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Background: Understanding the dynamics of epidemiologic trends in Alzheimer’s disease (AD) and related dementias (ADRD) and their epidemiologic causes is vital to providing important insights into reducing the burden associated with these conditions. Objective: To model the time trends in age-adjusted AD/ADRD prevalence and incidence-based mortality (IBM), and identify the main causes of the changes in these measures over time in terms of interpretable epidemiologic quantities. Methods: Trend decomposition was applied to a 5%sample of Medicare beneficiaries between 1991 and 2017. Results: Prevalence of AD was increasing between 1992 and 2011 and declining thereafter, while IBM increased over the study period with a significant slowdown in its rate of growth from 2011 onwards. For ADRD, prevalence and IBM increased through 2014 prior to taking a downwards turn. The primary determinant responsible for declines in prevalence and IBM was the deceleration in the increase and eventual decrease in incidence rates though changes in relative survival began to affect the overall trends in prevalence/IBM in a noticeable manner after 2008. Other components showed only minor effects. Conclusion: The prevalence and IBM of ADRD is expected to continue to decrease. The directions of these trends for AD are not clear because AD incidence, the main contributing component, is decreasing but at a decreasing rate suggesting a possible reversal. Furthermore, emerging treatments may contribute through their effects on survival. Improving ascertainment of AD played an important role in trends of AD/ADRD over the 1991-2009/10 period but this effect has exhausted itself by 2017.

Recently, Mahalanobis distance (DM) was suggested as a statistical measure of physiological dysregulation in aging individuals. We constructed DM variants using sets of biomarkers collected at the two visits of the Long Life Family Study (LLFS) and performed joint analyses of longitudinal observations of DM and follow-up mortality in LLFS using joint models. We found that DM is significantly associated with mortality (hazard ratio per standard deviation: 1.31 [1.16, 1.48] to 2.22 [1.84, 2.67]) after controlling for age and other covariates. GWAS of random intercepts and slopes of DM estimated from joint models found a genome-wide significant SNP (rs12652543, p=7.2 × 10-9) in the TRIO gene associated with the slope of DM constructed from biomarkers declining in late life. Review of biological effects of genes corresponding to top SNPs from GWAS of DM slopes revealed that these genes are broadly involved in cancer prognosis and axon guidance/synapse function. Although axon growth is mainly observed during early development, the axon guidance genes can function in adults and contribute to maintenance of neural circuits and synaptic plasticity. Our results indicate that decline in axons' ability to maintain complex regulatory networks may potentially play an important role in the increase in physiological dysregulation during aging.

Purpose: To quantitatively evaluate contributions of trends in incidence, relative survival, and stage at diagnosis to the dynamics in the prevalence of major cancers (lung, prostate, colon, breast, urinary bladder, ovaries, stomach, pancreas, esophagus, kidney, liver, and skin melanoma) among older U.S. adults age 65+. Methods: Trend partitioning was applied to the Surveillance, Epidemiology, and End Results Program data for 1973-2016. Results: Growth of cancer prevalence in older adults decelerated or even decreased over time for all studied cancers due to decreasing incidence and improving survival for most of cancers, with a smaller contribution of the stage at cancer diagnosis. Changes in prevalence of cancers of lung, colon, stomach, and breast were predominantly due to decreasing incidence, increasing survival and more frequent diagnoses at earlier stages. Changes in prevalence of some other cancers demonstrated adverse trends such as decreasing survival in localized and regional stages (urinary bladder and ovarian) and growing impact of late-stage diagnoses (esophageal cancer). Conclusion: While decelerating or decreasing prevalence of many cancers were due to a beneficial combination of decreasing incidence and increasing survival, there are cancers for which decelerating prevalence is due to the lack of improvement in their stage-specific survival and/or increasing frequency of diagnosis at advanced stages. Overall, if the observed trends persist, it is likely that cancer burden due to its prevalence in older U.S. population will be lower than it was projected in earlier studies.

