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Clear evidence exists for heritability of humanlongevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome-wide linkage scan thus far reported. Linkage analyses included 2118nonagenarian Caucasian sibling pairs that have been enrolled in 15 study centers of 11 European countries as part of the Genetics of Healthy Aging (GEHA) project. In the joint linkage analyses, we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD = 3.47), chromosome 17q12-q22 (LOD = 2.95), chromosome 19p13.3-p13.11 (LOD = 3.76), and chromosome 19q13.11-q13.32 (LOD = 3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1228 unrelated nonagenarian and 1907 geographically matched controls. Using a fixed-effect meta-analysis approach, rs4420638 at the TOMM40/ APOE/APOC1 gene locus showed significant association with longevity (P-value = 9.6 × 10 -8). By combined modeling of linkage and association, we showed that association of longevity with APOEe4 and APOEe2 alleles explain the linkage at 19q13.11-q13.32 with P-value = 0.02 and P-value = 1.0 × 10 -5, respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12-q22, and 19p13.3-p13.11. As the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.

A tight link exists between telomere length and both population doublings of a cell culture and age of a given organism. The more population doublings of the cell culture or the higher the age of the organism, the shorter the telomeres. The proposed model for telomere shortening, called the end replication problem, explains why the telomere erodes at each cellular turnover. Telomere length is regulated by a number of associated proteins through a number of different signaling pathways. The determinants of telomere length were studied using whole blood samples from 287 twin pairs aged 73 to 95 years. Structural equation models revealed that a model including additive genetic effects and non- shared environment was the best fitting model and that telomere length was moderately heritable, with an estimate that was sensitive to the telomere length standardization procedure. Sex-specific analyses showed lower heritability in males, although not statistically significant, which is in line with our earlier finding of a sex difference in telomere dynamics among the elderly and oldest-old.

Genetic-evolutionary theories of aging predict that the genetic variance for fitness traits increases with age, while epidemiological-gerontological theories predict an increase in the environmental variance for most traits. In this study we examine the age trajectories of the genetic and environmental variance in physical functioning in a sample of 4731 Danish twins aged 70+ who are being followed longitudinally every second year with up to four assessments completed. A biometric growth model (Neale and McArdle, 2000) was applied to a validated physical ability score. The model included an overall level effect, a rate of linear change effect, and residual effects. The best-fitting model was a sex-specific model including additive genetic and nonshared environmental factors affecting level and rate of change and only nonshared environmental factors affecting the wave-specific levels. For both sexes there is an approximate doubling of both the total variance and the genetic variance in the physical ability score over the four waves and, hence, a rather stable heritability. However, the heritability is approximately .10 for males and .30 for females in all four waves. The heritability of level and slope showed a similar pattern: .11–14 in males and .35–.39 in females. The increase in both additive genetic variance and environmental variance is in agreement with genetic-evolutionary and epidemiological-gerontological theories of aging, respectively. The present study suggests that overall level of strength may be a better phenotype for future molecular genetic studies on physical functioning in the elderly than rate of change, because rate of change is vulnerable to sample attrition due to mortality and dropout and because four waves were needed to be able to detect a heritability for rate of change of the same magnitude as the heritability for level of physical functioning.

A new method based on the recently developed relative risk approach is introduced, and applied to data from Italian centenarian study (965 subjects aged from 13 to 109 years old) for investigating influences on longevity by Tyrosine Hydroxylase (TH) gene variability. The strategic parameterization enables the model to disentangle the various ways by which HUMTHO1.STR alleles (alleles 6, 7, 8, 9, 10*, 10, as defined according to the number of repeats) may contribute in reducing or increasing the hazard of death with different patterns of influences. Among all the alleles, we have found that allele 10* (10 imperfect repeats) shows a remarkable dominant and beneficial effect that reduces the log hazard of death in an additive manner. The results confirm that HUMTHO1.STR polymorphism is involved in the modulation of human longevity.

