pathway analyses implicated a number of compounds as important upstream regulators of the proteins and implicated shared networks that underlie the observed associations with longevity. Overall, these results suggest that complex pathways, prominently including inflammation, are linked to the likelihood of attaining longevity. This work may serve to identify novel biomarkers for longevity and to understand the biology underlying lifespan.

The Healthy Aging Index analyzed over 15 years in the general population: The Doetinchem Cohort Study

The Healthy Aging Index (HAI), an index of physiological aging, has been demonstrated to predicts mortality, morbidity and disability. We studied the longitudinal development of the HAI to identify aging trajectories and evaluated the role of baseline sociodemographic characteristics and lifestyle factors of the trajectories. Four measurements with intervals of 5 years were included from the Doetinchem Cohort Study. The HAI reflects levels of systolic blood pressure, non-fasting plasma glucose levels, global cognitive functioning, plasma creatinine levels and lung functioning. The HAI score ranges from 0 to 10: higher scores indicate a better health profile. Latent class mixture modelling was used to model within-person change and to identify aging trajectories. Area under the curve was calculated per trajectory to estimate total healthy years. In total, 2324 women and 2013 men were included. One HAI trajectory was identified for women, and two trajectories for men, labelled 'gradual' aging (76%) and 'early' aging (24%). Men who were medium/high educated, below 36 years at baseline, complied with guidelines on physical activity and were not obese in any round were associated with increased odds to 'gradual' aging of 1.46 (CI: 1.18-1.81), 1.93 (CI: 1.42-2.62), 1.26 (1.02-1.57) and 1.76 (1.32-2.35), respectively. Between 30 and 70 years of age, men in the 'early' aging trajectory had the least healthy years (29.6 years), followed by women (30.1 years), and 'gradual' aging men (34.7 years). This study emphasizes that 'physiological aging' is not only an issue of older ages. Between 30 and 70 years of age, 'early' aging men and women had approximately five healthy years less compared to 'gradual' aging men. Lifestyle factors (e.g. nutrition and physical activity) seem to play an important role in optimal aging.

A 25-y longitudinal dolphin cohort supports that long-lived individuals in same environment exhibit variation in aging rates

Aging is a degradative process that varies among individuals. Due to limitations in defining and differentiating aging rates in human populations, understanding why some people appear to age slower than others has proven difficult. We analyzed 44 blood-based indices of health as candidate aging rate biomarkers collected over a 25-y period on a relevant, long-lived population of dolphins. Evidence of subsets of dolphins exhibiting slow and accelerated aging rates were detected, despite sharing the same environment, diet, and health care. Furthermore, some dolphin subsets were more likely to develop clinically relevant conditions, including anemia and immunosenescence. Our results support the notion that aging rates in long-lived mammals may be defined and provide insight into novel interventions to delay aging.

While it is believed that humans age at different rates, a lack of robust longitudinal human studies using consensus biomarkers meant to capture aging rates has hindered an understanding of the degree to which individuals vary in their rates of aging. Because bottlenose dolphins are long-lived mammals that develop comorbidities of aging similar to humans, we analyzed data from a well-controlled, 25-y longitudinal cohort of 144 US Navy dolphins housed in the same oceanic environment. Our analysis focused on 44 clinically relevant hematologic and clinical chemistry measures recorded during routine blood draws throughout the dolphins’ lifetimes. Using stepwise regression and general linear models that accommodate correlations between measures obtained on individual dolphins, we demonstrate that, in a manner similar to humans, dolphins exhibit independent and linear age-related declines in four of these measures: hemoglobin, alkaline phosphatase, platelets, and lymphocytes. Using linear regressions and analyses of covariance with post hoc Tukey–Kramer tests to compare slopes (i.e., linear age-related rates) of our four aging rate biomarkers among 34 individual dolphins aging from 10 y to up to 40 y old, we could identify slow and accelerated agers and differentiate subgroups that were more or less likely to develop anemia and lymphopenia. This study successfully documents aging rate differences over the lifetime of long-lived individuals in a controlled environment. Our study suggests that nonenvironmental factors influencing aging rate biomarkers, including declining hemoglobin and anemia, may be targeted to delay the effects of aging in a compelling model of human biology.