Aim: Experimental studies provided numerous evidence that caloric/dietary restriction may improve health and increase the lifespan of laboratory animals, and that the interplay among molecules that sense cellular stress signals and those regulating cell survival can play a crucial role in cell response to nutritional stressors. However, it is unclear whether the interplay among corresponding genes also plays a role in human health and lifespan. Methods: Literature about roles of cellular stressors have been reviewed, such as amino acid deprivation, and the integrated stress response (ISR) pathway in health and aging. Single nucleotide polymorphisms (SNPs) in two candidate genes (GCN2/EIF2AK4 and CHOP/DDIT3) that are closely involved in the cellular stress response to amino acid starvation, have been selected using information from experimental studies. Associations of these SNPs and their interactions with human survival in the Health and Retirement Study data have been estimated. The impact of collective associations of multiple interacting SNP pairs on survival has been evaluated, using a recently developed composite index: the SNP-specific Interaction Polygenic Risk Score (SIPRS). Results: Significant interactions have been found between SNPs from GCN2/EIF2AK4 and CHOP/DDI3T genes that were associated with survival 85+ compared to survival between ages 75 and 85 in the total sample (males and females combined) and in females only. This may reflect sex differences in genetic regulation of the human lifespan. Highly statistically significant associations of SIPRS [constructed for the rs16970024 (GCN2/EIF2AK4) and rs697221 (CHOP/DDIT3)] with survival in both sexes also been found in this study. Conclusion: Identifying associations of the genetic interactions with human survival is an important step in translating the knowledge from experimental to human aging research. Significant associations of multiple SNPxSNP interactions in ISR genes with survival to the oldest old age that have been found in this study, can help uncover mechanisms of multifactorial regulation of human lifespan and its heterogeneity.

Late life disability is a highly devastating condition affecting 20% or more of persons aged 65 years and older in the USA; it is an important determinant of acute medical and long-term care costs which represent a growing burden on national economies. Disability is a multifactorial trait that contributes substantially to decline of health/wellbeing. Accordingly, gaining insights into the genetics of disability could help in identifying molecular mechanisms of this devastating condition and age-related processes contributing to a large fraction of specific geriatric conditions, concordantly with geroscience. We performed a genome-wide association study of disability in a sample of 24,068 subjects from five studies with 12,550 disabled individuals. We identified 30 promising disability-associated polymorphisms in 19 loci at p < 10(−4); four of them attained suggestive significance, p < 10(−5). In contrast, polygenic risk scores aggregating effects of minor alleles of independent SNPs that were adversely or beneficially associated with disability showed highly significant associations in meta-analysis, p = 3.13 × 10(−45) and p = 5.60 × 10(−23), respectively, and were replicated in each study. The analysis of genetic pathways, related diseases, and biological functions supported the connections of genes for the identified SNPs with disabling and age-related conditions primarily through oxidative/nitrosative stress, inflammatory response, and ciliary signaling. We identified musculoskeletal system development, maintenance, and regeneration as important components of gene functions. The beneficial and adverse gene sets may be differently implicated in the development of musculoskeletal-related disability with the beneficial set characterized, e.g., by regulation of chondrocyte proliferation and bone formation, and the adverse set by inflammation and bone loss. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11357-019-00125-8) contains supplementary material, which is available to authorized users.