Udgivelsesdato: May OBJECTIVES: To describe the functional capacity and self‐rated health of a large cohort of nonagenarians.DESIGN: A cross‐sectional survey of all Danes born in 1905 (92–93 years of age), carried out August to October 1998.SETTING: Participants' homes.PARTICIPANTS: Two thousand two hundred and sixty‐two nonagenarians, corresponding to a participation rate of 63% (of these, 20% participated by proxy).MEASUREMENTS: Activities of daily living (ADLs) and self‐rated health were assessed by interview. Five items from Katz's ADLs (bathing, dressing, transfer, toileting, and eating) were used to construct a three‐level five‐item ADL scale (not disabled (no disabilities), moderately disabled (1–2 disabilities), severely disabled (3–5 disabilities)). From responses to a more extensive list of questions on ADLs (26 items), we identified scales of strength and agility by means of factor analysis. Furthermore, a 26‐item ADL scale was made. Physical performance tests (chair stand, timed walk, lifting a 2.7 kg box, maximum grip‐strength, and flexibility tests) were performed among nonproxy responders.RESULTS: According to the five‐item ADL scale, 50% of the men and 41% of the women were categorized as not disabled, while 19% and 22%, respectively, were categorized as severely disabled. The five‐item ADL scale correlated highly with the 26‐item ADL scale (r = 0.83). The ADL scales showed moderate‐to‐good correlation with each other (r = 0.74–0.83), and with the physical performance tests (r = 0.31–0.58). Only 3.7% of the women and 6.3% of the men walked (normal pace) with a speed of at least 1 meter per second, which is the minimum walking speed required to cross signaled intersections in Denmark. A total of 56% considered their health to be excellent or good. Of the participants, 74% were always or almost always satisfied with their lives, even though only 45% reported that they “felt well enough to do what they wanted.” The analyses showed that no single ADL item seemed to be of particular importance for how the participants rated their health.CONCLUSION: The Danish 1905 cohort survey is the largest and the only nationwide survey of a whole birth‐cohort of nonagenarians. A total of 2,262 fairly nonselected nonagenarians participated. The level of both self‐reported disability and functional limitations measured by physical performance tests among nonagenarians was high. Despite their lower mortality, women were more disabled than men and did not perform as well as men in the physical performance tests. Nevertheless, the majority of the participants considered their health to be good and were satisfied with their lives.

The logistic regression model is a popular model for data analysis in epidemiological research. In this paper, we use this model to analyze genetic data collected from gene–longevity association studies. This new approach models the probability of observing one genotype as a function of the age of investigated individuals. Applying the model to genotype data on the TH and 3′ApoB‐VNTR loci collected from an Italian centenarian study, we show how it can be used to model the different ways that genes affect survival, including sex‐ and age‐specific influences. We highlight the advantages of this application over other available models. The application of the model to empirical data indicates that it is an efficient and easily applicable approach for determining the influences of genes on human longevity.

This commentary calls attention to the value of combining genetic and epidemiologic methods in studies to understand the determinants of two crucial aspects of aging: ages at which certain outcomes (e.g., disease, mortality) occur and rates of change with age of individual's characteristics (e.g., physiologic functions, disease risk factors). Inclusion of age in the specification of traits in genetic epidemiologic studies could lead to improved strategies to increase healthy life expectancy and evaluate individuals' risk for age-related morbidity. Special issues that make genetic epidemiologic approaches important for studies of age-specified phenomena as well as opportunities and challenges for such studies are discussed, including study designs, sampling frames, databases, analytic tools, and related methodological issues. This commentary is based on a report prepared by the Aging and Genetic Epidemiology Working Group, convened by the National Institute on Aging to review opportunities for research on the genetic epidemiology of aging-related outcomes

It is generally accepted that the risk of disease and death vary markedly by age and sex. However, there are also inherited and acquired factors that cause vast differences in human susceptibility to many pollutant exposures. Most people are less familiar with this wide range of heterogeneity precipitated by genetic make-up, life style, occupation, nutrition, residence location, etc. The combined role of these many heterogeneity factors is often underestimated. Yet they are the major factors that determine the evolution of mortality and morbidity patterns within a population. In this paper, we examine a variety of heterogeneities present in environmental pollutant susceptibilities, briefly look at how attempts to recognize heterogeneity have played a role in efforts to regulate pollutants, consider how likely shifts in the composition of population may affect morbidity and mortality rates affected by environmental pollution, discuss how indirect heterogeneity factors can lead to additional complications in interpretations of pollution-related mortality statistics, and offer several suggestive models of heterogeneous susceptibility.

