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Background This study compared the mortality risk of long-lived siblings with the U.S. population average and their spouse controls, and investigated the leading causes of death and the familial effect in death pattern. Methods In the Long Life Family Study (LLFS), 1 264 proband siblings (mean age 90.1, standard deviation [ SD ] 6.4) and 172 spouses (83.8, 7.2) from 511 U.S.-based families were recruited and followed more than 12 years. Their survival function was compared with a birth cohort-, baseline age-, sex-, and race-matched pseudo sample from U.S. census data. To examine underlying and contributing causes, we examined in detail 338 deaths with complete death adjudication at the University of Pittsburgh Field Center through the year 2018. A familial effect on survival and death patterns was examined using mixed-effect models. Results The LLFS siblings had better survival than the matched U.S. population average. They also had slightly but not significantly better survival than their spouses' (HR = 1.18 [95%CI 0.94–1.49]) after adjusting for age and sex. Age at death ranged from 75 to 104 years, mean 91.4. The leading causes of death were cardiovascular disease (33.1%), dementia (22.2%), and cancer (10.7%). Mixed effect model shows a significant random effect of family in survival, with adjustment of baseline age and sex. There was no significant familial effect in the underlying cause of death or conditions directly contributing to death among siblings recruited by the University of Pittsburgh Field Center. Conclusions Our findings demonstrate a higher survival in the LLFS siblings than the U.S. census data, with a familial component of survival. We did not find significant correspondence in causes of death between siblings within families. [ABSTRACT FROM AUTHOR]

Background: Discovering patterns of cognitive domains and characterizing how these patterns associate with other risk factors and biomarkers can improve our understanding of the determinants of cognitive aging. Objective: To discover patterns of cognitive domains using neuropsychological test results in Long Life Family Study (LLFS) and characterize how these patterns associate with aging markers. Methods: 5,086 LLFS participants were administered neuropsychological tests at enrollment. We performed a cluster analysis of six baseline neuropsychological test scores and tested the association between the identified clusters and various clinical variables, biomarkers, and polygenic risk scores using generalized estimating equations and the Chi-square test. We used Cox regression to correlate the clusters with the hazard of various medical events. We investigated whether the cluster information could enhance the prediction of cognitive decline using Bayesian beta regression. Results: We identified 12 clusters with different cognitive signatures that represent profiles of performance across multiple neuropsychological tests. These signatures significantly correlated with 26 variables including polygenic risk scores, physical and pulmonary functions, and blood biomarkers and were associated with the hazard of mortality (p < 0.01), cardiovascular disease (p = 0.03), dementia (p = 0.01), and skin cancer (p = 0.03). Conclusion: The identified cognitive signatures capture multiple domains simultaneously and provide a holistic vision of cognitive function, showing that different patterns of cognitive function can coexist in aging individuals. Such patterns can be used for clinical intervention and primary care. [ABSTRACT FROM AUTHOR]

Background: The Long Life Family Study (LLFS) is a family based, prospective study of healthy aging and familial longevity. The study includes two assessments of cognitive function that were administered approximately 8 years apart.Objective: To test whether APOE genotype is associated with change of cognitive function in older adults.Methods: We used Bayesian hierarchical models to test the association between APOE alleles and change of cognitive function. Six longitudinally collected neuropsychological test scores were modelled as a function of age at enrollment, follow-up time, gender, education, field center, birth cohort indicator (≤1935, or >1935), and the number of copies of ɛ2 or ɛ4 alleles.Results: Out of 4,587 eligible participants, 2,064 were male (45.0%), and age at enrollment ranged from 25 to 110 years, with mean of 70.85 years (SD: 15.75). We detected a significant cross-sectional effect of the APOEɛ4 allele on Logical Memory. Participants carrying at least one copy of the ɛ4 allele had lower scores in both immediate (-0.31 points, 95% CI: -0.57, -0.05) and delayed (-0.37 points, 95% CI: -0.64, -0.10) recall comparing to non-ɛ4 allele carriers. We did not detect any significant longitudinal effect of the ɛ4 allele. There was no cross-sectional or longitudinal effect of the ɛ2 allele.Conclusion: The APOEɛ4 allele was identified as a risk factor for poorer episodic memory in older adults, while the APOEɛ2 allele was not significantly associated with any of the cognitive test scores. [ABSTRACT FROM AUTHOR]