Background Time trends of lung cancer prevalence and mortality are the result of three competing processes: changes in the incidence rate, stage-specific survival, and ascertainment at early stages. Improvements in these measures act concordantly to improve disease-related mortality, but push the prevalence rate in opposite directions making a qualitative interpretation difficult. The goal of this paper is to evaluate the relative contributions of these components to changes in lung cancer prevalence and mortality. Methods Partitioning of prevalence and mortality trends into their components using SEER data for 1973-2013. Results The prevalence of lung cancer increases for females and decreases for males. In 1998, the former was due to increased incidence (45%-50% of total trend), improved survival (40%-45%), and increased ascertainment at early stages (10%-15%). In males, a rapidly declining incidence rate overpowered the effects of survival and ascertainment resulting in an overall decrease in prevalence over time. Trends in lung cancer mortality are determined by incidence during 1993-2002 with noticeable contribution of survival after 2002. Conclusion Lung cancer incidence was the main driving force behind trends in prevalence and mortality. Improved survival played essential role from 2000 onwards. Trends in stage ascertainment played a small but adverse role. Our results suggest that further improvement in lung cancer mortality can be achieved through advances in early stage ascertainment, especially for males, and that in spite of success in treatment, adenocarcinoma continues to exhibit adverse trends (especially in female incidence) and its role among other histology-specific lung cancers will increase in the near future.

A major goal of aging research is identifying genetic targets that could be used to slow or reverse aging – changes in the body and extend limits of human lifespan. However, majority of genes that showed the anti-aging and pro-survival effects in animal models were not replicated in humans, with few exceptions. Potential reasons for this lack of translation include a highly conditional character of genetic influence on lifespan, and its heterogeneity, meaning that better survival may be result of not only activity of individual genes, but also gene–environment and gene–gene interactions, among other factors. In this paper, we explored associations of genetic interactions with human lifespan. We selected candidate genes from well-known aging pathways (IGF1/FOXO growth signaling, P53/P16 apoptosis/senescence, and mTOR/SK6 autophagy and survival) that jointly decide on outcomes of cell responses to stress and damage, and so could be prone to interactions. We estimated associations of pairwise statistical epistasis between SNPs in these genes with survival to age 85+ in the Atherosclerosis Risk in Communities study, and found significant (FDR < 0.05) effects of interactions between SNPs in IGF1R, TGFBR2, and BCL2 on survival 85+. We validated these findings in the Cardiovascular Health Study sample, with P < 0.05, using survival to age 85+, and to the 90th percentile, as outcomes. Our results show that interactions between SNPs in genes from the aging pathways influence survival more significantly than individual SNPs in the same genes, which may contribute to heterogeneity of lifespan, and to lack of animal to human translation in aging research.

The slow pace of global vaccination and the rapid emergence of SARS-CoV-2 variants suggest recurrent waves of COVID-19 in coming years. Therefore, understanding why deaths from COVID-19 are highly concentrated among older adults is essential for global health. Severe COVID-19 T-cell lymphopenia is more common among older adults, and it entails poor prognosis. Much about the primary etiology of this form of lymphopenia remains unknown, but regardless of its causes, offsetting the decline in T-cell count during SARS-CoV-2 infection demands fast and massive T-cell clonal expansion, which is telomere length (TL)-dependent. We have built a model that captures the effect of age-dependent TL shortening in hematopoietic cells and its effect on T-cell clonal expansion capacity. The model shows that an individual with average hematopoietic cell TL (HCTL) at age twenty years maintains maximal T-cell clonal expansion capacity until the 6th decade of life when this capacity plummets by more than 90% over the next ten years. The collapse coincides with the steep increase in COVID-19 mortality with age. HCTL metrics may thus explain the vulnerability of older adults to COVID-19. That said, the wide inter-individual variation in HCTL across the general population means that some younger adults with inherently short HCTL might be at risk of severe COVID-19 lymphopenia and mortality from the disease.Significance StatementDeclining immunity with advancing age is a general explanation for the increased mortality from COVID-19 among older adults. This mortality far exceeds that from viral illnesses such as the seasonal influenza, and it thus requires specific explanations. One of these might be diminished ability with age to offset the development of severe T-cell lymphopenia (a low T-cell count in the blood) that often complicates COVID-19. We constructed a model showing that age-dependent shortening of telomeres might constrain the ability of T-cells of some older COVID-19 patients to undertake the massive proliferation required to clear the virus that causes the infection. The model predicts that individuals with short telomeres, principally seniors, might be at a higher risk of death from COVID-19.