Suppose progress continues to be made in reducing mortality rates at all ages. What impact would this progress have on the size and age composition of the U.S. population? The supposition that mortality rates will continue to fall is admittedly questionable. The view popularized by James F. Fries is that "the median natural human life span is set at a maximum of 85 years with a standard error of less than one year" (Fries and Crapo, 1981). Paul Demeny, in making long-term population forecasts for the World Bank, assumes that even by the year 2100 there will be no country with a life expectancy above 82.5 years. Demeny notes that in some countries life expectancy seems to be slowly decreasing. The possibility of a general decline in life expectancy cannot be ruled out. On the other hand, as Demeny points out, "the upper limit to life expectancy" of 82.5 years "may yield to technological changes in medicine and to changes in life styles, perhaps even within the next few decades" (Demeny, 1984). As documented by Crimmins (1981), remarkably rapid progress in reducing mortality rates was made in the United States from 1968 to 1977. This progress has continued and even accelerated from 1977 to 1983. At most ages, including older ages, mortality rates over the last decade have been declining at a rate of one or two percent per year. Hope that this progress might continue is butressed by recent advances in the biological, medical, and gerontological sciences. The life sciences appear to be poised at roughly the point the physical sciences were a century ago and breakthroughs comparable to electricity, automobiles, television, and computers may be forthcoming in the areas of genetic engineering, prevention and treatment of such diseases as atherosclerosis, cancer, and diabetes, and perhaps understanding and control of the process of aging itself (see, e.g. Walford (1983), Bulkley (1983), and Rosenfeld (1976)). In this note, we explore three possibilities: no change in mortality rates, continued progress at two percent per year at all ages, and a radical breakthrough that cuts mortality rates in half in the year 2000. Our focus is on the impact of such scenarios on the size and age composition of the U.S. population. Because our aim is insight and not prediction, we assume that fertility rates stay unchanged and that net migration amounts to zero: these simplifications avoid obscuring the effects of mortality change with fertility or migration change....

The paper is devoted to the analysis of stochastic process models of mortality which can explain both selection and debilitation processes in the evolution of cohort mortality. The relative importance of each process is analyzed. The examples of various regimes of mortality evolution are demonstrated.

The LEXIS computer program, which was developed at the International Institute for Applied Systems Analysis (IIASA) and Duke University, is intended to aid demographers in the analysis of large arrays of data. Its application as a supplement t o other methods of graphic display is demonstrated in 'Thousands of Data at a Glance: Shaded Contour Maps of Demographic Surfaces" (Vaupel, Gambill, and Yashin, 1985) and will not be discussed here. This paper provides instructions on the use of the program, gives some hints concerning the art and craft of using the program in a creative way, and briefly describes the algorithm used in designing the program. A diskette containing a copy of the LEXIS program may be obtained from the authors or from IIASA. The program is copyrighted but the diskette is not protected against copying: please feel free to make and distribute copies. By making the program available to demographers and others interested in mapping the contours of surfaces, we hope to encourage the development of this method of data analysis. We would, of course, sincerely appreciate it if we and the International Institute for Applied Systems Analysis were acknowledged when the program or some modified version of it is used to produce maps for presentation or publication. Comments and suggestions are welcome!

Contour maps are useful for displaying demographic surfaces, including surfaces of population levels and fertility, marriage, and mortality rates. Most often the surfaces are defined over age and time, but other dimensions can be used such as life expectancy or population growth rate. This research report presents a bouquet of contour maps to suggest the broad potential of their use in demographic studies. The maps presented range from maps of Italian mortality, French population levels, and US birth rates, to maps of Coale and Demeny's and Brass's model life tables. The value of the maps lies in their substantive import: by giving demographers visual access to population surfaces, the maps can help demographers uncover and understand population patterns. The text of the research report adumbrates some of these patterns and discusses the use of contour maps in exploratory data analyses and model building, including the use of maps of residuals in fitting models to data.