The NIA Long Life Family Study (LLFS) is a longitudinal, multicenter, multinational, population-based multigenerational family study of the genetic and nongenetic determinants of exceptional longevity and healthy aging. The Visit 1 in-person evaluation (2006-2009) recruited 4 953 individuals from 539 two-generation families, selected from the upper 1% tail of the Family Longevity Selection Score (FLoSS, which quantifies the degree of familial clustering of longevity). Demographic, anthropometric, cognitive, activities of daily living, ankle-brachial index, blood pressure, physical performance, and pulmonary function, along with serum, plasma, lymphocytes, red cells, and DNA, were collected. A Genome Wide Association Scan (GWAS) (Ilumina Omni 2.5M chip) followed by imputation was conducted. Visit 2 (2014-2017) repeated all Visit 1 protocols and added carotid ultrasonography of atherosclerotic plaque and wall thickness, additional cognitive testing, and perceived fatigability. On average, LLFS families show healthier aging profiles than reference populations, such as the Framingham Heart Study, at all age/sex groups, for many critical healthy aging phenotypes. However, participants are not uniformly protected. There is considerable heterogeneity among the pedigrees, with some showing exceptional cognition, others showing exceptional grip strength, others exceptional pulmonary function, etc. with little overlap in these families. There is strong heritability for key healthy aging phenotypes, both cross-sectionally and longitudinally, suggesting that at least some of this protection may be genetic. Little of the variance in these heritable phenotypes is explained by the common genome (GWAS + Imputation), which may indicate that rare protective variants for specific phenotypes may be running in selected families. [ABSTRACT FROM AUTHOR]

Maintaining good cognitive function at older age is important, but our knowledge of patterns and predictors of cognitive aging is still limited. We used Bayesian model-based clustering to group 5064 participants of the Long Life Family Study (ages 49–110 years) into clusters characterized by distinct trajectories of cognitive change in the domains of episodic memory, attention, processing speed, and verbal fluency. For each domain, we identified 4 or 5 large clusters with representative patterns of change ranging from rapid decline to exceptionally slow change. We annotated the clusters by their correlation with genetic and molecular biomarkers, non-genetic risk factors, medical history, and other markers of aging to discover correlates of cognitive changes and neuroprotection. The annotation analysis discovered both predictors of multi-domain cognitive change such as gait speed and predictors of domain-specific cognitive change such as IL6 and NTproBNP that correlate only with change of processing speed or APOE genotypes that correlate only with change of processing speed and logical memory. These patterns also suggest that cognitive decline starts at young age and that maintaining good physical function correlates with slower cognitive decline. To better understand the agreement of cognitive changes across multiple domains, we summarized the results of the cluster analysis into a score of cognitive function change. This score showed that extreme patterns of change affecting multiple cognitive domains simultaneously are rare in this study and that specific signatures of biomarkers of inflammation and metabolic disease predict severity of cognitive changes. The substantial heterogeneity of change patterns within and between cognitive domains and the net of correlations between patterns of cognitive aging and other aging traits emphasizes the importance of measuring a wide range of cognitive functions and the need for studying cognitive aging in concert with other aging traits. [ABSTRACT FROM AUTHOR]

Background: Studies of longevity-enriched families are an important tool to gain insight into the mechanisms of exceptionally long and healthy lives. In the Long Life Family Study, the spouses of the members of the longevity-enriched families are often used as a control group. These spouses could be expected to have better health than the background population due to shared family environment with the longevity-enriched family members and due to assortative mating.Methods: A Danish cohort study of 5,363 offspring of long-lived siblings, born 1917-1982, and 4,498 "first spouses" of these offspring. For each offspring and spouse, 10 controls were drawn from a 5% random sample of the Danish population matched on birth year and sex. Mortality was assessed for ages 20-69 years during 1968-2013 based on prospectively collected registry data.Results: During the 45-year follow-up period, 437 offspring deaths and 502 offspring spouse deaths were observed. Compared with the background population, the hazard ratio for male offspring was 0.44 (95% confidence interval [CI]: 0.38-0.50) and for female offspring it was 0.57 (95% CI: 0.49-0.66). For male spouses, the hazard ratio was 0.66 (95% CI: 0.59-0.74), whereas for female spouses it was 0.64 (95% CI: 0.54-0.76). Sensitivity analyses in restricted samples gave similar results.Conclusion: The mortality for ages 20-69 years of spouses marrying into longevity-enriched families is substantially lower than the mortality in the background population, although long-lived siblings participation bias may have contributed to the difference. This finding has implications for the use of spouses as controls in healthy aging and longevity studies, as environmental and/or genetic overmatching may occur. [ABSTRACT FROM AUTHOR]

