Liubov S. Arbeeva

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.

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.

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 bodys 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.

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.

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.

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.

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 womens lifespan is more sensitive to the e4 allele than mens 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.

Dynamic Determinants of Longevity and Exceptional Health

It is well known from epidemiology that values of indices describing physiological state in a given age may influence human morbidity and mortality risks. Studies of connection between aging and life span suggest a possibility that dynamic properties of age trajectories of the physiological indices could also be important contributors to morbidity and mortality risks. In this paper we use data on longitudinal changes in body mass index, diastolic blood pressure, pulse pressure, pulse rate, blood glucose, hematocrit, and serum cholesterol in the Framingham Heart Study participants, to investigate this possibility in depth. We found that some of the variables describing individual dynamics of the age-associated changes in physiological indices influence human longevity and exceptional health more substantially than the variables describing physiological state. These newly identified variables are promising targets for prevention aiming to postpone onsets of common elderly diseases and increase longevity.

Evaluation of genotype-specific survival using joint analysis of genetic and non-genetic subsamples of longitudinal data

Small sample size of genetic data is often a limiting factor for desirable accuracy of estimated genetic effects on age-specific risks and survival. Longitudinal non-genetic data containing information on survival or disease onsets of study participants for whom the genetic data were not collected may provide an additional “reserve” for increasing the accuracy of respective estimates. We present a novel method for joint analyses of “genetic” (covering individuals for whom both genetic information and mortality/morbidity data are available) and “non-genetic” (covering individuals for whom only mortality/morbidity data were collected) subsamples of longitudinal data. Our simulation studies show substantial increase in the accuracy of estimates in such joint analyses compared to analyses based on genetic subsample alone. Application of this method to analysis of the effect of common apolipoprotein E (APOE) polymorphism on survival using combined genetic and non-genetic subsamples of the Framingham Heart Study original cohort data showed that female, but not male, carriers of the APOE e4 allele have significantly worse survival than non-carriers, whereas empirical analyses did not produce any significant results for either sex.

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.