Hum Genet (2006) 119: 312–321 DOI 10.1007/s00439-006-0144-y

ORIGINAL INVESTIGATION

Jacob vB. Hjelmborg Æ Ivan Iachine Æ Axel Skytthe James W. Vaupel Æ Matt McGue Æ Markku Koskenvuo Jaakko Kaprio Æ Nancy L. Pedersen Æ Kaare Christensen Genetic influence on human lifespan and

Received: 2 December 2005 / Accepted: 6 January 2006 / Published online: 4 February 2006 Springer-Verlag 2006

Abstract There is an intense search for longevity genes chance is higher for MZ than for DZ twins. The rela- in both animal models and humans. Human family tive recurrence risk of reaching age 92 is 4.8 (2.2, 7.5) studies have indicated that a modest amount of for MZ males, which is significantly greater than the the overall variation in adult lifespan (approximately 1.8 (0.10, 3.4) for DZ males. The patterns for females 20–30%) is accounted for by genetic factors. But it is and males are very similar, but with a shift of the not known if genetic factors become increasingly female pattern with age that corresponds to the better important for survival at the oldest ages. We study the female survival. Similar results arise when considering genetic influence on human lifespan and how it varies only those Nordic twins that survived past 75 years of with age using the almost extinct cohorts of Danish, age. The present large population based study shows Finnish and Swedish twins born between 1870 and genetic influence on human lifespan. While the esti- 1910 comprising 20,502 individuals followed until mated overall strength of genetic influence is compati- 2003–2004. We first estimate mean lifespan of twins by ble with previous studies, we find that genetic lifespan of co-twin and then turn to the relative influences on lifespan are minimal prior to age 60 but recurrence risk of surviving to a given age. Mean life- increase thereafter. These findings provide a support span for male monozygotic (MZ) twins increases 0.39 for the search for genes affecting longevity in humans, [95% CI (0.28, 0.50)] years for every year his co-twin especially at advanced ages. survives past age 60 years. This rate is significantly greater than the rate of 0.21 (0.11, 0.30) for dizygotic (DZ) males. Females and males have similar rates and these are negligible before age 60 for both MZ and DZ pairs. We moreover find that having a co-twin surviv- Introduction ing to old ages substantially and significantly increases the chance of reaching the same old age and this The success in identifying longevity genes in Nematoda, Drosophila and mouse has facilitated large scale efforts to identify longevity genes in humans (Johnson 2005). Human studies have suggested a moderate clustering of J. vB. Hjelmborg (&) Æ I. Iachine Æ A. Skytthe J. W. Vaupel Æ K. Christensen extreme longevity within families (Kerber et al. 2001; Institute of Public Health, University of Southern Denmark, Perls and Dellara 2003), and twin studies have indicated J. B. Winslovsvej 9 B, 5000 Odense C, Denmark that approximately 20–30% of the overall variation in E-mail: [email protected] lifespan can be attributed to genetic factors (Herskind Tel.: +45-6-5503375 et al. 1996; Ljungquist et al. 1998; Skytthe et al. 2003). Fax: +45-6-5503345 Our aim is to study the age dependence of genetic M. McGue influence on lifespan. Survival to older ages, e.g. 75, Department of Psychology, University of Minnesota, could change the genetic influence on lifespan in either Minneapolis, MN, USA direction. That is, removing early deaths could induce a M. Koskenvuo Æ J. Kaprio reduction in genetic influence because the influence of Department of Public Health, University of Helsinki, genetic diseases with high early mortality such as Helsinki, Finland familial hypercholesterolemia and cystic fibrosis (genetic diseases with increased mortality at younger ages) are N. L. Pedersen Department of Medical Epidemiology and Biostatistics, removed. On the other hand, many violent deaths are Karolinska Institute, Stockholm, Sweden excluded when considering only those who survived to 313 older ages and this could increase genetic influences, like-sexed twins. For twins dying or emigrating at an relatively speaking, by removing early ‘random’ deaths. early age it was impossible to obtain reliable data to be Knowing whether total genetic influences increase, used in zygosity classification. Consequently, pairs were remain constant or decrease with age may contribute to not followed-up if one or both partners died or emi- efforts of identifying genes that affect human lifespan, grated before age 6. The validity of zygosity classifica- and provide information about the feasibility of (envi- tion based on answers to mailed questionnaires has been ronmental) interventions. evaluated by comparison with the results of later blood Surviving to a given age is probably a multifactorial group