Healthspan pathway maps in C. elegans and humans highlight transcription, proliferation/biosynthesis and lipids

The molecular basis of aging and of aging-associated diseases is being unraveled at an increasing pace. An extended healthspan, and not merely an extension of lifespan, has become the aim of medical practice. Here, we define health based on the absence of diseases and dysfunctions. Based on an extensive review of the literature, in particular for humans and C. elegans, we compile a list of features of health and of the genes associated with them. These genes may or may not be associated with survival/lifespan. In turn, survival/lifespan genes that are not known to be directly associated with health are not considered. Clusters of these genes based on molecular interaction data give rise to maps of healthspan pathways for humans and for C. elegans. Overlaying healthspan-related gene expression data onto the healthspan pathway maps, we observe the downregulation of (pro-inflammatory) Notch signaling in humans and of proliferation in C. elegans. We identify transcription, proliferation/biosynthesis and lipids as a common theme on the annotation level, and proliferation-related kinases on the gene/protein level. Our literature-based data corpus, including visualization, should be seen as a pilot investigation of the molecular underpinnings of health in two different species. Web address: http://pathways.h2020awe.eu.

The healthy aging phenotype in older people in Manizales

Introducción.

El fenotipo de envejecimiento saludable está presente en aquellos individuos que envejecen con poca morbilidad, sin deterioro funcional ni cognitivo, y con un nivel aceptable de bienestar y de participación social.

Objetivo.

Establecer la frecuencia del fenotipo de envejecimiento saludable según un modelo multidimensional, uno biomédico y uno psicosocial, y determinar los factores de predicción en cada uno de ellos.

Materiales y métodos.

Se hizo un estudio de diseño transversal, observacional y descriptivo, que incluyó a 402 personas (50,1 % mujeres) de 65 años y más (promedio de edad, 69,2) en el área urbana de Manizales. El fenotipo de envejecimiento saludable se caracterizó en cinco dimensiones: salud metabólica y fisiológica, función física, función cognitiva, bienestar psicológico y bienestar social. Los factores asociados incluyeron aspectos sociodemográficos y de salud.

Resultados.

La prevalencia de envejecimiento saludable fue de 15,5 % en el modelo multidimensional, de 12,3 % en el biomédico y de 63,3 % en el psicosocial. El tener autopercepción de buena salud fue un factor de predicción independiente de envejecimiento saludable en los tres modelos, así como la satisfacción con los ingresos económicos en el modelo biomédico y en el psicosocial. Un tercer factor de predicción fue el estar casado, aunque fue significativo solamente en el modelo psicosocial.

Conclusiones.

La prevalencia del fenotipo de envejecimiento saludable fue baja en el modelo biológico y en el multidimensional (1 de cada 10 personas), y mayor en el modelo psicosocial (6 de cada 10). A pesar de ello, los factores predictores independientes fueron los mismos: la autopercepción de buena o muy buena salud, la satisfacción con los ingresos económicos y el estar casado.

Mortality in Relation to Changes in a Healthy Aging Index: The Health, Aging, and Body Composition Study

BACKGROUND

Baseline scores on a Healthy Aging Index (HAI), including five key physiologic domains, strongly predict health outcomes. This study aimed to characterize 9-year changes in a HAI and explore their relationship to subsequent mortality.

METHODS

Data are from the Health, Aging, and Body Composition study of well-functioning adults aged 70-79 years. A HAI, which ranges from 0 to 10, was constructed at years 1 and 10 of the study including systolic blood pressure, forced expiratory volume, digit symbol substitution test, cystatin C, and fasting glucose. The relationships between the HAI at years 1 and 10 and the change between years and subsequent mortality until year 17 were estimated from Cox proportional hazards models.

