TY - JOUR T1 - Accelerated epigenetic aging mediates link between adverse childhood experiences and depressive symptoms in older adults: Results from the Health and Retirement Study. JF - SSM Population Health Y1 - 2022 A1 - Klopack, Eric T A1 - Eileen M. Crimmins A1 - Cole, Steve W A1 - Seeman, Teresa E A1 - Carroll, Judith E KW - ACEs KW - Adverse childhood events KW - Ageing KW - depression KW - Epigenetic aging AB -

Adverse childhood experiences (ACEs) increase risk for depression at subsequent ages and have been linked to accelerated biological aging. We hypothesize that accelerated epigenetic aging may partially mediate the link between ACEs and depression. This study examines 3 three second-generation epigenetic aging measures (viz., GrimAge, PhenoAge, and DunedinPoAm38) as mediators of the link between ACEs and depressive symptoms in older adulthood. We utilize structural equation modeling to assess mediation in the Health and Retirement Study (N = 2672). Experiencing ACEs is significantly associated with an older GrimAge and a faster pace of aging via the DunedinPoAm38. Having an older GrimAge and faster DunedinPoAm38 pace of aging were also significantly associated with more depressive symptoms. PhenoAge was not significantly associated with depressive symptoms and was only associated with experiencing three ACEs. These associations were reduced by socioeconomic and lifestyle factors, including obesity and substance use. GrimAge explained between 9 and 14% of the association between ACEs and adult depressive symptoms, and DunedinPoAm38 explained between 2 and 7% of the association between ACEs and adult depressive symptoms. Findings indicate accelerated aging, as measured by GrimAge and DunedinPoAm38, is associated with ACEs and with depressive symptoms in older Americans. Findings also show these epigenetic aging measures mediate a portion of the association between ACEs and adult depressive symptoms. Epigenetic aging may represent a physiological mechanism underlying the link between early life adversity and adult depression. Weight maintenance and substance use are potentially important areas for intervention.

VL - 17 ER - TY - JOUR T1 - Age-related differences in T cell subsets in a nationally representative sample of people over age 55: Findings from the Health and Retirement Study. JF - The Journals of Gerontology, Series A Y1 - 2022 A1 - Bharat Thyagarajan A1 - Jessica Faul A1 - Vivek, Sithara A1 - Jung K Kim A1 - Nikolich-Žugich, Janko A1 - David R Weir A1 - Eileen M. Crimmins KW - Aging KW - CMV Seropositivity AB -

Though T cell immunosenescence is a major risk factor for age-related diseases, susceptibility to infections, and responses to vaccines, differences in T cells subset counts and representation by age and sex have not been determined for a large sample representative of the national population of the US. We evaluated the counts of T cell subsets including total, CD4+ and CD8+ T cells, and their naïve (Tn), effector memory (Tem) and effector subsets, in the context of age, sex and exposure to cytomegalovirus (CMV) infection among 8,848 Health and Retirement Study (HRS) participants, a nationally representative study of adults over 55 years. Total T cells (CD3+) and CD4+ cells declined markedly with age; CD8+ T cells declined somewhat less. While CD4+ T cell declines with age occurred for both CMV seropositive and CMV seronegative groups, total T cells and CD8+ cells were both substantially higher among the CMV seropositive group. Numbers of Tn CD4+ and CD8+ cells were strongly and inversely related to age, were better conserved among women, and were independent of CMV seropositivity. By contrast, accumulation of the CD8+ and CD4+ Tem and effector subsets was CMV-associated. This is the first study to provide counts of T cell subsets by age and sex in a national sample of older US adults over the age of 55 years. Understanding T cell changes with age and sex is an important first step in determining strategies to reduce its impact on age-related diseases and susceptibility to infection.