determinants and the misclassification rate has phenotype involving multiple biological processes, been found to be less than 5% (Hauge 1981; Chris- environmental influences and randomness. In particular, tiansen et al. 2003). it has been speculated whether and how genes are The Danish sample used in the present study consists involved in reaching the highest ages, which are central of 4,890 pairs of like-sex twins for which both members questions to the many ongoing efforts aimed at identi- survived 6 years of age. Twins born between 1870 and fying longevity-genes (Tan et al. 2004). As mentioned 1910 have been followed up through January 8th 2005, family studies have shown a moderate clustering of at which time their mortality status and hence lifespan extreme longevity within families. However, traditional was determined. The cohort is almost extinct (in 98% of family studies cannot, unlike twin studies, disentangle pairs both twins are dead) and the youngest surviving the effect of genes and environment. Furthermore, even twin was at least 94 years of age at last follow up. if genetic in origin this finding may be due to a clustering of genetic effects in certain families only and thus may not be detectable in populations. The Swedish twin registry To study longevity in a population a large study base is required. To this end, we were able to consider data The Swedish twin registry, which covers all twin births from the Swedish, Finnish and Danish national twin in Sweden between 1886 and 2002, was started in 1959, registries as part of the GenomEUtwin project. These by contacting all parish offices in Sweden to obtain jointly comprise the largest population-based sample of information on all twin births between 1886 and 1925. twins with almost complete lifespans ever studied. These Through contacts with the parishes, twins’ residences cohorts of Nordic twins show good representativeness were followed through 1947, when the Swedish per- for longevity studies. After infancy, twin cohorts have sonal registration number (PNR) was initiated. mortality rates similar to the background population Through parish records in 1947, PNR could be (Christensen et al. 1995; Vagero and Leon 1994). This recorded and subsequently matched to the national persists when comparing mortality rates of various population registry. All like-sexed pairs living in major causes of death (Christensen et al. 2001), indi- Sweden in 1960 were contacted by a postal ques- cating that twin survival is a good model for studying tionnaire. Information on intrapair similarity (for longevity. subsequent assignment of zygosity) and smoking status was collected at this time. Only the information from pairs in which both responded was kept and recorded. Materials and methods Zygosity determination has been validated in several studies, some including DNA markers, and is 98% Participants in the study consist of MZ and same sex DZ accurate (Lichtenstein et al. 2002). The register is up- pairs from the Danish, Finnish and Swedish twin dated for changes in vital status and addresses on a cohorts born between 1870 and 1910. monthly basis. (Cederlo¨ f 1966; Lichtenstein et al. 2002). The sample of Swedish twins used in this study con- sisted of 4,694 pairs of like-sexed twins born during The Danish twin registry 1886–1910, where both members were alive and living in Sweden as of the 1st of March 1961. Hence twins from This registry was established in 1954 as the first the youngest and oldest birthyears had to survive until nationwide twin registry in the world (Hauge 1981; the age of 51 and 75, respectively, and the sample thus Hauge et al. 1968). The birth registers from all 2,200 does not contain early deaths. For this study, the cohort parishes of the relevant calendar years were manually has been followed up through 14th of November 2003. scrutinized to identify all twin births. Through regional Hence the minimum age for a twin who is still alive at population registers (in operation since 1924) and other the end of follow up is 92 years of age. public sources, a search was made for the twins, or The Finnish Twin Cohort Study was started in 1974. whenever needed, their closest relatives. As soon as a All sets of persons born on the same day, in the same twin was traced, a questionnaire was sent to him or her. local community, of the same-sex and with the same If neither of the partners was alive, a questionnaire was surname at birth were identified to form the basis of the sent to the closest relative. Specific questions about the older Twin Cohort of twins born before 1958. A ques- degree of similarity between the partners of a pair were tionnaire mailed in 1975 to all pairs with both twins alive included in the questionnaire to assess zygosity in in 1974 was used to establish twinship and zygosity 314