RESULTS

Two thousand two hundred sixty-four participants had complete data on a HAI at year 1, of these 1,122 had complete data at year 10. HAI scores tended to increase (i.e. get worse) over 9-year follow-up, from (mean [SD]) 4.3 (2.1) to 5.7 (2.1); mean within-person change 1.5 (1.6). After multivariable adjustment, HAI score was related to mortality from year 1 (hazard ratio [95% confidence interval] = 1.17 [1.13-1.21] per unit) and year 10 (1.20 [1.14-1.27] per unit). The change between years was also related to mortality (1.08 [1.02-1.15] per unit change).

CONCLUSIONS

HAI scores tended to increase with advancing age and stratified mortality rates among participants remaining at year 10. The HAI may prove useful to understand changes in health with aging.

Measuring multimorbidity beyond counting diseases: systematic review of community and population studies and guide to index choice

OBJECTIVES

To identify and summarise existing indices for measuring multimorbidity beyond disease counts, to establish which indices include mental health comorbidities or outcomes, and to develop recommendations based on applicability, performance, and usage.

DESIGN

Systematic review.

DATA SOURCES

Seven medical research databases (Medline, Web of Science Core Collection, Cochrane Library, Embase, PsycINFO, Scopus, and CINAHL Plus) from inception to October 2018 and bibliographies and citations of relevant papers. Searches were limited to English language publications.

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Original articles describing a new multimorbidity index including more information than disease counts and not focusing on comorbidity associated with one specific disease. Studies were of adults based in the community or at population level.

RESULTS

Among 7128 search results, 5560 unique titles were identified. After screening against eligibility criteria the review finally included 35 papers. As index components, 25 indices used conditions (weighted or in combination with other parameters), five used diagnostic categories, four used drug use, and one used physiological measures. Predicted outcomes included mortality (18 indices), healthcare use or costs (13), hospital admission (13), and health related quality of life (7). 29 indices considered some aspect of mental health, with most including it as a comorbidity. 12 indices are recommended for use.

CONCLUSIONS

35 multimorbidity indices are available, with differing components and outcomes. Researchers and clinicians should examine existing indices for suitability before creating new ones.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017074211.

Parallel Progress in Perceived Age and Life Expectancy

BACKGROUND

Human life expectancy continues to rise in most populations. This rise not only leads to longer lives but also is accompanied by improved health at a given age, that is, recent cohorts show a reduction of biological age for a given chronological age. Despite or even because of the diversity of biomarkers of aging, an accurate quantification of a general shift in biological age across time has been challenging.

METHODS

Here, we compared age perception of facial images taken in 2001 over a decade and related these changes in age perception to changes in life expectancy.

RESULTS

We show that age perception changes substantially across time and parallels the progress in life expectancy. In 2012, people aged more than 70 years needed to look 2.3 years younger to be rated the same age as in 2002.

CONCLUSIONS

Our results suggest that age perception reflects the past life events better than predicts future length of life, that is, it is written in your face how much you have aged so far. We draw this conclusion as age perception among elderly individuals paralleled changes in life expectancy at birth but not changes in remaining life expectancies. We suggest that changes in age perception should be explored for younger age classes to inform on aging processes, including whether aging is delayed or slowed with increasing life expectancy.

Individual healthy aging indices, measurements and scores

The positive gerontological approach to aging has resulted in successive terminologies to describe the process of aging, including successful aging, active aging, healthy aging, or healthy and active aging, amongst others. Each definition proposed by geriatricians, psychologists, sociologists or public health specialists has been based on specific aspects of aging that are most important to the authors' discipline, explaining the current difficulty in determining which is the best set of criteria to determine "good aging". Two successive analyses of the measurements used in longitudinal studies from 1989 to 2018 testify to this heterogeneity in the types of questions proposed to evaluate the quality of the individual aging process. To confront this complexity, new and integrated indices have successively been proposed to quantify and qualify the survival period of aging individuals. The present paper aims to describe and compare the value of the "healthy aging index", the "modified healthy aging index", the "healthy aging score" and the "selfie aging test". Attempts to date to identify the best individual measurement of "aging well" have been interesting, and certainly show promise, but their limitations to specific populations call for more concerted effort from the scientific community to obtain worldwide validation. Another option would be to identify the best self-assessment questionnaire and include it in a mobile device, enabling longer term personal follow-up of aging functions. There is a clear lack of data of this type at present, and an urgent need to obtain such information, to enable early and targeted interventions.

