Understanding Alzheimer's disease in the context of aging: Findings from applications of stochastic process models to the Health and Retirement Study

There is growing literature on applications of biodemographic models, including stochastic process models (SPM), to studying regularities of age dynamics of biological variables in relation to aging and disease development. Alzheimer's disease (AD) is especially good candidate for SPM applications because age is a major risk factor for this heterogeneous complex trait. However, such applications are largely lacking. This paper starts filling this gap and applies SPM to data on onset of AD and longitudinal trajectories of body mass index (BMI) constructed from the Health and Retirement Study surveys and Medicare-linked data. We found that APOE e4 carriers are less robust to deviations of trajectories of BMI from the optimal levels compared to non-carriers. We also observed age-related decline in adaptive response (resilience) related to deviations of BMI from optimal levels as well as APOE- and age-dependence in other components related to variability of BMI around the mean allostatic values and accumulation of allostatic load. SPM applications thus allow revealing novel connections between age, genetic factors and longitudinal trajectories of risk factors in the context of AD and aging creating new opportunities for understanding AD development, forecasting trends in AD incidence and prevalence in populations, and studying disparities in those.

Relationship Between Serum IGF-1 and BMI Differs by Age

BACKGROUND

Serum levels of insulin-like growth factor 1 (IGF-1) and body mass index (BMI) are both associated with susceptibility to age-related diseases. Reports on the correlation between them have been conflicting, with both positive to negative correlations reported. However, the age ranges of the participants varied widely among these studies.

METHODS

Using data on 4241 participants (aged 24-110) from the Long Life Family Study, we investigated the relationship between IGF-1 and BMI by age groups using regression analysis.

RESULTS

When stratified by age quartile, the relationship between IGF-1 and BMI varied: in the first quartile (Q1, 20-58 years) the relationship was negative (β = -0.2, p = .002); in Q2 (58-66 years) and Q3 (67-86 years) the relationship was negative (β = -0.07, β = -0.01, respectively) but nonsignificant; and in Q4 (87-110 years) the relationship was positive (β = 0.31, p = .0002). This pattern did not differ by sex. We observed a similar age-related pattern between IGF-1 and BMI among participants in the third National Health and Nutritional Examination Survey.

CONCLUSIONS

Our results that the relationship between IGF-1 and BMI differs by age may explain some of the inconsistency in reports about their relationship and encourage additional studies to understand the mechanisms underlying it.

Genetics of physiological dysregulation: findings from the long life family study using joint models

Recently, Mahalanobis distance (D_M) was suggested as a statistical measure of physiological dysregulation in aging individuals. We constructed D_M 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 D_M and follow-up mortality in LLFS using joint models. We found that D_M 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 D_M 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 D_M constructed from biomarkers declining in late life. Review of biological effects of genes corresponding to top SNPs from GWAS of D_M 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.

Composite Measure of Physiological Dysregulation as a Predictor of Mortality: The Long Life Family Study

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 (D_M), 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 D_M 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 D_M was associated with significantly higher mortality risk (hazard ratio per standard deviation of D_M: 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.

"Physiological Dysregulation" as a Promising Measure of Robustness and Resilience in Studies of Aging and a New Indicator of Preclinical Disease

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.

Genetics of Human Longevity From Incomplete Data: New Findings From the Long Life Family Study

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.

How Well Does the Family Longevity Selection Score Work: A Validation Test Using the Utah Population Database

The Family Longevity Selection Score (FLoSS) was used to select families for the Long Life Family Study (LLFS) but has never been validated in other populations. The goal of this paper is to validate how well the FLoSS-based selection procedure works in an independent dataset. In this paper, we computed FLoSS using the lifespan data of 234,155 individuals from a large comprehensive genealogically-based resource, the Utah Population Database (UPDB), born between 1779 and 1910 with mortality follow-up through 2012-2013. Computations of FLoSS in a specific year (1980) confirmed the survival advantage of the "exceptional" sibships (defined by LLFS FLoSS threshold, FLoSS ≥ 7). We found that the subsample of the UPDB participants born after 1900 who were from the "exceptional" sibships had survival curves similar to that of the US participants from the LLFS probands' generation. Comparisons between the offspring of parents with "exceptional" and "ordinary" survival showed the survival advantage of the "exceptional" offspring. Investigators seeking to explain the extent genetics and environment contribute to exceptional survival will benefit from the use of exceptionally long-lived individuals and their relatives. Appropriate ranking of families by survival exceptionality and their availability for the purposes of providing genetic and phenotypic data is critical for selecting participants into such studies. This study validated the FLoSS as selection criteria in family longevity studies using UPDB.

Uncoupling associations of risk alleles with endophenotypes and phenotypes: insights from the ApoB locus and heart-related traits

Traditionally, genomewide association studies (GWAS) have emphasized the benefits of large samples in the analyses of age‐related traits rather than their specific properties. We adopted a realistic concept of genetic susceptibility to inherently heterogeneous, age‐related traits driven by the elusive role of evolution in their properties. We analyzed in detail the associations of rs693 and rs562338 polymorphisms representing the Apolipoprotein B locus with endophenotypes (total cholesterol [TC] and high‐density lipoprotein cholesterol) and phenotypes (myocardial infarction [MI] and survival) in four large‐scale studies, which include 20 748 individuals with 2357 MI events. We showed that a strong, robust predisposition of rs693 and rs562338 to TC (β = 0.72, P = 7.7 × 10⁻³⁰ for rs693 and β = −1.08, P = 9.8 × 10⁻⁴² for rs562338) is not translated into a predisposition to MI and survival. The rs693_A allele influences risks of MI and mortality after MI additively with lipids. This allele shows antagonistic effects—protecting against MI risks (β = −0.18, P = 1.1 × 10⁻⁵) or increasing MI risks (β = 0.15, P = 2.8 × 10⁻³) and mortality after MI, in different populations. Paradoxically, increased TC concentrations can be protective against MI for the rs693_A allele carriers. Our results uncouple the influences of the same alleles on endophenotypes and phenotypes despite potential causal relationships among the latter. Our strategy reveals virtually genomewide significance for the associations of rs693 with MI (P = 5.5 × 10⁻⁸) that is contrasted with a weak estimate following the traditional, sample‐size‐centered GWAS strategy (P = 0.16) in the same sample. These results caution against the use of the traditional GWAS strategy for gaining profound insights into genetic predisposition to healthspan and lifespan.