The lack of a formal definition of human longevity continues to generate confusion about its genetic and nongenetic determinants. In order to characterize how differences in birth year cohorts and percentiles of survival are associated with familial contribution to variation in survival, we estimated sibling relative risk of living to increasingly rare percentiles of survival based on a dataset of 1,917 validated sibships each containing at least one individual living to age 90 years. About 1,042 of the sibships included at least one individual who survived to age 100 and 511 included at least one individual who survived to age 105 and older. We show that sibling relative risk increases with older ages, sex, and earlier birth year cohorts of the proband and siblings of male 90-year-olds (5th percentile of survival) have 1.73 (95% CI: 1.5; 2.0) times the chance of living to age 90, while siblings of both male and female probands who survived to age 105 years (~0.01 percentile of survival) have 35.6 (95%CI: 15.1; 67.7) times the chance of living to age 105 compared with population controls. These results emphasize the importance of consistently defining the longevity phenotype in terms of rarity of survival for appropriate comparisons across studies. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To assess the relative incidence of age-related diseases in a group of centenarian offspring who have thus far been considered to be predisposed to “healthy” aging. DESIGN: Longitudinal study. SETTING: Nationwide sample. PARTICIPANTS: Four hundred forty centenarian offspring and 192 referent cohort subjects who met inclusion criteria of having initial and follow-up health questionnaire data available. Median age of both cohorts was 72 at the initial health questionnaire. MEASUREMENTS: Initial health questionnaires were collected from 1997 to 2006. Follow-up questionnaires were collected from 2004 to 2007. The mean period of follow-up was 3.5±1.7 years for the centenarian offspring and 3.9±2.2 years for the referent cohort. RESULTS: During the follow-up period, centenarian offspring had a 78% lower risk of myocardial infarction ( P<.04), 83% lower risk of stroke ( P<.004), and 86% lower risk of developing diabetes mellitus ( P<.005) than the referent cohort. There were no significant differences in new onset of other age-related diseases. Additionally, centenarian offspring were 81% less likely to die ( P<.01) than the referent cohort during the follow-up. CONCLUSION: These findings suggest that centenarian offspring retain some important cardiovascular advantages over time over similarly aged referent cohort subjects. These findings reinforce the notion that there may be physiological reasons that longevity runs in families and that centenarian offspring are more likely to age in better cardiovascular health and with a lower mortality than their peers. [ABSTRACT FROM AUTHOR]

• Childbearing at older ages affects the health and wellbeing of the mother. • Cognitive performance in long-live families was reported as an indicator of healthy aging. • Women with extended maternal age at last childbirth exhibited better cognitive profile compared to younger mothers. • The association between later maternal age and better cognitive profile in a long-life cohort supports the potential use of later age at childbirth as a marker for healthy aging. Extended maternal age has been suggested as marker of delayed age-associated disabilities. We use the Long Life Family Study (LLFS) offspring generation to investigate the association between extended maternal age at last childbirth and healthy-aging endophenotypes. We hypothesize that women with extended maternal age at last childbirth will exhibit healthier endophenotype profiles compared to younger mothers. The association between maternal age and age-related endophenotypes previously derived in LLFS was assessed using Generalized Estimating Equations to adjust for relatedness. The quartiles of the maternal age at last childbirth were modeled as the independent variables. Univariate analyses tested the association between maternal age at last childbirth and age at clinical assessment, education, field center, Apolipoprotein E (APOE) genotype, depression, stress, smoking and successful pregnancies. Only the variables significantly associated in the univariate analyses were considered in secondary multivariate analyses. Univariate analyses showed that compared to older mothers (age at last birth ≥35), mothers 30 years old or younger at last childbirth are less educated (12 ± 3 years versus 13 ± 3 years) and have a higher frequency of smoking (9% versus 3% for maternal age ≥35). Results showed that older mothers (age at last birth ≥31–34 or ≥ 35) demonstrated significantly better cognitive profiles (p = 0.017 and p = 0.021 respectively) compared with mothers with last childbirth age ≤30. Later maternal age among women from long-life families is associated with a better cognitive profile, supporting the hypothesis that later age at childbirth may be a marker for healthy aging. [ABSTRACT FROM AUTHOR]