Metabolite Profiles of Healthy Aging Index Are Associated With Cardiovascular Disease in African Americans: The Health, Aging, and Body Composition Study

Background

Metabolic dysfunction is a hallmark of differential aging, specifically in African Americans. Investigation of systemic metabolic state, multiorgan aging, and long-term cardiovascular outcome in African Americans has not been reported.

Methods

We studied 291 African American males in the Health, Aging, and Body Composition (Health ABC) study to identify circulating metabolites related to the Newman healthy aging index (HAI; a multiparametric score comprised of blood pressure, blood glucose, neurocognitive function, creatinine, and forced vital capacity). We examined the relationship of selected metabolites differential abundant at the extremes of HAI with long-term survival from cardiovascular mortality.

Results

The median age was 73 years. We identified 19 metabolites differentially expressed in blood in 86 study participants at the extremes of HAI (HAI 0-3: N = 30 vs 8-10: N = 56). At a median follow-up of 10 years, 78 participants (27 per cent) died from cardiovascular causes. After adjustment for age, body mass index, presence of prevalent cardiovascular disease, creatinine, and HAI, six of these 19 metabolites were associated with long-term cardiovascular mortality. Although several metabolites had been previously reported in Caucasians (eg, isocitrate), we identified several metabolites with unreported association with cardiac disease. Metabolites associated with HAI and cardiac death in African Americans specified pathways relevant to nitric oxide, oxidative stress, mitochondrial function, urea cycle, and gut microbial metabolism.

Conclusions

Metabolite profiling in African Americans identified known and novel metabolic pathways linked to HAI and cardiovascular death. Further investigation in larger patient cohorts is required to uncover race-based signatures of cardiovascular disease with aging.

Association of Biomarker and Physiologic Indices With Mortality in Older Adults: Cardiovascular Health Study

Background

A goal of gerontology is discovering aging phenotypes that reflect biological aging distinct from disease pathogenesis. Biomarkers that strongly and independently associated with mortality and that statistically attenuated chronologic age could be used to define such a phenotype. We determined the association of a Biomarker Index (BI) with mortality and compared it with a validated Physiologic Index (PI) in older adults.

Methods

The indices were constructed in the Cardiovascular Health Study, mean (SD) age 74.5 (5.1) years. The BI incorporated circulating levels of new biomarkers, including insulin-like growth factor-1, insulin-like growth factor-binding protein 3, amino-terminal pro-B-type natriuretic peptide, dehydroepiandrosterone sulfate, and interleukin-6, and was built in test (N = 2,197) and validation (N = 1,124) samples. The PI included carotid intima-media thickness, pulmonary capacity, brain white matter grade, cystatin-C, and fasting glucose. Multivariable Cox proportional hazards models predicting death were calculated with 10 years of follow-up.

Results

In separate age-adjusted models, the hazard ratio for mortality per point of the BI was 1.30 (95% confidence interval 1.25, 1.34) and the BI attenuated age by 25%. The hazard ratio for the PI was 1.28 (1.24, 1.33; 29% age attenuation). In the same model, the hazard ratio for the BI was 1.23 (1.18, 1.28) and for the PI was 1.22 (1.17, 1.26), and age was attenuated 42.5%. Associations persisted after further adjustment.

Conclusions

The BI and PI were significantly and independently associated with mortality. Both attenuated the age effect on mortality substantially. The indices may be feasible phenotypes for developing interventions hoping to alter the trajectory of aging.

