Mechanisms underlying familial aggregation of exceptional health and survival: A three-generation cohort study

Parental age at death is associated with age at first birth in offspring

PURPOSE

People age at different rates and the available evidence suggests that the rate of aging is partly inherited from previous generations. This heterogeneity in aging is evident already in midlife, but to what extent aging is associated with the timing of events earlier in life is not fully known. Here we aim to shed light on this topic by investigating the trade-off between reproduction and aging postulated by evolutionary theories of aging.

METHODS

Drawing on the inheritance of aging we use parental age at death as a proxy for aging-rates in the offspring, and study how age at first birth depends on this variable. We use data from an almost complete Swedish birth cohort comprising 92,359 individuals. Accelerated failure time models are used to estimate the association between parental age at death and age at first birth while adjusting for parental occupational class, educational attainment, and income.

RESULTS

Longer parental lifespans were consistently associated with older age at first births, both in men and women.

CONCLUSION

Our findings suggest that aging-related processes may be interrelated with the processes underlying the timing of reproduction and are in general agreement with evolutionary theories of aging.

Consequences of heterogeneity in aging: parental age at death predicts midlife all-cause mortality and hospitalization in a Swedish national birth cohort

BACKGROUND

The processes that underlie aging may advance at different rates in different individuals and an advanced biological age, relative to the chronological age, is associated with increased risk of disease and death. Here we set out to quantify the extent to which heterogeneous aging shapes health outcomes in midlife by following a Swedish birth-cohort and using parental age at death as a proxy for biological age in the offspring.

METHODS

We followed a nationwide Swedish birth cohort (N = 89,688) between the ages of 39 and 66 years with respect to hospitalizations and death. Cox regressions were used to quantify the association, in the offspring, between parental age at death and all-cause mortality, as well as hospitalization for conditions belonging to the 10 most common ICD-10 chapters.

RESULTS

Longer parental lifespan was consistently associated with reduced risks of hospitalization and all-cause mortality. Differences in risk were mostly evident from before the age of 50 and persisted throughout the follow-up. Each additional decade of parental survival decreased the risk of offspring all-cause mortality by 22% and risks of hospitalizations by 9 to 20% across the 10 diseases categories considered. The number of deaths and hospitalizations attributable to having parents not living until old age were 1500 (22%) and 11,000 (11%) respectively.

CONCLUSIONS

Our findings highlight that increased parental lifespan is consistently associated with health benefits in the offspring across multiple outcomes and suggests that heterogeneous aging processes have clinical implications already in midlife.

The Protective Effect of Familial Longevity Persists After Age 100: Findings From the Danish National Registers

BACKGROUND

A recent study suggested that the protective effect of familial longevity becomes negligible for centenarians. However, the authors assessed the dependence on familial longevity in centenarians by comparing centenarians with 1 parent surviving to age 80+ to centenarians whose same-sexed parent did not survive to age 80. Here we test whether the protective effect of familial longevity persists after age 100 using more restrictive definitions of long-lived families.

METHODS

Long-lived sibships were identified through 3 nationwide, consecutive studies in Denmark, including families with either at least 2 siblings aged 90+ or a Family Longevity Selection Score (FLoSS) above 7. Long-lived siblings enrolled in these studies and who reached age 100 were included. For each sibling, 5 controls matched on sex and year of birth were randomly selected among centenarians in the Danish population. Survival time from age 100 was described with Kaplan-Meier curves for siblings and controls separately. Survival analyses were performed using stratified Cox proportional hazards models.

RESULTS

A total of 340 individuals from long-lived sibships who survived to age 100 and 1 700 controls were included. Among the long-lived siblings and controls, 1 650 (81%) were women. The results showed that long-lived siblings presented better overall survival after age 100 than sporadic long-livers (hazard ratio [HR]  = 0.80, 95% confidence interval [CI]  = 0.71-0.91), with even lower estimate (HR = 0.65, 95% CI = 0.50-0.85) if familial longevity was defined by FLoSS.

CONCLUSIONS

The present study, with virtually no loss to follow-up, demonstrated a persistence of protective effect of familial longevity after age 100.