Pleiotropic Associations of Allelic Variants in a 2q22 Region with Risks of Major Human Diseases and Mortality

Gaining insights into genetic predisposition to age-related diseases and lifespan is a challenging task complicated by the elusive role of evolution in these phenotypes. To gain more insights, we combined methods of genome-wide and candidate-gene studies. Genome-wide scan in the Atherosclerosis Risk in Communities (ARIC) Study (N = 9,573) was used to pre-select promising loci. Candidate-gene methods were used to comprehensively analyze associations of novel uncommon variants in Caucasians (minor allele frequency~2.5%) located in band 2q22.3 with risks of coronary heart disease (CHD), heart failure (HF), stroke, diabetes, cancer, neurodegenerative diseases (ND), and mortality in the ARIC study, the Framingham Heart Study (N = 4,434), and the Health and Retirement Study (N = 9,676). We leveraged the analyses of pleiotropy, age-related heterogeneity, and causal inferences. Meta-analysis of the results from these comprehensive analyses shows that the minor allele increases risks of death by about 50% (p = 4.6×10⁻⁹), CHD by 35% (p = 8.9×10⁻⁶), HF by 55% (p = 9.7×10⁻⁵), stroke by 25% (p = 4.0×10⁻²), and ND by 100% (p = 1.3×10⁻³). This allele also significantly influences each of two diseases, diabetes and cancer, in antagonistic fashion in different populations. Combined significance of the pleiotropic effects was p = 6.6×10⁻²¹. Causal mediation analyses show that endophenotypes explained only small fractions of these effects. This locus harbors an evolutionary conserved gene-desert region with non-coding intergenic sequences likely involved in regulation of protein-coding flanking genes ZEB2 and ACVR2A. This region is intensively studied for mutations causing severe developmental/genetic disorders. Our analyses indicate a promising target region for interventions aimed to reduce risks of many major human diseases and mortality.

Biomedical research and medical care are traditionally focused on individual health conditions in order to postpone, ameliorate, or prevent the accumulation of morbidities in late life. An attractive idea is to find factors, which could reduce burden of not just one disease but a major subset of them to efficiently extend healthy lifespan. Here we focus on the analyses of genetic predisposition to risks of major human age-related diseases and mortality. The analyses highlight a locus in band 2q22.3 associated with risks of coronary heart disease, heart failure, stroke, diabetes, cancer, neurodegenerative diseases, and death. Our analyses indicate a promising target region for interventions aimed to reduce risks of many major human diseases and mortality.

Pleiotropic Meta-Analyses of Longitudinal Studies Discover Novel Genetic Variants Associated with Age-Related Diseases

Age-related diseases may result from shared biological mechanisms in intrinsic processes of aging. Genetic effects on age-related diseases are often modulated by environmental factors due to their little contribution to fitness or are mediated through certain endophenotypes. Identification of genetic variants with pleiotropic effects on both common complex diseases and endophenotypes may reveal potential conflicting evolutionary pressures and deliver new insights into shared genetic contribution to healthspan and lifespan. Here, we performed pleiotropic meta-analyses of genetic variants using five NIH-funded datasets by integrating univariate summary statistics for age-related diseases and endophenotypes. We investigated three groups of traits: (1) endophenotypes such as blood glucose, blood pressure, lipids, hematocrit, and body mass index, (2) time-to-event outcomes such as the age-at-onset of diabetes mellitus (DM), cancer, cardiovascular diseases (CVDs) and neurodegenerative diseases (NDs), and (3) both combined. In addition to replicating previous findings, we identify seven novel genome-wide significant loci (< 5e-08), out of which five are low-frequency variants. Specifically, from Group 2, we find rs7632505 on 3q21.1 in SEMA5B, rs460976 on 21q22.3 (1 kb from TMPRSS2) and rs12420422 on 11q24.1 predominantly associated with a variety of CVDs, rs4905014 in ITPK1 associated with stroke and heart failure, rs7081476 on 10p12.1 in ANKRD26 associated with multiple diseases including DM, CVDs, and NDs. From Group 3, we find rs8082812 on 18p11.22 and rs1869717 on 4q31.3 associated with both endophenotypes and CVDs. Our follow-up analyses show that rs7632505, rs4905014, and rs8082812 have age-dependent effects on coronary heart disease or stroke. Functional annotation suggests that most of these SNPs are within regulatory regions or DNase clusters and in linkage disequilibrium with expression quantitative trait loci, implying their potential regulatory influence on the expression of nearby genes. Our mediation analyses suggest that the effects of some SNPs are mediated by specific endophenotypes. In conclusion, these findings indicate that loci with pleiotropic effects on age-related disorders tend to be enriched in genes involved in underlying mechanisms potentially related to nervous, cardiovascular and immune system functions, stress resistance, inflammation, ion channels and hematopoiesis, supporting the hypothesis of shared pathological role of infection, and inflammation in chronic age-related diseases.

Protective role of the apolipoprotein E2 allele in age-related disease traits and survival: evidence from the Long Life Family Study

The apolipoprotein E (apoE) is a classic example of a gene exhibiting pleiotropism. We examine potential pleiotropic associations of the apoE2 allele in three biodemographic cohorts of long-living individuals, offspring, and spouses from the Long Life Family Study, and intermediate mechanisms, which can link this allele with age-related phenotypes. We focused on age-related macular degeneration, bronchitis, asthma, pneumonia, stroke, creatinine, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, diseases of heart (HD), cancer, and survival. Our analysis detected favorable associations of the ε2 allele with lower LDL-C levels, lower risks of HD, and better survival. The ε2 allele was associated with LDL-C in each gender and biodemographic cohort, including long-living individuals, offspring, and spouses, resulting in highly significant association in the entire sample (β = -7.1, p = 6.6 × 10^-44). This allele was significantly associated with HD in long-living individuals and offspring (relative risk [RR] = 0.60, p = 3.1 × 10^-6) but this association was not mediated by LDL-C. The protective effect on survival was specific for long-living women but it was not explained by LDL-C and HD in the adjusted model (RR = 0.70, p = 2.1 × 10^-2). These results show that ε2 allele may favorably influence LDL-C, HD, and survival through three mechanisms. Two of them (HD- and survival-related) are pronounced in the long-living parents and their offspring; the survival-related mechanism is also sensitive to gender. The LDL-C-related mechanism appears to be independent of these factors. Insights into mechanisms linking ε2 allele with age-related phenotypes given biodemographic structure of the population studied may benefit translation of genetic discoveries to health care and personalized medicine.

How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data

BACKGROUND AND OBJECTIVE

To clarify mechanisms of genetic regulation of human aging and longevity traits, a number of genome-wide association studies (GWAS) of these traits have been performed. However, the results of these analyses did not meet expectations of the researchers. Most detected genetic associations have not reached a genome-wide level of statistical significance, and suffered from the lack of replication in the studies of independent populations. The reasons for slow progress in this research area include low efficiency of statistical methods used in data analyses, genetic heterogeneity of aging and longevity related traits, possibility of pleiotropic (e.g., age dependent) effects of genetic variants on such traits, underestimation of the effects of (i) mortality selection in genetically heterogeneous cohorts, (ii) external factors and differences in genetic backgrounds of individuals in the populations under study, the weakness of conceptual biological framework that does not fully account for above mentioned factors. One more limitation of conducted studies is that they did not fully realize the potential of longitudinal data that allow for evaluating how genetic influences on life span are mediated by physiological variables and other biomarkers during the life course. The objective of this paper is to address these issues.

DATA AND METHODS

We performed GWAS of human life span using different subsets of data from the original Framingham Heart Study cohort corresponding to different quality control (QC) procedures and used one subset of selected genetic variants for further analyses. We used simulation study to show that approach to combining data improves the quality of GWAS. We used FHS longitudinal data to compare average age trajectories of physiological variables in carriers and non-carriers of selected genetic variants. We used stochastic process model of human mortality and aging to investigate genetic influence on hidden biomarkers of aging and on dynamic interaction between aging and longevity. We investigated properties of genes related to selected variants and their roles in signaling and metabolic pathways.

