Browsing by Author "Yashin, Anatoliy I"

Now showing 1 - 20 of 38

Open Access
A new algorithm for predicting time to disease endpoints in Alzheimer's disease patients.
(J Alzheimers Dis, 2014) Razlighi, Qolamreza R; Stallard, Eric; Brandt, Jason; Blacker, Deborah; Albert, Marilyn; Scarmeas, Nikolaos; Kinosian, Bruce; Yashin, Anatoliy I; Stern, Yaakov
BACKGROUND: The ability to predict the length of time to death and institutionalization has strong implications for Alzheimer's disease patients and caregivers, health policy, economics, and the design of intervention studies. OBJECTIVE: To develop and validate a prediction algorithm that uses data from a single visit to estimate time to important disease endpoints for individual Alzheimer's disease patients. METHOD: Two separate study cohorts (Predictors 1, N = 252; Predictors 2, N = 254), all initially with mild Alzheimer's disease, were followed for 10 years at three research centers with semiannual assessments that included cognition, functional capacity, and medical, psychiatric, and neurologic information. The prediction algorithm was based on a longitudinal Grade of Membership model developed using the complete series of semiannually-collected Predictors 1 data. The algorithm was validated on the Predictors 2 data using data only from the initial assessment to predict separate survival curves for three outcomes. RESULTS: For each of the three outcome measures, the predicted survival curves fell well within the 95% confidence intervals of the observed survival curves. Patients were also divided into quintiles for each endpoint to assess the calibration of the algorithm for extreme patient profiles. In all cases, the actual and predicted survival curves were statistically equivalent. Predictive accuracy was maintained even when key baseline variables were excluded, demonstrating the high resilience of the algorithm to missing data. CONCLUSION: The new prediction algorithm accurately predicts time to death, institutionalization, and need for full-time care in individual Alzheimer's disease patients; it can be readily adapted to predict other important disease endpoints. The algorithm will serve an unmet clinical, research, and public health need.
Open Access
Age patterns of incidence of geriatric disease in the U.S. elderly population: Medicare-based analysis.
(J Am Geriatr Soc, 2012-02) Akushevich, Igor; Kravchenko, Julia; Ukraintseva, Svetlana; Arbeev, Konstantin; Yashin, Anatoliy I
OBJECTIVES: To use the Medicare Files of Service Use (MFSU) to evaluate patterns in the incidence of aging-related diseases in the U.S. elderly population. DESIGN: Age-specific incidence rates of 19 aging-related diseases were evaluated using the National Long Term Care Survey (NLTCS) and the Surveillance, Epidemiology, and End Results (SEER) Registry data, both linked to MFSU (NLTCS-M and SEER-M, respectively), using an algorithm developed for individual date at onset evaluation. SETTING: A random sample from the entire U.S. elderly population (Medicare beneficiaries) was used in NLTCS, and the SEER Registry data covers 26% of the U.S. population. PARTICIPANTS: Thirty-four thousand seventy-seven individuals from NLTCS-M and 2,154,598 from SEER-M. MEASUREMENTS: Individual medical histories were reconstructed using information on diagnoses coded in MFSU, dates of medical services and procedures, and Medicare enrollment and disenrollment. RESULTS: The majority of diseases (e.g., prostate cancer, asthma, and diabetes mellitus) had a monotonic decline (or decline after a short period of increase) in incidence with age. A monotonic increase in incidence with age with a subsequent leveling off and decline was observed for myocardial infarction, stroke, heart failure, ulcer, and Alzheimer's disease. An inverted U-shaped age pattern was detected for lung and colon carcinomas, Parkinson's disease, and renal failure. The results obtained from the NLTCS-M and SEER-M were in agreement (excluding an excess for circulatory diseases in the NLTCS-M). A sensitivity analysis proved the stability of the incidence rates evaluated. CONCLUSION: The developed computational approaches applied to the nationally representative Medicare-based data sets allow reconstruction of age patterns of disease incidence in the U.S. elderly population at the national level with unprecedented statistical accuracy and stability with respect to systematic biases.
Open Access
Age trajectories of physiological indices in relation to healthy life course.
(Mech Ageing Dev, 2011-03) Arbeev, Konstantin G; Ukraintseva, Svetlana V; Akushevich, Igor; Kulminski, Alexander M; Arbeeva, Liubov S; Akushevich, Lucy; Culminskaya, Irina V; Yashin, Anatoliy I