VL - 77 IS - 5 ER - TY - JOUR T1 - Association of GrimAge DNA methylation components and 2-year mortality in the Health and Retirement Study JF - Innovation in Aging Y1 - 2021 A1 - Meier, Helen A1 - Colter Mitchell A1 - Eileen M. Crimmins A1 - Bharat Thyagarajan A1 - Jessica Faul KW - 2-year mortality KW - DNA Methylation KW - GrimAge AB - DNA methylation (DNAm) patterns related to age and aging phenotypes (i.e., epigenetic clocks) are of growing interest as indicators of biological age and risk of negative health outcomes. We investigated associations between the components of GrimAge, an epigenetic clock estimated from DNAm patterns for seven blood protein levels and smoking pack years, and 2-year mortality in the Health and Retirement Study (HRS) to determine if any of the DNAm subcomponents were driving observed associations. A representative subsample of individuals who participated in the HRS 2016 Venus Blood Study were included in this analysis (N=3430). DNAm was measured with the Infinium Methylation EPIC BeadChip. Deaths that occurred between 2016 and 2018 contributed to 2-year mortality estimates (N=159, 4.5% of the sample). Weighted logistic regression estimated the association first between GrimAge and 2-year mortality and second between the DNAm subcomponents and 2-year mortality. All models were adjusted for age, sex, race/ethnicity, education, current smoking status, smoking pack years and cell composition of the biological sample. The average GrimAge for participants with and without 2-year mortality was 77 years 68 years respectively. A one-year increase in GrimAge was associated with 17% higher odds of 2-year mortality (95% CI: 1.16, 1.17). Two of the seven DNAm blood protein subcomponents of GrimAge (TIMP metallopeptidase inhibitor 1, adrenomedullin) and DNAm smoking pack years were associated with 2-year mortality and DNAm smoking pack years appeared to drive the overall GrimAge association with 2-year mortality. GrimAge was a better predictor of 2-year mortality than the DNAm subcomponents individually. VL - 5 IS - Suppl _1 ER - TY - JOUR T1 - Associations of Age, Sex, Race/Ethnicity and Education with 13 Epigenetic Clocks in a Nationally Representative US Sample: The Health and Retirement Study. JF - The Journals of Gerontology: Series A Y1 - 2021 A1 - Eileen M. Crimmins A1 - Bharat Thyagarajan A1 - Morgan E. Levine A1 - David R Weir A1 - Jessica Faul KW - DNA Methylation KW - DunedinPoAm38 KW - Epigenetic Age KW - GrimAge KW - PhenoAgeAcceleration AB -

BACKGROUND: Many DNA methylation based indicators have been developed as summary measures of epigenetic aging. We examine the associations between 13 epigenetic clocks, including 4 second generation clocks, as well as the links of the clocks to social, demographic and behavioral factors known to be related to health outcomes: sex, race/ethnicity, socioeconomic status, obesity and lifetime smoking pack years.

METHODS: The Health and Retirement Study is the data source which is a nationally representative sample of Americans over age 50. Assessment of DNA methylation was based on the EPIC chip and epigenetic clocks were developed based on existing literature.

RESULTS: The clocks vary in the strength of their relationships with age, with each other and with independent variables. Second generation clocks trained on health related characteristics tend to relate more strongly to the sociodemographic and health behaviors known to be associated with health outcomes in this age group.

CONCLUSIONS: Users of this publicly available data set should be aware that epigenetic clocks vary in their relationships to age and to variables known to be related to the process of health change with age.

VL - 76 IS - 6 ER - TY - JOUR T1 - Age-Related Vulnerability to Coronavirus Disease 2019 (COVID-19): Biological, Contextual, and Policy-Related Factors. JF - Public Policy and Aging Report Y1 - 2020 A1 - Eileen M. Crimmins KW - COVID-19 KW - Immunosenescence KW - Mortality KW - Nursing homes AB - The detailed facts surrounding the coronavirus disease 2019 (COVID-19) pandemic are still evolving; however, one of the most shocking aspects of the COVID-19 pandemic is how lethal this condition is for the older population (Dowd et al., 2020). The risk for death and severe illness with COVID-19 is best predicted by age. The likelihood of death increases exponentially with age among those who contract the virus in all countries where this has been examined (Figure 1). Figure 1 shows the percent of confirmed cases ending in mortality, by age, for five countries near the beginning of June. In every country, the percent dying increases sharply after age 50, and the highest rates occur among the oldest persons. The age pattern is clear across the countries even though the mortality levels are quite different; the United States has had a much greater number of cases and deaths than the other countries in this figure, but the mortality level was higher in Italy. This difference in levels could be influenced by the proportion of diagnosed cases, which depends on testing, treatment of cases, and whether COVID-19 deaths include only those confirmed with a diagnostic test or include both confirmed and probable deaths (Sung & Kaplan, 2020). Even with these differences, the pattern of an exponential increase in death with age is clear. VL - 30 IS - 4 ER - TY - JOUR T1 - Analysis of dementia in the US population using Medicare claims: Insights from linked survey and administrative claims data. JF - Alzheimers Dement (N Y) Y1 - 2019 A1 - Chen, Yi A1 - Tysinger, Bryan A1 - Eileen M. Crimmins A1 - Julie M Zissimopoulos KW - Cognitive Ability KW - Dementia KW - Education KW - Medicare claims KW - Medicare linkage KW - Racial/ethnic differences AB -