RESULTS

We showed that the use of different QC procedures results in different sets of genetic variants associated with life span. We selected 24 genetic variants negatively associated with life span. We showed that the joint analyses of genetic data at the time of bio-specimen collection and follow up data substantially improved significance of associations of selected 24 SNPs with life span. We also showed that aging related changes in physiological variables and in hidden biomarkers of aging differ for the groups of carriers and non-carriers of selected variants.

CONCLUSIONS

. The results of these analyses demonstrated benefits of using biodemographic models and methods in genetic association studies of these traits. Our findings showed that the absence of a large number of genetic variants with deleterious effects may make substantial contribution to exceptional longevity. These effects are dynamically mediated by a number of physiological variables and hidden biomarkers of aging. The results of these research demonstrated benefits of using integrative statistical models of mortality risks in genetic studies of human aging and longevity.

Dynamics of biomarkers in relation to aging and mortality

Contemporary longitudinal studies collect repeated measurements of biomarkers allowing one to analyze their dynamics in relation to mortality, morbidity, or other health-related outcomes. Rich and diverse data collected in such studies provide opportunities to investigate how various socio-economic, demographic, behavioral and other variables can interact with biological and genetic factors to produce differential rates of aging in individuals. In this paper, we review some recent publications investigating dynamics of biomarkers in relation to mortality, which use single biomarkers as well as cumulative measures combining information from multiple biomarkers. We also discuss the analytical approach, the stochastic process models, which conceptualizes several aging-related mechanisms in the structure of the model and allows evaluating "hidden" characteristics of aging-related changes indirectly from available longitudinal data on biomarkers and follow-up on mortality or onset of diseases taking into account other relevant factors (both genetic and non-genetic). We also discuss an extension of the approach, which considers ranges of "optimal values" of biomarkers rather than a single optimal value as in the original model. We discuss practical applications of the approach to single biomarkers and cumulative measures highlighting that the potential of applications to cumulative measures is still largely underused.

Optimal Versus Realized Trajectories of Physiological Dysregulation in Aging and Their Relation to Sex-Specific Mortality Risk

While longitudinal changes in biomarker levels and their impact on health have been characterized for individual markers, little is known about how overall marker profiles may change during aging and affect mortality risk. We implemented the recently developed measure of physiological dysregulation based on the statistical distance of biomarker profiles in the framework of the stochastic process model of aging, using data on blood pressure, heart rate, cholesterol, glucose, hematocrit, body mass index, and mortality in the Framingham original cohort. This allowed us to evaluate how physiological dysregulation is related to different aging-related characteristics such as decline in stress resistance and adaptive capacity (which typically are not observed in the data and thus can be analyzed only indirectly), and, ultimately, to estimate how such dynamic relationships increase mortality risk with age. We found that physiological dysregulation increases with age; that increased dysregulation is associated with increased mortality, and increasingly so with age; and that, in most but not all cases, there is a decreasing ability to return quickly to baseline physiological state with age. We also revealed substantial sex differences in these processes, with women becoming dysregulated more quickly but with men showing a much greater sensitivity to dysregulation in terms of mortality risk.

Trade-offs in the effects of the apolipoprotein E polymorphism on risks of diseases of the heart, cancer, and neurodegenerative disorders: insights on mechanisms from the Long Life Family Study

The lack of evolutionary established mechanisms linking genes to age-related traits makes the problem of genetic susceptibility to health span inherently complex. One complicating factor is genetic trade-off. Here we focused on long-living participants of the Long Life Family Study (LLFS), their offspring, and spouses to: (1) Elucidate whether trade-offs in the effect of the apolipoprotein E e4 allele documented in the Framingham Heart Study (FHS) are a more general phenomenon, and (2) explore potential mechanisms generating age- and gender-specific trade-offs in the effect of the e4 allele on cancer, diseases of the heart, and neurodegenerative disorders assessed retrospectively in the LLFS populations. The e4 allele can diminish risks of cancer and diseases of the heart and confer risks of diseases of the heart in a sex-, age-, and LLFS-population-specific manner. A protective effect against cancer is seen in older long-living men and, potentially, their sons (>75 years, relative risk [RR]>75=0.48, p=0.086), which resembles our findings in the FHS. The protective effect against diseases of the heart is limited to long-living older men (RR>76=0.50, p=0.016), as well. A detrimental effect against diseases of the heart is characteristic for a normal LLFS population of male spouses and is specific for myocardial infarction (RR=3.07, p=2.1×10(-3)). These trade-offs are likely associated with two inherently different mechanisms, including disease-specific (detrimental; characteristic for a normal male population) and systemic, aging-related (protective; characteristic for older long-living men) mechanisms. The e4 allele confers risks of neurological disorders in men and women (RR=1.98, p=0.046). The results highlight the complex role of the e4 allele in genetic susceptibility to health span.

Birth Cohort, Age, and Sex Strongly Modulate Effects of Lipid Risk Alleles Identified in Genome-Wide Association Studies

Insights into genetic origin of diseases and related traits could substantially impact strategies for improving human health. The results of genome-wide association studies (GWAS) are often positioned as discoveries of unconditional risk alleles of complex health traits. We re-analyzed the associations of single nucleotide polymorphisms (SNPs) associated with total cholesterol (TC) in a large-scale GWAS meta-analysis. We focused on three generations of genotyped participants of the Framingham Heart Study (FHS). We show that the effects of all ten directly-genotyped SNPs were clustered in different FHS generations and/or birth cohorts in a sex-specific or sex-unspecific manner. The sample size and procedure-therapeutic issues play, at most, a minor role in this clustering. An important result was clustering of significant associations with the strongest effects in the youngest, or 3rd Generation, cohort. These results imply that an assumption of unconditional connections of these SNPs with TC is generally implausible and that a demographic perspective can substantially improve GWAS efficiency. The analyses of genetic effects in age-matched samples suggest a role of environmental and age-related mechanisms in the associations of different SNPs with TC. Analysis of the literature supports systemic roles for genes for these SNPs beyond those related to lipid metabolism. Our analyses reveal strong antagonistic effects of rs2479409 (the PCSK9 gene) that cautions strategies aimed at targeting this gene in the next generation of lipid drugs. Our results suggest that standard GWAS strategies need to be advanced in order to appropriately address the problem of genetic susceptibility to complex traits that is imperative for translation to health care.

How the effects of aging and stresses of life are integrated in mortality rates: insights for genetic studies of human health and longevity

Increasing proportions of elderly individuals in developed countries combined with substantial increases in related medical expenditures make the improvement of the health of the elderly a high priority today. If the process of aging by individuals is a major cause of age related health declines then postponing aging could be an efficient strategy for improving the health of the elderly. Implementing this strategy requires a better understanding of genetic and non-genetic connections among aging, health, and longevity. We review progress and problems in research areas whose development may contribute to analyses of such connections. These include genetic studies of human aging and longevity, the heterogeneity of populations with respect to their susceptibility to disease and death, forces that shape age patterns of human mortality, secular trends in mortality decline, and integrative mortality modeling using longitudinal data. The dynamic involvement of genetic factors in (i) morbidity/mortality risks, (ii) responses to stresses of life, (iii) multi-morbidities of many elderly individuals, (iv) trade-offs for diseases, (v) genetic heterogeneity, and (vi) other relevant aging-related health declines, underscores the need for a comprehensive, integrated approach to analyze the genetic connections for all of the above aspects of aging-related changes. The dynamic relationships among aging, health, and longevity traits would be better understood if one linked several research fields within one conceptual framework that allowed for efficient analyses of available longitudinal data using the wealth of available knowledge about aging, health, and longevity already accumulated in the research field.