This report is a product of a study of current and potential education programs at IIASA conducted by Dianne Goodwin and James Vaupel with the assistance of Olivia Carydias. The study was begun in July 1982 and completed on January 5, 1983. The first section of this report focuses on the Young Scientists Summer Program: the current program is evaluated, several recommendations for incremental improvements are suggested, and a "Summer Roundtable" program that could either supplement or replace the current program is proposed. The second section of this report considers opportunities for offering short courses (of one to three weeks' duration) at IIASA. Two broad options are described. IIASA could initiate a modest program of short courses based on IIASA research projects. In addition, IIASA might launch a program of East/West Colloquia. We considered a long list of options for education at IIASA. Most were easily ruled out based on the criteria we developed or the consensus of opinion we received. This report describes the relatively few remaining options worth further consideration.

Contour maps of Italian male and female mortality rates from age 0 to 79 and from 1870 to 1979 graphically display persistent global and prominent local patterns of mortality, simultaneously over age, by period, and for cohorts. The maps give demographers visual access to previously recognized features of the evolution of Italian mortality as well as focusing attention on some neglected features. Use of contour maps to display various kinds of mortality data, including mortality comparisons, may help demographers better understand the social and biological determinants of mortality.

This paper presents a bouquet of contour maps to suggest the broad potential of their use in demographic studies. Every picture presented could serve as the basis for a thousand words or more of explanation and analysis, but here we merely serve up the maps as illustrations of the method. For an example of how such maps can be used in demographic analysis, see Caselli, Vaupel, and Yashin (1985): Mortality in Italy--Contours of a Century of Evolution (CP-85-24, International Institute for Applied Systems Analysis, Laxenburg, Austria).

A number of multivariate stochastic process models have been developed to represent human physiological aging and mortality. In this paper, we extend those efforts by considering the effects of unobserved state variables on the age trajectory of physiological parameters. This is accomplished by deriving the Kolmogorov-Fokker-Planck equations for the distribution of the state variables conditionally on the process of the observed state variables. Proofs are given that this form of the process will preserve the Gaussian properties of the distribution. Strategies for estimating the parameters of the distribution of the unobserved variable are suggested based on an extension of the theory of Kalman filters to include systematic mortality selection. Implications of individual differences on the trajectories of the unobserved process for observed aging changes are discussed as well as the consequences of such modeling for dealing with other types of processes in heterogeneous populations.

The application of concentration curves and have-statistics to studies of dominance and evenness in reproductive success was discussed in Part I of this series of three papers. Concentration curves and have-statistics can also aid ecologists in studies of species diversity and community structure; a start in this direction was made by Patil and Taillie (1979) and Taillie (1979). Essentially, the method is the same as before except that now the "haves" are species rather than individuals and the "hads" are individuals, biomass, caloric intake, etc., rather than an individual's offspring. In addition, concentration curves and have-statistics can be applied to other ecological topics pertaining to variation and inequality, including the temporal or spatial distribution of some resource, such as food supply or rainfall. Various examples, from studies of diatoms, a community of herbaceous plants, a tropical forest, a model of niche preemption, and temporal variation in the breeding of tropical and temperate bird species illustrate this approach.

How does saving lives affect the force of mortality and lifetable statistics? How can the progress being made in reducing the force of mortality be interpreted in terms of lifesaving? How many times can a person expect to have his or her life saved as a result of this progress? We develop a model to answer these questions and illustrate the results using U.S. mortality rates for 1900 and 1980 and as projected for 2050.

The members of most populations gradually die off or drop out: people die, machines wear out, residents move out, etc. In many such "aging" populations, some members are more likely to "die" than others. Standard analytical methods largely ignore this heterogeneity; the methods assume that all members of a population at a given age face the same probability of death. This paper presents some mathematical methods for studying how the behavior over time of a heterogeneous population deviates from the behavior of the individuals that make up the population. The methods yield some startling results: individuals age faster than populations, eliminating a cause of death can decrease life expectancy, a population can suffer a higher death rate than another population even though its members have lower death rates, population death rates can be increasing even though its members' death rates are decreasing.