Introduction: Medicare claims data may be a rich data source for tracking population dementia rates. Insufficient understanding of completeness of diagnosis, and for whom, limits their use.

Methods: We analyzed agreement in prevalent and incident dementia based on cognitive assessment from the Health and Retirement Study for persons with linked Medicare claims from 2000 to 2008 (N = 10,450 persons). Multinomial logistic regression identified sociodemographic factors associated with disagreement.

Results: Survey-based cognitive tests and claims-based dementia diagnosis yielded equal prevalence estimates, yet only half were identified by both measures. Race and education were associated with disagreement. Eighty-five percent of respondents with incident dementia measured by cognitive decline received a diagnosis or died within the study period, with lower odds among blacks and Hispanics than among whites.

Discussions: Claims data are valuable for tracking dementia in the US population and improve over time. Delayed diagnosis may underestimate rates within black and Hispanic populations.

VL - 5 U1 - http://www.ncbi.nlm.nih.gov/pubmed/31198838?dopt=Abstract ER - TY - JOUR T1 - ASSOCIATIONS OF GENETICS AND LIFE COURSE CIRCUMSTANCES WITH A NOVEL AGING MEASURE THAT CAPTURES MORTALITY RISK JF - Innovation in Aging Y1 - 2019 A1 - Liu, Zuyun A1 - Chen, Xi A1 - Thomas M Gill A1 - Ma, Chao A1 - Eileen M. Crimmins A1 - Morgan E. Levine KW - Genetics KW - Mortality KW - mortality risk AB - We aimed to evaluate associations between a comprehensive set of factors, including genetics and childhood and adulthood circumstances, and a novel aging measure, Phenotypic Age (PhenoAge), which has been shown to capture mortality and morbidity risk in the U.S. population. Using data from 2339 adults (aged 51+) from the U.S. Health and Retirement Study, we found that together all 11 study domains (4 childhood and adulthood circumstances domains, 5 polygenic scores [PGSs] domains, and 1 demographics, and 1 behaviors domains) accounted for about 30\% of variance in PhenoAge after accounting for chronological age. Among the 4 circumstances domains, adulthood adversity was the largest contributor (9\%), while adulthood socioeconomic status (SES), childhood adversity, and childhood SES accounted for 2.8\%, 2.1\%, 0.7\%, respectively. All PGSs contributed 3.8\% of variance in PhenoAge (after accounting for chronological age). Further, using Hierarchical Clustering, we identified 6 distinct subpopulations/clusters based on the 4 circumstances domains, and 3 subpopulations/clusters of them that appear to represent disadvantaged circumstances were associated with higher PhenoAge. Finally, there was a significant gene-by-environment interaction between a previously validated PGS for coronary artery disease and the most apparently disadvantaged subpopulation/cluster, suggesting a multiplicative effect of adverse life course circumstances coupled with genetic risk on phenotypic aging. We concluded that socioenvironmental circumstances during childhood and adulthood account for a sizable proportion of differences in phenotypic aging among U.S. older adults. The disadvantaged subpopulations exhibited accelerated aging and the detrimental effects may be further exacerbated among persons with genetic predisposition to coronary artery disease. VL - 3 UR - https://doi.org/10.1093/geroni/igz038.1177 ER - TY - JOUR T1 - Associations of genetics, behaviors, and life course circumstances with a novel aging and healthspan measure: Evidence from the Health and Retirement Study. JF - PLoS Medicine Y1 - 2019 A1 - Liu, Zuyun A1 - Chen, Xi A1 - Thomas M Gill A1 - Ma, Chao A1 - Eileen M. Crimmins A1 - Morgan E. Levine KW - Genetics KW - Health Behavior KW - Life trajectories AB -