We analysed relationship between the risk of onset of "unhealthy life" (defined as the onset of cancer, cardiovascular diseases, or diabetes) and longitudinal changes in body mass index, diastolic blood pressure, hematocrit, pulse pressure, pulse rate, and serum cholesterol in the Framingham Heart Study (Original Cohort) using the stochastic process model of human mortality and aging. The analyses demonstrate how decline in resistance to stresses and adaptive capacity accompanying human aging can be evaluated from longitudinal data. We showed how these components of the aging process, as well as deviation of the trajectories of physiological indices from those minimising the risk at respective ages, can lead to an increase in the risk of onset of unhealthy life with age. The results indicate the presence of substantial gender difference in aging related decline in stress resistance and adaptive capacity, which can contribute to differences in the shape of the sex-specific patterns of incidence rates of aging related diseases.
Open Access
Aging and health--a systems biology perspective. Introduction.
(Interdiscip Top Gerontol, 2015) Jazwinski, S Michal; Yashin, Anatoliy I
Open Access
An age-structured extension to the vectorial capacity model.
(PLoS One, 2012) Novoseltsev, Vasiliy N; Michalski, Anatoli I; Novoseltseva, Janna A; Yashin, Anatoliy I; Carey, James R; Ellis, Alicia M
BACKGROUND: Vectorial capacity and the basic reproductive number (R(0)) have been instrumental in structuring thinking about vector-borne pathogen transmission and how best to prevent the diseases they cause. One of the more important simplifying assumptions of these models is age-independent vector mortality. A growing body of evidence indicates that insect vectors exhibit age-dependent mortality, which can have strong and varied affects on pathogen transmission dynamics and strategies for disease prevention. METHODOLOGY/PRINCIPAL FINDINGS: Based on survival analysis we derived new equations for vectorial capacity and R(0) that are valid for any pattern of age-dependent (or age-independent) vector mortality and explore the behavior of the models across various mortality patterns. The framework we present (1) lays the groundwork for an extension and refinement of the vectorial capacity paradigm by introducing an age-structured extension to the model, (2) encourages further research on the actuarial dynamics of vectors in particular and the relationship of vector mortality to pathogen transmission in general, and (3) provides a detailed quantitative basis for understanding the relative impact of reductions in vector longevity compared to other vector-borne disease prevention strategies. CONCLUSIONS/SIGNIFICANCE: Accounting for age-dependent vector mortality in estimates of vectorial capacity and R(0) was most important when (1) vector densities are relatively low and the pattern of mortality can determine whether pathogen transmission will persist; i.e., determines whether R(0) is above or below 1, (2) vector population growth rate is relatively low and there are complex interactions between birth and death that differ fundamentally from birth-death relationships with age-independent mortality, and (3) the vector exhibits complex patterns of age-dependent mortality and R(0) ∼ 1. A limiting factor in the construction and evaluation of new age-dependent mortality models is the paucity of data characterizing vector mortality patterns, particularly for free ranging vectors in the field.
Open Access
Biodemographic Analyses of Longitudinal Data on Aging, Health, and Longevity: Recent Advances and Future Perspectives.
(Adv Geriatr, 2017-06-02) Arbeev, Konstantin G; Akushevich, Igor; Kulminski, Alexander M; Ukraintseva, Svetlana V; Yashin, Anatoliy I
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.
Open Access
Biogenetic mechanisms predisposing to complex phenotypes in parents may function differently in their children.
(J Gerontol A Biol Sci Med Sci, 2013-07) Kulminski, Alexander M; Arbeev, Konstantin G; Christensen, Kaare; Stallard, Eric; Miljkovic, Iva; Barmada, Michael; Yashin, Anatoliy I
This study focuses on the participants of the Long Life Family Study to elucidate whether biogenetic mechanisms underlying relationships among heritable complex phenotypes in parents function in the same way for the same phenotypes in their children. Our results reveal 3 characteristic groups of relationships among phenotypes in parents and children. One group composed of 3 pairs of phenotypes confirms that associations among some phenotypes can be explained by the same biogenetic mechanisms working in parents and children. Two other groups including 9 phenotype pairs show that this is not a common rule. Our findings suggest that biogenetic mechanisms underlying relationships among different phenotypes, even if they are causally related, can function differently in successive generations or in different age groups of biologically related individuals. The results suggest that the role of aging-related processes in changing environment may be conceptually underestimated in current genetic association studies using genome wide resources.
Open Access
Birth Cohort, Age, and Sex Strongly Modulate Effects of Lipid Risk Alleles Identified in Genome-Wide Association Studies.