A computer-assisted mathematical modeling method that emphasizes the interaction between analysts and computers is presented. It combines algebraic and graph-theoretic approaches to extract a trade-off between human mental models and models based on the use of data collected from the system under study. The method is oriented to the modeling of the so-called "gray box" systems which often involve human behavioral aspects and also knowledge of the experts in relevant fields. By recursive dialogues with the computer, the modeler finds a system model which can be nonlinear with respect to descriptive variables. The structure of the computer program packages is also presented.

Given the central importance of diversity in ecology and the life sciences more generally, it is not surprising that a variety of methods and measures have been developed to describe and summarize diversity. In the two previous parts of this series of papers, comparisons were drawn between concentration curves and frequency distributions, the most widely used graphical display of variation, and between concentration curves and dominance-diversity curves. This final part of the three paper series compares various statistics that might be used to summarize diversity, with a focus on the usefulness of have-statistics as a supplement to more traditional measures. The first section of our discussion lays out some reasonable criteria and principles that good measures of diversity should satisfy: some traditional measures violate at least one of the criteria; the have-statistics pass the hurdles and have some desirable properties in addition. We then illustrate the use of different measures by way of examples drawn from Howard's studies of bullfrogs (discussed in Part I), the study of species diversity among diatoms (discussed in Part II), an analysis of mating systems of various birds, and a survey of human fertility in 41 countries.

The LEXIS computer program, which was developed at the International Institute for Applied Systems Analysis (IIASA) and Duke University, is intended to aid demographers in the analysis of large arrays of data. Its application as a supplement t o other methods of graphic display is demonstrated in Thousands of Data at a GLance: Shaded Contour Maps of PopuLation Surfaces (Vaupel. Gambill, and Yashin, forthcoming) and will not be discussed here. This paper provides instructions on the use of the program, gives some hints concerning the art and craft of using the program in a creative way, and briefly describes the algorithm used in designing the program. A diskette containing a copy of the LEXIS program is enclosed. The program is copyrighted but the diskette is not protected against copying: please feel free to make and distribute copies. By making the program available to demographers and others interested in mapping the contours of surfaces, we hope to encourage the development of this method of data analysis. We would, of course, sincerely appreciate it if we and the International Institute for Applied Systems Analysis were acknowledged when the program or some modified version of it is used to produce maps for presentation or publication. Comments and suggestions are welcome!

Concentration curves and a set of summary statistics called have-statistics are useful in ecological analyses of dominance and evenness among individuals in reproductive success. This approach complements, but does not replace, approaches based on frequency distributions and standard summary statistics. Examples are drawn from studies of bullfrogs, red deer, elephant seals, sculpins, fruit flies, and rice weevils, as well as from some theoretical models similar to the Wright-Fisher model of evolutionary genetics.

Important recent research by Samuel Preston and Ansley Coale (1982) extends the Lotka system of stable population equations (Lotka 1939) to any population. Here we present an alternative general system and describe its duality with the Preston-Coale system: We derive these results by considering the calculus of change on the surface of population density defined over age and time. We show that analysis of this Lexis surface leads to all the known fundamental relationships of the dynamics of single-region human populations, as well as some interesting new relationships.

Patterns of marriage and fertility in China have changed rapidly over the last three decades. Fertility has dramatically declined, especially before age 20 and after age 30. Marriage remains virtually' universal, but the age of first marriage, previously concentrated between ages 16 and 20, has shifted upward to between ages 20 and 25. These trends were sharply punctuated by marriage and fertility booms and slumps associated with the disturbances of the Great Leap Forward and the Cultural Revolution. Thus, strong age, period, and cohort fluctuations, some transient and others persistent, interact to produce a complex mosaic of turbulent demographic change. Coale masterfully analyzed these patterns of change. Here we supplement Coale's analysis by presenting and discussing some shaded contour maps of various surfaces of Chinese marriage and fertility rates. As discussed in detail elsewhere, such maps permit visualization of population surfaces defined over age and time and offer a panoramic view of the interaction of age, period, and cohort variations. Because the use of shaded maps of population surfaces is implicit in one of Lexis' original diagrams, and because the term Lexis surface is increasing being used to refer to surfaces of demographic rates defined over age and time, the shaded contour maps presented here might be called Lexis maps. An early instance of the use of contour maps (without shading) may be found in Delaporte's pioneering comparison of trends in age-specific mortality rates in various European countries. The data used to construct the Lexis maps are from China's one-per-thousand fertility survey conducted in 1982; the total sample size was a bit more than one million. The principle information gathered in the survey, which covered all of China except Tibet, Hong Kong, and Taiwan, comprised detailed marriage and fertility histories of more than 300 thousand women aged 15 to 67, gathered through face-to-face interviews. This information was then used to reconstruct the pattern of age-specific fertility rates in China from 1940 through 1981 and the pattern of age-specific first-marriage rates from 1950 through 1981. For both fertility and first-marriage rates, an urban vs. rural breakdown was also published for 1950 through 1981. Coale and several other analysts have scrutinized the quality of the data and conclude that the data are reasonably reliable and give a generally accurate representation of the evolving age-specific patterns of Chinese marriage and fertility. Coale used the survey data to construct a set of estimates of age-specific proportions of women ever married. We use these estimates, but otherwise the maps we present are based directly on the original data....