Objectives The regions with highest and lowest Alzheimer's disease (AD) mortality across the United States at state/county levels were identified and their contribution to the differences in total mortality rates between these regions was evaluated. The disease, disease group, sex, race/ethnicity, and place-of-death-related inter-region differences that engender the disparity in mortality were quantitatively described. The hypothesis that inter-regional differences in filling out death certificates are a major contributor to differences in AD mortality was tested. Design Retrospective evaluation of death certificate data. Setting The United States. Participants Deceased US residents, 1999-2018. Methods Region-specific age-adjusted mortality rates and group-specific rate decomposition. Results The county clusters with the highest and lowest AD mortality rates were in Washington (WA) and New York (NY), respectively, with other notable high-mortality clusters on the border of Tennessee, Georgia, and Alabama as well as in North Dakota and South Dakota. These patterns were stable over the 1999-2018 period. AD had the highest contribution to total mortality difference between WA and NY (156%, higher in WA), in contrast circulatory diseases had a contribution of comparable magnitude (154%) but were higher in NY. Differences in cause-of-death certificate coding, either through coding of non-AD dementias, or other conditions accompanying a potential AD death could not account for differences in AD mortality between NY and WA. Conclusions Inter-regional differences in filling out death certificates were not a major contributor to variation in AD mortality between the regions with the highest and lowest rates. The respective mitigation of the effects of neural and circulatory diseases and several other high-impact conditions would not negate the disparity in mortality between NY and WA.

Aim Experimental studies provided numerous evidence that caloric/dietary restriction may improve health and increase the lifespan of laboratory animals, and that the interplay among molecules that sense cellular stress signals and those regulating cell survival can play a crucial role in cell response to nutritional stressors. However, it is unclear whether the interplay among corresponding genes also plays a role in human health and lifespan. Methods Literature about roles of cellular stressors have been reviewed, such as amino acid deprivation, and the integrated stress response (ISR) pathway in health and aging. Single nucleotide polymorphisms (SNPs) in two candidate genes (GCN2/EIF2AK4 and CHOP/DDIT3) that are closely involved in the cellular stress response to amino acid starvation, have been selected using information from experimental studies. Associations of these SNPs and their interactions with human survival in the Health and Retirement Study data have been estimated. The impact of collective associations of multiple interacting SNP pairs on survival has been evaluated, using a recently developed composite index: the SNP-specific Interaction Polygenic Risk Score (SIPRS). Results Significant interactions have been found between SNPs from GCN2/EIF2AK4 and CHOP/DDI3T genes that were associated with survival 85+ compared to survival between ages 75 and 85 in the total sample (males and females combined) and in females only. This may reflect sex differences in genetic regulation of the human lifespan. Highly statistically significant associations of SIPRS [constructed for the rs16970024 (GCN2/EIF2AK4) and rs697221 (CHOP/DDIT3)] with survival in both sexes also been found in this study. Conclusion Identifying associations of the genetic interactions with human survival is an important step in translating the knowledge from experimental to human aging research. Significant associations of multiple SNPxSNP interactions in ISR genes with survival to the oldest old age that have been found in this study, can help uncover mechanisms of multifactorial regulation of human lifespan and its heterogeneity.

At a recent symposium on aging biology, a debate was held as to whether or not we know what biological aging is. Most of the participants were struck not only by the lack of consensus on this core question, but also on many basic tenets of the field. Accordingly, we undertook a systematic survey of our 71 participants on key questions that were raised during the debate and symposium, eliciting 37 responses. The results confirmed the impression from the symposium: there is marked disagreement on the most fundamental questions in the field, and little consensus on anything other than the heterogeneous nature of aging processes. Areas of major disagreement included what participants viewed as the essence of aging, when it begins, whether aging is programmed or not, whether we currently have a good understanding of aging mechanisms, whether aging is or will be quantifiable, whether aging will be treatable, and whether many non-aging species exist. These disagreements lay bare the urgent need for a more unified and cross-disciplinary paradigm in the biology of aging that will clarify both areas of agreement and disagreement, allowing research to proceed more efficiently. We suggest directions to encourage the emergence of such a paradigm.