(Kaprio et al. 1978), while further enquiries to local Conditional lifespan parish records and population registers was used to clarify whether subjects fulfilling the selection criteria We consider the analysis of regression of twin on co-twin were biological twins. This particular cohort of twins lifespan: DeFries and Fulker (1985) have shown how was subsequently contacted again in 1981 and 1990. twin similarity for a quantitative trait can be assessed by Zygosity has been determined by a very accurate and regressing the score of one twin on another. In general, validated deterministic algorithm (Sarna et al. 1978). the resulting regression coefficient is an estimate of the Vital status and causes of death are updated by com- corresponding twin correlation under the assumption of puter linkage using the unique personal identification symmetry between twin and co-twin (Rodgers and numbers assigned in the 1960s and consequently at birth McGue 1994). We use a regression approach to assess to all Finnish citizens and residents. Linkage is done MZ and DZ twin similarity for lifespan in the overall with the Population Register Centre of Finland (http:// sample as well as in subsets of the sample defined by www.vaestorekisterikeskus.fi) and Statistics Finland co-twin age at death. Pearson and Lawley (Aitken 1934) (Kaprio and Koskenvuo 2002). have shown that the regression coefficient is unaffected The Finnish sample used in this study consists of 667 by selection on the independent variable if the overall like-sexed pairs of twins born during 1880–1910, where regression is linear. Consequently, by conditioning on both members were alive and living in Finland as of 1st co-twin age at death we are able to determine whether of January 1974. Hence twins from the youngest and twin similarity for age at death is constant or varies oldest birthyears had to survive until the age of 64 and across the lifespan. Difference between regression slopes 94, respectively in order to be included, and the sample of MZ and DZ twins indicates the presence of genetic thus does not contain early deaths. effects. Because of the sex difference in lifespan, all For this study, the cohort is followed up through 1st analyses are conducted separately in the male and female of July 2003, so the minimum age for a twin who is still samples. alive at the end of follow up is 92 years of age. For this analysis, we use the almost extinct cohorts of Swedish, Danish and Finnish twins born between 1870 and 1910. To handle the differences in sampling proce- Analyses of twin similarity dures, we stratify the data into the two samples; the Danish twins surviving past age 6 and the combined The concept of age-specific genetic influence on the cohort of Swedish and Finnish twins surviving respective human lifespan is somewhat difficult to formalize, when dates of entrance. Expected lifespan conditional on compared to the question of age-specific genetic influ- co-twin lifespan is estimated for each sample. Estimates ences on a truly age-dependent phenotype, e.g. body are obtained in two ways from pairs in which both mass index (BMI). In the latter case, a distinct pheno- members were dead at last follow-up (9,956 out of type is defined at any age (e.g. BMI at age 60), it can be 10,251 pairs): as mean lifespan of twins over 5-year measured and studied using the traditional methods of intervals of co-twin lifespan and as the smoothed genetic analysis, yielding an age-trajectory of heritability expected lifespan of twins given lifespan of co-twin by of BMI. However, in the case of human longevity, there the lowess-method with bandwidth parameter 0.8 is only one phenotype for each individual: age at death, (Chambers et al. 1983; Stata Statistical Software College and it is therefore not as straightforward to define an Station 2005). Hence, we obtain graphs of expected age-specific measure of genetic influence on longevity, as lifespan of twin by lifespan of co-twin for MZ and DZ for BMI. We remark that one may consider ‘years of life twins. To further quantify twin similarity conditional on after a certain age’ as the phenotype and applying tra- co-twin age at death, we regress twin lifespan on co-twin ditional methods to the sample truncated by a given age, lifespan within specified intervals of co-twin age at death i.e. by taking all pairs where both members have sur- (e.g. after age 15, before 60, 60+, 75+ and age 85+). vived past that age. This procedure may be repeated for Data were double-entered since every twin is also a each chosen age cut-off. However, the estimation of co-twin. Due to within pair dependence, however, the heritability in remaining lifespan at each age of death robust variance estimator was used to take pair cluster- (year) by successive application of the polygenic model ing into account (Rogers 1993). Inferences were carried to each stratum defined by truncation of lifespan may out using standard methods (95% CI, two-sided t test). cause serious bias as pointed out in Martin and Wilson (1982) and in Iachine (2004). In our analysis, we consider two approaches. The first Survival to given age is based on studying the of MZ and DZ twins while conditioning on the co-twin lifespan in order To investigate the presence of genetic influences on to narrow the focus to certain age groups. In the second human lifespan, we also consider the dichotomous approach, we use the lifespan variable to define an age- phenotype of surviving to a given age. We compare dependent dichotomous phenotype (survival until a MZ and DZ twins with respect to relative recurrence given age) and analyse it using the traditional methods risk and tetrachoric correlation in reaching a certain of analysis for binary traits. age. From estimates of such measures for each year 315 from 6 to 92 years of age for MZ and DZ twins, we ensuring identical and complete ascertainment in all obtain an indication of possible genetic influence at three countries. Hence for the latter group who have various stages in life, including survival at the oldest already reached age 75, we study the presence of genetic ages. Greater MZ than DZ similarity in the above influences on remaining survival to a given age from 75 measures suggests a genetic influence under the equal to 92 years. environment assumption of MZ and DZ pairs (Neale Analyses are carried out using the Stata statistical and Cardon 1992). software (Efron and Tibshirani 1986; Stata Statistical The prevalence and the relative recurrence risk, k,of Software College Station 2005). A significance level of surviving up to a certain age defined as the ratio of the 5% is used. chance a twin reached a certain age given that the co-twin reached that age to the prevalence of reaching that age in the whole (sex-specific) twin population, are Results estimated using the maximum likelihood estimators given in for instance (Witte et al. 1999). We obtain an The Swedish, Finnish and Danish twin cohorts born estimator of k as the ratio of probandwise concordance before 1910 altogether comprise 9,272 male twins and rate to the prevalence estimates. Standard bootstrap 11,230 female twins. Numbers of twin pairs by methods (Efron and Tibshirani 1986) are used for the zygosity and gender are listed in Table 1 and ordered comparison of prevalence and probandwise concor- by pairs in which both survive, only one survived and dance rate for MZ and DZ pairs for each age and for neither survived up to a given age. Furthermore, constructing 95% confidence intervals. numbers are listed for those who survived past age 6 Differences in favour of MZ to DZ twins in above (Danish cohort born 1870–1910) and for those who relative recurrence risks suggest the presence of genetic survived past age 75 (Swedish, Finnish and Danish influences. For high prevalences, a small difference cohort born 1900–1910). between MZ and DZ concordance rates does not nec- essarily imply little genetic influence. This motivates a supplemental measure of similarity. A measure of Conditional lifespan similarity that relates to the polygenic model of quan- titative genetics is the tetrachoric correlation, i.e. the A graphical presentation of twin similarity for lifespan correlation in the bivariate normal distribution of in the Danish sample is given in Fig. 1 and for the (continuous) liability to survive to a given age (Neale combined Swedish and Finnish sample in Fig. 2. The and Cardon 1992). Briefly, the twin survives if the individual data points are the mean twin lifespans over liability to survive to a given age exceeds a certain 5-year intervals of co-twin age at death and the threshold. The tetrachoric correlation in surviving to a smoothed curves are obtained by lowess smoothing. The given age is then the correlation in twin liability. We mean lifespan of twins increases with co-twin lifespan estimate tetrachoric correlations for MZ and DZ pairs and this trend occurs more rapidly for MZ than for DZ by standard maximum likelihood methods (Kohler and twins when the co-twin exceeds approximately age 60 for Rodgers 1999). both males and females. Before age 60 no systematic The trait of survival to a given age is estimated for change in mean lifespan is observed for both MZ and two samples; First, the Danish cohort of twins born DZ pairs, males and females (Fig. 1 and Table 2). between 1870 and 1910 consisting of twins surviving Regressing twin lifespan on co-twin age at death for the 6 years of age and secondly for the Nordic cohort of Danish sample gives an overall regression coefficient of Danish, Swedish and Finnish cohorts born during 1900– 0.15 in MZ males with 95% CI (0.08, 0.22) and 0.10 1910 in which both twins survived past 75 years of age (0.04, 0.15) in DZ males; the comparable values in the

