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One method by which to identify fundamental biological processes that may contribute to age-related disease and disability, instead of disease-specific processes, is to construct endophenotypes comprising linear combinations of physiological measures. Applying factor analyses methods to phenotypic data (2006-2009) on 28 traits representing 5 domains (cognitive, cardiovascular, metabolic, physical, and pulmonary) from 4,472 US and Danish individuals in 574 pedigrees from the Long Life Family Study (United States and Denmark), we constructed endophenotypes and assessed their relationship with mortality. The most dominant endophenotype primarily reflected the physical activity and pulmonary domains, was heritable, was significantly associated with mortality, and attenuated the association of age with mortality by 24.1%. Using data (1997-1998) on 1,794 Health, Aging and Body Composition Study participants from Memphis, Tennessee, and Pittsburgh, Pennsylvania, we obtained strikingly similar endophenotypes and relationships to mortality. We also reproduced the endophenotype constructs, especially the dominant physical activity and pulmonary endophenotype, within demographic subpopulations of these 2 cohorts. Thus, this endophenotype construct may represent an underlying phenotype related to aging. Additional genetic studies of this endophenotype may help identify genetic variants or networks that contribute to the aging process. [ABSTRACT FROM AUTHOR]

Cardiovacular disease (CVD) is the leading cause of death among older adults and is often accompanied by functional decline. It is unclear what is driving this co-occurrence, but it may be behavioral, environmental and/or genetic. We used a family-based study to estimate the phenotypic and shared genetic correlation between CVD risk factors and physical and cognitive functional measures. Participants (n = 1,881) were from the Long Life Family Study, which enrolled families based on their exceptional longevity (sample mean age = 69.4 years, 44% female). Cardiovascular disease risk factors included carotid vessel measures [intima-media thickness and inter-adventitial diameter], obesity [body mass index (BMI) and waist circumference], and hypertension [systolic and diastolic blood pressures]. Function was measured in the physical [gait speed, grip strength, chair stand] and cognitive [digital symbol substitution test, retained and working memory, semantic fluency, and trail making tests] domains. We used SOLAR to estimate the genetic, environmental, and phenotypic correlation between each pair adjusting for age, age 2 , sex, field center, smoking, height, and weight. There were significant phenotypic correlations (range |0.05-0.22|) between CVD risk factors and physical and cognitive function (all P < 0.05). Most significant genetic correlations (range |0.21-0.62|) were between CVD risk factorsand cognitive function, although BMI and waist circumference had significant genetic correlation with gait speed and chair stand time (range |0.29-0.53|; all P < 0.05). These results suggest that CVD risk factors may share a common genetic-and thus, biologic-basis with both cognitive and physical function. This is particularly informative for research into the genetic determinants of chronic disease., (© 2021. The Author(s).)

Five healthy aging phenotypes were developed in the Long Life Family Study to uncover longevity pathways and determine if healthy aging across multiple systems clustered in a subset of long-lived families. Using blood pressure, memory, pulmonary function, grip strength, and metabolic measures (body mass index, waist circumference and fasting levels of glucose, insulin, triglycerides, lipids, and inflammatory markers), offspring were ranked according to relative health using gender-, age-, and relevant confounder-adjusted z-scores. Based on our prior work, families met a healthy aging phenotype if ≥ 2 and ≥ 50% of their offspring were exceptionally healthy for that respective phenotype. Among 426 families, only two families met criteria for three healthy aging phenotypes and none met criteria for four or more healthy aging phenotypes. Using Spearman correlation, the proportion of offspring within families with exceptionally healthy pulmonary function was correlated with the proportion of offspring within families with exceptional strength (r = 0.19, p = 0.002). The proportion of offspring within families meeting the healthy blood pressure and metabolic phenotypes were also correlated (r = 0.14, p = 0.006), and more families were classified as meeting healthy blood pressure and metabolic phenotypes (Kappa = 0.10, p = 0.02), as well as the healthy pulmonary and blood pressure phenotypes than expected by chance (Kappa = 0.09, p = 0.03). Other phenotypes were weakly correlated (|r| ≤ 0.07) with low pairwise agreement (Kappa ≤ 0.06). Among these families selected for familial longevity, correspondence between healthy aging phenotypes was weak, supporting the heterogeneous nature of longevity and suggesting biological underpinnings of each individual phenotype should be examined separately to determine their shared and unique determinants.