Health and Aging: Unifying Concepts, Scores, Biomarkers and Pathways

Despite increasing research efforts, there is a lack of consensus on defining aging or health. To understand the underlying processes, and to foster the development of targeted interventions towards increasing one's health, there is an urgent need to find a broadly acceptable and useful definition of health, based on a list of (molecular) features; to operationalize features of health so that it can be measured; to identify predictive biomarkers and (molecular) pathways of health; and to suggest interventions, such as nutrition and exercise, targeted at putative causal pathways and processes. Based on a survey of the literature, we propose to define health as a state of an individual characterized by the core features of physiological, cognitive, physical and reproductive function, and a lack of disease. We further define aging as the aggregate of all processes in an individual that reduce its wellbeing, that is, its health or survival or both. We define biomarkers of health by their attribute of predicting future health better than chronological age. We define healthspan pathways as molecular features of health that relate to each other by belonging to the same molecular pathway. Our conceptual framework may integrate diverse operationalizations of health and guide precision prevention efforts.

Heterogeneity of healthy aging: comparing long-lived families across five healthy aging phenotypes of blood pressure, memory, pulmonary function, grip strength, and metabolism

Five healthy aging phenotypes were developed in the Long Life Family Study to uncover longevity pathways and determine if healthy aging across multiple systems clustered in a subset of long-lived families. Using blood pressure, memory, pulmonary function, grip strength, and metabolic measures (body mass index, waist circumference and fasting levels of glucose, insulin, triglycerides, lipids, and inflammatory markers), offspring were ranked according to relative health using gender-, age-, and relevant confounder-adjusted z-scores. Based on our prior work, families met a healthy aging phenotype if ≥ 2 and ≥ 50% of their offspring were exceptionally healthy for that respective phenotype. Among 426 families, only two families met criteria for three healthy aging phenotypes and none met criteria for four or more healthy aging phenotypes. Using Spearman correlation, the proportion of offspring within families with exceptionally healthy pulmonary function was correlated with the proportion of offspring within families with exceptional strength (r = 0.19, p = 0.002). The proportion of offspring within families meeting the healthy blood pressure and metabolic phenotypes were also correlated (r = 0.14, p = 0.006), and more families were classified as meeting healthy blood pressure and metabolic phenotypes (Kappa = 0.10, p = 0.02), as well as the healthy pulmonary and blood pressure phenotypes than expected by chance (Kappa = 0.09, p = 0.03). Other phenotypes were weakly correlated (|r| ≤ 0.07) with low pairwise agreement (Kappa ≤ 0.06). Among these families selected for familial longevity, correspondence between healthy aging phenotypes was weak, supporting the heterogeneous nature of longevity and suggesting biological underpinnings of each individual phenotype should be examined separately to determine their shared and unique determinants.

Effect of Intentional Weight Loss on Mortality Biomarkers in Older Adults With Obesity

BACKGROUND

Observational research has identified several mortality biomarkers; however, their responsiveness to change is unknown. We tested whether the Healthy Aging Index (HAI) and other mortality biomarkers were responsive to intentional weight loss (WL), which is associated with lower mortality risk in recent meta-analyses.

METHODS

Older adults (70.3 ± 3.7 years) with obesity were randomized into a 6-month WL (n = 47) or weight stability (WS: ±5% baseline weight; n = 48) program. Baseline and 6-month HAI score (0-10) was calculated from component sum (each 0-2: systolic blood pressure, forced vital capacity [FVC], creatinine, fasting blood glucose [FBG], Montreal Cognitive Assessment), and gait speed, grip strength, Digit Symbol Substitution Test, FEV1, Interleukin-6, C-Reactive Protein, and Cystatin-C were assessed at baseline and 6 months.

RESULTS

Mean baseline HAI was 3.2 ± 1.6. By 6 months, WL participants lost 8.87 (95% CI: -10.40, -7.34) kg, whereas WS participants remained weight stable. WL group reduced HAI score (WL: -0.75 [95% CI: -1.11, -0.39] vs WS: -0.22 [95% CI: -0.60, 0.15]; p = .04), and components changing the most were FBG (WL: -3.89 [95% CI: -7.78, 0.00] mg/dL vs WS: 1.45 [95% CI: -2.61, 5.50] mg/dL; p = .047) and FVC (WL: 0.11 [95% CI: -0.01, 0.23] L vs WS: -0.05 [95% CI: -0.17, 0.08] L; p = .06). Among other biomarkers, only Cystatin-C significantly changed (WL: -2.53 [95% CI: -4.38, -0.68] ng/mL vs WS: 0.07 [95% CI: -1.85, 1.98] ng/mL; p = .04). Combining treatment groups, 1 kg WL was associated with a 0.07 (95% CI: 0.03, 0.12) HAI reduction (p < .01).