End of Life Events and Causes of Death in Danish Long-Lived Siblings: Reduced Dementia Risk Compared to Sporadic Long-Livers

Background

Better physical robustness and resilience of long-lived siblings compared to sporadic long-livers has been demonstrated in several studies. However, it is unknown whether long-lived siblings also end their lives better.

Objective

To investigate end-of-life (EoL) events (dementia diagnosis, medication, hospitalizations in the last 5 years of life), causes of death, and location of death in long-lived siblings compared to matched sporadic long-livers from the Danish population.

Methods

Long-lived siblings were identified through three nationwide Danish studies in which the inclusion criteria varied, but 99.5% of the families had at least two siblings surviving to age 90 + . Those who died between 2006 and 2018 were included, and randomly matched with sex, year-of-birth and age-at-death controls (i.e., sporadic long-lived controls) from the Danish population.

Results

A total of 5,262 long-lived individuals were included (1,754 long-lived siblings, 3,508 controls; 63% women; median age at death 96.1). Long-lived siblings had a significantly lower risk of being diagnosed with dementia in the last years of life (p = 0.027). There was no significant difference regarding the number of prescribed drugs, hospital stays, days in hospital, and location of death. Compared to controls, long-lived siblings presented a lower risk of dying from dementia (p = 0.020) and ill-defined conditions (p = 0.030).

Conclusions

In many aspects long-lived siblings end their lives similar to sporadic long-livers, with the important exception of lower dementia risk during the last 5 years of life. These results suggest that long-lived siblings are excellent candidates for identifying environmental and genetic protective factors of dementia.

Increasing number of long-lived ancestors marks a decade of healthspan extension and healthier metabolomics profiles

Globally, the lifespan of populations increases but the healthspan is lagging behind. Previous research showed that survival into extreme ages (longevity) clusters in families as illustrated by the increasing lifespan of study participants with each additional long-lived family member. Here we investigate whether the healthspan in such families follows a similar quantitative pattern using three-generational data from two databases, LLS (Netherlands), and SEDD (Sweden). We study healthspan in 2143 families containing index persons with 26 follow-up years and two ancestral generations, comprising 17,539 persons. Our results provide strong evidence that an increasing number of long-lived ancestors associates with up to a decade of healthspan extension. Further evidence indicates that members of long-lived families have a delayed onset of medication use, multimorbidity and, in mid-life, healthier metabolomic profiles than their partners. We conclude that both lifespan and healthspan are quantitatively linked to ancestral longevity, making family data invaluable to identify protective mechanisms of multimorbidity.

Turning Back the Clock: A Retrospective Single-Blind Study on Brain Age Change in Response to Nutraceuticals Supplementation vs. Lifestyle Modifications

BACKGROUND

There is a growing consensus that chronological age (CA) is not an accurate indicator of the aging process and that biological age (BA) instead is a better measure of an individual's risk of age-related outcomes and a more accurate predictor of mortality than actual CA. In this context, BA measures the "true" age, which is an integrated result of an individual's level of damage accumulation across all levels of biological organization, along with preserved resources. The BA is plastic and depends upon epigenetics. Brain state is an important factor contributing to health- and lifespan.

METHODS AND OBJECTIVE

Quantitative electroencephalography (qEEG)-derived brain BA (BBA) is a suitable and promising measure of brain aging. In the present study, we aimed to show that BBA can be decelerated or even reversed in humans (N = 89) by using customized programs of nutraceutical compounds or lifestyle changes (mean duration = 13 months).

RESULTS

We observed that BBA was younger than CA in both groups at the end of the intervention. Furthermore, the BBA of the participants in the nutraceuticals group was 2.83 years younger at the endpoint of the intervention compared with their BBA score at the beginning of the intervention, while the BBA of the participants in the lifestyle group was only 0.02 years younger at the end of the intervention. These results were accompanied by improvements in mental-physical health comorbidities in both groups. The pre-intervention BBA score and the sex of the participants were considered confounding factors and analyzed separately.

CONCLUSIONS

Overall, the obtained results support the feasibility of the goal of this study and also provide the first robust evidence that halting and reversal of brain aging are possible in humans within a reasonable (practical) timeframe of approximately one year.