BACKGROUND: An individual's rate of aging directly influences his/her susceptibility to morbidity and mortality. Thus, quantifying aging and disentangling how various factors coalesce to produce between-person differences in the rate of aging, have important implications for potential interventions. We recently developed and validated a novel multi-system-based aging measure, Phenotypic Age (PhenoAge), which has been shown to capture mortality and morbidity risk in the full US population and diverse subpopulations. The aim of this study was to evaluate associations between PhenoAge and a comprehensive set of factors, including genetic scores, childhood and adulthood circumstances, and health behaviors, to determine the relative contributions of these factors to variance in this aging measure.

METHODS AND FINDINGS: Based on data from 2,339 adults (aged 51+ years, mean age 69.4 years, 56% female, and 93.9% non-Hispanic white) from the US Health and Retirement Study, we calculated PhenoAge and evaluated the multivariable associations for a comprehensive set of factors using 2 innovative approaches-Shapley value decomposition (the Shapley approach hereafter) and hierarchical clustering. The Shapley approach revealed that together all 11 study domains (4 childhood and adulthood circumstances domains, 5 polygenic score [PGS] domains, and 1 behavior domain, and 1 demographic domain) accounted for 29.2% (bootstrap standard error = 0.003) of variance in PhenoAge after adjustment for chronological age. Behaviors exhibited the greatest contribution to PhenoAge (9.2%), closely followed by adulthood adversity, which was suggested to contribute 9.0% of the variance in PhenoAge. Collectively, the PGSs contributed 3.8% of the variance in PhenoAge (after accounting for chronological age). Next, using hierarchical clustering, we identified 6 distinct subpopulations based on the 4 childhood and adulthood circumstances domains. Two of these subpopulations stood out as disadvantaged, exhibiting significantly higher PhenoAges on average. Finally, we observed a significant gene-by-environment interaction between a previously validated PGS for coronary artery disease and the seemingly most disadvantaged subpopulation, suggesting a multiplicative effect of adverse life course circumstances coupled with genetic risk on phenotypic aging. The main limitations of this study were the retrospective nature of self-reported circumstances, leading to possible recall biases, and the unrepresentative racial/ethnic makeup of the population.

CONCLUSIONS: In a sample of US older adults, genetic, behavioral, and socioenvironmental circumstances during childhood and adulthood account for about 30% of differences in phenotypic aging. Our results also suggest that the detrimental effects of disadvantaged life course circumstances for health and aging may be further exacerbated among persons with genetic predisposition to coronary artery disease. Finally, our finding that behaviors had the largest contribution to PhenoAge highlights a potential policy target. Nevertheless, further validation of these findings and identification of causal links are greatly needed.

VL - 16 IS - 6 U1 - http://www.ncbi.nlm.nih.gov/pubmed/31211779?dopt=Abstract ER - TY - CHAP T1 - Ageing in North America: Canada and the United States T2 - Oxford Textbook of Geriatric Medicine Y1 - 2017 A1 - Eileen M. Crimmins A1 - Hiram Beltrán-Sánchez A1 - Lauren L Brown A1 - Yon, Yongjie A1 - Michel, Jean-Pierre A1 - Beattie, B. Lynn A1 - Martin, Finbarr C. A1 - Jeremy D Walston KW - Aging KW - Cross-National JF - Oxford Textbook of Geriatric Medicine PB - Oxford University Press CY - Cary, NC SN - 978-0198701590 ER - TY - JOUR T1 - Assessment of cognition using surveys and neuropsychological assessment: the Health and Retirement Study and the Aging, Demographics, and Memory Study. JF - J Gerontol B Psychol Sci Soc Sci Y1 - 2011 A1 - Eileen M. Crimmins A1 - Jung K Kim A1 - Kenneth M. Langa A1 - David R Weir KW - Age Factors KW - Aged KW - Aged, 80 and over KW - Cognition KW - Cognition Disorders KW - Dementia KW - Educational Status KW - Female KW - Humans KW - Interviews as Topic KW - Logistic Models KW - Longitudinal Studies KW - Male KW - Multivariate Analysis KW - Neuropsychological tests KW - Odds Ratio KW - Prevalence KW - Sex Factors KW - United States AB -