CONCLUSION

Intentional WL via caloric restriction reduced HAI score by 0.53 points, largely attributable to metabolic and pulmonary improvements.

A framework for selection of blood-based biomarkers for geroscience-guided clinical trials: report from the TAME Biomarkers Workgroup

Recent advances indicate that biological aging is a potentially modifiable driver of late-life function and chronic disease and have led to the development of geroscience-guided therapeutic trials such as TAME (Targeting Aging with MEtformin). TAME is a proposed randomized clinical trial using metformin to affect molecular aging pathways to slow the incidence of age-related multi-morbidity and functional decline. In trials focusing on clinical end-points (e.g., disease diagnosis or death), biomarkers help show that the intervention is affecting the underlying aging biology before sufficient clinical events have accumulated to test the study hypothesis. Since there is no standard set of biomarkers of aging for clinical trials, an expert panel was convened and comprehensive literature reviews conducted to identify 258 initial candidate biomarkers of aging and age-related disease. Next selection criteria were derived and applied to refine this set emphasizing: (1) measurement reliability and feasibility; (2) relevance to aging; (3) robust and consistent ability to predict all-cause mortality, clinical and functional outcomes; and (4) responsiveness to intervention. Application of these selection criteria to the current literature resulted in a short list of blood-based biomarkers proposed for TAME: IL-6, TNFα-receptor I or II, CRP, GDF15, insulin, IGF1, cystatin C, NT-proBNP, and hemoglobin A1c. The present report provides a conceptual framework for the selection of blood-based biomarkers for use in geroscience-guided clinical trials. This work also revealed the scarcity of well-vetted biomarkers for human studies that reflect underlying biologic aging hallmarks, and the need to leverage proposed trials for future biomarker discovery and validation.

Towards a toolkit for the assessment and monitoring of musculoskeletal ageing

The complexities and heterogeneity of the ageing process have slowed the development of consensus on appropriate biomarkers of healthy ageing. The MRC-Arthritis Research UK Centre for Integrated research into Musculoskeletal Ageing (CIMA) is a collaboration between researchers and clinicians at the Universities of Liverpool, Sheffield and Newcastle. One of CIMA’s objectives is to ‘Identify and share optimal techniques and approaches to monitor age-related changes in all musculoskeletal tissues, and to provide an integrated assessment of musculoskeletal function’, i.e. to develop a toolkit for assessing musculoskeletal ageing. This toolkit is envisaged as an instrument that can be used to characterise and quantify musculoskeletal function during ‘normal’ ageing, lend itself to use in large-scale, internationally important cohorts, and provide a set of biomarker outcome measures for epidemiological and intervention studies designed to enhance healthy musculoskeletal ageing. Such potential biomarkers include: biochemical measurements in biofluids or tissue samples, in vivo measurements of body composition, imaging of structural and physical properties, and functional tests. The CIMA Toolkit Working Group assessed candidate biomarkers of musculoskeletal ageing under these four headings, detailed their biological bases, strengths and limitations, and made practical recommendations for their use. In addition, the CIMA Toolkit Working Group identified gaps in the evidence base and suggested priorities for further research on biomarkers of musculoskeletal ageing.