Table 1 Number of twin pairs by age (in years) survived past

Age MZ male DZ male MZ female DZ female

Danish pairs—both survived past age 6 years 25+ 813/42/4 1,386/119/2 823/52/5 1,512/127/5 75+ 263/318/278 349/681/477 364/346/170 561/736/347 85+ 54/197/608 67/357/1,083 116/287/477 167/580/897 Swedish, Danish, Finnish pairs—both survived past age 75 years 75+ 397/25/2 581/62/1 618/27/2 1,120/79/0 80+ 219/151/54 290/279/75 449/156/42 754/382/63 85+ 106/163/155 108/287/249 234/271/142 374/558/267 90+ 30/109/285 28/169/447 93/218/336 103/439/657

Danish cohort born during 1870–1910, where both survived past age 6 years in the upper-half of the table. The combined Swedish, Danish and Finnish cohort born 1900–1910 and where both survived past age 75 years in the lower-half of the table. Numbers are listed in the order ’both survived/one survived/neither survived’ eae,respectively) females, and (males sample whole lines 0.8). (bandwidth smoothing lowess from arise by respectively) females, and (males sample whole lines 0.8). (bandwidth smoothing lowess from circles hollow ntelwrhl ftetbe(e h etfricuinciei) ubr netisaesoe tnaderradnme fpairs, of number and error standard slope, are entries in Numbers criteria). 1910 and inclusion 1886 for between born text cohort the Finnish and (see Swedish combined table the the and upper-half of respectively the lower-half in 1910 the and in 1870 between born cohort Danish 1886–1910 cohort joint Finnish and Swedish (>15) All 1870–1910 cohort Danish Age 2 Table by twins (MZ co-twin year of 5 interval lifespan given twin of lifespan deaths. early excluding 1886–1910 twin cohort joint Finnish and of Swedish co-twin of lifespan given 2 Fig. twins by (MZ co-twin of lifespan interval year 5 given twin Dots 1870–1910. cohort twin of Danish co-twin of lifespan given 1 Fig. 316 Z .2(.3 97 .4(.4 98 .3(.8 (604) (1,228) (0.08) (0.06) 0.43 0.30 (355) (565) (0.11) (0.11) 0.42 0.20 (1,808) (0.03) (918) 0.17 (0.04) 0.34 (1,213) (0.04) (716) 0.20 (0.05) 0.41 (1,930) (0.02) 0.17 (987) (0.03) 0.32 (1,380) (0.03) 0.15 (829) (0.03) 0.43 (385) (0.25) 0.64 (710) (0.18) 0.04 – (245) (0.31) 0.71 – – (692) (1,260) (0.10) (0.08) 0.36 0.25 – (575) (0.11) 0.39 (1,526) (0.05) (829) 0.19 (0.06) 0.30 (817) (0.06) – 0.39 (588) (0.06) (248) 0.02 (0.10) – 0.00 – (285) (0.10) – DZF 0.00 MZF (1,607) (0.03) 0.08 DZM (862) (0.04) 0.18 MZM (1,500) (0.03) 0.10 (851) (0.04) 0.15 DZF MZF DZM MZM olwcircles hollow oi circles solid r enlfsa o the for lifespan mean are the for lifespan mean are eoema iepnof lifespan mean denote enlfsa ftwin of lifespan Mean twin of lifespan Mean ersinsoeo xetdlfsa ftiscniinlo iepnitra fco-twin of interval lifespan on conditional twins of lifespan expected of slope Regression oi circles solid .Tecre arise curves The ). Dots Ztisby twins DZ , .Tecurves The ). Horizontal Horizontal eoemean denote Ztwins DZ , À £ .1(.5 51 .1(.5 148 .3(.9 103 .0(.5 (417) (0.25) 0.00 (1,023) (0.09) 0.23 (1,418) (0.05) 0.21 (581) (0.05) 0.01 0>0>5>85 >75 >60 60 Mean lifespan Mean lifespan Graphs bysex Graphs bysex 70 80 90 60 70 80 90 50 20 30 60 40 50 70 male male 60 80 70 Zlfsa DZlifespan MZ lifespan Zlfsa DZlifespan MZ lifespan 80 90 Cotwin lifespan Cotwin lifespan 90 100 100 20 50 30 60 40 50 70 female female 60 80 70 80 90 90 100 100 317 female sample are 0.18 (0.10, 0.26) and 0.08 (0.03–0.13), To sum up, Table 2 gives estimates of the regression respectively (see Table 2). These values are clearly con- coefficients that show (1) prior to age 60 (and after age 6) sistent with a modest heritability as estimated in previ- there is no indication of similarity in twin age at death; ous research. The relationship depicted in the figures, (2) From age 60 co-twin age at death is significantly however, suggests that the magnitude of twin similarity predictive of twin lifespan. For MZ twins lifespan is for