Exceptional memory performance in the Long Life Family Study.

Research to understand variability at the highest end of the cognitive performance distribution has been scarce. Our aim was to define a cognitive endophenotype based on exceptional episodic memory (EM) performance and to investigate familial aggregation of EM in families from the Long Life Family Study (LLFS). Using a sample of 1911 nondemented offspring of long-lived probands, we created a quantitative phenotype, EM (memory z ≥ 1.5), and classified LLFS families as EM and non-EM families based on the number of EM offspring. We then assessed differences in memory performance between LLFS relatives in the parental generation of EM families and those in non-EM families using multivariate analysis adjusted for APOE Apolipoprotein E genotype. LLFS relatives in the proband generation from EM families showed better EM performance than those from non-EM families (ß = 0.74, standard error = 0.19, p = 1.4 × 10(-4)). We demonstrated that there is a familial correlation of the EM endophenotype, suggesting that genetic variants might influence memory performance in long-lived families.

Apolipoprotein E and familial longevity.

Exceptional longevity is associated with substantial heritability. The ε4 allele in apolipoprotein E and the linked G allele in rs2075650 of TOMM40 have been associated with increased mortality and the ε2 allele with decreased mortality, although inconsistently. Offspring from long-lived families and spouse controls were recruited at 3 sites in the United States and Denmark. We used generalized estimating equations to compare the likelihood of carrying risk alleles in offspring (n = 2307) and spouse controls (n = 764), adjusting for age, sex, level of education, and family membership. The likelihood of carrying an APOE ε4 allele or a G allele in rs2075650 was lower (odds ratio [OR], 0.75; p = 0.005 and OR, 0.70; p = 0.002) and the likelihood of carrying an APOE ε2 allele was higher (OR, 1.5; p = 0.007) among family members in the offspring generation than among their spouse controls. Our findings support the hypothesis that both reduction in the frequency of the ε4 allele and increase in the frequency of the ε2 allele contribute to longevity.

Workshop on personal motion technologies for healthy independent living: executive summary.

The objective of the June 2010 "Workshop on Personal Motions Technologies for Healthy Independent Living" was to discuss personal motion technologies that might enable older adults and individuals with disability to live independently for longer periods. The 60 participants included clinicians, academic researchers, engineers, patient advocates, caregivers, members of the public, and federal representatives. The workshop was divided into 6 sessions that addressed the following: (1) use of technologies in identifying early indicators of disease or adverse events; (2) monitoring daily activities; (3) coping with impairment; (4) managing mild cognitive impairment; (5) rehabilitation and exercise in the home; and (6) caregiver support. Presentations and discussion focused on clinical needs, the health impact of addressing those needs, state-of-the-art technologies, and challenges to adoption of those technologies. Conclusions included the following: (1) Involvement of end-users in research and development will increase the likelihood that technologies will be adopted. (2) Integration of differing types of technology into a system that includes clinical measures is required for independent living. (3) Seniors are willing to sacrifice some privacy for an effective technology that keeps them in their homes as long as they control who receives their data. (4) Multilevel and multiscale models are needed to understand motion in the context of the environment and to design effective systems.

Do gender, disability, and morbidity affect aging rate in the LLFS? Application of indices of cumulative deficits.

We used an approach of cumulative deficits to evaluate the rate of aging in 4954 participants of the Long-Life Family Study (LLFS) recruited in the U.S. (Boston, New York, and Pittsburgh) and Denmark. We used an array of 85 health-related deficits covering major health dimensions including depression, cognition, morbidity, physical performance, and disability to construct several deficit indices (DIs) with overlapping and complementary sets of deficits to test robustness of the estimates. Our study shows that the DIs robustly characterize accelerated rates of aging irrespective of specific of deficits. When a wider spectrum of health dimensions is considered these rates are better approximated by quadratic law. Exponential rates are more characteristic for more severe health dimensions. The aging rates are the same for males and females. Individuals who contracted major diseases and those who were free of them exhibited the same aging rates as characterized by the DI constructed using mild deficits. Unlike health, disability can qualitatively alter the aging patterns of the LLFS participants. We report on systemic differences in health among the LLFS centenarians residing in New York and Boston. This study highlights importance of aggregated approaches to better understand systemic mechanisms of health deterioration in long-living individuals.

"Predicting" parental longevity from offspring endophenotypes: data from the Long Life Family Study (LLFS).

While there is evidence that longevity runs in families, the study of long-lived families is complicated by the fact that longevity-related information is available only for the oldest old, many of whom may be deceased and unavailable for testing, and information on other living family members, primarily descendents, is censored. This situation requires a creative approach for analyzing determinants of longevity in families. There are likely biomarkers that predict an individual's longevity, suggesting the possibility that those biomarkers which are heritable may constitute valuable endophenotypes for exceptional survival. These endophenotypes could be studied in families to identify human longevity genes and elucidate possible mechanisms of their influence on longevity. In this paper, we analyze data collected in the Long Life Family Study (LLFS) investigating whether indicators of physiological state, cognitive functioning and health/well-being among offspring predict longevity in parents. Good predictors can be used as endophenotypes for exceptional survival. Our analyses revealed significant associations between cumulative indices describing physiological state, as well as a number of offspring phenotypes, and parental lifespan, supporting both their familial basis and relevance to longevity. We conclude that the study of endophenotypes within families is a valid approach to the genetics of human longevity.

A family longevity selection score: ranking sibships by their longevity, size, and availability for study.

Family studies of exceptional longevity can potentially identify genetic and other factors contributing to long life and healthy aging. Although such studies seek families that are exceptionally long lived, they also need living members who can provide DNA and phenotype information. On the basis of these considerations, the authors developed a metric to rank families for selection into a family study of longevity. Their measure, the family longevity selection score (FLoSS), is the sum of 2 components: 1) an estimated family longevity score built from birth-, gender-, and nation-specific cohort survival probabilities and 2) a bonus for older living siblings. The authors examined properties of FLoSS-based family rankings by using data from 3 ongoing studies: the New England Centenarian Study, the Framingham Heart Study, and screenees for the Long Life Family Study. FLoSS-based selection yields families with exceptional longevity, satisfactory sibship sizes and numbers of living siblings, and high ages. Parameters in the FLoSS formula can be tailored for studies of specific populations or age ranges or with different conditions. The first component of the FLoSS also provides a conceptually sound survival measure to characterize exceptional longevity in individuals or families in various types of studies and correlates well with later-observed longevity.

Exceptional survival in human populations: National Institute on Aging perspectives and programs.

Identifying the factors that contribute to long and healthy life can lead to improved interventions that can help delay or prevent the onset of major aging-related diseases and disabilities and increase the time that older persons spend in good health. Studies on longevity and other exceptional survival outcomes can contribute to this knowledge. The National Institute on Aging (NIA) supports a considerable amount of basic, behavioral, demographic, epidemiologic, and clinical research on these topics, including a large research program on longevity assurance genes, primarily in laboratory animals, and in biodemographic aspects of longevity in humans and other species. This article describes NIA's activities regarding one important aspect of research on longevity and related phenotypes: exceptional survival phenotypes in humans, including exceptional longevity, health span, and active life expectancy.