OBJECTIVES: This study examines the similarity of cognitive assessments using 1 interview in a large population study, the Health and Retirement Study (HRS), and a subsample in which a detailed neuropsychiatric assessment has been performed (Aging, Demographics, and Memory Study [ADAMS]).

METHODS: Respondents are diagnosed in ADAMS as demented, cognitively impaired without dementia (CIND), or as having normal cognitive function. Multinomial logistic analysis is used to predict diagnosis using a variety of cognitive and noncognitive measures from the HRS and additional measures and information from ADAMS.

RESULTS: The cognitive tests in HRS predict the ADAMS diagnosis in 74% of the sample able to complete the HRS survey on their own. Proxy respondents answer for a large proportion of HRS respondents who are diagnosed as demented in ADAMS. Classification of proxy respondents with some cognitive impairment can be predicted in 86% of the sample. Adding a small number of additional tests from ADAMS can increase each of these percentages to 84% and 93%, respectively.

DISCUSSION: Cognitive assessment appropriate for diagnosis of dementia and CIND in large population surveys could be improved with more targeted information from informants and additional cognitive tests targeting other areas of brain function.

PB - 66 Suppl 1 VL - 66 Suppl 1 IS - Suppl 1 N1 - Crimmins, Eileen M Kim, Jung Ki Langa, Kenneth M Weir, David R P30 AG17265/AG/NIA NIH HHS/United States U01 AG009740/AG/NIA NIH HHS/United States Research Support, N.I.H., Extramural United States The journals of gerontology. Series B, Psychological sciences and social sciences J Gerontol B Psychol Sci Soc Sci. 2011 Jul;66 Suppl 1:i162-71. U1 - http://www.ncbi.nlm.nih.gov/pubmed/21743047?dopt=Abstract U2 - PMC3165454 U4 - Age Factors/Aged, 80 and over/Cognition/Cognition Disorders/ diagnosis/epidemiology/psychology/Cognition Disorders/ diagnosis/epidemiology/psychology/Dementia/ diagnosis/epidemiology/psychology/Dementia/ diagnosis/epidemiology/psychology/Educational Status/Female/Logistic Models/Longitudinal Studies/Multivariate Analysis/Neuropsychological Tests/Odds Ratio/Prevalence/Sex Factors/United States/epidemiology/United States/epidemiology ER - TY - CHAP T1 - Are International Differences in Health Similar to International Differences in Life-Expectancy? T2 - International Differences in Mortality at Older Ages: Dimensions and Sources Y1 - 2010 A1 - Eileen M. Crimmins A1 - Krista Garcia A1 - Jung K Kim ED - Eileen M. Crimmins ED - Samuel H. Preston ED - Barney Cohen KW - ELSA KW - Methodology KW - SHARE AB - The question addressed in this chapter is whether people in countries with relatively low life expectancy after age 50 have worse health than those in countries with longer life expectancy. We begin with a short discussion of the theoretical relationships between mortality and population health and the potential complexity of the link between measures of health and mortality. We then examine how indicators of health vary across countries and how closely differences in a set of health indicators correspond to differences in mortality across 10 countries. We note at the outset that most of the data we examine reflect analysis of cross-sectional differences in health; without comparable longitudinal data, there is little we can say about how the differences arose. The countries compared include Australia, Canada, Denmark, England, France, Italy, Japan, the Netherlands, Spain, and the United States. JF - International Differences in Mortality at Older Ages: Dimensions and Sources PB - National Academies Press CY - Washington, D.C. UR - https://www.ncbi.nlm.nih.gov/books/NBK62588/#:~:text=Two%20countries%20with%20the%20same,life%20expectancy%20could%20be%20higher. U4 - cross Cultural Comparison ER -