lifespan varies with age. increasing approximately 0.40 years in males and As Figs. 1 and 2 indicate the mean lifespan of twins 0.35 years in females for every additional year of co-twin tends to be proportional to co-twin lifespan when life from age 60 to at least age 85. For DZ twins, the co-twin lifespan exceeds 60 years (to at least 90 years). increase in lifespan is approximately 0.20 years in males By linear regression, the increase in mean lifespan for and 0.25 years in females for every additional year of Danish male MZ pairs is estimated at 0.39 year per co-twin life from age 60 to at least age 85. These data co-twin lifespan year with 95% CI (0.28, 0.50) when thus suggest minimal genetic effects on lifespans less co-twin lifespan exceeds 60 years (see Table 2). For than age 60 and moderate genetic effects on lifespans male DZ pairs, the rate is 0.21 (0.11, 0.30) and the greater than age 60. difference between MZ and DZ rates is significant The above estimates, obtained from pairs born be- (P<0.01). For Danish females, the increase in mean fore 1910 in which both members were dead at last lifespan is 0.30 (0.19, 0.42) for MZ pairs and 0.19 follow-up (9,956 out of 10,251 pairs), were practically (0.10, 0.29) year per co-twin lifespan year for DZ pairs unchanged when considering earlier, but extinct birth when co-twin lifespan exceeds 60 years; however, the cohorts indicating that the results are less sensitive to difference is not significant (P=0.14) in this case. the applied mild censoring concerning relatively few These differences remain or increase when co-twin pairs. Furthermore, restricting the combined Swedish lifespan exceeds older ages (75 and 85 years) as given and Finnish sample to the 1900–1910 birthcohort did in Table 2. The rates from the Danish sample with not affect results. The Danish sample with complete complete follow-up (i.e. survival past age 6) agree very follow-up (i.e. survival past age 6) showed virtually well with those estimated in the combined Swedish and unchanged estimates of regression slopes when the Finnish sample presented in Table 2, except possibly Swedish inclusion criteria were implemented on the for the highest age group. The Swedish and Finnish data, except from age 85 (results not shown). This sample shows a pattern of increase in mean lifespan indicates relative robustness of slopes towards the with co-twin lifespan (after age 60) for MZ and DZ truncation by date. From age 85, estimates of slope pairs that is consistent with a constant genetic influ- were very similar to those obtained from the combined ence on lifespan with age. For Swedish and Finnish Swedish and Finnish sample. male MZ pairs the rates are 0.43, 0.41 and 0.42 year per co-twin lifespan when co-twin lifespan exceeds age 60, 75 and 85, respectively, while for male DZ pairs Survival to given age the corresponding rates are 0.15, 0.20 and 0.20. Swedish and Finnish females show similar estimates Prevalence and relative recurrence risk for reaching a (0.32, 0.34 and 0.43 for MZ and 0.17, 0.17 and 0.30 given age from age 6 to age 92 was estimated for the for DZ pairs when co-twin lifespan exceeds age 60, 75 Danish cohort 1870–1910. The prevalence decreases with and 85, respectively). Hence the difference between MZ age as expected. There is no indication of systematic and DZ slopes shown in Table 2 remains almost difference in prevalence for MZ and DZ pairs (results not constant with increasing age and the differences are shown). Estimates of the relative recurrence risk of sur- significant (P< 0.001) except when co-twin lifespan viving to a given age are presented in Table 3 (including exceed 85 years (where P-values are 0.16 and 0.19 for inference results). The relative recurrence risk of surviv- males and females, respectively). ing up to some age from age 6 to 60 is close to 1 for both