Optimizing Translational Research for Exceptional Health and Life Span: A Systematic Narrative of Studies to Identify Translatable Therapeutic Target(s) for Exceptional Health Span in Humans

BACKGROUND

Exceptional longevity as manifested by the lower incidence and delayed onset of age-related disabilities/diseases that include cardiovascular disease, Alzheimer's disease, cancer is believed to be influenced by inherent protective molecular factors in exceptionally long-lived individuals. Unraveling these protective factors could lead to the discovery of therapeutic target(s) and interventions to promote healthy aging.

METHODS

In this context, the National Institute on Aging has established a collection of translational longevity research projects (ie, the Long-Life Family Study, the Longevity Consortium, Longevity Genomics, and the Integrative Longevity Omics) which are generating large omics data sets spanning the human genome to phenome and have embarked on cross-species multiomic data analyses integrating human and nonhuman species that display wide variation in their life spans.

RESULTS

It is expected that these studies will discover key signaling pathways that influence exceptional health span and identify therapeutic targets for translation to enhance health and life span. Other efforts related to translational longevity research include the "Comprehensive Evaluation of Aging-Related Clinical Outcomes and Geroproteins study," which focuses on potential effects in humans of polypeptides/proteins whose circulating levels change with age, and for which experimental evidence indicates reversal or acceleration of aging changes. The "Predictive Human Mechanistic Markers Network" is devoted to the development of predictive markers of aging, for target engagement when testing novel interventions for healthy aging.

CONCLUSION

We describe here the significance, the unique study design, categories of data sets, analytical strategies, and a data portal to facilitate open science and sharing of resources from these longevity studies to identify and validate potential therapeutic targets for healthy aging.

Familial aggregation of the aging process: biological age measured in young adult offspring as a predictor of parental mortality

Measures of biological age (BA) integrate information across organ systems to quantify "biological aging," i.e., inter-individual differences in aging-related health decline. While longevity and lifespan aggregate in families, reflecting transmission of genes and environments across generations, little is known about intergenerational continuity of biological aging or the extent to which this continuity may be modified by environmental factors. Using data from the Jerusalem Perinatal Study (JPS), we tested if differences in offspring BA were related to mortality in their parents. We measured BA using biomarker data collected from 1473 offspring during clinical exams in 2007-2009, at age 32 ± 1.1. Parental mortality was obtained from population registry data for the years 2004-2016. We fitted parametric survival models to investigate the associations between offspring BA and parental all-cause and cause-specific mortality. We explored potential differences in these relationships by socioeconomic position (SEP) and offspring sex. Participants' BAs widely varied (SD = 6.95). Among those measured to be biologically older, parents had increased all-cause mortality (HR = 1.10, 95% CI: 1.08, 1.13), diabetes mortality (HR = 1.19, 95% CI: 1.08, 1.30), and cancer mortality (HR = 1.07, 95% CI: 1.02, 1.13). The association with all-cause mortality was stronger for families with low compared with high SEP (P_interaction = 0.04) and for daughters as compared to sons (P_interaction < 0.001). Using a clinical-biomarker-based BA estimate, observable by young adulthood prior to the onset of aging-related diseases, we demonstrate intergenerational continuity of the aging process. Furthermore, variation in this familial aggregation according to household socioeconomic position (SEP) at offspring birth and between families of sons and daughters proposes that the environment alters individuals' aging trajectory set by their parents.

Physical resilience after a diagnosis of cardiovascular disease among offspring of long-lived siblings