Individuals at the same age in the same population differ along numerous risk factors that affect their chances of various causes of death. The frail and susceptible tend to die first. This differential selection may partially account for some of the puzzles in cancer epidemiology, including the lack of apparent progress in reducing cancer incidence and mortality rates over time.

Contour maps are useful for displaying demographic surfaces, including surfaces of population levels and fertility, marriage, and mortality rates. Most often the surfaces are defined over age and time, but such other dimensions can be used as life expectancy or population growth rate. This paper presents a bouquet of contour maps to suggest the broad potential of their use in demographic studies. The maps presented range from maps of Italian mortality, French population levels, and U.S. birth rates, to maps of Coale and Demeny's and Brass's model life tables. The value of the maps lies in their substantive import: by giving demographers visual access to population surfaces, the maps can help demographers uncover and understand population patterns. The text of the paper adumbrates some of these patterns and discusses the use of contour maps in exploratory data analyses and model building, including the use of maps of residuals in fitting models to data.

At current mortality rates, life expectancy is most responsive to change in mortality rates at older ages. Mathematical formulas that describe the linkage between change in age-specific mortality rates and change in life expectancy reveal why. These formulas also shed light on how past progress against mortality has been translated into increases in life expectancy--and on the impact that future progress is likely to have. Furthermore, the mathematics can be adapted to study the effect of mortality change in heterogeneous populations in which those who die at some age would, if saved, have a different life expectancy than those who live.

Heterogeneity is sometimes used as a synonym for variability or diversity; here it has a narrower meaning of variability with respect to mortality (or with respect to attributes of individuals that affect their mortality). This concept of heterogeneity is closely linked with the concept of selection: a heterogeneous population is one in which there is differential mortality and hence one in which selection is occurring. Because of the effects of selection, the patterns of mortality (or exit) in a heterogeneous population can differ qualitatively from the patterns of mortality in the constituent sub-populations. These qualitative differences can be surprising; unsuspecting researchers who are not wary of heterogeneity's ruses may fallaciously assume that observed patterns for the population as a whole also hold on the sub-population or individual level. Such incorrect inferences may produce erroneous policy recommendations, because the effect of an intervention usually depends on the behavior and response of individuals. In addition, because rates for homogeneous groups often follow simpler patterns than composite population rates, both theoretical and empirical research may be unnecessarily complicated by failure to recognize the effects of heterogeneity. The multiplicity of heterogeneity's ruses can be neatly illustrated in the simplest example of a heterogeneous population -- namely, a composite population that consists of two homogeneous sub-populations. It is not difficult to develop models of heterogeneous sub-populations that consist of a very large or infinite number of sub-populations. The ruses illustrated here could have been described in the context of such a model, but for purposes of simplicity and clarity, a focus on the most elementary kind of heterogeneous population seems appropriate. Moreover, it turns out that almost all the distinctive features of heterogeneous populations become apparent as soon as the transition is made from a homogeneous population to a mixed population with two major sub-populations.

