Survival to extreme ages clusters within families. However, identifying genetic loci conferring longevity and low morbidity in such longevous families is challenging. There is debate concerning the survival percentile that best isolates the genetic component in longevity. Here, we use three-generational mortality data from two large datasets, UPDB (US) and LINKS (Netherlands). We study 20,360 unselected families containing index persons, their parents, siblings, spouses, and children, comprising 314,819 individuals. Our analyses provide strong evidence that longevity is transmitted as a quantitative genetic trait among survivors up to the top 10% of their birth cohort. We subsequently show a survival advantage, mounting to 31%, for individuals with top 10% surviving first and second-degree relatives in both databases and across generations, even in the presence of non-longevous parents. To guide future genetic studies, we suggest to base case selection on top 10% survivors of their birth cohort with equally long-lived family members.

Research into the genetic component of human longevity can provide important insights in mechanisms that may protect against age-related diseases and multi-morbidity. Thus far only a limited number of robust longevity loci have been detected in either candidate or genome wide association studies. One of the issues in these genetic studies is the definition of the trait being either lifespan, including any age at death or longevity, i.e. survival above a diverse series of thresholds. Likewise heritability and segregation research have conflated lifespan with longevity. The heritability of lifespan estimated across most studies has been rather low. Environmental factors have not been sufficiently investigated and the total amount of genetic variance contributing to longevity has not been estimated in sufficiently well-defined and powered studies. Up to now, genetic longevity studies lack the required insights into the nature and size of the genetic component and the optimal strategies for meta-analysis and subject selection for Next Generation Sequencing efforts. Historical demographic data containing deep genealogical information may help in estimating the best definition and heritability for longevity, its transmission patterns in multi-generational datasets and may allow relevant additive and modifying environmental factors such as socio-economic status, geographical background, exposure to environmental effects, birth order, and number of children to be included. In this light historical demographic data may be very useful for identifying lineages in human populations that are worth investigating further by geneticists.

Human ageing is an extremely personal process leading across the life course of individuals to large population heterogeneity in the decline of functional capacity, health and lifespan. The extremes of this process are witnessed by the healthy vital 100-year-olds on one end and the 60-year-olds suffering from multiple morbid conditions on the other end of the spectrum. Molecular studies into the basis of this heterogeneity have focused on a range of endpoints and methodological approaches. The phenotype definitions most prominently investigated in these studies are either lifespan-related or biomarker based indices of the biological ageing rate of individuals and their tissues. Unlike for many complex, age-related diseases, consensus on the ultimate set of multi-biomarker ageing or lifespan-related phenotypes for genetic and genomic studies has not been reached yet. Comparable to animal models, hallmarks of age-related disease risk, healthy ageing and longevity include immune and metabolic pathways. Potentially novel genomic regions and pathways have been identified among many (epi)genomic studies into chronological age and studies into human lifespan regulation, with APOE and FOXO3A representing yet the most robust loci. Functional analysis of a handful of genes in cell-based and animal models is ongoing. The way forward in human ageing and longevity studies seems through improvements in the interpretation of the biology of the genome, in application of computational and systems biology, integration with animal models and by harmonization of repeated phenotypic and omics measures in longitudinal and intervention studies. This article is part of a Special Issue entitled: Model Systems of Aging - edited by "Houtkooper Riekelt".

Members of longevous families live longer than individuals from similar birth cohorts and delay/escape age-related diseases. Insight into this familial component of longevity can provide important knowledge about mechanisms protecting against age-related diseases. This familial component of longevity was studied in the Leiden Longevity Study which consists of 944 longevous siblings (participants), their parents (N = 842), siblings (N = 2,302), and spouses (N = 809). Family longevity scores were estimated to explore whether human longevity is transmitted preferentially through the maternal or paternal line. Standardized mortality ratios (SMRs) were estimated to investigate whether longevous siblings have a survival advantage compared with longevous singletons and we investigated whether parents of longevous siblings harbor a life-long sustained survival advantage compared with the general Dutch population by estimating lifetime SMRs (L-SMRs). We found that sibships with long-lived mothers and non-long-lived fathers had 0.41 (p = .024) less observed deaths than sibships with long-lived fathers and non-long-lived mothers and 0.48 (p = .008) less observed deaths than sibships with both parents non-long lived. Participants had 18.6 per cent less deaths compared with matched singletons and parents had a life-long sustained survival advantage (L-SMR = 0.510 and 0.688). In conclusion, genetic longevity studies may incorporate the maternal transmission pattern and genes influencing the entire life-course of individuals.

Globally, the lifespan of populations increases but the healthspan is lagging behind. Previous research showed that survival into extreme ages (longevity) clusters in families as illustrated by the increasing lifespan of study participants with each additional long-lived family member. Here we investigate whether the healthspan in such families follows a similar quantitative pattern using three-generational data from two databases, LLS (Netherlands), and SEDD (Sweden). We study healthspan in 2143 families containing index persons with 26 follow-up years and two ancestral generations, comprising 17,539 persons. Our results provide strong evidence that an increasing number of long-lived ancestors associates with up to a decade of healthspan extension. Further evidence indicates that members of long-lived families have a delayed onset of medication use, multimorbidity and, in mid-life, healthier metabolomic profiles than their partners. We conclude that both lifespan and healthspan are quantitatively linked to ancestral longevity, making family data invaluable to identify protective mechanisms of multimorbidity.

It remains unknown how different types of sources affect the reconstruction of life courses and families in large-scale databases increasingly common in demographic research. Here, we compare family and life-course reconstructions for 495 individuals simultaneously present in two well-known Dutch data sets: LINKS, based on the Zeeland province’s full-population vital event registration data (passive registration), and the Historical Sample of the Netherlands (HSN), based on a national sample of birth certificates, with follow-up of individuals in population registers (active registration). We compare indicators of fertility, marriage, mortality, and occupational status, and conclude that reconstructions in the HSN and LINKS reflect each other well: LINKS provides more complete information on siblings and parents, whereas the HSN provides more complete life-course information. We conclude that life-course and family reconstructions based on linked passive registration of individuals constitute a reliable alternative to reconstructions based on active registration, if case selection is carefully considered.