Health benefits of longevity-enriched families transmit across generations and a lower incidence of cardiovascular diseases (CVD) have been shown to contribute to this phenomenon. In the current study, we investigated whether the offspring of long-lived siblings also have better survival after a CVD diagnosis compared to matched controls, i.e., are they both robust and resilient? Offspring of long-lived siblings were identified from three nationwide Danish studies and linked to national registers. Offspring with first diagnosis of acute myocardial infarction, chronic ischemic heart disease, heart failure or cerebrovascular disease between 1996 and 2011 were included and matched with two controls from the Danish population on sex, year of birth and diagnosis, and type of CVD. Stratified Cox proportional-hazards models on the matching data were performed to study 10-year overall survival. A total of 402 offspring and 804 controls were included: 64.2% male with a median age at diagnosis of 63.0. For offspring and controls, overall survival was 73% and 65% at 10 years from diagnosis, respectively. Offspring of long-lived siblings had a significantly better survival than controls, and this association was slightly attenuated after controlling for marital status, medication and Charlson Comorbidity Index score simultaneously. This study suggested that offspring of long-lived siblings not only show lower CVD incidence but also a better survival following CVD diagnosis compared to matched population controls. The higher biological resilience appears to be a universal hallmark of longevity-enriched families, which makes them uniquely positioned for studying healthy aging and longevity mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10433-021-00641-7.

Low Risk for Developing Diabetes Among the Offspring of Individuals With Exceptional Longevity and Their Spouses

Little is known about the risk of type 2 diabetes (T2D) among the offspring of individuals with exceptional longevity. We determined the incidence of and potential risk and protective factors for T2D among the offspring of probands and offspring’s spouses (mean age=60 years, range 32-88 years) in the Long Life Family Study (LLFS), a multicenter cohort study of 583 two-generation families with a clustering of healthy aging and exceptional longevity. Incident T2D was defined as fasting serum glucose ≥126 mg/dl, or HbA1c of ≥6.5%, or self-reported with doctor diagnosis of T2D, or the use of anti-diabetic medication during a mean follow-up 7.9 ± 1.1 years. Among offspring (n=1105) and spouses (n=328) aged 45-64 years without T2D at baseline visit, the annual incident rate of T2D was 3.6 and 3.0 per 1000 person-years, respectively, while among offspring (n=444) and spouses (n=153) aged 65+ years without T2D at baseline, the annual incident rate of T2D was 7.2 and 7.4 per 1000 person-years, respectively. By comparison, the annual incident rate of T2D per 1000 person-years in the U.S. general population was 9.9 among those aged 45-64, and 8.8 among those aged 65+ years (2018 National Health Interview Survey). Baseline BMI, waist circumference, and fasting serum triglycerides were positively associated with incident T2D, whereas fasting serum HDL-C, adiponectin, and sex hormone binding globulin were protective against incident T2D among the offspring (all P&lt;0.05). Similar associations were observed among their spouses (all P&lt;0.05, except sex hormone binding globulin). In addition, we observed that among spouses, but not offspring, fasting serum interleukin 6 and insulin-like growth factor 1 were positively associated with incident T2D (P&lt;0.05 for both). Our study suggests that both offspring of long-living individuals and their spouses, especially middle-aged, share a similar low risk for developing T2D as compared with the general population. Our findings also raise the possibility that distinct biological risk and protective factors may contribute to T2D risk among offspring of long-lived individuals when compared with their spouses. Future studies are needed to identify the mechanisms underlying low T2D risk among the offspring of individuals with exceptional longevity, and also among their spouses.

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.

PsychoAge and SubjAge: development of deep markers of psychological and subjective age using artificial intelligence

Aging clocks that accurately predict human age based on various biodata types are among the most important recent advances in biogerontology. Since 2016 multiple deep learning solutions have been created to interpret facial photos, omics data, and clinical blood parameters in the context of aging. Some of them have been patented to be used in commercial settings. However, psychological changes occurring throughout the human lifespan have been overlooked in the field of “deep aging clocks”.

In this paper, we present two deep learning predictors trained on social and behavioral data from Midlife in the United States (MIDUS) study: (a) PsychoAge, which predicts chronological age, and (b) SubjAge, which describes personal aging rate perception. Using 50 distinct features from the MIDUS dataset these models have achieved a mean absolute error of 6.7 years for chronological age and 7.3 years for subjective age. We also show that both PsychoAge and SubjAge are predictive of all-cause mortality risk, with SubjAge being a more significant risk factor.

Both clocks contain actionable features that can be modified using social and behavioral interventions, which enables a variety of aging-related psychology experiment designs. The features used in these clocks are interpretable by human experts and may prove to be useful in shifting personal perception of aging towards a mindset that promotes productive and healthy behaviors.