Genetics of aging, health, and survival: dynamic regulation of human longevity related traits

Background: The roles of genetic factors in human longevity would be better understood if one can use more efficient methods in genetic analyses and investigate pleiotropic effects of genetic variants on aging and health related traits.

Data and methods: We used EMMAX software with modified correction for population stratification to perform genome wide association studies (GWAS) of female lifespan from the original FHS cohort. The male data from the original FHS cohort and male and female data combined from the offspring FHS cohort were used to confirm findings. We evaluated pleiotropic effects of selected genetic variants as well as gene-smoking interactions on health and aging related traits. Then we reviewed current knowledge on functional properties of genes related to detected variants.

Results: The eight SNPs with genome-wide significant variants were negatively associated with lifespan in both males and females. After additional QC, two of these variants were selected for further analyses of their associations with major diseases (cancer and CHD) and physiological aging changes. Gene-smoking interactions contributed to these effects. Genes closest to detected variants appear to be involved in similar biological processes and health disorders, as those found in other studies of aging and longevity e.g., in cancer and neurodegeneration.

Conclusions: The impact of genes on longevity may involve trade-off-like effects on different health traits. Genes that influence lifespan represent various molecular functions but may be involved in similar biological processes and health disorders, which could contribute to genetic heterogeneity of longevity and the lack of replication in genetic association studies.

Biodemographic Analyses of Longitudinal Data on Aging, Health, and Longevity: Recent Advances and Future Perspectives

Biodemography became one of the most innovative and fastest growing areas in demography. This progress is fueled by the growing variability and amount of relevant data available for analyses as well as by methodological developments allowing for addressing new research questions using new approaches that can better utilize the potential of these data. In this review paper, we summarize recent methodological advances in biodemography and their diverse practical applications. Three major topics are covered: (1) computational approaches to reconstruction of age patterns of incidence of geriatric diseases and other characteristics such as recovery rates at the population level using Medicare claims data; (2) methodological advances in genetic and genomic biodemography and applications to research on genetic determinants of longevity and health; and (3) biodemographic models for joint analyses of time-to-event data and longitudinal measurements of biomarkers collected in longitudinal studies on aging. We discuss how such data and methodology can be used in a comprehensive prediction model for joint analyses of incomplete datasets that take into account the wide spectrum of factors affecting health and mortality transitions including genetic factors and hidden mechanisms of aging-related changes in physiological variables in their dynamic connection with health and survival.

Joint Analyses of Longitudinal and Time-to-Event Data in Research on Aging: Implications for Predicting Health and Survival

Longitudinal data on aging, health, and longevity provide a wealth of information to investigate different aspects of the processes of aging and development of diseases leading to death. Statistical methods aimed at analyses of time-to-event data jointly with longitudinal measurements became known as the "joint models" (JM). An important point to consider in analyses of such data in the context of studies on aging, health, and longevity is how to incorporate knowledge and theories about mechanisms and regularities of aging-related changes that accumulate in the research field into respective analytic approaches. In the absence of specific observations of longitudinal dynamics of relevant biomarkers manifesting such mechanisms and regularities, traditional approaches have a rather limited utility to estimate respective parameters that can be meaningfully interpreted from the biological point of view. A conceptual analytic framework for these purposes, the stochastic process model of aging (SPM), has been recently developed in the biodemographic literature. It incorporates available knowledge about mechanisms of aging-related changes, which may be hidden in the individual longitudinal trajectories of physiological variables and this allows for analyzing their indirect impact on risks of diseases and death. Despite, essentially, serving similar purposes, JM and SPM developed in parallel in different disciplines with very limited cross-referencing. Although there were several publications separately reviewing these two approaches, there were no publications presenting both these approaches in some detail. Here, we overview both approaches jointly and provide some new modifications of SPM. We discuss the use of stochastic processes to capture biological variation and heterogeneity in longitudinal patterns and important and promising (but still largely underused) applications of JM and SPM to predictions of individual and population mortality and health-related outcomes.

Age, gender, and cancer but not neurodegenerative and cardiovascular diseases strongly modulate systemic effect of the Apolipoprotein E4 allele on lifespan

Enduring interest in the Apolipoprotein E (ApoE) polymorphism is ensured by its evolutionary-driven uniqueness in humans and its prominent role in geriatrics and gerontology. We use large samples of longitudinally followed populations from the Framingham Heart Study (FHS) original and offspring cohorts and the Long Life Family Study (LLFS) to investigate gender-specific effects of the ApoE4 allele on human survival in a wide range of ages from midlife to extreme old ages, and the sensitivity of these effects to cardiovascular disease (CVD), cancer, and neurodegenerative disorders (ND). The analyses show that women's lifespan is more sensitive to the e4 allele than men's in all these populations. A highly significant adverse effect of the e4 allele is limited to women with moderate lifespan of about 70 to 95 years in two FHS cohorts and the LLFS with relative risk of death RR = 1.48 (p = 3.6×10⁻⁶) in the FHS cohorts. Major human diseases including CVD, ND, and cancer, whose risks can be sensitive to the e4 allele, do not mediate the association of this allele with lifespan in large FHS samples. Non-skin cancer non-additively increases mortality of the FHS women with moderate lifespans increasing the risks of death of the e4 carriers with cancer two-fold compared to the non-e4 carriers, i.e., RR = 2.07 (p = 5.0×10⁻⁷). The results suggest a pivotal role of non-sex-specific cancer as a nonlinear modulator of survival in this sample that increases the risk of death of the ApoE4 carriers by 150% (p = 5.3×10⁻⁸) compared to the non-carriers. This risk explains the 4.2 year shorter life expectancy of the e4 carriers compared to the non-carriers in this sample. The analyses suggest the existence of age- and gender-sensitive systemic mechanisms linking the e4 allele to lifespan which can non-additively interfere with cancer-related mechanisms.

Discovering genetic origins of healthspan and lifespan could lead to breakthroughs in increasing the years of healthy and long life. In this paper we characterize the association of the e4 allele of the well-studied ApoE gene with lifespan in two generations of participants of large longitudinal studies, the Framingham Heart Study and the Long Life Family Study, and investigate the role of major human diseases such as cardiovascular disease, cancer, and neurodegenerative disorders in this association. This wide range of systemic analyses is possible given the large sample with directly genotyped ApoE polymorphism available from these studies (N = 9841, with 2557 deaths). The analyses show that women's lifespan is more sensitive to the e4 allele than men's in these populations. However, the strongly adverse effect of the e4 allele is not observed for all women, but only for those 70 to 95 years old. Cardiovascular disease, cancer, and neurodegenerative disorders do not mediate the association of the e4 allele with lifespan. However, cancer, but not cardiovascular and neurodegenerative diseases, non-additively enhances this effect resulting in 4.2 years of difference in mean lifespan for the e4 allele carriers compared to the non-carriers.

