Navigating Black Aging: The Biological Consequences of Stress and Depression

Objectives Black persons in the US are more likely to suffer from social inequality. Chronic stress caused by social inequality and racial discrimination results in weathering of the body that causes physiological dysregulation and biological age being higher than chronological age (accelerated aging). Depression has been linked to both racial discrimination and accelerated aging and accelerated aging has been demonstrated to be higher in Black than White persons, on average. However, we know little about accelerated aging across the life course in Black Americans. Methods We used mixed effects growth models to measure biological age acceleration, measured with cardiometabolic markers, over a 20-year period in Black participants of the Coronary Artery Risk Development in Young Adults Study (CARDIA) who were aged 27 - 42 years at analytic baseline. We included an interaction between depressive symptoms and time to determine whether risk of depression was associated with a faster rate of biological aging. Results We found that the rate of biological aging increased over a 20-year span and that those at risk for depression had a faster rate of biological aging than those not at risk. We also found that various social factors were associated with biological age acceleration over time. Discussion Given the known association between perceived racial discrimination and depressive symptoms, we provide a novel instance of the long-term effects of social inequality. Specifically, biological age acceleration, a marker of physiological dysregulation, is associated with time among Black persons and more strongly associated among those with depressive symptoms.

Early-Life Racial Discrimination, Racial Centrality, and Adult Allostatic Load Among African American Older Adults

This study evaluated the life course processes through which early life racial discrimination (ELRD) and racial centrality (i.e., the importance of Black identity to one’s sense of self) interact to shape allostatic load (AL) among African American (AA) adults aged 50+ in the Nashville Stress and Health Study (N=260). Adolescent ELRD was associated with greater racial centrality in adulthood and conferred 35% greater risk of high adult AL; greater centrality was also linked to high adult AL. Centrality accounts for 24% of the association between ELRD and AL. ELRD and centrality interact to shape adult AL, such that racial centrality is protective against high AL for adults who experienced racial discrimination as children or adolescents. Findings highlight the multiple pathways through which race-related stressors and psychosocial resources interact to shape physiological dysregulation in later life and underscore the health significance of racial identity for older AAs.

Genes Involved in Physiological Dysregulation and Decline in Resilience: Role in Alzheimer’s Disease

Our recent GWAS of a composite measure of physiological dysregulation (PD) in the Long Life Family Study (LLFS) found that the top genes associated with age-related changes in PD are involved in biological pathways relevant to maintaining neural networks and brain resilience. In our prior work, PD itself was linked to resilience-related traits. Alzheimer’s disease (AD) is a heterogeneous trait and it may involve an accelerated decline in resilience with age as a contributing factor. We proposed that genes associated with aging-changes in PD and brain resilience may contribute to AD risk. We investigated interactions between SNPs in such candidate genes with AD in LLFS and Health and Retirement Study (HRS). Our analysis revealed significant interactions between SNPs in UNC5C and other genes with AD, in both LLFS and HRS. These findings support roles of genetic interactions with UNC5C gene (implemented in axon growth and neuronal apoptosis) in AD.

Understanding and Measuring Frailty: Insights From the Canadian NuAge and CLSA Cohorts

Frailty is one of the most central concepts in geriatrics; nonetheless, multiple definitions and operationalizations abound, and the underlying biology remains a topic of much discussion. Here, we bring together four talks that join questions of understanding with questions of measurement, in order to explore how answering each is necessary to make progress on the other. We cannot measure frailty if we have not understood and defined it, but we cannot understand if we cannot measure it and study it. Turcot et al. present work on operationalizing frailty in the NuAge cohort. Mayo et al. establish a scale to test the extent to which frailty can be operationalized as a ladder rather than a condition, again using the NuAge cohort. Mendo et al. use mediation analyses to understand how grip strength and other aspects of frailty may play a role in the relationship between diabetes and atherosclerosis. Ghachem et al. test the relationship between physiological dysregulation of different systems and different criteria of the Fried model, in order to assess the evidence for frailty as an emergent physiological state. Together, these talks will push the boundaries of how we think about frailty at levels ranging from biological to clinical to operational.

The Frailty Syndrome: An Emergent Property of Parallel Dysregulation in Multiple Physiological Systems?

Despite its widespread presence in older adults, frailty etiology is still unclear, being associated with dysregulation in diverse physiological systems. Here, we show evidence that frailty emerges from broad loss of homeostasis integrated through complex systems dynamics. Using the NuAge and WHAS cohorts, we calculated Mahalanobis distance-based physiological dysregulation in six systems and tested the breadth, diffuseness, and nonlinearity of associations between frailty and system-specific dysregulation. We found clear support for breadth of associations, but only partial support for diffuseness and nonlinearity: 1) physiological dysregulation is positively associated with frailty in many or all systems, depending on analyses; 2) the number of dysregulated systems or the total amount of dysregulation are more predictive than individual systems, but results only partially replicated across cohorts; 3) dysregulation trends are exponential, but not always significant. These results suggest, but do not fully prove, that frailty is an emergent property of complex systems dynamics.

Race Differences in Allostatic Load Among Black and White Men: Does Age Matter?