Table 3 Relative survival probabilities of twins given survived age of co-twin compared with the prevalence of survived age for twins, i.e. relative recurrence risks by age

Age MZ male DZ male MZ female DZ female

25+ 1.00 (1.00, 1.01) 1.00 (1.00, 1.00) 1.00 (1.00, 1.01) 1.00 (1.00, 1.00) 50+ 1.00 (0.99, 1.01) 1.01 (1.00, 1.02) 1.01 (1.00, 1.02) 1.00 (0.99, 1.01) 60+ 1.01 (0.99, 1.03) 1.01 (0.99, 1.02) 1.02 (1.00, 1.03) 1.01 (1.00, 1.02) 70+ 1.11 (1.07, 1.15) 1.05 (1.02, 1.09) 1.05 (1.02, 1.07) 1.02 (1.00, 1.05) 75+ 1.27 (1.20, 1.34) 1.11 (1.05, 1.17) 1.11 (1.07, 1.15) 1.07 (1.03, 1.11) 80+ 1.43 (1.27, 1.58) 1.23 (1.11, 1.35) 1.20 (1.12, 1.27) 1.18 (1.12, 1.24) 85+ 1.99 (1.60, 2.39) 1.68 (1.37, 1.98) 1.52 (1.34, 1.69) 1.31 (1.18, 1.45) 90+ 3.58 (2.12, 5.03) 1.88 (0.82, 2.95) 2.18 (1.68, 2.68) 1.43 (1.08, 1.78) 92+ 4.83 (2.17, 7.49) 1.76 (0.07, 3.45) 2.50 (1.71, 3.29) 1.57 (1.03, 2.11)