Emerging evidence from experimental and clinical research suggests that stress-related genes may play key roles in AD development. The fact that genome-wide association studies were not able to detect a contribution of such genes to AD indicates the possibility that these genes may influence AD non-linearly, through interactions of their products. In this paper, we selected two stress-related genes (GCN2/EIF2AK4 and APP) based on recent findings from experimental studies which suggest that the interplay between these genes might influence AD in humans. To test this hypothesis, we evaluated the effects of interactions between SNPs in these two genes on AD occurrence, using the Health and Retirement Study data on white indidividuals. We found several interacting SNP-pairs whose associations with AD remained statistically significant after correction for multiple testing. These findings emphasize the importance of nonlinear mechanisms of polygenic AD regulation that cannot be detected in traditional association studies. To estimate collective effects of multiple interacting SNP-pairs on AD, we constructed a new composite index, called Interaction Polygenic Risk Score, and showed that its association with AD is highly statistically significant. These results open a new avenue in the analyses of mechanisms of complex multigenic AD regulation.

Longer lifespan is accompanied by a larger number of chronic diseases among older adults. Because of a growing proportion of older adults in the U.S., this brings the problem of age-related morbidity to the forefront as a major contributor to rising medical expenditures. We evaluated 15-year time trends (from 1998 to 2013) in the prevalence of 48 acute and chronic non-cancer diseases and cancers in older U.S. adults aged 65+ and estimated the annual percentage changes of these prevalence trends using SEER-Medicare and HRS-Medicare data. We found that age-adjusted prevalence of cancers of kidney, pancreas, and melanoma, as well as diabetes, renal disease, limb fracture, depression, anemia, weight deficiency, dementia/Alzheimer's disease, drug/medications abuse and several other diseases/conditions increased over time. Conversely, prevalence of myocardial infarction, heart failure, cardiomyopathy, pneumonia/influenza, peptic ulcer, and gastrointestinal bleeding, among others, decreased over time. There are also diseases whose prevalence did not change substantially over time, e.g., a group of fast progressing cancers and rheumatoid arthritis. Analysis of trends of multiple diseases performed simultaneously within one study design with focus on the same time interval and the same population for all diseases allowed us to provide insight into the epidemiology of these conditions and identify the most alarming and/or unexpected trends and trade-offs. The obtained results can be used for health expenditures planning for growing sector of older adults in the U.S.

Despite evident success in clarifying many important features of Alzheimer's disease (AD) the efficient methods of its prevention and treatment are not yet available. The reasons are likely to be the fact that AD is a multifactorial and heterogeneous health disorder with multiple alternative pathways of disease development and progression. The availability of genetic data on individuals participated in longitudinal studies of aging health and longevity, as well as on participants of cross-sectional case-control studies allow for investigating genetic and non-genetic connections with AD and to link the results of these analyses with research findings obtained in clinical, experimental, and molecular biological studies of this health disorder. The objective of this paper is to perform GWAS of AD in several study populations and investigate possible roles of detected genetic factors in developing AD hallmarks and in other health disorders. The data collected in the Framingham Heart Study (FHS), Cardiovascular Health Study (CHS), Health and Retirement Study (HRS) and Late Onset Alzheimer's Disease Family Study (LOADFS) were used in these analyses. The logistic regression and Cox's regression were used as statistical models in GWAS. The results of analyses confirmed strong associations of genetic variants from well-known genes APOE, TOMM40, PVRL2 (NECTIN2), and APOC1 with AD. Possible roles of these genes in pathological mechanisms resulting in development of hallmarks of AD are described. Many genes whose connection with AD was detected in other studies showed nominally significant associations with this health disorder in our study. The evidence on genetic connections between AD and vulnerability to infection, as well as between AD and other health disorders, such as cancer and type 2 diabetes, were investigated. The progress in uncovering hidden heterogeneity in AD would be substantially facilitated if common mechanisms involved in development of AD, its hallmarks, and AD related chronic conditions were investigated in their mutual connection.