Genetic Structures of Population Cohorts Change with Increasing Age: Implications for Genetic Analyses of Human aging and Life Span

BACKGROUND

Correcting for the potential effects of population stratification is an important issue in genome wide association studies (GWAS) of complex traits. Principal component analysis (PCA) of the genetic structure of the population under study with subsequent incorporation of the first several principal components (PCs) in the GWAS regression model is often used for this purpose.

PROBLEM

For longevity related traits such a correction may negatively affect the accuracy of genetic analyses. This is because PCs may capture genetic structure induced by mortality selection processes in genetically heterogeneous populations.

DATA AND METHODS

We used the Framingham Heart Study data on life span and on individual genetic background to construct two sets of PCs. One was constructed to separate population stratification due to differences in ancestry from that induced by mortality selection. The other was constructed using genetic data on individuals of different ages without attempting to separate the ancestry effects from the mortality selection effects. The GWASs of human life span were performed using the first 20 PCs from each of the selected sets to control for possible population stratification.

RESULTS

The results indicated that the GWAS that used the PC set separating population stratification induced by mortality selection from differences in ancestry produced stronger genetic signals than the GWAS that used PCs without such separation.

CONCLUSION

The quality of genetic estimates in GWAS can be improved when changes in genetic structure caused by mortality selection are taken into account in controlling for possible effects of population stratification.

Trade-off in the effect of the APOE gene on the ages at onset of cardiocascular disease and cancer across ages, gender, and human generations

Decades of studies of candidate genes show their complex role in aging-related traits. We focus on apolipoprotein E e2/3/4 polymorphism and ages at onset of cardiovascular diseases (CVD) and cancer in the parental and offspring generations of the Framingham Heart Study participants to gain insights on the role of age and gender across generations in genetic trade-offs. The analyses show that the apolipoprotein E e4 allele carriers live longer lives without cancer than the non-e4 allele carriers in each generation. The role of the e4 allele in onset of CVD is age- and generation-specific, constituting two modes of sexually dimorphic genetic trade-offs. In offspring, the e4 allele confers risk of CVD primarily in women and can protect against cancer primarily in men of the same age. In the parental generation, genetic trade-off is seen in different age groups, with a protective role of the e4 allele against cancer in older men and its detrimental role in CVD in younger women. The puzzling complexity of genetic mechanisms working in different genders, ages, and environments calls for more detail and systemic analyses beyond those adapted in current large-scale genetic association studies.

The role of lipid-related genes, aging-related processes, and environment in healthspan

The inherent complexity of aging-related traits can temper progress in unraveling the genetic origins of healthspan. We focus on two generations in the Framingham Heart Study, the original (FHS) and offspring (FHSO) cohorts, to determine whether aging-related processes in changing environments can substantially impact the role of lipid-related genes discovered in candidate gene (the apolipoprotein E (APOE) e2/3/4 polymorphism) and genome-wide (the APOB rs1042034 (C/T)) studies, in regulation of total cholesterol (TC) and onset of cardiovascular disease (CVD). We demonstrate that the APOE e4 allele and APOB CC genotype can play detrimental, neutral, and protective sex-specific roles in the etiology of CVD at different ages and in different environments. We document antagonistic roles for the e4 allele in the onset of CVD characterized by detrimental effects at younger ages (RR≤ 75 years = 1.49, P = 7.5 × 10(-4) ) and protective effects at older ages (RR76+years = 0.77, P = 0.044) for FHS participants. We found that disregarding the role of aging erroneously nullifies the significant effects of the e4 allele in this sample (RR = 0.92, P = 0.387). The leading biogenetic pathways mediating genetic effects on CVD may be more relevant to lipid metabolism for APOB than APOE. Aging-related processes can modulate the strength of genetic associations with TC in the same individuals at different chronological ages. We found substantial differences in the effects of the same APOE and APOB alleles on CVD and TC across generations. The results suggest that aging-related processes in changing environments may play key roles in the genetics of healthspan. Detailed systemic integrative analyses may substantially advance the progress.

How lifespan associated genes modulate aging changes: lessons from analysis of longitudinal data

BACKGROUND AND OBJECTIVE

The influence of genes on human lifespan is mediated by biological processes that characterize body's functioning. The age trajectories of these processes contain important information about mechanisms linking aging, health, and lifespan. The objective of this paper is to investigate regularities of aging changes in different groups of individuals, including individuals with different genetic background, as well as their connections with health and lifespan.

DATA AND METHOD

To reach this objective we used longitudinal data on four physiological variables, information about health and lifespan collected in the Framingham Heart Study (FHS), data on longevity alleles detected in earlier study, as well as methods of statistical modeling.

RESULTS

We found that phenotypes of exceptional longevity and health are linked to distinct types of changes in physiological indices during aging. We also found that components of aging changes differ in groups of individuals with different genetic background.

CONCLUSIONS

These results suggest that factors responsible for exceptional longevity and health are not necessary the same, and that postponing aging changes is associated with extreme longevity. The genetic factors which increase lifespan are associated with physiological changes typical of healthy and long-living individuals, smaller mortality risks from cancer and CVD and better estimates of adaptive capacity in statistical modeling. This indicates that extreme longevity and health related traits are likely to be less heterogeneous phenotypes than lifespan, and studying these phenotypes separately from lifespan may provide additional information about mechanisms of human aging and its relation to chronic diseases and lifespan.

How genes influence life span: the biodemography of human survival

BACKGROUND

In genome-wide association studies (GWAS) of human life span, none of the genetic variants has reached the level of genome-wide statistical significance. The roles of such variants in life span regulation remain unclear.

DATA AND METHOD

A biodemographic analyses was done of genetic regulation of life span using data on low-significance longevity alleles selected in the earlier GWAS of the original Framingham cohort.

RESULTS

Age-specific survival curves considered as functions of the number of longevity alleles exhibit regularities known in demography as "rectangularization" of survival curves. The presence of such pattern confirms observations from experimental studies that regulation of life span involves genes responsible for stress resistance.

CONCLUSION

Biodemographic analyses could provide important information about the properties of genes affecting phenotypic traits.

The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span

A better understanding of processes and mechanisms linking human aging with changes in health status and survival requires methods capable of analyzing new data that take into account knowledge about these processes accumulated in the field. In this paper, we describe an approach to analyses of longitudinal data based on the use of stochastic process models of human aging, health, and longevity which allows for incorporating state of the art advances in aging research into the model structure. In particular, the model incorporates the notions of resistance to stresses, adaptive capacity, and "optimal" (normal) physiological states. To capture the effects of exposure to persistent external disturbances, the notions of allostatic adaptation and allostatic load are introduced. These notions facilitate the description and explanation of deviations of individuals' physiological indices from their normal states, which increase the chances of disease development and death. The model provides a convenient conceptual framework for comprehensive systemic analyses of aging-related changes in humans using longitudinal data and linking these changes with genotyping profiles, morbidity, and mortality risks. The model is used for developing new statistical methods for analyzing longitudinal data on aging, health, and longevity.