Developing a toolkit for the assessment and monitoring of musculoskeletal ageing

The complexities and heterogeneity of the ageing process have slowed the development of consensus on appropriate biomarkers of healthy ageing. The Medical Research Council–Arthritis Research UK Centre for Integrated research into Musculoskeletal Ageing (CIMA) is a collaboration between researchers and clinicians at the Universities of Liverpool, Sheffield and Newcastle. One of CIMA’s objectives is to ‘Identify and share optimal techniques and approaches to monitor age-related changes in all musculoskeletal tissues, and to provide an integrated assessment of musculoskeletal function’—in other words to develop a toolkit for assessing musculoskeletal ageing. This toolkit is envisaged as an instrument that can be used to characterise and quantify musculoskeletal function during ‘normal’ ageing, lend itself to use in large-scale, internationally important cohorts, and provide a set of biomarker outcome measures for epidemiological and intervention studies designed to enhance healthy musculoskeletal ageing. Such potential biomarkers include: biochemical measurements in biofluids or tissue samples, in vivo measurements of body composition, imaging of structural and physical properties, and functional tests. This review assesses candidate biomarkers of musculoskeletal ageing under these four headings, details their biological bases, strengths and limitations, and makes practical recommendations for their use. In addition, we identify gaps in the evidence base and priorities for further research on biomarkers of musculoskeletal ageing.

Eleven Telomere, Epigenetic Clock, and Biomarker-Composite Quantifications of Biological Aging: Do They Measure the Same Thing?

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

Index of Healthy Aging in Chinese Older Adults: China Health and Retirement Longitudinal Study

OBJECTIVES

To characterize the distribution of an index of healthy aging-the Chinese Healthy Aging Index (CHAI)-in Chinese adults aged 60 and older according to sociodemographic characteristics and geographic region and to examine the association between the CHAI and mortality, disability, and functional limitation over 4 years.

DESIGN

Nationally representative cohort study.

SETTING

China Health and Retirement Longitudinal Study.

PARTICIPANTS

Chinese adults aged 60 and older (N=3,740).

MEASUREMENTS

Six CHAI components (systolic blood pressure, peak expiratory flow, Telephone Interview for Cognitive Status, estimated glomerular filtration rate, fasting glucose, C-reactive protein) were scored 0 (healthiest), 1, and 2 (unhealthiest) according to sex-specific tertiles or clinically relevant cut-points and summed to construct the CHAI (range 0-12).

RESULTS

Mean CHAI score was 5.6; 5.7% had a score of 0 to 2 (healthiest), 23.0% a score of 3 or 4, 37.5% a score of 5 or 6, and 33.8% a score of 7 to 12 (unhealthiest). Participants who were younger, more educated, and married were much more likely to have an ideal CHAI profile (score 0-2). Age-adjusted prevalence of an ideal CHAI profile ranged from 1.7% in the south to 8.1% in the north. After multivariable adjustment, persons with a CHAI score of 3 to 12 had substantially higher odds of mortality, disability, and functional limitation than those with a score of 0 to 2. The CHAI further stratified outcomes for persons with no clinically recognizable comorbidities.

CONCLUSION

Substantial variation exists in the CHAI according to sociodemographic characteristics and geographic regions. The CHAI could identify Chinese elderly adults with low risk of adverse outcomes and provide incremental value for risk prediction beyond clinically diagnosed comorbidities.

Association between lifetime risk of atrial fibrillation and mortality in the oldest old

BACKGROUND

Age is the strongest predictor of atrial fibrillation (AF), yet little is known about AF incidence in the oldest old.

HYPOTHESIS

AF incidence declines after age 90 years, and morbidity is compressed into a brief period at the end of life.

METHODS

In this retrospective, longitudinal cohort study of patients (born 1905-1935), we examined cumulative lifetime incidence of AF and its impact on mortality. Data included records from 1 062 610 octogenarians, 317 161 nonagenarians, and 3572 centenarians. Kaplan-Meier curves were used to estimate cumulative incidence of AF by age group, incidence rates were compared using log-rank tests, and Cox proportional hazards model was used to estimate unadjusted hazard ratios. The primary outcome was AF incidence at age > 80 years; the secondary outcome was mortality.

