Association of Aging-Related Endophenotypes With Mortality in 2 Cohort Studies: the Long Life Family Study and the Health, Aging and Body Composition Study

Systemic inflammation in relation to exceptional memory in the Long Life Family Study (LLFS)

Background and objectives

We previously found a substantial familial aggregation of healthy aging phenotypes, including exceptional memory (EM) in long-lived persons. In the current study, we aim to assess whether long-lived families with EM and without EM (non-EM) differ in systemic inflammation status and trajectory.

Methods

The current study included 4333 participants of the multi-center Long Life Family Study (LLFS). LLFS families were classified as EM (556 individuals from 28 families) or non-EM (3777 individuals from 416 families), with 2 or more offspring exhibiting exceptional memory performance (i.e. having baseline composite z-score representing immediate and delayed story memory being 1.5 SD above the mean in the nondemented offspring sample) considered as EM. Blood samples from baseline were used to measure inflammatory biomarkers including total white blood cell (WBC) and its subtypes (neutrophils, lymphocytes, monocytes) count, platelet count, high sensitivity C-reactive protein, and interleukin-6. Generalized linear models were used to examine cross-sectional differences in inflammatory biomarkers at baseline. In a sub-sample of 2227 participants (338 subjects from 24 EM families and 1889 from 328 non-EM families) with repeated measures of immune cell counts, we examined whether the rate of biomarker change differed between EM and non-EM families. All models were adjusted for family size, relatedness, age, sex, education, field center, APOE genotype, and body mass index.

Results

LLFS participants from EM families had a marginally higher monocyte count at baseline (b = 0.028, SE = 0.0110, p = 0.010) after adjusting for age, sex, education, and field site, particularly in men (p < 0.0001) but not in women (p = 0.493) (p-interaction = 0.003). Over time, monocyte counts increased (p < 0.0001) in both EM and non-EM families, while lymphocytes and platelet counts decreased over time in the non-EM families (p < 0.0001) but not in the EM families. After adjusting for multiple variables, there was no significant difference in biomarker change over time between the EM and non-EM families.

Discussion

Compared with non-EM families, EM families had significantly higher monocyte count at baseline but had similar change over time. Our study suggests that differences in monocyte counts may be a pathway through which EM emerges in some long-lived families, especially among men.

Association between late maternal age and age-related endophenotypes in the Long Life Family Study

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.

Co-Inheritance of Variation in All-Cause Mortality and Biochemical Risk Factors

Biomarkers may be useful endophenotypes for genetic studies if they share genetic sources of variation with the outcome, for example, with all-cause mortality. Australian adult study participants who had reported their parental survival information were included in the study: 14,169 participants had polygenic risk scores (PRS) from genotyping and up to 13,365 had biomarker results. We assessed associations between participants' biomarker results and parental survival, and between biomarker results and eight parental survival PRS at varying p-value cut-offs. Survival in parents was associated with participants' serum bilirubin, C-reactive protein, HDL cholesterol, triglycerides and uric acid, and with LDL cholesterol for participants' fathers but not for their mothers. PRS for all-cause mortality were associated with liver function tests (alkaline phosphatase, butyrylcholinesterase, gamma-glutamyl transferase), metabolic tests (LDL and HDL cholesterol, triglycerides, uric acid), and acute-phase reactants (C-reactive protein, globulins). Association between offspring biomarker results and parental survival demonstrates the existence of familial effects common to both, while associations between biomarker results and PRS for mortality favor at least a partial genetic cause of this covariation. Identification of genetic loci affecting mortality-associated biomarkers offers a route to the identification of additional loci affecting mortality.

NIA Long Life Family Study: Objectives, Design, and Heritability of Cross Sectional and Longitudinal Phenotypes

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.

A novel healthy metabolic phenotype developed among a cohort of families enriched for longevity

BACKGROUND

Long-lived individuals and their offspring have healthier metabolic characteristics than expected, such as more favorable levels of fasting glucose, insulin, and lipids than controls without longevity. Dysregulation in metabolic pathways has also shown to predict accelerated aging. Using information from the Long Life Family Study (LLFS), a multi-center study of two-generation families selected for exceptional longevity, we developed an indicator of healthy metabolism to determine whether metabolic health was more prevalent in a subset of LLFS families and whether it was heritable and associated with other metrics of healthy aging.

METHODS

A Latent Profile Analysis was applied to age- and gender-adjusted z-scores of fasting levels of glucose, insulin, triglycerides, and high-density lipoprotein cholesterol, body mass index, waist circumference, interleukin-6, and C-reactive protein. Families were defined as meeting the healthy metabolic phenotype if ≥2 and ≥50% of their offspring were classified into a latent subgroup with a profile of healthier metabolic markers than expected given age and gender relative to all LLFS offspring.

RESULTS

The log odds of being classified into the latent subgroup with a healthy profile of metabolic markers was heritable (h² = 0.40, p < 0.001). Among 388 families, 39 (10%) met the healthy metabolic phenotype. Participants from these families had somewhat better cognition than those from remaining families. Proband-generation participants from families who met the healthy metabolic phenotype also had better pulmonary functioning and physical performance.

CONCLUSIONS

The better cognition, pulmonary function, and physical performance among probands from families with the healthy metabolic phenotype may indicate that this subset of LLFS families have a more extreme longevity phenotype than other LLFS families since cognitive, physical, and pulmonary function are top mortality predictors for older adults. Future work is needed to determine if rare or protective alleles confer a healthy metabolic phenotype in this subset of LLFS families with exceptional metabolism.