Polygenic effects of common single-nucleotide polymorphisms on life span: when association meets causality

Recently we have shown that the human life span is influenced jointly by many common single-nucleotide polymorphisms (SNPs), each with a small individual effect. Here we investigate further the polygenic influence on life span and discuss its possible biological mechanisms. First we identified six sets of prolongevity SNP alleles in the Framingham Heart Study 550K SNPs data, using six different statistical procedures (normal linear, Cox, and logistic regressions; generalized estimation equation; mixed model; gene frequency method). We then estimated joint effects of these SNPs on human survival. We found that alleles in each set show significant additive influence on life span. Twenty-seven SNPs comprised the overlapping set of SNPs that influenced life span, regardless of the statistical procedure. The majority of these SNPs (74%) were within genes, compared to 40% of SNPs in the original 550K set. We then performed a review of current literature on functions of genes closest to these 27 SNPs. The review showed that the respective genes are largely involved in aging, cancer, and brain disorders. We concluded that polygenic effects can explain a substantial portion of genetic influence on life span. Composition of the set of prolongevity alleles depends on the statistical procedure used for the allele selection. At the same time, there is a core set of longevity alleles that are selected with all statistical procedures. Functional relevance of respective genes to aging and major diseases supports causal relationships between the identified SNPs and life span. The fact that genes found in our and other genetic association studies of aging/longevity have similar functions indicates high chances of true positive associations for corresponding genetic variants.

Effect of the APOE Polymorphism and Age Trajectories of Physiological Variables on Mortality: Application of Genetic Stochastic Process Model of Aging

We evaluated effects of the APOE polymorphism (carriers versus noncarriers of the e4 allele) and age trajectories of total cholesterol (CH) and diastolic blood pressure (DBP) on mortality risk in the Framingham Heart Study (original cohort). We found that long-lived carriers and noncarriers have different average age trajectories and long-lived individuals have consistently higher levels and less steep declines at old ages compared to short-lived individuals. We applied the stochastic process model of aging aimed at joint analyses of genetic and nongenetic subsamples of longitudinal data and estimated different aging-related characteristics for carriers and noncarriers which otherwise cannot be evaluated from data. We found that such characteristics differ in carriers and noncarriers: (1) carriers have better adaptive capacity than noncarriers in case of CH, whereas for DBP the opposite situation is observed; (2) mean allostatic trajectories are higher in carriers and they differ from “optimal” trajectories minimizing mortality risk; (3) noncarriers have lower baseline mortality rates at younger ages but they increase faster than those for carriers resulting in intersection at the oldest ages. Such observations strongly indicate the presence of a genetic component in respective aging-related mechanisms. Such differences may contribute to patterns of allele- and sex-specific mortality rates.

Trade-off in the effects of the apolipoprotein E polymorphism on the ages at onset of CVD and cancer influences human lifespan

Progress in unraveling the genetic origins of healthy aging is tempered, in part, by a lack of replication of effects, which is often considered a signature of false-positive findings. We convincingly demonstrate that the lack of genetic effects on an aging-related trait can be because of trade-offs in the gene action. We focus on the well-studied apolipoprotein E (APOE) e2/3/4 polymorphism and on lifespan and ages at onset of cardiovascular diseases (CVD) and cancer, using data on 3924 participants of the Framingham Heart Study Offspring cohort. Kaplan-Meier estimates show that the e4 allele carriers live shorter lives than the non-e4 allele carriers (log rank = 0.016). The adverse effect was attributed to the poor survival of the e4 homozygotes, whereas the effect of the common e3/4 genotype was insignificant. The e3/4 genotype, however, was antagonistically associated with onsets of those diseases predisposing to an earlier onset of CVD and a later onset of cancer compared to the non-e4 allele genotypes. This trade-off explains the lack of a significant effect of the e3/4 genotype on survival; adjustment for it in the Cox regression model makes the detrimental effect of the e4 allele highly significant (P = 0.002). This trade-off is likely caused by the lipid-metabolism-related (for CVD) and nonrelated (for cancer) mechanisms. An evolutionary rationale suggests that genetic trade-offs should not be an exception in studies of aging-related traits. Deeper insights into biological mechanisms mediating gene action are critical for understanding the genetic regulation of a healthy lifespan and for personalizing medical care.

Modeling hematopoietic system response caused by chronic exposure to ionizing radiation

A new model of the hematopoietic system response in humans chronically exposed to ionizing radiation describes the dynamics of the hematopoietic stem cell compartment as well as the dynamics of each of the four blood cell types (lymphocytes, neutrophiles, erythrocytes, and platelets). The required model parameters were estimated based on available results of human and experimental animal studies. They include the steady-state number of hematopoietic stem cells and peripheral blood cell lines in an unexposed organism, amplification parameters for each blood line, parameters describing proliferation and apoptosis, parameters of feedback functions regulating the steady-state numbers, and characteristics of radiosensitivity related to cell death and non-lethal cell damage. The model predictions were tested using data on hematological measurements (e.g., blood counts) performed in 1950-1956 in the Techa River residents chronically exposed to ionizing radiation since 1949. The suggested model of hematopoiesis is capable of describing experimental findings in the Techa River Cohort, including: (1) slopes of the dose-effect curves reflecting the inhibition of hematopoiesis due to chronic ionizing radiation, (2) delay in effect of chronic exposure and accumulated character of the effect, and (3) dose-rate patterns for different cytopenic states (e.g., leukopenia, thrombocytopenia).

Trade-offs between cancer and other diseases: do they exist and influence longevity?

Relationships between aging, disease risks, and longevity are not yet well understood. For example, joint increases in cancer risk and total survival observed in many human populations and some experimental aging studies may be linked to a trade-off between cancer and aging as well as to the trade-off(s) between cancer and other diseases, and their relative impact is not clear. While the former trade-off (between cancer and aging) received broad attention in aging research, the latter one lacks respective studies, although its understanding is important for developing optimal strategies of increasing both longevity and healthy life span. In this paper, we explore the possibility of trade-offs between risks of cancer and selected major disorders. First, we review current literature suggesting that the trade-offs between cancer and other diseases may exist and be linked to the differential intensity of apoptosis. Then we select relevant disorders for the analysis (acute coronary heart disease [ACHD], stroke, asthma, and Alzheimer disease [AD]) and calculate the risk of cancer among individuals with each of these disorders, and vice versa, using the Framingham Study (5209 individuals) and the National Long Term Care Survey (NLTCS) (38,214 individuals) data. We found a reduction in cancer risk among old (80+) men with stroke and in risk of ACHD among men (50+) with cancer in the Framingham Study. We also found an increase in ACHD and stroke among individuals with cancer, and a reduction in cancer risk among women with AD in the NLTCS. The manifestation of trade-offs between risks of cancer and other diseases thus depended on sex, age, and study population. We discuss factors modulating the potential trade-offs between major disorders in populations, e.g., disease treatments. Further study is needed to clarify possible impact of such trade-offs on longevity.