(PLoS One, 2015) Kulminski, Alexander M; Culminskaya, Irina; Arbeev, Konstantin G; Arbeeva, Liubov; Ukraintseva, Svetlana V; Stallard, Eric; Wu, Deqing; Yashin, Anatoliy I
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.
Open Access
Dynamics of biomarkers in relation to aging and mortality.
(Mech Ageing Dev, 2016-06) Arbeev, Konstantin G; Ukraintseva, Svetlana V; Yashin, Anatoliy I
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.
Open Access
Effect of the APOE Polymorphism and Age Trajectories of Physiological Variables on Mortality: Application of Genetic Stochastic Process Model of Aging.
(Scientifica (Cairo), 2012) Arbeev, Konstantin G; Ukraintseva, Svetlana V; Kulminski, Alexander M; Akushevich, Igor; Arbeeva, Liubov S; Culminskaya, Irina V; Wu, Deqing; Yashin, Anatoliy I
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.
Open Access
Epidemiology of geographic disparities in heart failure among US older adults: a Medicare-based analysis.
(BMC public health, 2022-07) Yu, Bin; Akushevich, Igor; Yashkin, Arseniy P; Yashin, Anatoliy I; Lyerly, H Kim; Kravchenko, Julia
Background
There are prominent geographic disparities in the life expectancy (LE) of older US adults between the states with the highest (leading states) and lowest (lagging states) LE and their causes remain poorly understood. Heart failure (HF) has been proposed as a major contributor to these disparities. This study aims to investigate geographic disparities in HF outcomes between the leading and lagging states.
Methods
The study was a secondary data analysis of HF outcomes in older US adults aged 65+, using Center for Disease Control and Prevention sponsored Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database and a nationally representative 5% sample of Medicare beneficiaries over 2000-2017. Empiric estimates of death certificate-based mortality from HF as underlying cause of death (CBM-UCD)/multiple cause of death (CBM-MCD); HF incidence-based mortality (IBM); HF incidence, prevalence, and survival were compared between the leading and lagging states. Cox regression was used to investigate the effect of residence in the lagging states on HF incidence and survival.
Results
Between 2000 and 2017, HF mortality rates (per 100,000) were higher in the lagging states (CBM-UCD: 188.5-248.6; CBM-MCD: 749.4-965.9; IBM: 2656.0-2978.4) than that in the leading states (CBM-UCD: 79.4-95.6; CBM-MCD: 441.4-574.1; IBM: 1839.5-2138.1). Compared to their leading counterparts, lagging states had higher HF incidence (2.9-3.9% vs. 2.2-2.9%), prevalence (15.6-17.2% vs. 11.3-13.0%), and pre-existing prevalence at age 65 (5.3-7.3% vs. 2.8-4.1%). The most recent rates of one- (77.1% vs. 80.4%), three- (59.0% vs. 60.7%) and five-year (45.8% vs. 49.8%) survival were lower in the lagging states. A greater risk of HF incidence (Adjusted Hazards Ratio, AHR [95%CI]: 1.29 [1.29-1.30]) and death after HF diagnosis (AHR: 1.12 [1.11-1.13]) was observed for populations in the lagging states. The study also observed recent increases in CBMs and HF incidence, and declines in HF prevalence, prevalence at age 65 and survival with a decade-long plateau stage in IBM in both leading and lagging states.
Conclusion
There are substantial geographic disparities in HF mortality, incidence, prevalence, and survival across the U.S.: HF incidence, prevalence at age 65 (age of Medicare enrollment), and survival of patients with HF contributed most to these disparities. The geographic disparities and the recent increase in incidence and decline in survival underscore the importance of HF prevention strategies.
Open Access
Estimation and validation of a multiattribute model of Alzheimer disease progression.
(Med Decis Making, 2010-11) Stallard, Eric; Kinosian, Bruce; Zbrozek, Arthur S; Yashin, Anatoliy I; Glick, Henry A; Stern, Yaakov
OBJECTIVES: To estimate and validate a multiattribute model of the clinical course of Alzheimer disease (AD) from mild AD to death in a high-quality prospective cohort study, and to estimate the impact of hypothetical modifications to AD progression rates on costs associated with Medicare and Medicaid services. DATA AND METHODS: The authors estimated sex-specific longitudinal Grade of Membership (GoM) models for AD patients (103 men, 149 women) in the initial cohort of the Predictors Study (1989-2001) based on 80 individual measures obtained every 6 mo for 10 y. These models were replicated for AD patients (106 men, 148 women) in the 2nd Predictors Study cohort (1997-2007). Model validation required that the disease-specific transition parameters be identical for both Predictors Study cohorts. Medicare costs were estimated from the National Long Term Care Survey. RESULTS: Sex-specific models were validated using the 2nd Predictors Study cohort with the GoM transition parameters constrained to the values estimated for the 1st Predictors Study cohort; 57 to 61 of the 80 