Redefining Aging in HIV Infection Using Phenotypes

Purpose of review

This article critically reviews the utility of “phenotypes” as behavioral descriptors in aging/HIV research that inform biological underpinnings and treatment development. We adopt a phenotypic redefinition of aging conceptualized within a broader context of HIV infection and of aging. Phenotypes are defined as dimensions of behavior, closely related to fundamental mechanisms, and, thus, may be more informative than chronological age. Primary emphasis in this review is given to comorbid aging and cognitive aging, though other phenotypes (i.e., disability, frailty, accelerated aging, successful aging) are also discussed in relation to comorbid aging and cognitive aging.

Recent findings

The main findings that emerged from this review are as follows: (1) the phenotypes, comorbid aging and cognitive aging, are distinct from each other, yet overlapping; (2) associative relationships are the rule in HIV for comorbid and cognitive aging phenotypes; and (3) HIV behavioral interventions for both comorbid aging and cognitive aging have been limited.

Summary

Three paths for research progress are identified for phenotype-defined aging/HIV research (i.e., clinical and behavioral specification, biological mechanisms, intervention targets), and some important research questions are suggested within each of these research paths.

A novel healthy blood pressure phenotype in the Long Life Family Study

BACKGROUND

Hypertension tends to run in families and has both genetic and environmental determinants. We assessed the hypothesis that a novel healthy blood pressure (BP) phenotype is also familial and sought to identify its associated factors.

METHODS

We developed a healthy BP phenotype in the Long Life Family Study, a cohort of two-generation families selected for longevity. Participants from the offspring generation (n = 2211, ages 32-88) were classified as having healthy BP if their age-adjusted and sex-adjusted SBP z-score was between -1.5 and -0.5. Offspring on antihypertensive medications were classified as not having healthy BP. Families with at least two offspring (n = 419 families) were defined as meeting the healthy BP phenotype if at least two and at least 50% of their offspring had healthy BP.

RESULTS

Among 2211 offspring, 476 (21.5%) met the healthy BP phenotype. When examining the 419 families, only 44 (10.5%) families met the criteria for the healthy BP phenotype. Both offspring and probands from families with healthy BP performed better on neuropsychological tests that place demands on complex attention and executive function when compared with offspring and probands from remaining families. Among families with the healthy BP phenotype compared with families without, a higher proportion of offspring met the American Heart Association definition of ideal cardiovascular health (10.8 versus 3.8%, respectively; driven by BP, smoking status, and BMI components).

CONCLUSION

In this cohort of familial longevity, few families had a novel healthy BP phenotype in multiple members. Families with this healthy BP phenotype may represent a specific pathway to familial longevity.

Age-Related Biomarkers in LLFS Families With Exceptional Cognitive Abilities

Background

We previously demonstrated familial aggregation of memory performance within the Long Life Family Study (LLFS), suggesting that exceptional cognition (EC) may contribute to their exceptional longevity. Here, we investigated whether LLFS families with EC may also exhibit more favorable profiles of other age-related biomarkers.

Methods

Nondemented offspring of the LLFS probands scoring 1.5 SD above the mean in a cognitive phenotype were classified as participants with EC. Families were categorized into EC (n = 28) and non-EC families (n = 433) based on having at least two EC offspring. Adjusted general estimating equations were used to investigate whether EC families had a better longevity and age-related biomarker profiles than non-EC families.

Results

EC families exhibited higher scores on familial longevity than non-EC families (average Family Longevity Selection Score of 12 ± 7 vs 9 ± 8, p = 2.5 × 10-14). EC families showed a better a metabolic profile (β = -0.63, SE = 0.23, p = .006) than non-EC families. The healthier metabolic profile is related to obesity in an age-dependent fashion. The prevalence of obesity in EC families is significantly lower compared with non-EC families (38% vs 51%, p = .015) among family members less than 80 years of age; however, among EC family members 80 years of age and older, the prevalence of obesity is higher (40% vs 38%, p = .011). EC families also showed better physical/pulmonary function than non-EC families (β = 0.51, SE = 0.25, p = .042).

Conclusions

Long-live families with EC are characterized by a healthier metabolic profile which is related to the prevalence of obesity in the older family members. Our results suggest that familial exceptional longevity may be achieved through heterogeneous yet correlated pathways.

Genomewide Association Scan of a Mortality Associated Endophenotype for a Long and Healthy Life in the Long Life Family Study

Background

Identification of genes or fundamental biological pathways that regulate aging phenotypes and longevity could lead to possible interventions to increase healthy longevity.

Methods

Using data from the Long Life Family Study, we performed genomewide association analyses on an endophenotype construct, LF1, comprising a linear combination of traits across health domains. LF1 primarily reflected traits from the pulmonary and physical activity domains.

Results

We detected a significant association between LF1 and a locus on chromosome 10p15 (p-value = 4.65 × 10-8) and suggestive evidence (p-value < 5 × 10-6) for association on chromosomes 1, 2, 8, 12, 15, 18, and 22. Using data from the Health, Aging and Body Composition Study, we subsequently replicated the association for the 1p13 region near the NBPF6 locus (p-value = 3.65 × 10-4).

Conclusions

Our analyses indicate that loci influencing a healthy aging endophenotype construct predominantly comprised of pulmonary and physical function domains may be located on chromosome 1p13 near the NBPF6 locus. Further investigation of this possible locus and other suggestive loci may reveal novel biological pathways that influence healthy aging.