Early hematopoietic effects of chronic radiation exposure in humans

The major goal of this study is to investigate and quantitatively describe the nature of the relationship between the characteristics of chronic exposure to ionizing radiation and specific patterns of hematopoiesis reduction. The study is based on about 3,200 hemograms taken for inhabitants of the Techa riverside villages over the years 1951-1956, i.e., the period characterized by a gradual decrease in dose rates. The mean cumulative red bone marrow dose was 333.6 + or - 4.6 mGy. The approach to statistical analyses involved both empirical methods and modeling (generalized linear models and logistic regressions). The results of the analyses highlighted a gradual increase in the frequency of cytopenias with dose rate. The impact of exposure on hematopoiesis reduction patterns was found to be more substantial than that of age and health status. Dose rates resulting in a two-fold increase in the frequency of cytopenias have been estimated.

Modeling deterministic effects in hematopoietic system caused by chronic exposure to ionizing radiation in large human cohorts

A new model of the hematopoietic system for humans chronically exposed to ionizing radiation allows for quantitative description of the initial hematopoiesis inhibition and subsequent increase in the risks of late stochastic effects such as leukemia. This model describes the dynamics of the hematopoietic stem cell compartment as well as the dynamics of each of the three blood cell types (leukocytes, erythrocytes, and platelets). The model parameters are estimated from the results of other experiments. They include the steady-state numbers of hematopoietic stem cells and peripheral blood cell lines for an unexposed organism, amplification parameters for each blood cell line, parameters describing the proliferation and apoptosis, parameters of feedback functions regulating the steady-state numbers, and characteristics of radiosensitivity in respect to cell death and non-lethal cell damages. The dynamic model of hematopoiesis is applied to the data on a subcohort of the Techa River residents with hematological measurements (e.g., blood counts) performed in 1950-1956 (which totals to about 3,500 exposed individuals). Among well-described effects observed in these data are the slope values of the dose-effect curves describing the hematopoietic inhibition and the dose rate patterns of the fractions of cytopenic states (e.g., leukopenia, thrombocytopenia). The model has been further generalized by inclusion of the component describing the risk of late stochastic effects. The risks of the development of late effects (such as leukemia) in population groups with specific patterns of early reactions in hematopoiesis (such as leukopenia induced by ionizing radiation) are investigated using simulation studies and compared to data.

Leukocyte telomere length is associated with disability in older u.s. Population

OBJECTIVES

To determine whether mean leukocyte telomere length (LTL) serves as a biomarker of disability assessed according to activities of daily living (ADLs) and what factors may modify this relationship.

DESIGN

Retrospective cross-sectional study.

SETTING

A subset of the National Long Term Care Survey (NTLCS), a Medicare-based U.S. population longitudinal study focused on trends of overall health and functional status in older adults.

PARTICIPANTS

Six hundred and twenty-four individuals from the 1999 wave of the NTLCS cohort.

MEASUREMENTS

Relative LTL determined according to quantitative polymerase chain reaction. LTL has previously been shown to correlate with common age-related disorders and mortality, as well as with socioeconomic status.

RESULTS

A sex difference in LTL was observed but not age-dependent shortening or association with socioeconomic status. LTL was associated with disability and functional status assessed according to ADLs. The association between ADLs and LTL was stronger in subjects without diabetes mellitus, whereas associations were not seen when only subjects with diabetes mellitus were analyzed. Associations between LTL and cardiovascular disease (CVD) and cancer were also present in the group without diabetes mellitus but not in the group with diabetes mellitus.

CONCLUSION

These findings support the concept that LTL is a biomarker of overall well-being that is predictive of disability of older individuals in the U.S. population. Diabetes mellitus plays an important role as a modifier of the association between LTL and disability, CVD, and cancer. These associations have clinical implications because of the potential predictive value of LTL and deserve further investigation.

Polymorphisms in the ACE and ADRB2 genes and risks of aging-associated phenotypes: the case of myocardial infarction

Multiple functions of the beta2-adrenergic receptor (ADRB2) and angiotensin-converting enzyme (ACE) genes warrant studies of their associations with aging-related phenotypes. We focus on multimarker analyses and analyses of the effects of compound genotypes of two polymorphisms in the ADRB2 gene, rs1042713 and rs1042714, and 11 polymorphisms of the ACE gene, on the risk of such an aging-associated phenotype as myocardial infarction (MI). We used the data from a genotyped sample of the Framingham Heart Study Offspring (FHSO) cohort (n = 1500) followed for about 36 years with six examinations. The ADRB2 rs1042714 (C-->G) polymorphism and two moderately correlated (r(2) = 0.77) ACE polymorphisms, rs4363 (A-->G) and rs12449782 (A-->G), were significantly associated with risks of MI in this aging cohort in multimarker models. Predominantly linked ACE genotypes exhibited opposite effects on MI risks, e.g., the AA (rs12449782) genotype had a detrimental effect, whereas the predominantly linked AA (rs4363) genotype exhibited a protective effect. This trade-off occurs as a result of the opposite effects of rare compound genotypes of the ACE polymorphisms with a single dose of the AG heterozygote. This genetic trade-off is further augmented by the selective modulating effect of the rs1042714 ADRB2 polymorphism. The associations were not altered by adjustment for common MI risk factors. The results suggest that effects of single specific genetic variants of the ADRB2 and ACE genes on MI can be readily altered by gene-gene or/and gene-environmental interactions, especially in large heterogeneous samples. Multimarker genetic analyses should benefit studies of complex aging-associated phenotypes.

Early hematopoiesis inhibition under chronic radiation exposure in humans

The major goal of this study was to identify and quantitatively describe the association between the characteristics of chronic (low-dose rate) exposure to (low LET) ionizing radiation and cellularity of peripheral blood cell lines. About 3,200 hemograms (i.e., spectra of blood counts) obtained over the years of maximal exposure to ionizing radiation (1950-1956) for inhabitants of the Techa River were used in analyses. The mean cumulative red bone marrow dose (with standard errors), calculated using Techa River Dosimetry System-2000, was 333.6 +/- 4.6 mGy (SD = 259.9 mGy, max = 1151 mGy) to the year 1956. The statistical approach included both empirical methods for estimating frequencies of cytopenic states of the investigated blood cell lines (e.g. neutrophile, platelets, erythrocyte, etc.), and regression methods, including generalized linear models and logistic regressions which allowed taking into account confounding factors (e.g., attained age, age at maximal exposure, presence of concomitant diseases, and demographic characteristics). The results of the analyses demonstrated hematopoiesis inhibition manifested by a decrease in peripheral blood cellularity and an increase in the frequency of cytopenia in all blood cell lines (leukocytes, including lymphocytes, monocytes, neutrophiles, as well as platelets and erythrocytes). The intensity of hematopoiesis inhibition in the period of maximal exposures is determined by the combined influence of the dose rate and cumulative dose. The contribution of specific confounding factors was quantified and shown to be much less important than dose characteristics. The best predictor among dose characteristics was identified for each blood cell line. A 2-fold increase in dose rate is assumed to be a characteristic of radiosensitivity and a quantitative characteristic of the effect.