Although Black-White disparities in health and mortality among men persist, there has been a paucity of work focusing on race differences in physiological dysregulation of biological processes resulting from the cumulative impact of stressors among men. The purpose of this study was to assess potential race differences in Allostatic Load (AL) among adult men and if such differences varied by age. Data were drawn from the 1999-2016 NHANES and the study population included 21,529 non-Hispanic Black (NHB) and 34,282 Non-Hispanic White (NHW) born in US. Adjusting for potential confounders, NHB men 25-44 and 45-64 had a higher AL score (OR = 1.19, 95% confidence interval (CI) 1.00, 1.42) and (OR = 1.14, 95% confidence interval (CI) 1.02, 1.28) NHW men. No race differences with respect to AL score were observed among the other age groups. The results suggest that age plays a role in race differences in AL

Physiological Dysregulation, Frailty, and Impacts on Adverse Health and Functional Outcomes

Background: Multi-system physiological dysregulation (PD) may represent a biological endo-phenotype of clinical frailty. We investigated the co-occurrence of PD with physical frailty and its contributions to the known impact of frailty on adverse health outcomes.Methods: Data of 2,725 participants from the Singapore Longitudinal Aging Studies (SLAS-2), included baseline measures of physical frailty and PD derived from Mahalanobis distance (Dm) value of 23 blood biomarkers. We analyzed their concurrent association and their impacts on 9-year mortality, MMSE cognition, GDS depression, number of medications, disability, and hospitalization at baseline and follow up (mean 4.5 years).Results: Global PD (Log10Dm, mean = 1.24, SD = 0.24) was significantly but weakly associated with pre-frailty-and-frailty. Controlling for age, sex and education, pre-frailty-and-frailty (HR = 2.12, 95% CI = 1.51–3.00) and PD (HR = 3.88, 95% CI = 2.15–6.98) predicted mortality. Together in the same model, mortality HR associated with pre-frailty-and-frailty (HR = 1.83, 95% CI = 1.22–2.73) and PD (HR = 3.06, 95% CI = 1.60–5.85) were reduced after additionally adding global PD to the prediction model. The predictive accuracy for mortality were both approximately the same (PD: AUC = 0.62, frailty: AUC = 0.64), but AUC was significantly increased to 0.68 when combined (p < 0.001). Taken into account in the same model, frailty remained significantly associated with all health and functional outcomes, and PD was significantly associated with only MMSE, disability and medications used. In secondary analyses, there were mixed associations of system-specific PDs with frailty and different adverse outcomes.Conclusions: Co-existing PD and physical frailty independently predict mortality and functional and health outcomes, with increased predictive accuracy when combined. PD appears to be a valid representation of a biological endo-phenotype of frailty, and the potential utility of such subclinical measures of frailty could be further studied.

An Objective Metric of Individual Health And Aging For Population Surveys

Background: Generalized, biomarker-based metrics of health status have numerous applications in fields ranging from sociology and economics to clinical research. We recently proposed a novel metric of health status based on physiological dysregulation measured as a Mahalanobis distance (DM) among clinical biomarkers. While DM was not particularly sensitive to the choice of biomarkers, it required calibration when used in different populations, making it difficult to compare findings across studies. To facilitate its use, here we aimed to identify and validate a standard version of DM that would be highly stable across populations, while using fewer biomarkers drawn exclusively from common blood panels. Methods: Using three datasets, we identified nine-biomarker (DM9) and seventeen-biomarker (DM17) versions of DM, choosing biomarkers based on their consistent levels across populations. We validated them in a fourth dataset. We assessed DM stability within and across populations by looking at correlations of DM versions calibrated using different populations or their demographic subsets. We used regression models to compare these standard DM versions to allostatic load and self-assessed health in their association with diverse health outcomes. Results: DM9 and DM17 were highly stable across population subsets (mean r = 0.96 and 0.95, respectively) and across populations (mean r = 0.94 for both). Performance predicting health outcomes was competitive with allostatic load and self-assessed health, though performance of these markers were somewhat variable for different health outcomes. Conclusions: Both DM9 and DM17 are highly stable within and across populations, supporting their use as objective metrics of health status. DM17 performs slightly better than DM9 and at least as well as other comparable metrics, but requires more biomarkers. The metrics we propose here are easy to measure with data that are available in a wide array of panel, cohort, and clinical studies.

Can I Buy My Health? A Genetically Informed Study of Socioeconomic Status and Health

Background A large literature demonstrates associations between socioeconomic status (SES) and health, including physiological health and well-being. Moreover, gender differences are often observed among measures of both SES and health. However, relationships between SES and health are sometimes questioned given the lack of true experiments, and the potential biological and SES mechanisms explaining gender differences in health are rarely examined simultaneously. Purpose To use a national sample of twins to investigate lifetime socioeconomic adversity and a measure of physiological dysregulation separately by sex. Methods Using the twin sample in the second wave of the Midlife in the United States survey (MIDUS II), biometric regression analysis was conducted to determine whether the established SES-physiological health association is observed among twins both before and after adjusting for potential familial-level confounds (additive genetic and shared environmental influences that may underly the SES-health link), and whether this association differs among men and women. Results Although individuals with less socioeconomic adversity over the lifespan exhibited less physiological dysregulation among this sample of twins, this association only persisted among male twins after adjusting for familial influences. Conclusions Findings from the present study suggest that, particularly for men, links between socioeconomic adversity and health are not spurious or better explained by additive genetic or early shared environmental influences. Furthermore, gender-specific role demands may create differential associations between SES and health.