Parentheses: 95% confidence intervals. Danish twin cohort born during 1870–1910 and survived age 6 years 318

MZ and DZ twins. For this age interval of relatively high For the Nordic elderly who already survived past prevalence genetic effects in surviving to these ages still 75 years of age presented in Fig. 3, MZs are significantly may be present as noted above but not reflected in the more correlated than DZs and the difference remains relative recurrence risk measure. Starting from around relatively constant with age for both males and females. age 60, the relative recurrence risk increases with This indicates a constant and significant heritability in increasing survived age for both male and female twins liability to reaching a given age due to genetic effects of and is higher for MZ twins than DZ twins. Also, power the total variance, i.e., the heritability, from 75 to for detecting this difference in recurrence risk increases at 92 years of age for this selected group who already this age range as individuals die. Furthermore, the dif- reached age 75. Moreover, this is compatible with the ference in relative recurrence risk between MZ twins and observed almost constant increase in difference between DZ twins in Table 3 increases with age from age 60 and MZ and DZ relative recurrence rates shown in Fig. 3. onwards indicating survival advantage with age due to The results presented above persist when stratifying genetic effects in both males and females. by country, i.e. the same patterns of change in the sim- The differences between MZ and DZ pairs are sig- ilarity measures for MZ and DZ pairs were observed for nificant (P<0.01) at each age. It is noteworthy that the Swedish, Finnish and Danish cohorts separately the estimates of relative recurrence risk similar to those although differences in mortality rates exist among the for males are found for females at a 5–10 year higher three countries. Similarly, changing the birthcohort age range as seen from Table 3. For the highest age either by narrowing or widening the defining birthyear group, the relative risk of a female MZ twin reaching interval had no observed influence on the results. age 92 given that her co-twin reached this age is 2.5 (1.7–3.3) compared to the risk of reaching age 92 for female twins generally. For DZ female twins, the Discussion relative recurrence risk of reaching age 92 is 1.6 (1.03– 2.1). For males, the relative recurrence risk for reach- Based on a large population-based and almost exhaus- ing age 92 it is 4.8 (2.2,7.5) for MZ and 1.8 (0.1,3.4) tive sample of twins more than 90 years of follow up, we for DZ pairs. find evidence of familial clustering of longevity. The Figure 3 presents the relative recurrence rate by age present study is the first to demonstrate that at popu- for the restricted cohort of those Nordic twins born lation level genetic variants for survival may exist with a during 1900–1910, where both survived past 75 years of pattern compatible with a significant and constant age. The relative recurrence risk is 1 for both MZ and to increasing influence of genetic factors with age. That DZ pairs at age 75 and then the same pattern evolves as is, we find among elderly that the difference in mean above of increasing differences in relative recurrence risk lifespan of twins by co-twin lifespan is in favour of MZ between MZ twins than DZ twins with increasing age twins relative to DZ twins and increases with age. Fur- for both males and females. This clearly indicates the thermore, our findings indicate a proportional change in presence of genetic influence at old ages. lifespan by co-twin lifespan for both MZ and DZ pairs