individual measures contributed significantly to the GoM models. Simulated, cost-free interventions in the rate of progression of AD indicated that large potential cost offsets could occur for patients at the earliest stages of AD. CONCLUSIONS: AD progression is characterized by a small number of parameters governing changes in large numbers of correlated indicators of AD severity. The analysis confirmed that the progression of AD represents a complex multidimensional physiological process that is similar across different study cohorts. The estimates suggested that there could be large cost offsets to Medicare and Medicaid from the slowing of AD progression among patients with mild AD. The methodology appears generally applicable in AD modeling.
Open Access
Evaluation of genotype-specific survival using joint analysis of genetic and non-genetic subsamples of longitudinal data.
(Biogerontology, 2011-04) Arbeev, Konstantin G; Ukraintseva, Svetlana V; Arbeeva, Liubov S; Akushevich, Igor; Kulminski, Alexander M; Yashin, Anatoliy I
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.
Open Access
Explicating heterogeneity of complex traits has strong potential for improving GWAS efficiency.
(Sci Rep, 2016-10-14) Kulminski, Alexander M; Loika, Yury; Culminskaya, Irina; Arbeev, Konstantin G; Ukraintseva, Svetlana V; Stallard, Eric; Yashin, Anatoliy I
Common strategy of genome-wide association studies (GWAS) relying on large samples faces difficulties, which raise concerns that GWAS have exhausted their potential, particularly for complex traits. Here, we examine the efficiency of the traditional sample-size-centered strategy in GWAS of these traits, and its potential for improvement. The paper focuses on the results of the four largest GWAS meta-analyses of body mass index (BMI) and lipids. We show that just increasing sample size may not make p-values of genetic effects in large (N > 100,000) samples smaller but can make them larger. The efficiency of these GWAS, defined as ratio of the log-transformed p-value to the sample size, in larger samples was larger than in smaller samples for a small fraction of loci. These results emphasize the important role of heterogeneity in genetic associations with complex traits such as BMI and lipids. They highlight the substantial potential for improving GWAS by explicating this role (affecting 11-79% of loci in the selected GWAS), especially the effects of biodemographic processes, which are heavily underexplored in current GWAS and which are important sources of heterogeneity in the various study populations. Further progress in this direction is crucial for efficient use of genetic discoveries in health care.
Open Access
Genetic Structures of Population Cohorts Change with Increasing Age: Implications for Genetic Analyses of Human aging and Life Span.
(Ann Gerontol Geriatr Res, 2017-06-02) Yashin, Anatoliy I; Wu, Deqing; Arbeev, Konstantin G; Arbeeva, Liubov S; Akushevich, Igor; Kulminski, Alexander; Culminskaya, Irina; Stallard, Eric; Ukraintseva, Svetlana V
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.
Open Access
Genetics of aging, health, and survival: dynamic regulation of human longevity related traits.
(Front Genet, 2015) Yashin, Anatoliy I; Wu, Deqing; Arbeeva, Liubov S; Arbeev, Konstantin G; Kulminski, Alexander M; Akushevich, Igor; Kovtun, Mikhail; Culminskaya, Irina; Stallard, Eric; Li, Miaozhu; Ukraintseva, Svetlana V
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.
Open Access
How genes influence life span: the biodemography of human survival.
(Rejuvenation Res, 2012-08) Yashin, Anatoliy I; Wu, Deqing; Arbeev, Konstantin G; Stallard, Eric; Land, Kenneth C; Ukraintseva, Svetlana V
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.
Open Access
How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data.
(N Am Actuar J, 2016) Yashin, Anatoliy I; Arbeev, Konstantin G; Wu, Deqing; Arbeeva, Liubov; Kulminski, Alexander; Kulminskaya, Irina; Akushevich, Igor; Ukraintseva, Svetlana V
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.
Open Access
How lifespan associated genes modulate aging changes: lessons from analysis of longitudinal data.
(Front Genet, 2013) Yashin, Anatoliy I; Arbeev, Konstantin G; Wu, Deqing; Arbeeva, Liubov S; Kulminski, Alexander; Akushevich, Igor; Culminskaya, Irina; Stallard, Eric; Ukraintseva, Svetlana V
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.
Open Access
How the effects of aging and stresses of life are integrated in mortality rates: insights for genetic studies of human health and longevity.
(Biogerontology, 2016-02) Yashin, Anatoliy I; Arbeev, Konstantin G; Arbeeva, Liubov S; Wu, Deqing; Akushevich, Igor; Kovtun, Mikhail; Yashkin, Arseniy; Kulminski, Alexander; Culminskaya, Irina; Stallard, Eric; Li, Miaozhu; Ukraintseva, Svetlana V
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.

Browsing by Author "Yashin, Anatoliy I"

Results Per Page

Sort Options

Background

Methods

Results

Conclusion