Recently suggested novel implementation of the statistical distance measure (DM) for evaluating “physiological dysregulation” (PD) in aging individuals (based on measuring deviations of multiple biomarkers from baseline or normal physiological states) allows reducing high-dimensional biomarker space into a single PD estimate. Here we constructed DM using biomarker profiles from FRAMCOHORT (Framingham Heart Study) and CHS (Cardiovascular Health Study) Research Materials obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center, and estimated effect of PD on total survival, onset of unhealthy life (proxy for “robustness”) and survival following the onset of unhealthy life (proxy for “resilience”). We investigated relationships between PD and declines in stress resistance and adaptive capacity not directly observed in data. PD was more strongly associated with the onset of unhealthy life than with survival after disease suggesting that declines in robustness and resilience with age may have overlapping as well as distinct mechanisms. We conclude that multiple deviations of physiological markers from their normal states (reflected in higher PD) may contribute to increased vulnerability to many diseases and precede their clinical manifestation. This supports potential use of PD in health care as a preclinical indicator of transition from healthy to unhealthy state.

Aims To identify how efforts to control the diabetes epidemic and the resulting changes in diabetes mellitus, type II (T2D) incidence and survival have affected the time-trend of T2D prevalence. Methods A newly developed method of trend decomposition was applied to a 5% sample of Medicare administrative claims filed between 1991 and 2012. Results Age-adjusted prevalence of T2D for adults age 65+ increased at an average annual percentage change of 2.31% between 1992 and 2012. Primary contributors to this trend were (in order of magnitude): improved survival at all ages, increased prevalence of T2D prior to age of Medicare eligibility, decreased incidence of T2D after age of Medicare eligibility. Conclusions Health services supported by the Medicare system, coupled with improvements in medical technology and T2D awareness efforts provide effective care for individuals age 65 and older. However, policy maker attention should be shifted to the prevention of T2D in younger age groups to control the increase in prevalence observed prior to Medicare eligibility.

The special design of the Long Life Family Study provides a unique opportunity to investigate the genetics of human longevity by analyzing data on exceptional lifespans in families. In this article, we performed two series of genome wide association studies of human longevity which differed with respect to whether missing lifespan data were predicted or not predicted. We showed that the use of predicted lifespan is most beneficial when the follow-up period is relatively short. In addition to detection of strong associations of SNPs in APOE, TOMM40, NECTIN2, and APOC1 genes with longevity, we also detected a strong new association with longevity of rs1927465, located between the CYP26A1 and MYOF genes on chromosome 10. The association was confirmed using data from the Health and Retirement Study. We discuss the biological relevance of the detected SNPs to human longevity.

Unraveling the underlying biological mechanisms or pathways behind the effects of genetic variations on complex diseases remains one of the major challenges in the post-GWAS (where GWAS is genome-wide association study) era. To further explore the relationship between genetic variations, biomarkers, and diseases for elucidating underlying pathological mechanism, a huge effort has been placed on examining pleiotropic and gene-environmental interaction effects. We propose a novel genetic stochastic process model (GSPM) that can be applied to GWAS and jointly investigate the genetic effects on longitudinally measured biomarkers and risks of diseases. This model is characterized by more profound biological interpretation and takes into account the dynamics of biomarkers during follow-up when investigating the hazards of a disease. We illustrate the rationale and evaluate the performance of the proposed model through two GWAS. One is to detect single nucleotide polymorphisms (SNPs) having interaction effects on type 2 diabetes (T2D) with body mass index (BMI) and the other is to detect SNPs affecting the optimal BMI level for protecting from T2D. We identified multiple SNPs that showed interaction effects with BMI on T2D, including a novel SNP rs11757677 in the CDKAL1 gene (P = 5.77 × 10-7 ). We also found a SNP rs1551133 located on 2q14.2 that reversed the effect of BMI on T2D (P = 6.70 × 10-7 ). In conclusion, the proposed GSPM provides a promising and useful tool in GWAS of longitudinal data for interrogating pleiotropic and interaction effects to gain more insights into the relationship between genes, quantitative biomarkers, and risks of complex diseases.