Beta2-adrenergic receptor gene polymorphisms as systemic determinants of healthy aging in an evolutionary context

The Gln(27)Glu polymorphism but not the Arg(16)Gly polymorphism of the beta2-adrenergic receptor (ADRB2) gene appears to be associated with a broad range of aging-associated phenotypes, including cancers at different sites, myocardial infarction (MI), intermittent claudication (IC), and overall/healthy longevity in the Framingham Heart Study Offspring cohort. The Gln(27)Gln genotype increases risks of cancer, MI and IC, whereas the Glu(27) allele or, equivalently, the Gly(16)Glu(27) haplotype tends to be protective against these diseases. Genetic associations with longevity are of opposite nature at young-old and oldest-old ages highlighting the phenomenon of antagonistic pleiotropy. The mechanism of antagonistic pleiotropy is associated with an evolutionary-driven advantage of carriers of a derived Gln(27) allele at younger ages and their survival disadvantage at older ages as a result of increased risks of cancer, MI and IC. The ADRB2 gene can play an important systemic role in healthy aging in evolutionary context that warrants exploration in other populations.

Date of eclosion modulates longevity: insights across dietary-restriction gradients and female reproduction in the mexfly Anastrepha ludens

We use unique experimental data on daily reproduction and survival of individual fruit flies from eight cohorts eclosed at different dates in 2004 and 2005 who were treated with varying proportions of sugar and yeast and subject to different caloric restrictions (CR). We investigate the relationship between eclosion date and longevity across diets and reproduction in Anastrepha ludens. We show that eclosion date can be associated with uncontrolled external or internal factor(s) which can modulate longevity of males and females independently of diet and reproduction to the extent similar to the effect of diet on longevity. The effect of diet manipulation on longevity is sensitive to date of eclosion with the role of CR in life extension ranging from beneficial to harmful. Interaction of date of eclosion with compositional changes of sugar and yeast but not with CR is responsible for life extension. Highly protein-enriched diets reliably maximize reproduction but not life span. Decreased longevity of flies treated with high-protein diets may be associated with harmful consequences of protein ingestion but is unlikely a result of high reproduction rates. We present evidence for the presence of two frailty-sensitive weakly interacting mechanisms of longevity in female flies associated with differences in predisposed fitness.

Exceptional survivors have lower age trajectories of blood glucose: lessons from longitudinal data

Exceptional survival results from complicated interplay between genetic and environmental factors. The effects of these factors on survival are mediated by the biological and physiological variables, which affect mortality risk. In this paper, we evaluated the role of blood glucose (BG) in exceptional survival using the Framingham heart study data for the main (FHS) and offspring (FHSO) cohorts. We found that: (1) the average cross-sectional age patterns of BG change over time; (2) the values of BG level among the longest lived individuals in this study differ for different sub-cohorts; (3) the longitudinal age patterns of BG differ from those of cross-sectional ones. We investigated mechanisms forming average age trajectories of BG in the FHS cohort. We found that the two curves: one, characterizing the average effects of allostatic adaptation, and another, minimizing mortality risk for any given age, play the central role in this process. We found that the average BG age trajectories for exceptional survivors are closer to the curve minimizing mortality risk than those of individuals having shorter life spans. We concluded that individuals whose age trajectories of BG are located around the curve minimizing chances of premature death at each given age have highest chances of reaching exceptional longevity.

Maintaining physiological state for exceptional survival: What is the normal level of blood glucose and does it change with age?

The levels of blood glucose (BG) in humans tend to increase with age deviating from the norm specified for the young adults. Such elevation is often considered as a factor contributing to an increase in risks of disease and death. The proper use of intervention strategies coping with or preventing consequences of BG elevation requires understanding the roles of external forces and intrinsic senescence in this process. To address these issues, we performed analyses of longitudinal data on BG collected in the Framingham Heart Study using methods of descriptive statistics and statistical modeling. The approach allows us to separate effects of persistent external disturbances from "normal" aging-related changes due to the senescence process. We found that the BG level corresponding to the lowest mortality risk tends to increase with age. The changes in the shape of the mortality risk with age indicate the aging-related decline in resistance to stresses affecting the BG level. The results show that analyzing longitudinal data using advanced methods may substantially increase our knowledge on factors and mechanisms responsible for aging-related changes in humans.

Health-related phenotypes and longevity in danish twins

Aging studies can be facilitated by refocusing from longevity phenotypes to their proxies (intermediate phenotypes). Robust selection of the intermediate phenotypes requires data on such phenotypes and life span measured in the same individuals, which is not always the case in aging studies. A promising approach is to select intermediate phenotypes using information on longevity measured in related individuals. We evaluated feasibility of this approach focusing on 32 geriatric diseases as potential intermediate phenotypes of longevity assessed in the Longitudinal Study of Aging Danish Twins. Our analyses reveal that geriatric diseases measured in some family members can predict life span in the other family members both individually and cumulatively ensuring that this approach for selection of intermediate phenotypes is feasible. The cumulative-trait approach is more promising for such studies compared with the individual-trait approach. Heritable health dimensions contributing to a decrease of life span have sex-insensitive and sex-specific components.

Genetic model for longitudinal studies of aging, health, and longevity and its potential application to incomplete data

Many longitudinal studies of aging collect genetic information only for a sub-sample of participants of the study. These data also do not include recent findings, new ideas and methodological concepts developed by distinct groups of researchers. The formal statistical analyses of genetic data ignore this additional information and therefore cannot utilize the entire research potential of the data. In this paper, we present a stochastic model for studying such longitudinal data in joint analyses of genetic and non-genetic sub-samples. The model incorporates several major concepts of aging known to date and usually studied independently. These include age-specific physiological norms, allostasis and allostatic load, stochasticity, and decline in stress resistance and adaptive capacity with age. The approach allows for studying all these concepts in their mutual connection, even if respective mechanisms are not directly measured in data (which is typical for longitudinal data available to date). The model takes into account dependence of longitudinal indices and hazard rates on genetic markers and permits evaluation of all these characteristics for carriers of different alleles (genotypes) to address questions concerning genetic influence on aging-related characteristics. The method is based on extracting genetic information from the entire sample of longitudinal data consisting of genetic and non-genetic sub-samples. Thus it results in a substantial increase in the accuracy of statistical estimates of genetic parameters compared to methods that use only information from a genetic sub-sample. Such an increase is achieved without collecting additional genetic data. Simulation studies illustrate the increase in the accuracy in different scenarios for datasets structurally similar to the Framingham Heart Study. Possible applications of the model and its further generalizations are discussed.

Cumulative deficits and physiological indices as predictors of mortality and long life

We evaluated the predictive potential for long-term (24-year) survival and longevity (85+ years) of an index of cumulative deficits (DI) and six physiological indices (pulse pressure, diastolic blood pressure, pulse rate, serum cholesterol, blood glucose, and hematocrit) measured in mid- to late life (44-88 years) for participants of the 9th and 14th Framingham Heart Study examinations. For all ages combined, the DI, pulse pressure, and blood glucose are the strongest determinants of both long-term survival and longevity, contributing cumulatively to their explanation. Diastolic blood pressure and hematocrit are less significant determinants of both of these outcomes. The pulse rate is more relevant to survival, whereas serum cholesterol is more relevant to longevity. Only the DI is a significant predictor of longevity and mortality for each 5-year age group ranging from 45 to 85 years. The DI appears to be a more important determinant of long-term risks of death and longevity than are the physiological indices.