In 2004, the integrated European project GEHA (Genetics of Healthy Ageing) was initiated with the aim of identifying genes involved in healthy ageing and longevity. The first step in the project was the recruitment of more than 2500 pairs of siblings aged 90years or more together with one younger control person from 15 areas in 11 European countries through a coordinated and standardised effort. A biological sample, preferably a blood sample, was collected from each participant, and basic physical and cognitive measures were obtained together with information about health, life style, and family composition. From 2004 to 2008 a total of 2535 families comprising 5319 nonagenarian siblings were identified and included in the project. In addition, 2548 younger control persons aged 50-75years were recruited. A total of 2249 complete trios with blood samples from at least two old siblings and the younger control were formed and are available for genetic analyses (e.g. linkage studies and genome-wide association studies). Mortality follow-up improves the possibility of identifying families with the most extreme longevity phenotypes. With a mean follow-up time of 3.7years the number of families with all participating siblings aged 95years or more has increased by a factor of 5 to 750 families compared to when interviews were conducted. Thus, the GEHA project represents a unique source in the search for genes related to healthy ageing and longevity. In 2004, the integrated European project GEHA (Genetics of Healthy Ageing) was initiated with the aim of identifying genes involved in healthy ageing and longevity. The first step in the project was the recruitment of more than 2500 pairs of siblings aged 90years or more together with one younger control person from 15 areas in 11 European countries through a coordinated and standardised effort. A biological sample, preferably a blood sample, was collected from each participant, and basic physical and cognitive measures were obtained together with information about health, life style, and family composition. From 2004 to 2008 a total of 2535 families comprising 5319 nonagenarian siblings were identified and included in the project. In addition, 2548 younger control persons aged 50-75years were recruited. A total of 2249 complete trios with blood samples from at least two old siblings and the younger control were formed and are available for genetic analyses (e.g. linkage studies and genome-wide association studies). Mortality follow-up improves the possibility of identifying families with the most extreme longevity phenotypes. With a mean follow-up time of 3.7years the number of families with all participating siblings aged 95years or more has increased by a factor of 5 to 750 families compared to when interviews were conducted. Thus, the GEHA project represents a unique source in the search for genes related to healthy ageing and longevity.

Udgivelsesdato: 2007-Apr The aim of the 5-year European Union (EU)-Integrated Project GEnetics of Healthy Aging (GEHA), constituted by 25 partners (24 from Europe plus the Beijing Genomics Institute from China), is to identify genes involved in healthy aging and longevity, which allow individuals to survive to advanced old age in good cognitive and physical function and in the absence of major age-related diseases. To achieve this aim a coherent, tightly integrated program of research that unites demographers, geriatricians, geneticists, genetic epidemiologists, molecular biologists, bioinfomaticians, and statisticians has been set up. The working plan is to: (a) collect DNA and information on the health status from an unprecedented number of long-lived 90+ sibpairs (n = 2650) and of younger ethnically matched controls (n = 2650) from 11 European countries; (b) perform a genome-wide linkage scannning in all the sibpairs (a total of 5300 individuals); this investigation will be followed by linkage disequilibrium mapping (LD mapping) of the candidate chromosomal regions; (c) study in cases (i.e., the 2650 probands of the sibpairs) and controls (2650 younger people), genomic regions (chromosome 4, D4S1564, chromosome 11, 11.p15.5) which were identified in previous studies as possible candidates to harbor longevity genes; (d) genotype all recruited subjects for apoE polymorphisms; and (e) genotype all recruited subjects for inherited as well as epigenetic variability of the mitochondrial DNA (mtDNA). The genetic analysis will be performed by 9 high-throughput platforms, within the framework of centralized databases for phenotypic, genetic, and mtDNA data. Additional advanced approaches (bioinformatics, advanced statistics, mathematical modeling, functional genomics and proteomics, molecular biology, molecular genetics) are envisaged to identify the gene variant(s) of interest. The experimental design will also allow (a) to identify gender-specific genes involved in healthy aging and longevity in women and men stratified for ethnic and geographic origin and apoE genotype; (b) to perform a longitudinal survival study to assess the impact of the identified genetic loci on 90+ people mortality; and (c) to develop mathematical and statistical models capable of combining genetic data with demographic characteristics, health status, socioeconomic factors, lifestyle habits.