Age is major risk factor for AD; however, relationships between aging and AD are not well understood. Decline in physiological resilience is universal feature of human aging that may also play role in AD. Aging-related pathways (such as IGF-I/P53/mTOR-mediated) that are involved in tissue resilience work in concert to decide outcomes of cell responses to stress/damage, such as survival, apoptosis, autophagy, etc. We hypothesized that interplay among genes in these pathways may influence AD risk as result of epistasis (GxG). We estimated effects of pairwise epistasis between SNPs in 53 genes from respective pathways on AD risk in the LLFS compared with other data (HRS, CHS, LOADFS). We found significant (fdr

The time trend of prevalence and mortality of major cancers is the result of three competing processes: changes in the incidence rate, stage-specific survival, and ascertainment at early stages. Partitioning approach allows for evaluating the relative contribution of each of these competing processes to the overall trend. In this report we applied the partitioning methodology developed for the SEER registry data for prostate, colorectal, lung, female breast, bladder, ovarian, stomach, pancreas, kidney, liver cancers and melanoma. The analysis involves the design and estimation of four models for each cancer site: i) incidence rate using the Armitage-Doll model with individual predisposition modeled by the gamma distribution, ii) probability of relative survival after cancer diagnosis using the Weibull model for time after disease onset, iii) frequencies of stage at onset, and iv) mortality in the general population using the Gompertz model. B-splines are used to fit the time patterns of model parameters obtained for each year Relative contributions of the partitioning components were evaluated for individual cancers (e.g., increase of prevalence in prostate cancer in 2000 was due to increased incidence (59%), improved survival (29%), and improve stage ascertainment (12%)) and compared among all considered cancers. The results were discussed in the light of the effect of the accumulation of survivors occurring in early years (due to improving survival) and their higher mortality (because of higher prevalence of survivors) in later years (i.e., mortality is transferred to latter time periods due to overall improvements in survival).

Biological aging results in changes in an organism that accumulate over age in a complex fashion across different regulatory systems, and their cumulative effect manifests in increased physiological dysregulation (PD) and declining robustness and resilience that increase risks of health disorders and death. Several composite measures involving multiple biomarkers that capture complex effects of aging have been proposed. We applied one such approach, the Mahalanobis distance (DM), to baseline measurements of various biomarkers (inflammation, hematological, diabetes-associated, lipids, endocrine, renal) in 3,279 participants from the Long Life Family Study (LLFS) with complete biomarker data. We used DM to estimate the level of PD by summarizing information about multiple deviations of biomarkers from specified “norms” in the reference population (here, LLFS participants younger than 60 years at baseline). An increase in DM was associated with significantly higher mortality risk (hazard ratio per standard deviation of DM: 1.42; 95% confidence interval: [1.3, 1.54]), even after adjustment for a composite measure summarizing 85 health-related deficits (disabilities, diseases, less severe symptoms), age, and other covariates. Such composite measures significantly improved mortality predictions especially in the subsample of participants from families enriched for exceptional longevity (the areas under the receiver operating characteristic curves are 0.88 vs. 0.85, in models with and without the composite measures, p = 2.9 × 10−5). Sensitivity analyses confirmed that our conclusions are not sensitive to different aspects of computational procedures. Our findings provide the first evidence of association of PD with mortality and its predictive performance in a unique sample selected for exceptional familial longevity.