Fig. 3 Twin pairs surviving Males Females past age 75 years only. Tetrachoric correlation (left 1 2 vertical axis) and relative recurrence rate, RRR (right vertical axis) of twin pairs by .8 survived age. Swedish, Finnish 1.8 and Danish cohort born during 1900–1910 and survived past .6 age 75 years 1.6 .4 1.4 Tetrachoric correlation .2 1.2 1 0 75 80 85 90 75 80 85 90 Survived Age MZ corr. DZ corr. MZ RRR DZ RRR 319 and that the rate of change is significantly higher for MZ may be studied using models accounting for time- than DZ pairs. These findings suggest minimal genetic dependent gene expression patterns that would predict effects on lifespans less than age 60 and moderate genetic genetic influence at various ages. For developing such effects on lifespans greater than age 60. Also, when models of quantitative genetics, our estimates of (dif- considering the chance of surviving to a certain age, we ference in) relative recurrence risk and correlation for observe a significantly stronger dependence on co-twin MZ and DZ pairs may serve as a useful guideline, since survival for MZ pairs than for DZ pairs among those results would need to be replicated or predicted by such aged 60 years or over. a unified model. During the last decade, a series of twin studies have In our study, we did not observe substantial differ- shown that approximately 20–30% of the overall varia- ences in prevalence of surviving to a given age between tion in lifespan is caused by genetic differences. This zygosity groups for all ages. The pattern of increasing seems to be a rather consistent finding in various Nordic relative recurrence risks with age is very similar for countries in different time periods and even so among males and females although with later onset for females, other species not living in the wild (Finch and Tanzi 1997; which corresponds to the better female survival. The Herskind et al. 1996; Ljungquist et al. 1998;Mousseau Nordic cohorts of twins are homogeneous on many and Roff 1987). Although we do not estimate heritability genetical and environmental factors and good agreement as a function of age, our findings support the existence of in the similarity measures was observed across cohorts such an influence at various stages in human lifespan, in (at ages where comparison is possible). particular among elderly (as seen from the significant Clustering of late deaths in a few families with many difference in MZ and DZ dependence measures). extreme long-living individuals has provided support for Two alternative views in gerontological research have a familial component. Perls and co-workers found that led to opposite predictions regarding the importance of the risk ratio of survival for siblings of centenarians genetic factors with age. First, is the expectation that the versus siblings of 73-year-old was about 4 for ages 80–94 accumulation of unique environmental exposures during (Perls et al. 1998; Perls and Dellara 2003). Kerber et al. a long life is the major determinant of lifespan and (2001) also found, based on Mormon genealogies, an health at older ages (Harris et al. 1992), which predicts increased recurrence risk for siblings for surviving to decreased heritability at older ages. Alternatively, evo- extreme ages, although the estimate was somewhat lower lutionary biologists have argued that the reduced selec- than found by Perls. Gudmundsson et al. (2000) using tive pressure against deleterious genetic the population-based genealogy in Iceland, found that expressed only late in life predicts an increase in genetic the first-degree relatives of the probands who live to an variance among the oldest (Partridge and Gems 2002). extreme old age (the 95% percentile) are twice as likely Our findings suggest that genetic effects are important as the controls to survive to the same age. It is note- for survival at older ages. These effects may arise either worthy that our results on relative survival risk by age through central pathways (‘longevity enabling genes’) or for DZ siblings (as seen in Table 3) are in good agree- indirectly through genes associated with disease or states ment with these findings regarding pattern of estimates of certain mortality risk (Johnson 2005). for both genders [see for instance, Perls and Dellara The validity of these findings assumes that environ- (2003)]. Furthermore, since based on twin cohorts, mental factors of importance for the trait act the same which allows for better disentanglement of environ- for MZ and DZ twins (the ‘equal environments mental and genetical origin of effects, our findings assumption’). Many such factors may be suspected (like strongly support that genetic effects are among the social support, closeness in residence, etc.) that would mechanisms in surviving to higher ages. inflate our estimates of genetic influence. However, the There is probably considerable genetic heterogeneity observed patterns in similarity of MZ and DZ pairs with for lifespan, and it is possible that in some families there age indicate a relatively constant advantage in survival is a considerable genetic component, but which accounts from moment to moment and the shift of this pattern for only a fraction of the variance in the population at with age between sexes merely suggests a genetic origin large. A similar scenario is found in breast cancer where of influences. twin studies (Lichtenstein et al. 2000) suggest a small The interpretation of our findings depends on the fact overall genetic contribution, but where the genes that the genetic influence measures we have considered BRCA1 and BRCA2 within some families confer a are cumulative in : The dichotomous phenotype major risk (Narod and Foulkes 1994). Some evidence for of survival until a given age and the conditional expected decreasing genetic susceptibility to death from coronary longevity by definition are not completely restricted to heart disease with age is given in (Marenberg et al. genetic effects in a specific age group. The genetic 1994). It is, however, suggested in (Zdravkovic et al. influence demonstrated may not necessarily be of local 2002) that genetic factors to coronary heart age-specific nature, e.g. in the sense of increased disease mortality are in operation throughout the entire expression of some deleterious or protective longevity lifespan. We note that genetic factors associated with genes at certain ages, but might also be due to genes one single high risk disease may be less influential at reducing mortality in the younger age groups. This issue older age groups. 320

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