RESULTS

The cumulative AF incidence rate was 5.0% in octogenarians, 5.4% in nonagenarians, and 2.3% in centenarians. Octogenarians and nonagenarians had a higher risk of AF incidence compared to centenarians (adjusted hazard ratio 8.74, 95% confidence interval [CI]: 6.31-12.04; and 2.98, 95% CI: 2.17-4.1, respectively). The lowest hazard ratio for mortality in patients with AF compared to those without was 2.3 (95% CI: 2.3-2.4) in patients who were on antiplatelet and anticoagulant medication and had a score of 0 on the Elixhauser comorbidity index score.

CONCLUSIONS

Although AF incidence increased with age, being a centenarian was associated with reduced incidence and compression of morbidity. Patients with AF had a higher adjusted mortality rate. However, data suggest that a regimen of anticoagulants and antiplatelets may reduce risk of mortality in patients over 80 with an AF diagnosis.

A novel healthy blood pressure phenotype in the Long Life Family Study

BACKGROUND

Hypertension tends to run in families and has both genetic and environmental determinants. We assessed the hypothesis that a novel healthy blood pressure (BP) phenotype is also familial and sought to identify its associated factors.

METHODS

We developed a healthy BP phenotype in the Long Life Family Study, a cohort of two-generation families selected for longevity. Participants from the offspring generation (n = 2211, ages 32-88) were classified as having healthy BP if their age-adjusted and sex-adjusted SBP z-score was between -1.5 and -0.5. Offspring on antihypertensive medications were classified as not having healthy BP. Families with at least two offspring (n = 419 families) were defined as meeting the healthy BP phenotype if at least two and at least 50% of their offspring had healthy BP.

RESULTS

Among 2211 offspring, 476 (21.5%) met the healthy BP phenotype. When examining the 419 families, only 44 (10.5%) families met the criteria for the healthy BP phenotype. Both offspring and probands from families with healthy BP performed better on neuropsychological tests that place demands on complex attention and executive function when compared with offspring and probands from remaining families. Among families with the healthy BP phenotype compared with families without, a higher proportion of offspring met the American Heart Association definition of ideal cardiovascular health (10.8 versus 3.8%, respectively; driven by BP, smoking status, and BMI components).

CONCLUSION

In this cohort of familial longevity, few families had a novel healthy BP phenotype in multiple members. Families with this healthy BP phenotype may represent a specific pathway to familial longevity.

Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare

The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals.

A Modified Healthy Aging Index and Its Association with Mortality: The National Health and Nutrition Examination Survey, 1999-2002

BACKGROUND

Comorbidity indices that are based on clinically recognized disease do not capture the full spectrum of health. The Healthy Aging Index (HAI) was recently developed to describe a wider range of health and disease across multiple organ systems. We characterized the distribution of a modified HAI (mHAI) by sociodemographics in a representative sample of the U.S. population. We also examined the association of the mHAI with mortality across individuals with different levels of clinically recognizable comorbidities.

METHODS

Data are from the National Health and Nutrition Examination Survey (1999-2000, 2001-2002) on 2,451 adults aged 60 years or older. Five mHAI components (systolic blood pressure, Digit Symbol Substitution Test, cystatin C, glucose, and respiratory problems) were scored 0 (healthiest), 1, or 2 (unhealthiest) by sex-specific tertiles or clinically relevant cutoffs and summed to construct the mHAI.

RESULTS

The mean mHAI score was 4.3; 20.6% had a score of 0-2. 33.2% had a score of 3-4, 31.0% had a score of 5-6, and 15.2% had a score of 7-10. Mean mHAI scores were lower in adults who were younger, non-Hispanic whites, more educated, and married/living with partner. After multivariate adjustment, per unit higher of the mHAI was associated with higher all-cause mortality (HR = 1.19, 95% CI = 1.11-1.27) and higher cardiovascular mortality (HR = 1.23, 95% CI = 1.11-1.35). Within each comorbidity category (0, 1, 2, 3, 4+), the mHAI was still widely distributed and further stratified mortality.

CONCLUSIONS

Substantial variation exists in the mHAI across sociodemographic subgroups. The mHAI could provide incremental value for mortality risk prediction beyond clinically diagnosed chronic diseases among elders.